VIP* 25
        AfiWMA
        i
I
     I
                                   f,A

-------
      Proceedings of the 1992 U.S. EPA/A&WMA
            International Symposium
 Measurement of Toxic and
     Related Air Pollutants
            Jointly sponsored by the
       U.S. Environmental Protection Agency's
Atmospheric Research and Exposure Assessment Laboratory
                  and the
        Air & Waste Management Association
       Air & Waste Management Association
            Pittsburgh, Pennsylvania

-------
                                    VIP-25
                Measurement of Toxic and Related Air Pollutants
                   Proceedings of the 1992 U.S. EPA/A&WMA
                            International Symposium
                        Report Number EPA/600/R-92/131
                               Publication Policy
This publication contains technical papers published essentially as they were presented at a
recent U.S. EPA/A&WMA International Symposium. The papers have not been subjected
to the Air & Waste Management Association's editorial review procedures and opinions
expressed herein are not to be interpreted as having the endorsement or support of the
Association.
                                    Notice
The information in this document has been funded wholly or in part by the United States
Environmental Protection Agency under a cost-sharing agreement 682/30107 to the Air &
Waste Management Association. It has been subjected to the Agency's peer and administra-
tive review, and it has been approved for publication as an EPA document. Mention of trade
names or commercial products does not constitute endorsement or recommendation for use.
   Copies of this book are available from the Air & Waste Management Association for
   $90 ($60 for Association members). For a complete publications listing, contact the
   Order Fulfillment Clerk, A&WMA, P.O. Box 2861, Pittsburgh, PA 15230, or phone
   (412) 232-3444, fax (412) 232-3450.
                                Copyright 1992
                      Air & Waste Management Association
                                P.O. Box 2861
                              Pittsburgh, PA 15230

-------
                                  Contents

Preface                                                                     xv

Conference Committees                                                      xvi

                           Session 1 - Kuwaiti Oil Fires
                   William Hunt, Jr. and Robert Stevens, Chairmen

Overview of the Kuwait Oil Fires   W.E Hunt, Jr.                                  3
                 Session 2 - Measurement of Polar Volatile Organics
                           Joachim D. Pleil, Chairman

Microbial Volatile Organic Compound Production by Indoor Air Microorganisms
J. C. Rivers, J.D, Pleil and R. W. Wiener                                          19

Moisture Management Techniques Applicable to Whole Air Samples Analyzed by
Method TO-14  L.D. Ogle, D.A. Brymer, C.J. Jones, et al *                       25

Field Measurements of Atmospheric Polynuclear Aromatic Hydrocarbon Concentra-
tions and Phase Distribution at TAMS Sites  T.J. Kelly, J.C. Chuang, P.J.  Callahan,
etal.                                                                        31
                       Session 3 - Indoor Air Measurements
                            Dennis Naugle, Chairman

Household Exposures to Benzene from Showering with Gasoline-Contaminated
Groundwater  A.B. Lindstrom, V.R. Highsmith, T.J. Buckley, etal                   39

A Two-Chamber Design for Testing the Sink Effect with Dynamic Concentration
Profiles  K. Krebs and Z. Guo                                                 45

* Names of additional authors may be found in the Author Index

-------
Adsorption and Re-emission of Ethylbenzene Vapor from Interior Surfaces in an
Indoor Air Quality Test House   Z Guo, M.A, Mason, K.N. Gunn, et al.              51

Assessment of Indoor Air Exposure to Medical Waste Incinerator Emissions
by Extractive Fourier Transform Infrared Spectroscopy and Conventional
Sampling  E.D, Winegar, J.B. Hicks and WE Herget                              57

Practical Limitations of Multisorbent Traps and Concentrators for Characterization
of Organic Contaminants of Indoor Air  M.A. Mason, K. Krebs, N. Roache, et al.     65

Fundamental Mass Transfer Models Applied to Evaluating the Emissions of Vapor-
Phase Organics from Interior Architectural Coatings  Z. Guo andB.A. Tichenor      71

Evaluation of the Effectiveness of Several Types of Air Cleaners in Reducing the
Hazards of Indoor Radon Decay Products  N. Montassier, P.K, Hopke, Y. Shi, et al.    77

Measurement of Indoor Radon Levels in 13 New Florida Homes  J.L fyson and
C.R. Withers                                                                 83

Effects of Ventilation on Smoking Lounge Air Quality  P.R. Nelson, R.B. Hege,
J.M. Conner, et al                                                            89
                    Session 4 - Chemometrics and Data Analysis
                            Donald R. Scott, Chairman

An Observational Based Analysis of Ozone Production for Urban Areas in North
Carolina  A.A.Adams and V.P.Aneja                                            97

Stationary Source Sampling and Analysis Directory  M.D. Jackson, L.D. Johnson,
K. W. Baughman, et al                                                        103
                    Session 5 - Effects of Pollution on Materials
                             John Spence, Chairman

Pollutant Deposition to Metals Monitored Using Precipitation Runoff  S.D. Cramer
andLG. McDonald                                                         111

The Effect of Specimen Size and Orientation on the Atmospheric Corrosion of
Galvanized Steel  J. W. Spence, F.W. Lipfert and S. Katz                          117

Corrosion of Monumental Bronzes   J.D. Meakin andS.I. Sherwood               123
                                      IV

-------
 Removal of CaCO3 Extender in Residential Coatings by Atmospheric Acidic
 Deposition  W.C. Miller, R.E. Forms, R.D. Gilbert, etal.                         129

 A Study of the Effects of Acidic Pollutants on Automotive Finishes
 N. Rungsimuntakul, D. White, R. Forms, etal                                   135

 Physical Damage Formation on Automotive Finishes due to Acidic Reagent
 Exposure   D. White, R. Forms, R. Gilbert, et al                                141

 Diffusivity and Chemical Reactivity of Sulfur Dioxide with an Alkyd Paint
 W.H. Simendinger and CM. Balik                                              147

 Monitoring the Effects of Building-Influenced Microclimate Variation on the Dry
 Deposition of Sulfur Dioxide  D.A. Dolske                                     153
                           Session 6 - Personal Samplers
                    James Mulik and Petros Koutrakis, Chairmen

The Passive Sampling Device as a Simple Tool for Assesssing Ecological Change
J.D. Mulik, J.L Yarns, P. Koutrakis, et al,                                        165

Personal Exposure Models for Sulfates and Aerosol Strong Acidity  H.H, Suh, J.D.
Spengler and P. Koutrakis                                                     170

A National Pilot Study on Occurrence of Airborne VOCs in Residences  R. Otson,
P. Fellin and R. Whitmore                                                     176

Indoor Dispersion Modelling of Toluene  C.S. Davis andR. Otson                 182

Field Test and Laboratory Evaluation of a Lightweight, Modular Designed, Personal
Sampler for Human Biomarker Studies  R. Williams, L Brooks,  V.Marple, et al.     188
                          Session 7 - Source Monitoring
                             Joseph Knoll, Chairman

Development of a Test Method for Chlorinated Organic Compounds  B.A. Pate,
M.R, Peterson and R.K.M. Jayanty                                              197

Field Validation of Two California Air Resources Board Stationary Source Test
Methods  C.D. Lentz, C. Catronovo, G. Lindner, et al.                            203

-------
Proposed Sampling Method 306-A for the Determination of Hexavalent Chromium
Emissions from Electroplating and Anodizing Facilities  F, Clay                  209

Innovative Sensing Techniques for Monitoring and Measuring Selected Dioxins,
Furans and Polycyclic Aromatic Hydrocarbons in Stack Gas  J.A. Draves, D.-P
Dayton and T.J. Logan                                                       214

Determination of Total Gaseous Hydrocarbon Emissions from an Aluminum Rolling
Mill Using Methods 25, 25A and an Oxidation Technique  S.S. Parmar, M. Short
and W. Powers                                                              228

Development of an Analysis Method for Total Nonmethane Volatile Organic Carbon
Emissions from Stationary Sources  M.D. Jackson, J.E. Knoll, M.R. Midgett, et al.  236

Source Characterization of Air Toxics from Rocket Engine Tests  J,L. Downs, B.L
Boyes, S.L. Pierett, et al.                                                     244
                  Session 8 - Acid Aerosols and Related Pollutants
                    Petros Koutrakis and James Mulik, Chairmen

Overview of the AREAL Acid Aerosol Research Program  L.J. Purdue, D.A. Pahl
and WE,  Wilson                                                             259

Measurement of Partial Vapor Pressure of Ammonia over Acid Ammonium Sulfate
Solutions by an Integral Method  P. Koutrakis, MJ. Wolfson, B, Aurian-Blajeni,
et al                                                                       264

An Assessment of Acid Fog  EW Lipfert                                      271

Acid Aerosol Measurement Methods: Studies of Extraction and Analytical Effects
T.G. Ellestad,  L.L. Hodson, S.J. Randtke,  et al                                  282

Development and Validation of a Model for Predicting Short Term Acid Aerosol
Concentrations from the HSPH Continuous Sulfate/Thermal Speciation Monitor
G. Allen and P. Koutrakis                                                     288

Measurement of Atmospheric Formic and Acetic Acids: Methods  Evaluation and
Results from Field Studies   J.E. Lawrence and P. Koutrakis                       295

Meteorological and Seasonal Variability in Acid Aerosol Levels and in the Degree
of Acid Aerosol Neutralization  J.R. Brook, K. Hayden, M. Raizenne, et al          306
                                      VI

-------
Acidic Gases and Aerosols in the Eastern and Western United States   E.S. Edgerton
and B.E. Martin                                                           312

Sulfate Air Pollution as an Index of Atmospheric Acidity   EW. Lipfert and
R.E. Wyzga                                                                321

Gas and Paniculate Phase Acids and Oxidants in Two University Libraries
DJ. Eatough, N. Williams, L Lewis,  et al                                      333

Measurements of Nitrous Acid: Variables Affecting Indoor Concentrations
M. Brauer                                                                344
                 Session 9 - Lake Michigan Urban Air Toxics Study
                     Gary Evans and Gerald Keeler, Chairmen

Lake Michigan Urban Air Toxics Study: Design and Overview   G.E Evans, AJ,
Hoffman and DA. Pahl                                                     355

Summer 1991 Field Measurements  N.E. Bovme                               361

Atmospheric Mercury Measurements: Recent Observations in the Great Lakes
Basin  M Hoyer, C, Lamborg, G, Keeler, et al                                367

Ambient Air Monitoring and Analysis for Polycyclic Aromatic Hydrocarbons
J.C. Chuang, D.B. Davis, M. Kuhlman, et al                                   373

Atmospheric Acidity Measurements during the Lake Michigan Urban Air Toxics
Study  C. Lamborg, GJ. Keeler and G. Evans                                 379

Dry Deposition and Coarse Particles Size Distributions Measured during LMUATS
K.E. Noll TM Hoben, G.C. Fang, etal.                                      386
                     Session 10 - VOC Methods Development
                          William McClenny, Chairman

Evaluation of a Sorbent-Based Preconcentrator for Analysis ofVOCs in Air
Using Gas Chromatography and Atomic Emission Detection  K.D. Oliver,
E.H. Daughtrey, Jr. and W.A, McClenny                                       395

Design Considerations for an Automated On-Line Air Sampling System
G. Broadway, E. Woolfenden, J. Ryan, et al.                                    401
                                      vu

-------
Advances in High Speed Gas Chromatography for Monitoring Gas and Vapor
Contaminants in Workplace and Ambient Air  H. Ke, S.P Levine and R. Berkley    407

Evaluation of Commercially-Available Portable Gas Chromatographs  R.E. Berkley,
M. Miller, J.C. Chang, etal.                                                  413

System for Real Time, Hourly Analysis of C2 - CJO Compounds in Air Using
55 Minute Sample Integration  P.J. Milne, R.G. Zika, C.T. Farmer, et al            419

On-Line Monitoring of Nitrous Oxide from Combustion Sources Using an
Automated Gas Chromatograph System  J.V.Ryan and S.A, Karns                427

Combined Supercritical Fluid Chromatography/Microsuspension Mutagenicity
Assay of Environmental Tobacco Smoke  D.J. Eatough, T.D. Parrish, E.S. Francis,
etal.                                                                      433

Air Monitoring during Daim Removal Activities Using a Field Portable Microchip
Gas Chromatograph  L.P. Kaelin, R. Wynnyk, M. Pueyo, et al                    445

Continuous Real Time Formaldehyde Measurements in  Ambient and Test
Atmospheres   T.J. Kelly,  G.F. Ward and C.R. Fortune                            454
                          Session .11 - Quality Assurance
                            Shri Kulkarni, Chairman

Accuracy Assessment of EPA Protocol Gases Purchased in 1991   E.A. Coppedge,
TJ. Logan, M.R. Midgett, et al                                               463

Preparation of Performance Evaluation Audit Samples for the Determination of
Impurities in CFCs  SJ. Wasson, S. VKulkarni, CO. Whitaker, etal               469

Ensuring Data Quality via Preliminary Analysis of Measurement Error Variability
LA. Stefanski                                                              475

Quality Assurance for an Alternative Analytical Method for Highly Concentrated
VOST Samples   J.D. Evans, D. Halsell and J. Hawkins                          481

Ozone Episodes in Atlanta, Georgia: Analysis of Air Quality Data  Gathered during
the Summer of 1990 Using an Observation Based Model  C.A. Cardelino,
W.L. Chameides and L. Perdue                                               488
                                     VUl

-------
Quality Assurance Planning for Stationary Source Field Sampling  M.D. Jackson
and M.R. Midgett                                                           494

Data Validation Guidance for Ambient Air Measurement Methods  A. Rosecrance   499

Method Evaluation of the Draft Statement of Work for Analysis of Ambient Air -
Air Toxic Semivolatile Compounds for the Superfund Contract Laboratory Program
R.J. Sullivan, M. Zimmerman, S.M. Pankas, et al                                506

The Evolution of the National Dry Deposition Network Quality Assurance Program
S.S, Isil, C.A. Boehnke and C. G. Manos, Jr.                                     516

Customer/Supplier Accountability and Quality Assurance Program Implementation
R.K. Patterson                                                              520
                 Session 12 - SS Canister Cleaning and Techniques
                           R.K.M. Jayanty, Chairman

A Technique for Cleaning SUMMA* Canisters and the Subsequent Effects of
Storage on Canister Cleanliness   C.L, Shaulis, D.A. Brymer, L.D. Ogle, etal       527

The Effect of Water on Recoveries in SorbentTube and SUMMA Canister Analysis
JM Soroka, R. Issacs, G. Ball, et al                                           532

A Critical Evaluation of TO-1 and TO-2 Method for the Analysis of Ambient Air
Volatile Organic Compounds  A.S. Williams andS.A. Guest                      539

Stability of Multicomponent Gaseous VOC Standards in Cylinders JJ.E McAndrew,
E.R. Kebbekus and R.  Gajjar                                                 545
                       Session 13 -Atmospheric Chemistry
                           Bruce W. Gay, Jr., Chairman

Gaseous Hydrogen Peroxide Concentrations in Raleigh, North Carolina   M. Das
andVP.Aneja                                                              553

Modeling of Cloud Water Acidity: Comparison between Theory and Experiments
N.-H. Lin, T.P. DeFelice and V.K. Saxena                                       559

Computer Estimation of the Atmospheric Gas-Phase Reaction Rate of Organic
Compounds with Hydroxyl Radicals and Ozone   W.M. Meylan and P.H. Howard    565

-------
 Isoprene Emissions from Willow Oak Trees  S.A. Meeks, B. W. Gay, Jr. and
 B.E. Tilton                                                                 571
              Session 14 - Remote Sensing FTIR Open Path Techniques
                  Thomas Pritchett and William Vaughan, Chairmen

Operational Considerations for the Use of FTIR Open Path Techniques under Field
Conditions  G.M, Russwurm                                                579

A Technique to Derive Background Spectra from Sample Spectra for Open Path
FTIR Spectroscopy Applications  R.J. Kricks, D.E. Pescatore, R.H. Kagann, et al  582

A Methodology to Determine Minimum Detection Limits for Site-Specific Target
Compounds Using Open Path FTIR Spectroscopy   D.E. Pescatore, RJ. Kricks,
R.L. Scotto, et al.                                                           595

VOC  Emission Rate Estimation from FTIR Measurements and Meteorological Data
R.E. Carter, Jr., D.D. Lane, G.A. Marotz, et al.                                  601

A Comparison of VOC Concentrations Assessed by Open Path FTIR and Canisters
G.A. Marotz, D.D. Lane, R.E. Carter, Jr., et al.                                  607

FTIR  Open Path Monitoring of Fugitive Emissions from a Surface Impoundment
during a Bioremediation Test Program  R.H. Kagann, W.A. Butler andJ.R.  Small    615

Airborne Lidar Mapping of Ozone Concentrations during the Lake Michigan Ozone
Study  E.E. Uthe, J.M. Livingston andN.B. Nielsen                             628

Application of a Frequency-Agile Lidar System for Environmental Monitoring
J. Leonelli, L. Carr andL.  Fletcher                                           641

Signal Processing for Chemical Microsensors   N. Kyriakopoulos and T. ul Haq     647

Open  Path Ambient Measurements of Pollutants with a DOAS System  C.R Conner,
B. W. Gay, Jr., WE. Karches, et al.                                             654
                   Session 15 - Air Pollution Dispersion Modeling
                        S.P. Arya and S.T. Rao, Chairmen

Multiplying Factors to Convert One Hour Maximum Concentration Screening
Estimates for Sources Influenced by Building Wake Effects  L.H. Nagler          663

-------
Multizonal Mass Balance Modeling of Benzene Dispersion in a Private Residence
A. Lansari, A.B. Lindstrom, B.D. Templeman, et al.                              669

Comparison of Modeled Concentration Profiles Using Site-Specific and Constant-
Condition Meteorological Data for the ISCLT and PAL Models  J. Streicher and
B. Templeman                                                             675

Atmospheric Deposition of Toxic Metals to Lake Michigan: Preliminary Annual
Model Calculations  T.L. Clark                                             681

Wind Tunnel Modeling for Evaluating the Dispersion of Toxic Chemicals
R.L. Petersen and CE. Wisner                                                687

Deposition Modeling of Chlorinated Dioxins and Furans   M.B.G. Pilkington and
S.G. Zemba                                                               694

Further Development of an Interactive Air Transport Model for Superfund Site
Applications  K.T. Stroupe and J.S. Touma                                    700

Estimation of Dispersion Parameters by SF6 Tracer in the Tropics  M.P. Singh,
P. Aganval,  S. Nigam, et al.                                                  706
                 Session 16 - Measurement Methods Development
                            Philip Hopke, Chairman

Method Development for the Analysis of Vinyl Chloride in Gaseous and PVC Resin
Samples   M. Tardif, E. Dowdall and C.H. Chiu                                713

Sampling and Measurement of Phenol and Methylphenols (Creosols) in Air by
HPLC Using a Modified Method TO-8  S.A. Bratton                           719

Application of Solid Phase Extraction to the DNPH Impinger Method for Carbonyl
Compounds  K, Fung                                                     725

Immuno-Based Methodology for Use in Airborne Paniculate Monitoring   B, Riggle 730

The Determination of Sub Part-per-Billion Levels of VOCs in Air by Pre-
concentration from Small Sample Volumes   N.A, Kirshen and E.B. Almost         734

Performance Assessment of the Portable and Lightweight LOZ-3 Chemiluminescence
Type Ozone Monitor  L.A. Topham, G.I. Mackay and H.L Schiff                 745
                                     XI

-------
Measurements of NOy, NOx and N02 Using a New Converter-Sequencer and
Sensitive Lummox® Detection  J. W. Drummond, P.B. Shepson, G.L Mackay, et al.   750

A Field Portable Analyzer for On-Site Analysis of Odorant Levels  R. C. Mitchner  756

Low Level Monitoring of Halomethanes, Saturated and Unsaturated Halogenated
Hydrocarbons in Air   A. Linenberg and D.S. Robinson                          762

Simultaneous In-Plume and In-Stack  Sampling for Analysis of a Detached Plume
at a Cement Plant  L Edwards, E. Winegar and L W. Cover                     770
                       Session 17 - Lead in the Environment
                    Sharon Harper and Laurie Schuda, Chairmen

Evaluation of a Filter Compositing Procedure for Possible Incorporation in the
Federal Reference Method for Lead   W.A. Loseke, S.L. Harper, L.J. Pranger, et al.  779

Engineering Study to Explore Improvements in Vacuum Dust Collection  B.S. Lim,
J.J. Breen, J. Schwemberger, et al.                                            785

The Development and Validation of a Reliable Household Dust Surface Wipe
C. Weisel, P. Yang, T. Wainman, et al.                                          791

Quality Assurance Considerations in the Analysis for Lead in Urban Dust by
Energy Dispersive X-ray Fluorescence  H.A. Vincent and DM. Boyer             796
                     Session 18 - Ambient Air Measurements
                             Dennis Lane, Chairman

A Review of Speciated NMOC Data   K. Baugues                             805

What is the Ambient Monitoring Technology Information Center?  J.B. Elkins, Jr.   811

A Summary of NMOC, NOx and NMOC/NOx Data Collected between 1984 and
1988   K. Baugues                                                         815

Comparing Nonmethane Organic Compound, NOx and Daily Maximum Ozone
Concentrations by Site and by Year  R.A. McAllister, P.L O'Hara, J.E. Robbinst
etal                                                                     821
                                     xu

-------
 Performance of the Annular Denuder System in an Outdoor Ambient Air Pollution
 Study   S.C.Mauch                                                         827

 The Kodak Park Ambient Air Monitoring Network: Results after Two Years of
 Operation  DM Hendricks, S. Santanam, R.G. Merrill, etal                    832

 Near Real Time Measurements of Pentachlorophenol in Ambient Air by Mobile
 Mass Spectrometry  G.B. De Brou, A. C, Ng and N.S. Karellas                   838

 Massachusetts 1991 NMOG Monitoring Program  T.R. McGrath                  844
                     Session 19 - VOC Monitoring Techniques
                    Larry Ogle and Delbert Eatough, Chairmen

Noncryogenic Concentration of Ambient Hydrocarbons for Subsequent Nonmethane
and VOC Analysis  D.A. Levaggi, W. Oyung and R. V Zerrudo                    857

Direct Measurement of Volatile Organics in Liquid Pesticide Formulations  M.R.
Peterson, Y.H. Straley, R.K.M. Jayanty, et al                                    864

PCBs by Perchlorination: A Method Tailored to Ambient Air Field Samples Rich
in PAHs but Lean in PCBs  & Dombro, J. Hurley, C, Crowley, et al               870

Field Evaluation of Several Methods for Monitoring Ethylene Oxide Emissions from
Hospital Sterilizers  K. Mongar                                             877

The Evaluation of the Concentration of Semivolatile Hydrocarbons (in the C12- CIg
Range) Emitted from Motor Vehicles  B.  Zielinska and K.K. Fung                883

Moisture Management Techniques Applicable to Whole Air Samples Analyzed by
Method TO-14  L.D.  Ogle, D.A. Brymer,  C.J. Jones,  et al                        889

A Novel Approach for Gathering Data on Solvent Cleaning  M.A. Serageldin, J.C.
Berry and D.L Salman                                                      895
                  Session 20 - Semivolatile Organic Measurements
                             Gary Hunt, Chairman

State-of-the-Art Capability for Determination of Chlorinated Dioxins and Dibenzo-
furans in Ambient Air  C Tashiro, R.E. Clement, P. Steer, etal.                   905
                                     XUl

-------
Gas Exchange of Hexachlorocyclohexane in the Great Lakes  L.L. McConnell,
W.E. Gotham and T.F, Bidleman                                               911

Ambient Impacts of Coke and Coke By-Products Manufacturing on Selected
Pollutant Levels in Neighboring Communities   R. Markov, A.C. Olsakovsky and
J.P.Fillo                                                                   915

Impact of West Virginia Forest Fires on Ohio Air Quality  K. Riggs, W. Piispanen,
J. Chuang, et al                                                             927

Evaluation of the Inpacts of an RDF Fuelled Incinerator on Air Toxic Concentrations
in the Windsor Area  T. Dann                                                933

The Dioxin/Furan Emission Profile for an RDF Fired Resource Recovery Facility
J.C. Seme                                                                  940
                    Session 21 - Risk and Exposure Assessment
                            Lance Wallace. Chairman

Assessing Exposure and Risk to the Nation's Ecological Resources  J.H.B. Garner,
D.E. Hyatt and D,A. Vallero                                                   957

Use of Personal Measurements for Ozone Exposure Assessment   L-J.S. Liu, P.
Koutrakis, H.H. Suh, et al                                                    962

Public Exposure to Organic Vapors in Los Angeles   S.D. Colome, A.L Wilson,
Y. Tian, et al                                                                968

An Exposure Assessment and Risk Assessment Regarding the Presence of
Tetrachloroethene in Human Breastmilk  J.S. Schreiber                          975

-------
The Time-Course and Sensitivity of Muconic Acid as a Biomarker for Human
Environmental Exposure to Benzene    T.J. Buckley, A.B. Lindstrom,
VR. Highsmith, et al                                                         981

                                   Session 22
                    Measurement of Hazardous Waste Emissions
                   Richard Grume and Joseph Laznow, Chairmen

Mercury in Air and Rainwater in the Vicinity of a Municipal Resource Recovery
Facility in Northwestern New Jersey   A.  Greenberg, I. Wojteriko, H.-W. Chen, et al   989

Polynuclear Aromatic Hydrocarbon Concentrations in the Emissions from Waste
Combustion at Selected Municipal, Medical/Municipal and Research Incinerators
L. Brooks, R. Williams, J. Meares, et al.                                         998

Characterization of the Air Pollutants Emitted from the Simulated Open Burning
of Automobile Recycling Fluff  J. V. Ryan, C, C. Lutes and P.M. Lemieux           1004

Air Emission Rate Measurements of VOCs and SVOCs Emitted from an In Situ
Bioremediation Pilot-Scale Test on Surface Impoundment Sludge   W.A. Butler      1016

                                   Session 23
                                    General
                          William Gutknecht, Chairman

Geographical Distribution and Source Type Analysis of Toxic Metal Emissions
W.G, Benjey andD.H. Coventry                                              1029

Field Screening Filters Used in Monitoring Air Quality for Metals with a Field-
Portable X-ray Fluorescence Spectrometer  M.B. Bernick, J.  Corcoran,
PR. Campagna, etal                                                       1035

Overall Efficiency of Inlets Sampling at Small Angles in the Yaw and Pitch
Orientations from Horizontal Aerosol Flows  S. Hangal and K, Witteke            1044

Comparison of Aerosol Acidity in Urban and Semi-Rural Environments
R.M. Burton, W.E. Wilson, P Koutrakis, etal.                                   1051

Aerosol Acidity Characterization of Large Metropolitan Areas: Pilot and Planning
for Philadelphia   JM Waldman, P. Koutrakis, R. Burton, et al.                    1063

Subject Index                                                              1072
Author Index                                                               1080

-------
                             Preface


     The 1992 U.S. EPA/A&WMA International Symposium, Measurement
of Toxic  and Related Air  Pollutants,  was held  in  Durham,  North
Carolina, on May 4-9,  1992.  This yearly symposium is sponsored by
the United States  Environmental  Protection Agency,  Atmospheric
Research and  Exposure Assessment  Laboratory and the Air &  Waste
Management Association.
     Courses  offered, in  conjunction with  the symposium,  were
taught by  leaders in the  field  of air pollution  monitoring and
measurement   and   focused  on  basic  sampling   and  analytical
methodology as well as advanced methods for monitoring air toxics.
     The  four  day technical  program  consisted  of  200  papers
presented in twenty three separate  sessions.  Individual sessions
concentrated on recent advances in the measurement and monitoring
of toxic and related air  pollutants.  This included air pollutants
found  in  the ambient  atmosphere,  in the  indoor  air,  and  as
emissions  from  stationary and mobile  sources.   Exhibits  were  on
display  from seventy instrument  and consulting  services.  The
keynote  address  was  presented  by  Edythe  McKinney,  Assistant
Secretary  for the  Environment, The  Department  of Environmental
Health and Natural Resources of the State of North Carolina.
     Measurement and  monitoring research  efforts are designed to
anticipate  potential  environmental  problems.     This  research
supports regulatory actions by developing an in-depth understanding
of the nature of processes that impact  compliance with regulations
and  evaluating the  effectiveness  of health  and  environmental
protection  through the  monitoring of long-term trends.   EPA's
Atmospheric  Research  and  Exposure  Assessment  Laboratory,  at
Research Triangle Park, North Carolina  is responsible for research
and  development  of  new  methods,  techniques   and  systems  for
detection,  identification  and characterization  of  pollutants  in
emission  sources  and in indoor  and  ambient environments.    The
Laboratory has the responsibility of implementation of a national
quality assurance  program  for air  pollutant measurement systems,
and supplying technical  support to Agency regulatory programs on
local, regional,  and  global scale.  Thirty  four NATO scientists
from twelve countries participated in the symposium.
     The  A&WMA  provides  a  neutral   forum  where  environmental
professionals share technical and managerial  information about air
pollution  control  and  waste management.    1992  was  the  12th
consecutive year of holding the symposium and the 7th year of its
co-sponsorship with the A&WMA.
     The objective of the symposium is to provide a forum for the
exchange of ideas on recent advances  for the  reliable and accurate
measurement and monitoring of toxic and related air pollutants in
indoor, ambient,  and source  atmospheres.   The  large numbers  of
presentations   and  attendance  to   the   symposium   represents
advancements  and  interest in current  measurement  and  monitoring
capabilities.
                                        Bruce W. Gay Jr. (U.S. EPA)
                                        R.K.M.  Jayanty (RTI)
                                        Technical Program Chairmen
                                XV

-------
                Conference Committees

                Technical Program Committee
                        Cochairmen
              Bruce W. Gay, Jr., AREAL, U.S. EPA
           R.K.M. Jayanty, Research Triangle Institute

                        Committee
              William Hunt, Jr., OAQPS, U.S. EPA
               Robert Stevens, AREAL, U.S. EPA
               Joachim Pleil, AREAL, US. EPA
           Dennis Naugle, Research Triangle Institute
                Donald Scott, AREAL, US. EPA
                John Spence, AREAL, U.S. EPA
                James Mulik, AREAL, US. EPA
        Petros Koutrakis, Harvard School of Public Health
               Joseph Knoll, AREAL, U.S. EPA
                Gary Evans, AREAL, U.S. EPA
               Gerald Keeler, AREAL, U.S. EPA
             William McClenny, AREAL, U.S. EPA
            Shri Kulkarni, Research Triangle Institute
               Thomas Pritchett, ERT, U.S. EPA
         William Vaughan, Environmental Solutions, Inc.
            S.P. Arya, North Carolina State University
ST. Rao, New York State Department of Environmental Conservation
               Philip Hopke, Clarkson University
               Sharon Harpe, AREAL, U.S. EPA
                   Laurie Schuda, US. EPA
               Dennis Lane, University of Kansas
                  Larry. Ogle, Radian Corp.
           Delbert Eatough, Brigham Young University
                     Gary Hunt,  ENSR
             Lance Wallace, EPIC/ORD, US. EPA
           Richard Crume, Midwest Research Institute
              Joseph Laznow, J.L.  and Associates
         William Gutknecht, Research Triangle Institute

               General Conference Committee
                       Cochairmen
                Gary Foley, AREAL, US. EPA
     Martin E. Rivers, Air & Waste Management Association
                           XVI

-------
    Research Triangle Park Chapter
        Vandy Bradow, Chairman
      Mark Shanis, Vice Chairman
        Ann Naismith, Secretary
         Gary Snow, Treasurer
      Jim Southerland, Membership
     South Atlantic States Section
       Susan Wierman, Chairman
      Cathy Taylor, Vice Chairman
       Robert Kaufman, Secretary
       Douglas Pefton, Treasurer
     John Daniel, Jr., Membership
       Ronald Bradow, Education
     Toxic Air Pollutants Division
         Gary Hunt, Chairman
      Dave Patrick, Vice Chairman
Ambient Monitoring Committee (EM-3)
     Thompson Pace III, Chairman
     R.K.M. Jayanty, Vice Chairman
        Paul Soloman, Secretary
 Source Monitoring Committee (EM-4)
        Mark Siegler, Chairman
     James Jahnke, Vice Chairman
       J. Ron Jernigan, Secretary
                XVU

-------
                 Session 1
              Kuwaiti Oil Fires
William Hunt, Jr. and Robert Stevens, Chairmen

-------
          Overview of the Kuwait Oil Fires

                William F. Hunt, Jr.
        U.  S.  Environmental  Protection  Agency
    Office of Air Quality Planning and Standards
          Research Triangle Park, NC 27711
USEPA/Air and Waste Management Association Symposium
  Measurement  of Toxic  and Related Air Pollutants
                     Durham,  NC
                     Hay  1992

-------
 INTRODUCTION
     Attacks on the environment began in late January 1991, when
 the government of  Iraq ordered millions of barrels of crude oil
 released into the  Persian Gulf from tankers and oil terminals
 located off the coast of occupied Kuwait.  Less than a month
 later, as Iraq's armies were driven from Kuwait, they blew up
 more than 700 oil  wells, storage tanks, refineries and
 facilities.  The fires originated in seven oil fields, located
 both north and south of Kuwait City with the majority centered in
 the Greater Burgan Oil Field, south of the Kuwait City Airport
 (Figure 1).  In every war there is damage to the environment, but
 deliberately discharging oil and blowing up wells had neither
 economic nor military benefit.  The Iraqi government waged war
 against the environment itself.

      An estimated nine hundred million barrels were burned or
 spilled onto the land during the 9 months the fires burned,
 enough oil to supply the United States for 50 days.  Fortunately,
 once the fire fighting equipment was in place and the fire
 fighting teams gained more experience, the fires were
 extinguished at a  much greater rate than was originally
 anticipated (Figure 2).  Some experts had expected the fire
 fighting effort to continue for as many as five years.  Over 80
 percent of the world's oil-fire fighting expertise was in Kuwait
 during this environmental disaster.1  By mid-May,  just 80 of  the
 burning wells had  been extinguished, half were out by August, and
 by early November, the last fires were put out.  This disaster
 spawned new approaches to extinguishing oil fires including
 mounting jet engines on tanks to "blow" the fires out and using
 liquid nitrogen to displace oxygen to suffocate the flames.

 Public Health Concern
     Air pollution models, which were run in the United States
 and Saudi Arabia,  predicted that very high particulate matter,
 sulfur dioxide (SO2)  and  hydrogen  sulfide (H2S) levels would
 occur during episodic meteorological conditions, seriously
 impacting human health.  The predicted air pollution levels were
 comparable to those which resulted in increased mortality in
 London in 19522,  New  York in 19663, and in Donora, Pennsylvania
 in 1948*.  These  events provide  the  clearest  evidence  for an
 association between SO2/particulate  air  pollution  and  death.
 During these events,  a striking increase in daily mortality
 occurred, when unfavorable meteorological conditions resulted in
 several days of stagnation and greatly increased concentration of
 atmospheric pollutants.  Deaths occurred primarily among persons
already afflicted with cardiac and respiratory diseases, though
 some healthy persons were affected.   Relevant U. S. National
Ambient Air Quality standards (NAAQS), U. S.  Significant Harm
 Levels and Saudi Arabian Meteorology and Environmental Protection
Administration standards are indicated in Table 1.  The
 Significant Harm Levels are those which should never be reached

-------
Figure  1.  Map of Kuwait and its  oil fields.
                 SAUDI

                ARABIA
                                                    Oilfields of Kuwait
                                                         QOfliU wUkBa gft production
Figure 2.  Number of Kuwait oil wells on fire, March through
            November  1991.
   600
   500
  1991: March   Apr!    fttoy    Jum   July   August  StpttmlMr  October  NovttnlMr

-------
to avoid increased mortality.

     Because of the concern for the health of Americans and our
Allies in Kuwait and the Eastern Province of Saudi Arabia, the U.
S. Persian Gulf Risk Evaluation Team was sent to the Middle East
on March 10, 1991 at the request of the Saudi Government and the
U. S. Embassy.  The U.. S. Embassy in Saudi Arabia voiced its
additional concerns about the health effects of the fires on the
hundreds of thousands of U. S. troops in the region as well as
the thousands of American citizens residing in Saudi Arabia and
other Gulf countries.  The paper will review the work of the Team
and the efforts that were taken to assess the magnitude of the
air pollution problem, focussing on the initial air pollution
impact assessment, the development of the Gulf Regional Air
Monitoring Plan and a comparison of the Team's monitoring efforts
with other international efforts.

U. S. PERSIAN GULF RISK EVALUATION TEAM

Purpose
     The primary objectives of the Team* were  to obtain
preliminary, short-term data on the emissions from the smoke
coming from the oil well fires at a variety of locations to:

     1.   Determine if there was an acute health effect
          associated with.the H2S,  SOa and particulates, three
          pollutants that were expected to be emitted from the
          burning oil wells;

     2.   Identify and quantify the gaseous and particulate
          products resulting from the fires;

     3.   Determine if air pollution is threatening areas where
          American citizens are located; and

     4.   Assess the impact of the war on the Kuwait and Saudi
          Arabian health infrastructure and its ability to
          respond to the crisis.

     Based upon these objectives, the Team proceeded to collect
limited, real time air pollution measurements from the Kuwait oil
fields, as well as from locations in Kuwait and Saudi Arabia
where troops, embassy officials and citizens work and reside.  In
addition to the ambient air pollution monitoring effort, members
of the Team conducted a number of interviews with health
officials in the U. S. and Allied military as well health
officials in Kuwait and Saudi Arabia to evaluate the extent of
acute respiratory problems related to smoke exposure.

Initial Results
     The only way to fully comprehend the impact of the oil fires
was to see them.  I had the opportunity to fly over the fires

-------
Table  l.  USEPA National Ambient Air Quality Standards' and
Significant Harm Levels (SHL)b and Saudi  Arabia Meteorology and
Environmental Protection Administration  (MEPA)  Standards0.
Pollutant
Particulate
Matter
Agency
MEPA
                USEPA
Standard
ug/m3 (ppm)

340  (PM15)
80   (PM15)
           150  (PM10)
           50   (PM10)
USEPA/SHL 600  (PM10)

USEPA      260  (TSP)"
           75   (TSP)"
USEPA/SHL lOOO(TSP)
Sulfur  Dioxide MEPA
                USEPA
           800 (0.28)
           400 (0,14)
           85  (0.03)
           365 (0.14)
           80  (0.03)
USEPA/SHL 2620(1.00)
Hydrogen
Sulfide
Carbon
Monoxide
Ozone
Nitrogen
Dioxide
MEPA



USEPA

MEPA



USEPA



MEPA

USEPA



MEPA



USEPA
200  (0.14)
40   (0.03)

None

40,000  (35)
10,000  (9)

40,000  (35)
10,000  (9)

295  (0.15)

235  (0.12)
660  (0.35)
100  (0.053)

100  (0.053)
Averaging Allowable
Time       Exceedances
24 hours
l year
1 x per  year
0
                24 hours  once per  year"
                1 year    0
                24 hours  0
                                           24 hours
                                           1 year
                                           24 hours
                           1 x per year
                           0
                           0
                1 hour    2 x per  30  days
                24 hours  1 x per  year
                l year    0
24 hours
1 year
24 hours

1 hour
24 hours
1 hour
8 hours

1 hour
8 hours

1 hour

Daily
max. hr.

1 hour
1 year

1 year
1 x per  year
0
0

1 x per  year
0
2 x per  30 days
2 x per  30 days

1 x per  year
l x per  year

2 x per  30 days

once per year"
2 x per  30 days
0
     MAMW dof In* lovala of air quality noodad to protect public hMltb.          .   „, .„
                                               of Inlnont dinoar to public
             Ban Lovola axo !•¥•!• novox to bo «co*dod bocauM
     •audl atandaxda doflM !•¥•!• of *lr quality nmd«d to protoot public toooltli
     •tuidud lovol not to bo •xooodod on «n *v«r*o* of MM titan OIMO pox y»«r.   ...  ....
     Ttw total auBpondod partloulato (TH>> Mtandardii won roplacod vltb ttoo PHiO at»nd«rd» In 1»»7

-------
with the United States Army in a Black Hawk Helicopter.  As far
as the eye could see, the wells were burning.  Collectively, the
plumes from the combined fires formed a super plume.  It was as
if we were flying through Helli  Figures 3 and 4 are photographs
that I took from the helicopter.  Figure 3 is a long view of the
fires on the horizon with the plumes being combined to form the
super plume.  You will note that as the smokes rises you can see
a wind sheer effect where the plume moves in a different
direction as it rises in altitude.  Figure 4 is a photograph of a
single fire taken on March 25, 1991 at approximately 10:00 a.m.
with a 200 millimeter (mm) lens by looking directly into the Al
Burgan Oil Field.  The sky is as black as night.  Perhaps U. s.
Environmental Protection Agency (USEPA) Administrator William K.
Reilly said it best, "If Hell had a National Park, it would be
those burning oil fires!116  The overwhelming question was how to
address this incredible mess?

     Air monitoring.  Within several days of arrival, the Team
went to Kuwait to collect real time measurements of total
particulates, SO,,  H3S and volatile organic compounds  (VOC).
These measurements were collected at 13 locations in Kuwait and
Saudi Arabia - at the U. S. Embassies in Kuwait City and Riyadh,
Saudi Arabia; at the Meteorology and Environmental Protection
Administration in Dhahran, Saudi Arabia; at five oil well fields;
and at various locations near the oil fields in Kuwait.  The
monitoring campaigns were conducted during March 13-20 and March
24-27, 1991.  Most of the measurements were collected over short
time periods ranging from 10 to 32 minutes.  The measurements
taken during these campaigns were collected using portable
battery operated monitoring devices.  The electrical power grid
in Kuwait was not functioning because of war damage, so it was
not possible to use traditional monitoring instruments which need
electrical power.

     The ten to 32 minute particulate measurements collected in
Kuwait ranged from 10 to 5400 micrograms per cubic meter (ug/m3).
As would be expected, the highest measurement occurred in the
Kuwait oil fields near a burning pool of oil.  In a populated
area, the highest particulate concentration (935 ug/m1)  was
collected over a 20 minute period.  It was measured at the Al
Ahmadi Hospital south of Kuwait City.  The hospital was impacted
by an oil fire a quarter of a mile away.  The old U. S. total
suspended particulate (TSP) National Ambient Air Quality Standard
(NAAQS) can be used as a guide to compare these concentration
levels.  The old TSP NAAQS was a 24-hour average concentration of
260 ug/m1.  Eleven  of the  25 ten to  32 minute total  particulate
measurements collected in Kuwait exceeded the concentration level
of 260 ug/m3.  This  is where the comparison  ends because of the
differences in averaging times.

     The SOa monitor that was  initially  used had a detection
limit of 1 to 2 parts per million (ppm).  Of the 24 S0a

-------
Figure 3. Long view of the fires on the horizon with the
individual pluses being combined to form a super plumef March 25,
1991.
Figure 4. Single oil well fire in the Al Burgan Oil Field,
25, 1991 at 10:05 a.m.

-------
measurements collected by the Team during the March 13-20 and
March 24-27 campaigns, 17 of them were recorded as 0.0 ppm, 5
were recorded as 1.0 ppm (2620 ug/m3), and 2 were recorded as 2.0
ppm (5240 ug/m1).   A different SOa monitor with a detection  limit
of 0.1 ppm did not indicate SO2.   Therefore, the  SOa levels  of 1
to 2 ppm should be viewed with caution.  In addition to the real
time measurement devices, 25 passive  sampling devices were worn
by Team members while they were collecting air pollution
measurements with the real time instruments.  Unlike the real
time measurements that were collected over short time periods of
10 to 32 minutes, these measurements were collected over periods
of several hours at a time.  The passive monitors were worn
during the first measurement campaign.  The samples were analyzed
by EPA's Atmospheric Exposure and Assessment Laboratory7 (AREAL)
and the concentrations ranged from 4 to 50 ug/m3.

     In addition to the U. S. Team efforts, the Kuwait
Environment Protection Council monitored S0a at four temporary
hospital locations in Kuwait city using an SO, bubbler
(acidimetric) method from March 13 to 24, 1991.  The SOa bubblers
were operated by generators at the hospitals.  The highest  24-
hour concentration observed was 219 ug/m3.   The results obtained
by the U. S. Team, in combination with the S0a measurements
collected by the Kuwait Environment Protection Council, were the
basis for the conclusion that the S0a concentrations did not
present an imminent danger to U. S. troops, U. S. citizens, our
Allies or the citizens of Kuwait.  No exceedances of the 24-hour
U. S. NAAQS of 365 ug/m1 for SOa were  observed.

     The highest HaS was measured in  Kuwait at the Sabiriyan well
plume on March 19, 1991 with a concentration of 0.042 ppm.  Of
the 25 H2S measurements collected by  the  Team during the March
13-20 and March 24-27 campaigns, 13 of them were recorded as 0.0
ppm, 7 were less than or equal to 0.01 ppm, 2 less than  .02 ppm,
and the remaining three concentrations were 0.024. ppm, 0.032 ppm
and 0.042 ppm.  While there is no U.  S. NAAQS for HaS,  there are
Saudi MEPA standards for H3S of 0.14  ppm  for one  hour and 0.03
for 24 hours.  The Occupational Safety and Health Administration
(OSHA) Permissible Exposure Limit (PEL) is 10 ppm for one hour.
Since the measured HaS  levels are below the one hour MEPA
standard and substantially below the OSHA PEL, Has was  not deemed
to be a problem.

     With respect to the initial content of the particulate
matter, the Team did detect polycyclic aromatic hydrocarbons and
trace metals, such as nickel, chromium and vanadium, which are
known or suspected cancer causing agents.  These were detected in
small amounts in smoke and soils near the source of the fires.
The preliminary analysis of the particulate matter did not reveal
any chemicals at levels of concern.

     Health Assessment.  The initial health interviews with
                                10

-------
medical personnel in the affected areas suggested that
subpopulatlons, such as individuals with asthma and chronic
obstructive lung disease, may experience exacerbation of their
symptoms.  Special health concerns, warnings, advisories, and
precautions were clearly warranted for these individuals.  It was
felt that the air pollution impact of the fires did not appear to
be life threatening under the exposure conditions observed in
March 1991 but, if meteorological conditions changed, such as
poor air mixing or plume touch down, there could be adverse
health effects for susceptible individuals.  The long term
effects are not readily ascertainable at this time due to
insufficient data on the populations exposed, the composition of
the smoke plume, the impact of the oil pools and long term
meteorological patterns.  The problem was particularly aggravated
in Kuwait where the scientific infrastructure was severely
damaged.

The Gulf Regional Air Monitoring Plan
     In addition to the air monitoring campaigns, the U. S.
Persian Gulf Risk Evaluation Team developed the finlf Regional Air
Monitoring Plan in conjunction with the Saudi Arabian Meteorology
and Environmental Protection Administration.*  The plan was
needed as a follow on to the initial air monitoring campaigns and
health surveys for the following reasons:

     1.   To provide an early warning health advisory system for
     the Gulf Region to respond to the air pollution resulting
     from the Kuwait oil fires.

     2.   To track the air pollution from the Kuwait oil fields
     over time to assess the potential long term health and
     ecological effects.

     3.   To facilitate evaluations of models which were used to
     predict the local and regional scale behavior of the oil
     field emissions.

     The plan was developed with King Faud University of
Petroleum and Minerals in Dhahran, the Cooperation Council for
the Arab States of the Gulf (CCG), and the Saudi Arabian Oil
Company (ARAMCO).  Based upon extensive discussions, a
prioritized plan was proposed, which consisted of five separate
phases.  The first phase dealt with the implementation of an
early warning system.  A system was proposed based on an
adaptation of the USEPA's Pollutant Standards Index (PSI).9  The
warning system was intended particularly for Kuwait and the
Eastern Province of Saudi Arabia.  The second phase dealt with
the creation of a PMi0 Monitoring Network using portable PM10
monitors.10-" . PM10 focuses on those particles with aerodynamic
diameters smaller than 10 micrometers, which are likely to be
responsible for adverse health effects, because of their ability
to reach the lower regions of the respiratory tract.  The
                                11

-------
 portable PM10 monitors had the advantage that they could operate
 without the need for electrical power,  which was critical in
 Kuwait because there was no electrical  power there.   In addition,
 there was no PM10 monitoring in the Gulf Region and the principal
 impact from the fires was in the form of participate.   The
 network was implemented using portable  PM10 monitors in Kuwait,
 Saudi Arabia and Bahrain.  These were furnished by the USEPA.
 The third phase called for the characterization of the plume by
 conducting aerial sampling.  The fourth phase called for the
 development of a more complete profile  of the smoke plume
 constituents.  This phase of the plan introduced several new
 technologies to the region, along with  the required training.
 As a result, we were able to develop the capability within Kuwait
 and Saudi Arabia for aerosol and particulate monitoring.  The
 fifth and most ambitious phase called for a more extensive air
 monitoring network in the Gulf region which would both build upon
 the existing networks in Saudi Arabia and Kuwait and extend into
 the other Gulf nations affected by the  Kuwait oil fires.  The
 objectives of the fifth phase were met  to some extent in both
 Kuwait and Saudi Arabia.

 Comparison with Other International Efforts
      In addition to the U.  S.  effort, there were other
 international efforts.  Figure 5 compares particulate and SO,
 data collected by the Kuwait Environmental Protection Council
 (KEPC), the French government12, and the U. S. Persian Gulf Risk
 Evaluation Team.   Different measures of particulate  are used
 complicating the comparisons.   The KEPC collected total suspended
 particulate and PM10 concentrations (measured with portable PM10
 monitors provided by the USEPA).   The French collected suspended
 particulate measured by the black smoke method.   The US Team
 measured total particulate  during its initial campaign in March
 1991 and later introduced portable PM10  monitors to the region.
 In general,  the black smoke method,  the total suspended
 particulate measurement and the total particulate measurement
 methods would all give higher readings  than the PM10 measurement
.method, which focuses on those particles with aerodynamic
 diameters smaller than 10 micrometers.   Further complications are
 the different time periods  during which the measurements are made
 and the different sampling  locations in both Kuwait  City and in
 the oil fields and the limited amount of data collected.  The
 reader must keep all of these limitations in mind when examining
 the data.   In compiling these statistics,  I took the liberty of
 averaging across  both time  and space calculating PMi0and SO,
 arithmetic means  for Kuwait City,  Ahmadi village and hospital and
 the Kuwait oil fields.    Figure 5 compares average concentrations
 measured in Kuwait City (before and during the fires),  Ahmadi,
 the oil fields and for purposes of comparison Los Angeles,  CA and
 Pittsburgh,  PA.13  The arithmetic means  of the particulate
 measurements are  all of a comparable magnitude given the
 different instrument methods that were  used to collect the data.
 As would be expected,  the particulate measurements in  the oil
                                12

-------
fields are higher  than those in Kuwait City.  The averages
represent measurements collected in the March-April-May,  1991
time period.  The  PM10 arithmetic mean concentration of 259  ug/ra3
in Kuwait City  is  significantly above the highest annual
arithmetic mean concentrations observed in Los Angeles of 55
ug/m1 and in Pittsburgh, PA  of  43  ug/m3.  Interestingly, the
Kuwait City April  19901* average suspended particulate matter
concentration of 460  ug/m1 is greater than  the average suspended
particulate concentration of 252 ug/m1 observed in Kuwait City in
March-April 1991 during the  fires.  The PM10 and  particulate
average measured by the French Team are comparable  in magnitude
to the KEPC average.   This is not entirely unexpected because
measured particulate  concentrations in Kuwait were  some of  the
highest measured in the world before the fires and  will be  high
again now that  the fires are out.   This is due to wind blown
dust.  The particulate measurements collected in Ahmadi and in
the oil fields  were much higher than those observed in Kuwait
City as would be expected.   The particulate averages are  based on
limited data.   Al  Ahmadi village and hospital are very close to
the oil fields.  In fact,  Al Ahmadi hospital was impacted by an
oil fire a quarter mile away and the high concentrations  reflect
this.

Figure 5. Comparison  of particulate and SOa average levels
measured in Kuwait and the United States before and during  the
fires.

                 (April 990)
  KimraftCttv

DuHnaVmOm
  KiMMhOty

        KEPC
                                              I 480
                (March-May 1991)

                  tot \
                                    280
       Ahmad (VWag* and HcMptUl)

          U.S. TMRI p*HT.r~
                                             J«"
                               1B7
                                                J514
 Kuwait CM FW*

     U.S. Tarn

       French
                                                             | 742
                                                       696
     U.S.CMu   (Annual Means. 1990)
       Lo.Ano.i-
                                 13

-------
     The highest peak PM10 concentrations observed in Kuwait were
concentrations of 5400 ug/m3 measured by the U. S. Team for a 15
minute period, 2030 ug/m3 measured by the French Team for one
hour and 1160 ug/m3 measured by the KEPC.  The magnitude of these
concentrations compare with a  PM10 concentration of 826  ug/m3,
which was recorded on March 23,  1988 at  a rural site in the State
of Washington and attributed to  wind blown dust.

     The average SO, concentration measured in Kuwait City in
April 1990 before the war was  5  ug/m3.   In March 1991, the KEPC
collected SO2 measurements at four temporary hospital locations
in Kuwait City.  The composite average of the  S02 measurements at
the four temporary locations was 35 ug/m3.  In April, the KEPC
reestablished both its Mansoriya and Reqa air  monitoring sites  in
Kuwait City, which recorded monthly averages of 8  and 4 ug/m3,
respectively.  These concentrations are  comparable to those
measured before the war.   An examination of Figure 5 shows
significantly higher SO, measured by the French Team in both
Ahmadi and in the oil fields.  The higher average  of 157 ug/m3
calculated for Ahmadi village  and hospital is  based  upon 11
hourly measurements collected  on two days (March 31  and April 1).
The higher average of 368  ug/m3 in the  Kuwait oil fields is based
upon 16 hourly measurements taken on three separate  days (March
30, April 3, and April 4)  at three different locations.  The S03
measurements ranged from  0 to  948 ug/m3.   The average
concentrations for SO, measured in Kuwait City compare with
annual SOa  averages of 10 and 73 ug/m3 for Los  Angeles and
Pittsburgh, respectively.

CONCLUSIONS
     The U. S. Persian Gulf Risk Evaluation Team successfully
accomplished its mission  to evaluate the  air pollution  impact of
the Kuwait oil fires in spite  of  overwhelming  problems  that had
to be dealt with.  The U.  S. Team's initial air monitoring
appraisal has largely been substantiated  by the  French  Team and
by the KEPC.  In addition  to the initial  air monitoring and
health assessments, the U. S.  Team developed the Gulf Regional
Air Monitoring Plan, most  of which was implemented.   The Plan was
adopted by the World Health Organization  and became  the basis for
the international air monitoring effort that followed.

     Early in the crisis, there  were predictions that the fires
would cause catastrophic health  effects.  Accordingly,  this paper
focussed on the principal pollutants - particulate,  S0a, and
HaS - because these were the ones known to have acute health
hazards at high concentrations.   Premature death of  susceptible
people (individuals with asthma  and other lung diseases and high
risk groups including the elderly, children, and pregnant women)
can occur when polluted air remains trapped over a populated area
for several days.  Fortunately,  that did  not occur.  Prevailing
winds effectively dispersed smoke from the oil  fires during the
time when most of the wells were burning, and  most of the fires
                                14

-------
were extinguished before the beginning of the winter season when
weather inversions would have been more likely to cause extended
periods of stagnant air over Kuwait city.  The air monitoring
data showed that the particulate levels were high, but that the
S0a levels were significantly lower than predicted.   In fact,  the
average SOa levels in Kuwait City were similar to levels measured
in U. S. cities.

     Under normal conditions in Kuwait, particulate levels are
high due to the sandstorms.  The difference in particulate matter
between normal conditions versus the oil fires is due to the
content of the particulate.  Included in the particulate matter
from the fires were polycyclic aromatic hydrocarbons and trace
metals such as nickel, chromium and vanadium, which are known or
suspected cancerous agents.  These were largely detected in small
amounts in smoke and soils near the fires, but not at sampling
stations located downwind.  The unique nature of this
environmental problem - intermittent exposure to pollution from a
large yet declining number of fires - will make long-term health
assessments extremely difficult.  Fortunately, the fires were
extinguished way ahead of schedule.

REFERENCES

1.   Environmental Crisis in the Gulf, the U. S. Response. U.  S.
Environmental Protection Agency, Washington, D. C., 1992.

2.   Air Quality Criteria for Particulate tffflttf"" and Sulfur
Dioxidef u. S. Environmental Protection Agency, Environmental
Criteria and Assessment Office, Research Triangle Park, NC 27711,
December 1981.

3.   M. Glasser, L. Greenberg and F. Field, "Mortality and
Morbidity During a Period of High Levels of Air Pollution, New
York, November 23-25, 1966."  Arch. Environ. Health, Vol. 15,  pp.
684-694, 1967.

4.   Air Pollution in Donora. Pa.r Epidemiology of the Unusual
Smog Episode of October 1948, Public Health Bulletin No. 306,  U.
S. Public Health Service, Washington, D. C., 1949.

5.   Kuwait Oil Firesjlnteraqency Interim Report. U. S.
Environmental Protection Agency, Washington, D. C., April 3,
1991.

6.   EPA Journal, U. S. Environmental Protection Agency, Office
of Public Affairs, Vol. 17, Number 3, Washington, D. C.
July/August 1991.

7.   J. Mulik, AREAL Director*s Monthly Status Report. U. S.
Environmental Protection Agency,,Atmospheric Research and
Exposure Assessment Laboratory, Research Triangle Park, NC, April
                                15

-------
10, 1991.

8.   W. Hunt, G. Start and A. Bond, Gulf Regional Air Monitoring
Plan, U. S. Persian Gulf Risk Evaluation Team, Dhahran, Saudi
Arabia, April 5, 1991.

9.   W. F. Hunt, Jr., "The U. S. Environmental Protection
Agency's Recommended Pollutant Standards Index (PSI)," presented
at the Critical Review of Air Pollution Index Systems in the
United States and Canada," 69th annual meeting of the Air
Pollution Control Assoc., Portland, OR, June 29, 1976.

10.  J. Schweiss, "Fundamental Importance of Saturation Sampling
and Air Monitoring Network Design," presented at the Air and
Haste Management Association Meeting, Los Angeles, June 1989.

11.  D. Arkell, "A low cost saturation sampling method,"
presented at the Pacific Northwest International Section, Air and
Waste Management Association, Spokane, WA, November 1989.

12.  G. Thibaut, P. Lameloise, R. Masse, J. LaFuma, A. Person and
M. Pasquereau, Final Report - Measurement Campaign of the
Regional Mobile Laboratory for Measurement of Air Quality in
Kuwaitr 27 March to 4 April 1991, Surveillance de la Qualite de
L'Air en Ile-De-France, Paris, France, May 27, 1991.

13.  National Air Quality and Emissions Trends Report, 1990, EPA-
450/4-91-023, U. S. Environmental Protection Agency, Office of
Air Quality Planning and Standards, Research Triangle Park, NC
27711, November 1991.

14.   Monthly Environmental Quality Data, April 1990, Ministry of
Public Health, Kuwait Environmental Protection Office.
                                16

-------
              Session 2
Measurement of Polar Volatile Organics
     Joachim D. Pleil,  Chairman

-------
        MICROBIAL VOLATILE ORGANIC COMPOUND
    PRODUCTION BY INDOOR AIR MICROORGANISMS
                                    Joan C. Rivers
        ManTech Environmental Technology, Inc., Research Triangle Park, NC 27709

                        Joachim D. Pleil and Russell W. Wiener
               Atmospheric Research and Exposure Assessment Laboratory
         U.S. Environmental Protection Agency, Research Triangle Park, NC 27711

ABSTRACT
      Indoor air quality is  a significant environmental  and occupational health issue.  The
production of volatile  organic compounds  (VOCs) by metabolically active microorganisms is
important to indoor air quality because many microbial VOCs  have offensive odors and the
potential to cause adverse health effects. The identification of microbial VOCs and factors which
influence their production is important to understanding the contribution of microbially produced
VOCs to total indoor air quality. In this study, several unidentified funga! and bacterial strains
were isolated from indoor  air environments  and grown on a variety of substrates.  VOC
characterizations were conducted on  microbial  headspace  air  by  gas  chromatography/mass
spectroscopy analysis. Several VOCs were detected that may adversely affect indoor air quality.
Some of these compounds  include  methyl mercaptan,  dimethyldisulfide, dimethyltrisulfide,
trimethylamine, and indole.  Factors which influence microbial VOC production were identified.
      The research described in this article has been funded in part by the U.S. Environmental
Protection Agency  through contract 68-DO-0106.   It has  been subjected  to Agency review and
approved for publication.  Mention of trade names or commercial products does not constitute
endorsement or recommendation for use.

INTRODUCTION
      Volatile organic compounds (VOCs) resulting from microbial metabolism may significantly
contribute to indoor air quality. With  increasing  awareness in energy conservation, modern day
building construction reduces outdoor air exchange rates, thus trapping compounds inside buildings
and exposing occupants to VOCs at higher concentrations and for longer periods of time than ever
before.  Microbial VOCs may accumulate within buildings whenever conditions are favorable for
microbial growth and air ventilation rates are low.
      Health  effects associated with exposure  to VOCs produced by actively metabolizing
microbial species have been hypothesized but not well documented.112 Such health effects include
annoyance, irritation of the  mucous membranes,  headaches,  dizziness, and nausea. In a recent
report, two compounds, namely l-butoxy-2-propanol and 2-methyl propionic acid, were detected
in air samples taken in from a "tight" building where occupants complained of foul odors.  One
of the compounds, l-butoxy-2-propanol, was detected from the headspace gas of a laboratory-grown
bacterial culture isolated from the heating, ventilating,  and air conditioning (HVAC) system in the
building. During a survey of Canadian  homes, three compounds of possible fungal origin, namely,
3-methyl-l-butanol, 2-hexanone,  and 2-heptanone were detected by gas chromatography/mass
spectroscopy (GC/MS) analysis of the  indoor air  in these environments.4
      In order to determine the contribution of  microbial VOCs to indoor air quality, common
microbial metabolites must be identified and characterized further. Since conventional bioaerosol
monitoring methods sometimes fail to identify sources of microbial contamination, the development
of microbial VOC analysis  as a tool to identify sources of  contamination would be extremely
                                          19

-------
beneficial to building investigators. Microbial VOC analysis by GC/MS has long been used in the
food and agricultural industries to identify spoiled foods5 and contaminated foodstuffs.6"9
      The purpose of this study was to identify VOCs produced by several strains of bacteria and
fungi isolated from building environments. The microorganisms were grown on different types of
laboratory media and then analyzed for VOC emissions by GC/MS. The influence of speciation
and the influence of substrate composition on VOC production were examined.  Headspace gas
analysis of a mixed microbial culture obtained from a HVAC filter was used to demonstrate the
effect of culture age on VOC emission profiles.  The application of the GC/MS technology for
measuring microbial  VOCs emitted  from  biologically contaminated building materials  and
identifying microbial VOCs that may pose a human health problem in indoor air environments was
addressed.

METHODOLOGY
Microbial Isolation
      Microorganisms were collected from several sources. Air samples were collected with two-
stage Andersen samplers in the basement stairwell of the EPA Annex building located in Research
Triangle Park, North Carolina, on trypticase soy agar (TSA) plates.  After incubation for several
days at 30 °C, the plates were examined for bacterial and fungal growth. Several predominant
fungal (numbered F1A-F1B) and bacterial (numbered  B1A-B1C) strains were picked from the
plates and chosen for further study.  Another fungal strain (numbered F1C) was isolated from an
air-handling unit in a state office building in Takoma, Washington. Even though the  strains were
not taxonomically identified, all of the isolates exhibited unique colony morphologies and were
considered to be different species. Studies were  also conducted on mixed strains found in house
dust collected on HVAC filters.

Microbial Growth
      The evolution  of  VOCs was  monitored with respect to microbial isolate and  media
composition. The bacterial and fungal strains were isolated to purity on TSA and malt extract agar
(MEA) plates, respectively.  Bacterial strains were grown under static conditions in trypticase soy
broth (TSB) at 30 • C for several days and used to inoculate slants of TSA.  Spore suspensions
prepared from mature fungal growth on  MEA plates served as the inocula for TSA and MEA
slants used for the fungal analyses.  Bacterial slant  cultures were grown at 30 *C for a period of
several days, depending upon the growth  rate of the individual strains.  Slants of MEA and TSA
inoculated with the fungal species were incubated for 3-5 days at 25 ' C.  Slants were usually grown
and analyzed in duplicate.
      In another set of experiments, small sections of residential filters (ranging in  weight from
0.5 to 1.0 g) were aseptically placed  in sterile 200-mL gas washing bottles.  Filter sections were
incubated in TSB at room temperature for several days under static conditions. Sterile water was
added to the system periodically to account for evaporation.  For time course studies, the washing
bottles were  connected directly to the GC/MS system, and humidified zero air (National Specialty
Gases, Scientific Grade, Research Triangle Park, NC) was passed through the bottles at a rate of
30 air exchanges per hour. Preliminary experiments indicated that the  zero air is not a potential
source of contamination for the growth media. The evolution of VOCs was monitored with respect
to time (i.e., age of the culture).

GC/MS Analysis
      The HVAC mixed-culture reactions and the slant cultures were analyzed for VOC emissions
by GC/MS by using a Nutech 320-1 electronics module (Nutech Corp., Durham, NC) and an ITS40
ion-trap-based GC/MS system (Finnigan MAT, San Jose, CA). The washing bottles containing the
mixed cultures  were  connected  directly  to the instrumentation, whereas the slant tubes were
                                           20

-------
removed from the incubator and placed, uncapped, in a clean gas washing bottle fitted with Teflon
connectors and sampling lines.  The systems were purged with humidified zero air at a rate of 30
air exchanges per hour. The compounds eluted from the system were tentatively identified through
a search of the Finnigan general purpose data base and the EPA/NIH mass spectral data base.
When possible, compound identifications were confirmed with known standards.  VOC emissions
from uninoculated culture tubes, sterile culture media, and dry filters were monitored for quality
assurance purposes.

RESULTS AND DISCUSSION

Fungal VOC Emissions
      The  fungal isolates, F1A-F1C, were grown on TSA and MEA slants for 3-5  days prior to
analysis to examine the effects of substrate composition and speciation on VOC production.  Strain
F1A produced relatively few VOCs when grown on TSA and MEA media (data not  shown). The
organism produced methyl ethyl ketone on both types of media, but only isoprene  was detected
from the TSA culture. Strain FIB did not produce any  detectable levels of VOCs on either type
of media, except for a small amount of ethanol on MEA (data not shown).  Strain F1C produced
the most interesting results of the three isolates (Figure 1).  Methyl mercaptan, dimethyisulfide, and
dimethyldisulfide were produced by the isolate  when  grown  on  TSA media.  Conversely,
acetaldehyde, ethanol, and a 5-carbon alcohol were produced by F1C on MEA media. Another
peak was detected from the MEA culture and tentatively identified as a 4-carbon alcohol. The
results from this study indicate that speciation and substrate composition are important factors for
VOC production.   Borjesson  et al.10 demonstrated that substrate  composition  affects VOC
production by the fungus Penicittium auraniiogriseum, and a change in carbon source affects terpene
production by Ceraiocystis sp.11

Bacterial VOC Emissions
       The effect of speciation on VOC production was also demonstrated with the three bacterial
isolates included in the study. The isolates, B1A-B1C, were grown on TSA slants for 48 h prior to
VOC analysis. Table I indicates the VOCs produced by the three organisms under the specified
growth conditions. Several compounds such as methyl mercaptan, 2-methyl propanal, methyl ethyl
ketone, 1-butanol, and n-hexanal were produced by  all of the organisms.  Compounds such as
acetaldehyde, ethanol,  dimethyldisulfide, n-heptanal, dimethyltrisulfide, and benzaldehyde were
produced differentially by the three species.  The differences in the VOC profiles probably reflect
the individual metabolisms of the three isolates tested.

Mixed Culture VOC Emissions
       Sections of HVAC filters covered with a fine layer of house dust were incubated in sterile
gas washing bottles with TSB as the growth substrate to illustrate that VOC emissions change with
respect to  time in a mixed culture reaction.  House dust was chosen as the microbial inoculum
because it contains many organisms, both fungal and bacterial, common to indoor air environments.
Figure 2 illustrates the changes in VOC production with  respect to time for the culture. After 18 h
of incubation, no VOCs were detected outside of those  found with the uninoculated medium. By
48 h, methanol,  methyl mercaptan, ethanol, and a 5-carbon alcohol were detectable, and growth
was visibly apparent in the  culture  flask.  By 72 h,  numerous  additional  VOCs were detected
including trimethylamine, dimethyldisulfide, dimethyltrisulfide, indole, and several unidentifiable
peaks.  After 90 h of incubation, phenol was detected, along with increases in indole production.
       This study illustrated that the specific microbial VOCs emitted from a mixed culture are a
function of culture age. The variation in VOC emissions with respect to time is expected, for it
directly reflects the metabolic changes resulting as the  microorganisms successively use different
substrates in the media, first the simple sugars and then the complex substrates, such as peptones
                                            21

-------
and fatty acids.  Ethanol, a main by-product of glucose fermentation, appeared early on in the
experiment and subsided as glucose was depleted from the media.  Methyl mercaptan and other
sulfur-containing compounds appeared later in the experiment and were likely a result of amino
acid degradation.  Indole, an intermediate formed in tryptophan biosynthesis and degradation,
appeared very late in the experiment.

CONCLUSIONS
       The GC/MS method employed in this study is useful for the identification of VOCs
produced by strains of bacteria and fungi common to indoor air environments  when grown on
laboratory  media.  Several  of  the  compounds  identified,  such  as  methyl  mercaptan,
dimethyldisulfide, dimethyltrisulfide,  trimethvlamine,  and indole, are odor irritants and  could
negatively impact indoor air quality.  The results of this study indicate that VOC production is
dependent upon the species of organism being tested, substrate composition, and culture age. In
order  to use  GC/MS  analysis of microbial  VOCs  as an  index  of microbial growth  and
contamination in indoor air environments, further work of this type is needed.  Since substrate
composition affects VOC production, the next step in the process is to identify VOCs produced by
common indoor air microorganisms grown on different building substrates  such as ceiling tile and
carpeting. The identification of a VOC panel unique to microorganisms and produced routinely
in biologically contaminated buildings would be beneficial in the diagnosis of "sick" buildings or
work environments with poor indoor air quality.

REFERENCES
1.  R.A. Sampson, "Occurrence  of moulds in modern living and working  environments," Eur. J.
Epidemiol. 1: 54-61 (1985).
2. S. Batterman, N. Bartoletta and H. Burge, "Fungal volatiles of potential  relevance to indoor air
quality,"  Proceedings of the 84th Annual Meeting of A&WMA. Vancouver, British, Columbia,
Document # 91-62.9, 1991.
3.  C.E. McJilton, SJ.  Reynolds,  AJ, Streifel and R.L. Pearson, "Bacteria and indoor  odor
problems- three case studies," Am. Ind. Hyg. Assoc. J. 51: 545-549 (1990).
4.  J.D. Miller, A.M. LaFlamme, Y. Sobol, P. Lafontaine and R. Greenhalgh, "Fungi and fungal
products in some Canadian homes," Int. Biodeterioration 24: 103-120 (1988).
5.  L.R,  Freeman, G.J. Silverman, P. Angelini, C. Merritt, Jr. and  W.B. Esselsen, "Volatiles
produced by  microorganisms isolated from refrigerated chicken  at  spoilage," Appl. Environ.
Microbiol. 32:  222-231 (1976).
6.  E. Kaminski, S. Stawicki and E. Wasowicz, "Volatile flavor compounds produced by molds of
Aspergillus. Penicillium. and fungi imperfecti," Appl. Microbiol. 27: 1001-1004 (1974).
7. E. Wasowicz, E. Kaminski, H. Kollmannsberger, S. Nitz, R.G. Berger and F. Drawert, "Volatile
components of sound and musty wheat grains," Chcm. Mikrobiol. Tcchnol. Lebensm. 11: 161-168
(1988).
8. D. Tuma, R.N. Sinha, W.E. Muir and D. Abramson, "Odor volatiles associated with microflora
in damp ventilated and  non-ventilated bin-stored bulk wheat," Int. Food Microbiol. 8:  103-119
(1989).
9. T, Borjesson, U. Stollman, P. Adamek and A. Kaspersson, "Analysis of volatile compounds for
detection of molds in stored cereals,"  Cereal Chem. 66: 300-304 (1989).
10. T. Borjesson,  U. Stollman and J. Schnurer, "Volatile metabolites and other indicators of
Penicillium aurantiogriseum growth on different substrates." Appl. Environ. Microbiol. 56:3705-3710
(1990).
11. E. Sprecher and H.P. Hanssen, "Influence of strain specificity and culture conditions on terpene
production by fungi," Planta Med. 44: 41-43 (1982).
                                           22

-------
      Table I.  VOCs produced by three bacterial isolates grown on TSA media.'
                                                     Bacterial Isolate
Compound	Media Blank	B1A	BIB	B1C
acetaldehyde                       -                         +
methyl mercaptan                  -             +           +           +
ethanol                           -             +           +
acetone                          +             +           +           +
Freon 113                        +             +           +           +
2-methyI propanal                  -             +           +           +
methyl ethyl ketone                 -             +           +           +
3-methyl butanal                  +             +           +           +
1-butanol                          -             +           +           +
n-pentanal                         -                         +
1-pentanol                         -                         +           +
dimethyldisulfide                   -             +           -           +
n-hexanal                          -             +           +           -f
n-heptanal                         -             -           +           +
dimetbyltrisulfide                   -             +           -           +
benzaldehyde                       -             -            +          .
  * (+) = VOC detected; (-) = VOC not detected.
                                     23

-------

                                             I
                MM    4200    4800
                   Scan Number
                                  MM
                                                   I
                                                     I
                                                                  H
                                                         i
                                                        •'•"•—*"»«•- *•—-«,—.
                                              MM
                                                              Scan Number
                                                                MOO
 Figure 1.     Chromatograms illustrating the effect of media composition on VOC emissions.
             VOC  profiles are depicted for the  fungus F1C grown on (A) TSA media  and
             (B) MEA media.

JSf
'5
^e
I
B- -
4000 -r-
<-
_OC
|
£

A

! f ,
1 	 L 	 '
	 1 — 	 1 — — i 	 1 	 r 	 •
3000 3600 4200 4800 5400
Scan Number
C
1
i
1 1 ,
1
1 1 ' 1
«St_ ..... ft „ . ^ Jj
1 ' T 	 1— 	 T 	
3000 3600 4200 4800 5400
                                              4000
                                            -«
                                            f

:
i
i
B

•j
1 [
XLi. .lrt.lf ^, ^.jyj ^

3000 3600 4200


.. _J

i 	 1 	 [
4800 5400
                                             4000
                                            0£
                                            I
                  Scan Number
                                                            Scan Number
1
-
I
1
1
1
L




!
uiu;
— r~ 	
D i


1
, L




yj

                                                           3600
                                                                  4200    4800
                                                                               5400
                                                            Scan Number
Figure 2.
Chromatograms illustrating the effect of culture age on VOC emissions. House dust
    added to TSB in a gas washing bottle and incubated at room temperature  VOC
   files are depicted for the culture at (A) 18 h, (B) 48 h, (C) 72 h, and (D)  90 h
                                         24

-------
         MOISTURE MANAGEMENT TECHNIQUES APPLICABLE TO
            WHOLE AIR SAMPLES ANALYZED BY METHOD TO-14
          Larry D. Ogle, David A. Brymer, Christopher J. Jones and Pat A. Nahas
                                 Radian Corporation
                                8501 North Mopac Blvd.
                                   P.O. Box 201088
                               Austin, Texas 78720-1088


ABSTRACT
      Analysis of polar organic compounds collected in canisters using US EPA Compendium
Method TO-14 is of interest to a number of industries and agencies.  However, it is commonly
known that moisture in the sample can interfere with the analysis. Most methods used to remove
water also remove the light polar compounds.  This paper will describe a method developed to
reduce the amount of water delivered to the analytical system after cryogenic concentration.  The
method has been determined to improve compound retention time stability, increase analytical
precision, and give more reproducible recoveries of polar and non-polar compounds independent
of sample relative humidity.

INTRODUCTION
      Cryogenic concentration and thermal desorption of water into a chromatographic system
during the analysis of ambient air  for volatile organic compounds (VOCs) has been shown to
adversely affect chromatography, sensitivity and/or detector reliability.1"4  When using subambient
chromatography, water concentrated from the sample can form ice plugs in the column resulting
in poor peak resolution and retention time shifts, thus making compound identification difficult.
The  moisture can also extinguish a flame ionization detector or exceed the pressure increases
tolerated by a GC/MS system during analysis.  Nation membranes and sorbents may be used to
remove moisture from the sample prior to cryogenic concentration, but they have been shown to
partially or completely remove small, polar organic compounds such as alcohols, aldehydes and
ketones. These devices may also be a source of contamination or carryover from sample to sample
if not properly conditioned.
      A novel approach to the management of water concentrated from ambient samples such that
it does not adversely effect chromatography or detector systems has been developed. It is based
on condensation of moisture from the saturated carrier gas stream during thermal desorption. A
Moisture Management System (MMS) was installed on a Radian designed and built automated
cryogenic interface used to analyze ambient air samples. The MMS system was then evaluated for
recoveries of compounds having a wide range of polarities and volatilities.
      A statistically based experiment was designed to study the inter-relationship between the
Moisture Management System (MMS), relative humidity, compound class, compound concentration,
interface autosampler position, and canister size and the effects of each of these parameters on
precision and accuracy of analyte concentration measurements.  The results of these experiments
led to further studies designed to determine the optimum operating parameters for the MMS.

EXPERIMENTAL DESIGN
      The MMS consists of an aluminum block which encases a short length of 0.125 inch o.d.
tubing between the cryogenic trap and the transfer line to the GC. The device is passively cooled
by nitrogen gas from the cryotraps as liquid nitrogen is sprayed on the traps during  sample
                                          25

-------
concentration. The temperature of the device is regulated by an 80 W cartridge heater controlled
by an Omega temperature controller.
       The system is configured such that the sample flows through the MMS during concentration.
During thermal desorption, the chromatographic carrier gas flow backflushes the traps and transfers
the desorbed organics and water vapor through the MMS. Thermal desorption of the cryotraps at
600°/minute supersaturates the helium gas with water vapor which then condenses in the cool MMS
region. Through the manipulation of temperature, desorption time and system configuration, the
amount of water removed and the recoveries of organic compounds of interest can be  maximized.
       Table I shows the parameters chosen for the statistical analysis of the MMS.  As can be
observed, a complex study design was chosen to determine the effects of the MMS temperature on
compound recovery and precision. The study design also determined the effects of variables such
as canister size, relative humidity in the canister, concentration of the analytes, different mixtures
of compounds, and the manifold position on the automated interface on precision  and accuracy.
The experimental matrix was designed to evaluate treatment combinations in such a manner to
determine the main effects and interactions  of greatest interest. A randomized scheme was used
to assign treatment combinations to the experimental units.
       Each canister was analyzed four times over a period of five days with  the MMS at 130°C,
twice at 0°C and then again at 130°C.  Between the second and  third  analyses, canisters on
manifold positions  1 and 2 were switched with those on positions 8 and 7, respectively. All analyses
were by name lonization Detector.  Four determinations were lost due to a liquid nitrogen leak
exhausting the supply of liquid nitrogen during the analyses. This loss did not  adversely effect the
outcome of the study.
       The results of this study led to a second study designed to maximize compound recoveries
and minimize water transfer to the column through optimization of the operating temperature for
the MMS and the  cryotrap desorption time. These variables were systematically changed and
compound recoveries and reproducibilities were calculated.  The optimum conditions  were
determined and seven replicate analyses of a standard canister were made to establish precision
and accuracy.

RESULTS AND DISCUSSION
       The results of the study outlined in Table  I were analyzed using a SAS statistical program.
The following conclusions were  drawn from this statistical analysis: the valve position on the
manifold was not significant; recoveries of methanol, ethanol, isopropanol, and 1,4-dioxane were
affected when the MMS was at 0°C; the recoveries of hydrocarbons, nalogenates, aromatics, ethers,
aldehydes and ketones were not affected; there were  no observed effects caused  by compound
concentrations; recoveries of compounds not affected by the MMS were weakly, but significantly,
affected by compound mixture and relative humidity; the effects of the MMS on these compounds
was less than the effects of mixture and humidity; and the residual effects after removing the effects
of the tested parameters represented system,  including hardware, variability and were less than one
percent at high concentrations and 4 to 5%  at low concentrations.
       The recoveries of the alcohols and  1,4-dioxane were depressed by the condensation of
moisture in the MMS at 0°C.  In addition,  the  quantitative results for these compounds had a
higher degree of variability than the non-polar test compounds. The coefficients of variation for
the four analyses ranged between 50% at high  concentrations and 20%  at  low concentrations.
Coefficients of variation for the non-polar compounds (unaffected  by the MMS) were around 1%
at high concentrations and 5% at low concentrations.
       The conclusion that relative humidity and compound mixture have an affect on the results
was expected. Even though most of the moisture  is removed by the MMS, the  amount of moisture
representing saturation of the carrier gas at  that particular temperature will be transferred to the
                                           26

-------
column. Since the injection time was six minutes and the MMS was slowly wanning from (PC to
around 25°C during this time due to conductive heating from the  cryotrap, some water was
transferred to the column which affected the chromatography of all compounds in the retention
window in which water eluted. The weak significance of compound mixture verifies that there is
some interaction between compounds during trapping and chromatograpby. However, most of the
interaction is thought to be in the chromatography and subsequent integration of the peaks.
      A number of experiments were then performed to determine the optimum temperature for
the MMS, since operation at (TC affected the reproducibility of the polar organics (Study 2). The
optimum temperature was found to be 1S°C with a six minute injection time.  A standard canister
of mixture 1 (Table I) at 70% relative humidity and polar compound concentrations between 3 and
50 ppb was analyzed six times within one day. Table II provides a comparison of retention times
and recoveries determined for a selected group of compounds  on analytical systems with and
without a MMS. Reproducibility data for Studies 1 and 2 are presented in Table HI.

CONCLUSIONS
      The Moisture Management System is an effective tool for reducing the amount of water
delivered to the column during analysis  of VOCs.  The operating parameters must be optimized,
but under optimum conditions, the reproducibility and recovery of all organics is excellent at ppb
levels.  Recoveries of heavier VOCs and a variety of compound classes are unaffected by the MMS.
Compound mixture and relative humidity were determined in Study 1 to have small effects on the
reproducibility of  analyses.  Effects of system variability on VOC analyses was concentration
dependent, but was measured at 1 to 5% in this study.
                                    REFERENCES

1.    J.D. PleO, W.A. McClenny and K.D. Oliver, "Dealing with water in GC/MS analyses of
      whole air samples", presented at the  1989  Pittsburgh Conference and Exposition on
      Analytical Chemistry and Applied Spectroscopy, Atlanta, GA, March, 1989.

2.    J.D. Pleil, KJD. Oliver and WA  McClenny, "Enhanced performance of nafion dryers in
      removing water from air samples prior to gas chromatographic analysis", JA££A, 37:244-248,
      1987.

3,    L.D. Ogle, R.B. White, DA Brymer and  M.C. Shepherd, "Applicability of GC/MS
      instrumentation for the analysis of undried air toxic samples", Proceedings of the 1989
      EPA/APCA International Symposium on Measurement of Toxic and Related Air Pollutants,
      Research Triangle Park, NC, May, 1989, pp. 824-829.

4.    D.B. Cardin and C.C. Lin, "Analysis of selected polar and non-polar compounds in air using
      automated 2-dimensional chromatograpny", Proceeding* of the 1991 US. EPA/A&WMA
      International Symposium on Measurement of Toxic and Related Air Pollutants, Research
      Triangle Park, NC, May, 1991, pp. 552-557.
                                          27

-------
                                                         Table I
                                        MMS Validation Experimental Design
Temp, of
MMS
0° and 130°C
Canister
Number
1
2
3
4
5
6
7
8
Canister
Sizc(L)
15
6
6
15
6
15
15
6
Component
Mixture"
1
1
1&2
1
1&2
1&2
1
1&2
Relative
Humidity (%)
70
70
70
10
70
10
10
10
Relative
Concentration1*
High
Low
High
Low
Low
Low
High
High
Manifold
Positions
2-7
6
4
8-* 1
1-8
3
5
7-2
* Mixture 1 contains vinyl chloride, methanol, ethanol, acetone, diethyl ether, isopropanol, methylene chloride,
1,2-dichloroethane, benzene, cyclohexane, 1,4-dioxane, trichloroethylene, and toluene.

Mixture 2 contains propionaldehyde, 2,3-dimethylbutane, 2-butanone, 2-pentanone, methylisobutylketone, 1-octene,  1-nonene, p-
chlorotoluene, 1-decene,  t-butylbenzene, and n-undecane.
 High; Mixture 1: 57 to 1400 ppbv
 Low; Mixture 1:  1 to 28 ppbv
Mixture 2:  150 to 250 ppbv
Mixture 2:  3 to 5 ppbv

-------
                                                      Table II
                                Comparison of Retention Times and Recoveries for
                                  Selected Compounds With and Without a MMS
COMPOUND
Vinyl chloride
Methanol
Ethanol
Acetone
Diethyl ether
Isopropanol
Methylene chloride
n-Henane
1 ,2-Dichloroethane
Benzene
Cyclohexane
1,4-Dioxane
Trichloroethylene
Toluene
WITHOUT MMS
Retention
Time
(rain)*
9.07
11.03
13.76
14.18
15.38
15.60
NA
NA
NA
22.35
22.73
NA
NA
26.72
R.T.
Std.
Dev.
0.076
0.43
0.21
0.96
0.13
0.10
NA
NA
NA
0.064
0.056
NA
NA
0.045
Recovery"
10% RH
135
88.8
73.5
125
77.0
65.4
125
NA
112
100
102
56.3*
NA
Recovery"
70% RH
119
289
177
145
115
102
116
NA
104
100
86.2
95e
121
WITH MMS
Retention
Time
(min)c
8.22
10.09
12.94
13.35
14.88
14.66
NA
NA
NA
21.60
21.97
NA
NA
26.05
R.T.
Std.
Dev.
0.017
0.13
0.051
0.021
0.004
0.025
NA
NA
NA
0.012
0.058
NA
NA
0.024
Recovery*"
(15*C/70%
RH)
98.4
61.0
43.5
76.7
54.5d
85.6
103
98.6
100
90.3
36.1
96.0
98.3
•Represents 2 analyses each at 0, 50, 100 and 100+ percent RH
^Normalized to Benzene
'Represents 3 analyses each at 30 and 70 percent RH
"Diethyl ether and isopropanol coeluted during these determinations
•Trichloroethylene and 1,4-dioxane coeluted during these determinations

-------
                                                  Table III
                     Reproducibility of Replicate Analyses Under Study 1 Conditions and
                           Optimum MMS Conditions for Low ppb Concentrations
Compound
Vinyl chloride
Methanol
Ethanol
Acetone
Diethyl ether
Isopropanol
Methylene chloride
1,2-Dichloroethane
Benzene
Cyclohexane
1,4-Dioxane
Trichloroethylene
Toluene
Relative Standard Deviations
Study 1 Conditions'
RH = 70%
5.8
14
13
6.2
1.0
4.0
11
5.1
2.8
18
18"
13
RH= 10%
6.4
30
24
10
2.8
22
15
6.3
3.4
11
10
1.5
Relative Standard Deviations
MMSatlS^C*
1.1
3.1
4.0
1.6
2.6C
4.2
2.7
1.3
1.8
20
13
0.8
• Four replicates 5 days, MMS at 0°C for 2 runs and 130°C for 2 runs.
b Six replicates within the same day, RH = 70%
c Diethyl ether and Isopropanol summed due to incomplete separation
d 1,4-Dioxane and Trichloroethylene summed due to incomplete separation.

-------
              FIELD MEASUREMENTS OF ATMOSPHERIC POLYNUCLEAR
             AROMATIC HYDROCARBON CONCENTRATIONS AND PHASE
                             DISTRIBUTION AT TAMS SITES

                 Thomas J. Kelly, Jane C. Chuang, and Patrick J. Callahan
                               Battelle Columbus Operations
                                     505 King Avenue
                               Columbus, Ohio  43201-2693

                            Robert G. Lewis and Joachim Pleil
                  Atmospheric Research and Exposure Assessment Laboratory
                           U.S. Environmental Protection Agency
                     Research Triangle Park, North Carolina  27711-2055

Abstract
   This paper reports on sampling for vapor- and particle-phase polynuclear aromatic hydrocarbons
(PAH), at sites in Boston and Houston formerly used in the  Toxic Air Monitoring Study (TAMS).
The purposes of this work were 1)  to develop means for conducting  PAH sampling with unskilled
operators at sites  remote from  the analytical  laboratory, 2) to evaluate the performance of the
filter/XAD/denuder approach under those sampling conditions,  and 3) to obtain ambient measure-
ments of PAH concentrations and phase distributions in various  seasons at the two sites.  Sampling
was performed by shipping prepared filter/XAD modules and denuders to site operators in Boston
and Houston, and returning them in specially designed refrigerated  containers to prevent sample
degradation prior to extraction and  analysis.  The field sampling took place between August  1990
and August 1991 and included shipment and analysis of field blanks, performance of simultaneous
duplicate sampling, and separate extraction of some filter and XAD samples to assess the extent of
sampling artifacts for the volatile PAH species.  The shipping procedures prevented losses of PAH
from collected samples, maintained low blank levels, and simplified the sampling'procedures for the
field operators.  The field sampling and laboratory analysis methods provided precise measurement
of total atmospheric PAH levels, as evidenced by relative standard deviations ranging from 7  to 22
percent for the 19 target PAH  species  in the  duplicate field samples.  Contamination of samples
taken with the compound annular denuder was observed for some of the most volatile PAHs, due to
volatilization of these  compounds present as impurities in the commercial silicone grease used to
coat the  denuder.  This contamination  prevented  determination  of  phase  distribution for a few
compounds under some conditions.  However, for most of the target PAHs, phase distributions were
determined,  indicating a wide range of particle/vapor distribution, and clear seasonal changes in
those distributions.

INTRODUCTION
   Semivolatile organic compounds  in the atmosphere are defined as those which may be present in
both the  vapor and paniculate state simultaneously, their phase .distribution  being determined by
their volatility, the ambient temperature, and their  affinity for  the adsorbed phase composition on
atmospheric particles.  An important class of toxic semivolatile compounds is the polynuclear aro-
matic hydrocarbons (PAHs).1'5  These compounds can be collected by particle filters  followed by
sorbent traps, which  together collect the total  of particle and  vapor phases, but volatilization of
collected particle-phase material  from the filter prevents accurate determination of the ambient  phase
distribution.4'3  Knowledge of the phase distribution  is necessary to assess the potential toxicily and
environmental fate of the PAHs.  To  address this problem,  a high-volume compound annular
denuder (CAD) was developed,6 and was tested in a series of experiments  in Columbus, Ohio.7

-------
However, the Columbus  sampling  was conducted by careful and highly  skilled operators  at their
own laboratory;  use of the CAD in remote field sampling  was not attempted.  The aims of the
present  study were  to devise  means for deploying the filter/sorbent/CAD approach in sampling at
remote sites with unskilled operators, to evaluate the approach under those conditions,  and to obtain
PAH concentration and phase distribution data from the field sampling.

EXPERIMENTAL
   The two sampling sites for this work were formerly part of the U.S. EPA Toxics Air Monitoring
System  (TAMS) network.  One was  located  in  downtown  Boston, Massachusetts,  and the other
about 20 km east of downtown Houston, Texas, in Deer Park.  The Boston site is impacted heavily
by automotive traffic and general  urban sources, while the Houston  site is  in a semi-rural  area
downwind of large oil  refineries and chemical plants.  Sampling was conducted from August 1990
through August 1991 at both sites, on approximately every 14th day, commencing at 0600 local time
and continuing for 24 hours.  Collocated duplicate samples and field blanks were taken periodically,
and  field spikes  were taken at the start  of the study (see below).  The field  operators were local
residents who had served as site operators for the TAMS study, and who had no previous experience
in PAH measurements.
   The basic air sampler used a 104-mm Pallflex 2500-QATUP quartz-fiber particle filter followed
by a glass  vapor trap containing 55 g of Supel-Pak-2 precleaned Amberlite XAD-2  resin.8  This
sampler was operated  simultaneously  with  a  collocated identical  sampler equipped  with  a high-
volume CAD.5"' The inner walls of the CAD were coated with Dow Corning high-vacuum grease.
The  basic sampler was used to determine total PAH concentration, while the collocated denuder-
equipped sampler was  used to determine particle-associated  PAHs.   Vapor  phase  concentrations
were calculated by  subtracting denuder results from those obtained with  the basic sampler.  Both
samplers were operated at nominal flow rates of 110 L/min, with actual flows  measured at the time
of sampling.
   A total  of 43 field samples (22 in  Boston,  21 in Houston) were taken. For all but two sets of
samples from both sites,  the corresponding  filter and XAD-2 samples were combined and Soxhlet
extracted with dichloromethane (DCM) for 16 hours. For two samples from each site, the filter and
XAD-2  samples  were extracted separately using DCM in order to determine  artifact values.  The
DCM extract was concentrated by Kuderna-Danish (K-D) evaporation and the  extract  was analyzed
by gas chromatography/mass spectrometry (GC/MS) using procedures described elsewhere.5-9  The
estimated precision  for the analytical method is  10 percent.   The estimated detection limit for the
target compounds was 0.01 ng/m3 based  on  150 m3 of air sampled.  The objective of implementing
filter/XAD/CAD sampling at the TAMS sites was accomplished by rapid shipment and return of a
single package containing all the required sampling materials.  Sealed filter/XAD sampling modules
and precoated denuder assemblies were shipped to and from the two monitoring sites by commercial
overnight delivery  service.  For this procedure,  specially-modified ice chests were used that held
each component in  a stable, protected manner and permitted the addition of ice packs for the return
trip to Columbus, Ohio, for chemical analysis.  This procedure  simplified the  activities of the field
operators and minimized the chance of sample contamination.
   The vapor-phase and particle-bound levels of each target compound were calculated using the
following equations:

         FX,,,  =    P + V                                (1)
         FX,,   =    P + (1-E)V                            (2)
         V     =    (F^nd - FXj)                           £.

         P     =    FX^-V                              (4)
                                            32

-------
where     FX^j  =    Measured concentrations from filter and XAD-2 combined sample for non-
                      denuder sampler;
          FXj   =    Measured concentrations from  filter  and XAD-2 combined  sample  for
                      denuder sampler;
          P     =    Estimated concentration of particle-bound target compound;
          V     =    Estimated concentration of vapor-phase target compound; and
          E     =    Calculated denuder adsorption efficiency for each target compound.

RESULTS
   Method Evaluation.  Several approaches were used to evaluate the sampling methods.  Cleaned
XAD cartridges spiked with naphthalene-dj, acridine-d9, and chrysene-di2 were initially shipped to
and from the sites to serve as field controls.   Recoveries of  the  latter two  compounds were
essentially  identical  to  those  obtained  from  laboratory  controls,  while  that  of  the  volatile
naphthalene-d8 was about 20 percent less  (76 versus 96 percent).   These  results indicated minimal
losses of collected PAHs as a result of the sample shipping procedures.  Filter/XAD field blank
modules  were also shipped to and from the sites on several occasions.  Analysis of  these blanks
indicated PAH levels similar to those on blanks from previous, more controlled, field sampling.0-* -5
Furthermore, the measured blank levels amounted  to typically less than 10 percent of the levels
observed in field samples.  These results indicate that minimal sample contamination occurred as a
result of the snipping and handling procedures.  Additional evaluation of the method was  provided
by  side-by-side duplicate  samples at both sites.   Relative  standard  deviations for the 19 target
compounds from duplicate sampling averaged 11.5 percent in Boston and 14.9 percent in Houston;
considering individual compounds using duplicate data from  both  sites, relative standard deviations
ranged from 7 to 22 percent.  These results indicate that good quality control was maintained in the
field sampling.  One problem observed was contamination of some PAHs in samples collected with
the CAD.  This was traced to volatilization of PAHs present in  the silicone grease  and  released
during sampling, especially in warm weather.  This problem does not affect  measurement of total
PAH concentrations,  but did prevent determination of phase  distributions in some seasons for some
compounds.
    Amble^ Patai  The ambient concentrations of total (vapor + particle) PAHs from  the two sites
are summarized by season in Table I.  The PAH are  listed in their order of elution in the  GC
analysis; i.e., approximately in order of decreasing volatility.  The most abundant PAH found in air
from both Boston and Houston sites was naphthalene, and the least abundant PAH was  dibenzo[a,h]
anthracene for  most  samples.  In general, higher concentrations  of most 4-  to 7-ring PAH were
found in Boston.  The 2- to 3-ring PAHs showed comparable concentrations at the two  sites, except
that in the winter the concentrations of most 2- to 3-ring PAH were higher in samples from  Houston
than in those from Boston.  The higher concentrations of the relatively volatile PAH in Houston may
be due to the contribution of the nearby petroleum  refinery source. On the other hand, the higher
concentrations of most 4- to 7-ring PAH at the Boston site may be attributed  to the heavier mobile
source emissions and fuel combustion.
    In Boston,  maximum  concentrations of most 2- to  3-ring PAHs were observed  in  summer,
whereas  maximum concentrations  of most 4- to 7-ring compounds  were observed in winter. Similar
seasonal trends in  concentration occurred in Houston, though they were less pronounced,  probably
due to the smaller range of seasonal average temperature in Houston (12°C winter to 28°C summer)
relative to that in Boston (1°C to 24°C).
    The phase distribution behavior of several target PAHs is summarized  in Figure 1,  which shows
the average measured percent vapor by season in samples from both sites. Data for the most vola-
tile PAHs are shown only for the  winter season, due to the contamination  from the denuder coating,
noted above. Figure 1 shows that the 3-ring PAHs  are predominantly  in the vapor phase, the 4-ring
                                             33

-------
PAHs are 10-50 percent vapor, depending on season, and the 6- to 7-ring PAHs are predominantly
in the particle  phase  in all seasons.  Several of the  targeted PAHs are not shown in Figure 1.
Naphthalene and acenaphthene were omitted because no good denuder data could be obtained. The
benzofluoranthene isomers  showed 3 to  10 percent vapor phase  composition  (range 0-57 percent),
but could not  be completely  separated  by GC.   Of the four  least volatile PAHs,  dibenzo[a,h]
anthracene, which exhibited the largest vapor component (mean 7 percent, range 0-56 percent), was
chosen for plotting.   The  mean vapor phase fraction was 0 percent for indeno[l,2,3-c,d]pyrene,
benzo[g,h,i]perylene, and coronene in Houston, while in Boston the mean vapor fractions were 3 to
7 percent.  At the Boston site, the lowest percentages of vapor-phase PAH were observed in winter.
This finding is in agreement with  the ambient temperature data, i.e., lower  proportions of vapor-
phase PAHs are present at lower temperatures.   However, this  seasonal difference in phase-distri-
bution of PAH  concentrations was not as pronounced in the data from Houston.  This is due at least
in part to the smaller seasonal differences in ambient temperatures in Houston.   The four samples on
which separate analyses of Miter and XAD were performed allowed  calculation of the extent of vola-
tilization artifact occurring  during sampling.  The median artifact was 17 to 44 percent of the total
for the more volatile PAHs, and 0 to 15 percent for the least volatile.  As expected, volatilization
artifact was greater at higher sampling temperatures,  i.e., a mean value of 18 percent at 7°C and 66
percent at 19°C for the volatile PAHs.
   In previous evaluations of the denuder approach,3 the Dubinin-Radushkevich (D-R) isotherm pro-
vided good results in  duplicating observed PAH phase distributions.  In the present study, applica-
tion of the D-R isotherm to all samples from both sites produced mixed results. Although phase dis-
tributions for benz[a]anthracene and  chrysene in Houston and for  phenanthrene and  anthracene in
Boston were  well predicted, the isotherm provided poor agreement  for other compounds.   This
result is thought to result from the different compositions and much greater variability of the present
particle-phase PAHs  relative to those observed in Columbus, Ohio.5'10  In  the present measure-
ments, the adsorbed  phase composition  was quite variable  and of necessity  incompletely charac-
terized.  The present results indicate  the D-R isotherm shows promise for prediction of PAH phase
distributions, but may require characterization of the adsorbed phase on a sample-by-sample basis to
be fully useftil.

CONCLUSIONS
   Good quality control in  PAH sampling at distant sites can be achieved with the filter/XAD/CAD
approach,  provided  sampling materials  are  shipped  and  handled  using procedures like those
developed here.  The  validity of determining PAH phase distributions with a  CAD under true Meld
conditions is demonstrated by the present work.  Simplification of the PAH sampling methods would
be valuable, however, in order to reduce the cost of measuring phase distributions and sampling
artifacts.

ACKNOWLEDGMENTS
   We thank Sydney  Gordon, Robert Coutant, Gary  Evans, and Jeffrey Childers for technical
assistance; David Davis for sample preparation;  and Vanessa Katona for data analyses.  We also
thank Larry Butts of the Texas Air Control Board and John Lane of the Massachusetts Department
of Environmental Protection for supplying auxiliary data.

REFERENCES
 1.    W. Cautreels and K.  Van Cauwenberghe, Atmos. Environ.  12: 1133 (1978).
 2.    H. Yamasaki, K. Kuwata, and H. Miyamoto, Environ. Sci. Technol. 16: 189 (1982).
 3.    T.  F. Bidleman, W.  N. Billings,  and W. T. Foreman,  Environ. Sci.  Technol. 20:  1038
      (1986).
                                             34

-------
 6.
7.
 8.
 9.
10.
R. G. Lewis, "Problems associated with sampling for semivolatile organic chemicals in air,*
in Proceedings of 1986 EPA-APCA Symposium on Measurement of Toxic Air Pollutants,"
VIP-7, Air Pollution Control Association, Pittsburgh, 1986, pp 134-145.
R. W.  Coutant, L. Brown, J. C. Chuang,  R. M. Riggin, and R. G. Lewis, Atmos. Environ.
22: 403 (1988).
R. W. Coutant, P. J. Callahan,  M. R. Kuhlman, and R. G. Lewis, Atmos. Environ. 23: 2205
(1989).
R. W. Coutant, P. J. Callahan, I.  C. Chuang, and R.  G. Lewis,  "Efficiency of silicone
grease-coated  denuders  for collection of polynuclear  aromatic hydrocarbons*,  Alum.
EnviiojL, 26, in press (1992).
R. G. Lewis and M. D. Jackson, Anal. Chem. 54; 592 (1982).
J. C. Chuang, S. W. Hannan, and N. K. Wilson, Environ. Sci. Technol. 21: 798 (1987).
T. J. Kelly, J. C.  Chuang,  P. J. Callahan,  "Research  for  Polar  Volatile Organics and
Semivolatile Phase-Distributed  Organics Utilizing JAMS  Sites",  Final report to U.S. EPA,
Contract No. 68-DO-0007, WA-1 and -23, BatteUe, Columbus. Ohio, April 1992.
        Table I.  Total (vapor + particle) concentrations of airborne PAHs in two cities***
                                             Mean Concentration ng/m3
Compound
Naphthalene
Acenaphthene
Fluorene
Huorenone
Phenanthrene
Anthracene
Fluoranthene
Pyrene
Cyclopenta[c,d]pyrene
Benz[a]anthracene
Chrysene
Benzofluoranthenes
Benzo[e]pyrene
Benzo[a]pyrene
Indeno[l,2,3-c,d]pvrene
Dibenzo[a,h]anthracene
Benzo[g,h,i]perylene
Coronene
Boston
Summer
606
24.1
36.2
10.2
101
3.0
16.7
8.4
0.3
0.9
1.0
1.1
0.4
0.4
0.5
0.3
0.6
0.3
Fall
569
16.9
18.0
6.5
52.1
2,9
11.8
10.7
0.5
0,8
1.3
1.6
0.8
0.8
0.7
0.2
1.3
0.8
Winter
453
5.7
10.0
8.2
30.2
1.6
9.4
8.3
1.1
2.0
2.1
2.9
1.0
1.5
2.0
0.4
3:2
2.7
Spring
255
4.3
5.5
2.7
18.2
1.0
6.8
4.7
0.6
0.9
1.0
2.1
0.7
1.2
1.2
0.3
1.6
1.0
Summer
515
22.8
24.2
5.4
50.1
1.4
10.2
7.9
0.2
0.6
0.6
0.5
0.2
0.2
0.2
0.2
0.3
0.2
Houston
Fall
441
15.8
19.9
6.4
45.9
1.8
10.0
11.8
0.2
0.7
1.0
0.4
0.3
0.2
0.2
0.2
0.4
0.3
Winter
671
12.8
18.0
7.2
37.9
2.2
6.7
6.4
0.2
0.4
0.7
1.0
0.4
0.4
0.8
0.2
1.4
0.9
Spring
153
5.5
5.0
1.3
11.2
0.5
3.8
2.3
0.1
0.1
0.2
0.2
0.1
0.2
0.2
0.2
0.3
0.4
      (a)  Data are from PS-1 sampler without denuder, adjusted to STP conditions.
                                            35

-------
OJ
to
80
Q.
0 60
Q.
(0
> 40
_C
lo 20
0s*
100
0)
w
5 80
D.
0 60
Q.
ra
> 40
^ 2°
0s-
n
BOS
: jl
;TON
i i
• i

•
/
/
/
/
/
/

•T-
/
/
\ /
s /
V /
V / -
s / ~
V . / -
T "
S i
V '.
\
\
\ ' ;
V 72
V / ~
-•
r /
1,
-
* /-
•
/
S/
'-
r
'/-


ji f
M
i
n
7




•
^z



^
-
11
Summer
Fall
Win
Spr
rn FIT i
ter
ing
fl '

HOU
STON

•
•
/
/
/
/
/
/ -
jl
\ / -
s / ;
v / -
ii
/
1 /
/
/
/
/
/
\ /
-
'li
/
/
/
/
/
r ^
• ' /
/
i /
\ / .
-
IT ^
/
/
/
/
u
-
L
-
i,
1
L
J M
(1
FL
FN
                                 PHE    ANT    FLAN   PYR   CPPY    BAA   CHRY   BEP    BAP    DBA
FIGURE 1.   Proportions of airborne PAHs in vapor phase in Boston and Houston. Vertical bars represent average
percent vapor phase for all sampling days during the indicated season.  Range of deviation from the average is
indicated by superimposed vertical scales. Fl, fluorene; FN,  fluorenone; Phe, phenanthene; Ant, anthracene;
Flan, fluoranthene; Pyr, pyrene; CPPy, cyclopenta[c,d]pyrene; BaA, benz[a]anlhracene; Chry, chrysene;
BeP, benzo[e]pyrene;  BaP, benzo[a]pyrene;  DBA, dibenzo[a,h]anthracene. Data for the first four PAHs could
not be calculated accurately except for the winter season due to contamination from the denuder.
(Note: Asterisk indicates that no vapor phase component was  detected in any  sample.)

-------
       Session 3
Indoor Air Measurements
Dennis Naugle, Chairman

-------
        Household  Exposures to Benzene  from Showering  with
                    Gasoline-Contaminated Ground  Water

     By: Andrew B.  Lindstrom1, V. Ross Highsmith1, Timothy J. Buckley1, William J. Pate2,
                         Larry C. Michael1, and R. Mark Johnson4

    1 U.S. EPA, Atmospheric Research and Exposure Assessment Laboratory, RTF, NC 27711
 2 NC Department of Environment, Health, and Natural Res., P.O. Box 27687, Raleigh, NC 27611
              3 Research Triangle Institute, P.O. Box  12194, RTP, NC 27709-2194
                    4 Acurex Corporation, P.O. Box 13109, RTP, NC 27709


ABSTRACT

      In a private residence using benzene-contaminated  ground water (»  300 ^6/0. a series of
experiments were performed to assess the benzene exposures that occur in the shower stall, bathroom,
master bedroom, and  living room as a result of a single 20 minute shower.  Sampling methodologies
used in  this  assessment included; fixed site Summa™-polished canisters and Tenax GC* cartridges;
personal Tenax GC*  devices; and, grab samples collected with glass gas-tight syringes.  Integrated
Summa™ and Tenax GC® samples were collected from the target microenvironments over 20,  60, and
240 minute periods.  These results are contrasted with the long-term personal samples  (6 h) and grab
samples that were collected at 0, 10, 18, 20,25, 25.5, and 30 minutes. Results indicate that maximum
benzene concentrations occurred in the shower stall (758  - 1673 /*g/mj) and bathroom (366 - 498
^g/m3).  The total dermal and inhalation dose resulting from a single 20 minute shower was estimated
to be equivalent to the inhalation dose that occurs during 6 h occupation of the house ( •• 135 jtg).  The
benzene dose relating  to a single shower and continuous occupancy of the residence  was shown to be
approximately 551 jig/day, with the shower accounting for 25 % of the daily total (4  % dermal and 21
% inhalation), and the remaining 75 % relating to respiration in the house for the balance of the day.

      This paper has been reviewed in accordance with the U.S. Environmental Protection Agency's
peer review and administrative review policies and approved for presentation and publication.  Mention
of trade names or commercial products does not constitute endorsement or recommendation for use.
INTRODUCTION

      Use of volatile organic compound (VOC) contaminated ground water for ordinary domestic
purposes  can lead to important oral, dermal, and inhalation exposures.  Several recent studies have
demonstrated that the inhalation route may be as important as, or more important than, direct ingestion
of contaminated water1-2.   Studies have also demonstrated that  residential  water  use can  lead to
significant airborne exposures in areas remote from the water use zone1.  Much of this preceding work
concerning the water-to-air transfer of pollutants and resulting exposures has been conducted with
radon4, trichloroethylene1, and chloroform*.  This study characterizes household benzene exposures that
can occur with the use of gasoline contaminated water.

      The Environmental Protection Agency has estimated that between 100,000 - 400,000 of the 3 -
5 million underground storage tanks used in the U.S. for underground liquid petroleum or chemical
                                            39

-------
 storage may have been leaking at one time or another during their lifetime6. This presents significant
 ground water contamination problems which can in turn lead to serious oral, dermal, and inhalation
 exposures resulting from normal domestic water use. This investigation  was conducted in a single
 family residence known to be using benzene-contaminated groundwater. Chemical analyses performed
 by North Carolina Department of Environment, Health,  and Natural Resources indicate that  the
 contaminant is a petroleum product (unpublished data). Specific objectives of this investigation include:
 (1) assess shower related exposures that occur in various parts of the house as a result of a single 20
 minute shower; (2) examine the relationships between contaminant levels monitored using Tenax-GC®,
 Summa™ polished canisters, and glass, gas-tight syringes; and, (3) support concurrent modeling and
 human exposure biomarker studies.

 METHODS

       A series of experiments were conducted in a 290 m1  (3100 ft2) north  central  North Carolina
 single family residence from June 11-13,  1991,  The residential water was supplied from a single 30
 m deep well located on the homeowners1 property. Contamination was first discovered in 1986 when
 an unusual odor was noticed by the residents of the house.  After a water test  showed benzene at 425
 Hg/t, the homeowners stopped drinking the water and installed a small (15 x 9 cm) charcoal filtration
 device in the main water supply line. The residents continued to use the water for bathing and washing.
 From 1986 -1991 benzene was measured in the water despite the filter (and perhaps because of varying
 filter efficiencies) at concentrations ranging between 33 and 673 pg/t.

       Identical experiments  were conducted on three  consecutive days  following an established
 protocol.  The experiments involved an individual taking a 20 minute shower with the bathroom door
 closed, allowing that individual five minutes to dry off and dress, and  then opening the bathroom door
 and allowing him to leave.  This individual then participated in blood and breath sampling in support
 of the biomarker segment  of this study7.  Whole air samples  were collected in Summa™ polished
 canisters8 using conventional mass flow control devices in bathroom, bedroom, living room, and in the
 ambient air.  To save space and avoid electrical hazards, canister samples were collected using flow
 restrictors in  the  shower and bathroom.   Tenax GC* samples  were also collected  in the shower,
 bathroom, and living  room8.  The integrated samples were collected over 20, 60, and  240 minute
 periods, all beginning as the shower was turned on and the bathroom door was closed. Glass, gas-tight
 syringe samples were simultaneously collected from the shower, bathroom,  bedroom, and living room
 at 0, 10, 18, 20, 25, 25.5,  and  30  minutes, and at additional times in selected areas until the end of
 each study period. The members of the sampling team that were initially stationed in the bathroom and
 the living room wore personal Tenax GC* sampling devices to assess their exposures.  Water samples
 were collected for VOC analysis at the shower head from a preaerator bypass valve, and at drain level
 at the beginning and end of each shower period to provide a measure of water-to-air transfer efficiency.
 Water temperature and flow rate were also measured at the beginning and end  of each shower period.
The  entire  experiment was reviewed and approved by  an appropriate  Human  Subjects  Review
 Committee.

       The glass, gas-tight syringe samples were analyzed on-site using a Photovac 10S50 portable gas
 chromatograph.  Samples  (1  ml) were injected onto a CPSIL-5 (Photovac,  Inc.) capillary column
operated  at 40 °C with 10 ml/min zero air carrier gas flow.  Canister samples were analyzed on an
LKB 2091 magnetic sector GC/MS/COMP system operated in the multiple ion detection mode. Tenax
GC® and water samples were analyzed on an HP5988A quadrupole GC/MS/COMP system operated in
multiple ion detection mode. The water samples were analyzed by purging 5 ml aliquots of each sample
onto Tenax GC® cartridges with 480 ml helium (40 ml/min for 12 min)  followed by thermal desorption.
                                             40

-------
 RESULTS/DISCUSSION

       Three laboratory control canisters had mean benzene recoveries of 96 % with a relative standard
 deviation (RSD) of 2 %, and six field control Tenax GC® cartridges had mean recoveries of 128 % (18
 % RSD). Eleven syringe field controls had mean benzene recoveries of 97 %  (9 % RSD).  Three field
 control water samples had mean benzene recoveries of 72 % (15 % RSD).  Field blank canister, Tenax
 GC®, syringe, and water samples were all reported to be at or below their levels of detection (40 ng/m3,
 0.4 ng/m?t 0.16/ig/m3, and 0.6fig/l, respectively).

       Analysis of blind performance evaluation Tenax GC* and Summa™ canister samples resulted in
 benzene  recoveries ranging from  36 - 64 %, and 73 & 76 %, respectively.  The lower than normal
 spike sample  recoveries most likely resulted from the  wide calibration range required  to  support
 expected sample loadings. Blank Tenax GC* and Summa™ canister samples reported below their limit
 of detection (0.4 and 40.0 jtg/m3, respectively).  Excellent agreement was observed in daily duplicate
 60 minute Summa™ canister and Tenax GC®  samples, with a median relative difference of 4.2 % (range
 0 - 10.3 %).  Analysis of duplicate syringe samples showed  a median relative difference of 20.2 %
 (range 3.6 - 40.7 %).

       Waterborne benzene concentrations from the preshower head samples ranged from 185 - 367
 Hg/t (N  = 5, mean = 292 /tg/£,) while drain level samples ranged from below the detectable limit (0.6
 liglt) to  198 fig/t.  This results in a mean  water-to-air transfer efficiency of 0.88 (range 0.73 - >
 0.99).  Analysis of the syringe sample benzene concentrations suggests a wave of benzene moving from
 the shower stall to the rest of the house over approximately 60 minutes. Figure 1 is a plot of benzene
 levels during the June 12 experiment. Peak  benzene concentrations in the shower stall were collected
 in the 18 minute sample on June llth and 12th (758 and 832 ng/m3 respectively), and in the 20 minute
 sample on June 13th (1673 ftg/m3). Benzene concentrations in the bathroom tended to increase for the
 first ten minutes and then remain uniformly elevated for the duration  of each shower period.  Peak
 bathroom concentrations were collected in the 10 minute sample on the llth (366 jig/m3), in  the 25  min
 sample on  the  12th (371 jig/m3), and in the 25 min  sample on the 13th (498  /ig/m3).   Maximum
 bedroom benzene levels occurred immediately as, or shortly after, the bathroom door was opened, with
 peaks at 30 min on the 11th (81 /xg/m3), at 25.5 min on the 12th (146 ^g/m3), and at 30 min on the 13th
 (125 /ig/m3). The highest benzene concentrations in the living room were found  still later, with peak
 levels at 36 min on the  llth (40 /tg/m3), 70 minutes on the 12th (62 /*g/m3), and at 48 min on the 13th
 (54 /ig/m3).

       Overall, the collocated integrated Summa™ and Tenax  GC* samples were in good general
 agreement. The relationship between the two sampling methods can be described by the linear model:

                       [Tenax GC*] = 0.89 x [Summa™] + 41.36 /*g/m3
                                                                                  (1)
                         with an r =  0.95 at a P < 0.001  (Figure 2).

This regression line is not significantly different from the line of one-to-one correspondence (F = 2.82,
 P = 0.0908). Although the Tenax GC® benzene concentrations were typically higher than the Summa™
canisters  (mean difference 21.9 /*g/mj, standard error of the difference = 12.5)., a paired T-test shows
 the two sampling methods were not significantly different (N = 17, T  = -1.75, P = 0.0984).

       The personal exposures of the two monitoring team members, assessed using personal Tenax
GC® monitors, were examined and compared with the microenvironmental results.  For the first 30
                                             41

-------
 minutes of each experiment one individual was based in the bathroom and the other in the living room.
 After the shower period was completed,  however, these individuals were free to move to other parts
 of the house to assist in sample processing. Their daily personal inhalation dose can be calculated using
 the following equation5:

                              DJ = CA x MV x T x F         (2)

 Where D; = inhalation absorbed dose (/tg); CA = concentration of benzene in the air (pg/rn3); MV =
 minute ventilation rate (0.014 mVmin); T =  duration of exposure (min); F  =  fraction of benzene
 absorbed (70  %, based on 100 % absorption of alveolar ventilation volume)9.  Using this model, we
 can estimate that the benzene dose for the individual in the bathroom ranged from 97.7 to 184 /xg (mean
 = 133.3 /ig). Although the first 20  minutes of exposure in  the bathroom corresponds to only 6 % of
 the total experimental period (6 h),  the results from the fixed-site 20 minute bathroom Tenax GC*
 samples indicate this period accounted for between 18-38 % of this individual's daily absorbed dose.
 Slightly reduced exposures are estimated  for the  individual in the living room (53.0 to 111 /tg, mean
 = 78.9 /ig). Site specific mean 4 h doses (based  on mean Tenax GC* +  Summa™ canister data) were
 calculated to be 122 /ig for the bathroom, 100  /tg for the bedroom, and 79.4 /tg for the living room.

       The individual 20 minute showers had inhalation doses ranging from 79.6 -105 /ig (ave = 95.9
 ^g).  Adding the average dose absorbed in the  bathroom during the 5.5 minutes following the shower
 (using the overall 20 & 25 minute mean syringe level of 318 /tg/m3) gives a total average shower-related
 inhalation dose of 113 /ig.

       The average dermal dose resulting from the 20 min showers was calculated to be 22 jig using
 the following equation10:

                            DD  =  CW x SA x K,, x T x U       (3)

 Where: DD = dermally absorbed dose (/tg); CW = concentration of benzene in water (292 jig//); SA
 = surface area  of the 6'4" male volunteer (2090 cm2); K,,  = benzene dermal permeability constant
 (0.11 cm/hr)11; U = units conversion (U/1000 cmj). This leads to a total average shower-related dose
 of 135 /xg - an exposure comparable to what the other members of the sampling crew received  in 6
 hours. Using the results of this experiment as  a model, we  can calculate a typical daily exposure for
 the residents of this house by adding  the shower-related total to an additional 23.6 hours of inhalation
 exposure at the average 4 hour living room concentration (30 fig/m* x 0.014 mVmin x 1415  min x 0.7
 = 416  /ig).   This leads to  a total  benzene dose of  approximately 551  /ig/day,  with the shower
 accounting for 25% of the daily total  (4 % dermal and 21 %  inhalation), and the remaining 75 % from
 continuous respiration in the house.

       It is useful to compare the exposures estimated in this experiment to benzene exposures reported
 for other activities.  Smoking cigarettes, for example, may represent a fairly comparable benzene dose.
 With an average value of 40  /ig of benzene delivered per cigarette (23 mg tar/cig.)n, a single daily
 shower and  24 hour occupation of this house delivers  the same benzene dose as smoking about 14
cigarettes.

 CONCLUSIONS

      The results of this study suggest the potential for elevated benzene exposures resulting from
residential use of gasoline-contaminated ground  water.  The total dermal  and inhalation exposure
                                             42

-------
resulting from a single 20 minute shower was estimated to  be equivalent to the inhalation exposure
vjhich would occur during 6 h occupation of Ihe house (» 135 jtg).  The absorbed dose relating to a
single 20 minute shower and continuous occupancy of the residence was shown to be approximately 551
Mg/day, with the shower accounting for 25 % of the daily total (4 % dermal and 21 % inhalation), and
the remaining 75  % relating to respiration in the house for the balance of the day.  This was found to
be approximately equivalent to the benzene dose received from smoking  14 cigarettes.  This  study
confirms the observations made in similar studies regarding the importance of inhalation exposures
resulting from a single shower, both in the shower stall and in areas far removed from the bathroom.

        Differences in benzene concentration  measured with Summa™ polished canisters and collocated
Tenax GC* cartridges were not found to be statistically significant.  Samples collected with glass, gas-
tight syringes demonstrated a pulse of benzene moving from the shower stall through the rest of the
house  over the course of  approximately 60  minutes.   This sampling  method  may  be useful  in
determining instantaneous contaminant concentrations  in multiple locations in future  studies.

REFERENCES

1 •      N J. Giardino, E. Gumerman, N.A. E*men. J.B. Andetawn, C.R. Wilkei, and M.I. Small, -Real-Time air measurements of
        trichloroediylene in domestic bathrooms using contaminated water," in Prooeedinesof the 5th International Conference on Indoor
        Air Quality and Climate: Indoor Air '90. Vol 2.  International Conference on Indoor Air Quality and Ctiroaie, Ottawa. 1990,
        pp 707 -712,

2-      T.B. McKone,  "Human exposure to volatile organic compound* in household tap water: the indoor inhalation pathway,"
        Inviron. Sci Techqo}. 21: 1194 (1987).

3-      C,R. Willed, M.J.  Small, J.B, Andetawn, and I. Marshall, "Air quality model for volatile constituents from indoor luei of
        wa«r,"  in Proceeding  of the  5
-------
  1,000
co"
CD
   800
   600
   200
         Figure 1.  Portable GC  Data
                    June 12,1991
                         Shower
         i i  i  i
               V  i  i i  i
               10      18 20   25.5  30
                       Time (minutes)
             Shower Stall Bathroom Bedroom Living Room
              	A—   •••*••   Q   --•-
                                      48
    Figure 2.  Tenax/Sumrna Comparison
   1,000
      30
 R*- 0910
 Y - 0890X + 41 36
 Dotwd Line Slope - 1
50        100       200   300
       Summa Benzene (/jg/m3)
 slope = 1 Shower Stall  Bathroom Living Room
          A      *      •
500
                                                   1,000
                           44

-------
   A TWO-CHAMBER DESIGN FOR TESTING THE  SINK
 EFFECT WITH DYNAMIC  CONCENTRATION PROFILES
                              Kenneth Krebs and Zhishi GUO
                             Acurex Environmental Corporation
                     P.O. Box 13109, Research Triangle Park, NC  27709


ABSTRACT
      An experimental system has been developed to evaluate the effects of adsorption and desorption
of air pollutants from indoor materials.  This design was implemented to generate a transient organic
vapor exposure profile representing a first order decaying source. This design allows one to reproducibly
generate  a  predictable,  easily modeled dynamic source of organic vapors  for  use in  exposure
experiments. This paper describes experiments conducted to evaluate  the performance of the system.
A special form of the dynamic sink model suitable to the system has also been developed. Testing with
wallboard and ethylbenzene indicated that the results generated from the new method were comparable
with the previously reported values determined from a flow-through chamber with a constant source.
This method complements and supplements the regular flow-through chamber method.  It simulates the
real  indoor conditions more closely  and is less time consuming.   It is therefore suitable for air
pollutants/materials screening.

INTRODUCTION
      Interior surfaces can adsorb air pollutants through either physical or chemical adsorption. The
dividing line between the two, however, is not always sharp.  When the gas molecules are held on the
surfaces by relatively weak forces, namely intermolecular van der Waals  forces or weak chemical
bonding, the adsorbed molecules can be released when the difference of chemical potentials between gas
phase and surface phase is in favor of desorption.
    For indoor air quality concerns, this adsorption and consequent desorption (sometimes known as the
sink effect) is undesirable because it increases long-term human exposure. Due to the great impact of
surface adsorption on indoor air quality, the study of the sink effects has received ever increasing
attention. Efforts have been made to investigate the characteristics of this heterogeneous mass transfer
phenomenon.
    Several experimental techniques have been used to characterize the sink effect, including batch
reactors1, gas-solid chromatography1, electronic microbalance2, and flow-through chambers3' . Among
these techniques, the flow-through chambers provide the conditions closest to those found in real indoor
environments (i.e., temperature, humidity, continuous dilution, and the pattern of air turbulence). This
method utilizes a constant  source to  fill the chamber,  in  which a sink sample is present.  After the
equilibrium condition is approached, the source is stopped and the decay of chamber concentration is
monitored.  This method is relatively time-consuming because an equilibrium status is  desired.  In
addition, in each test, there are two distinct phases: the accumulation phase (when source is on) and the
decay phase (when source is off), and the data from the two phases often must be treated separately.
In real indoor environments, most sources are finite and dynamic. Many examples of human activities
generate organic vapor concentrations of a dynamic nature.  Examples include  the painting of a room
or the use of cleaning products.  These activities are characterized by an initially high outburst of
emissions followed by a gradual decrease.  The experimental setup described below was designed to
simulate indoor environmental conditions by generating concentration vs. time curves that are more likely
                                            45

-------
to be found in real buildings, and to avoid some of the disadvantages of the regular flow-through
chamber method.

THE EXPERIMENTAL SYSTEM
       This design employs two 53-liter electropolished stainless steel environmental test chambers. One
serves as the "source" chamber and the other the "test" chamber. The chambers were plumbed together
as depicted in Figure 1. The air flow from the clean air generator is divided into two branches: one is
directed to the source chamber to serve as the carrier gas of the pollutant (qt), and the other is the clean
air bypass (Q-qj).  Two control valves allowed the source chamber to be isolated  from the clean air
purge or to be in-line with the test chamber. The organic vapor of interest is introduced into the source
chamber, and the test material resides in the test chamber.
       The concentrations from the test chamber were monitored by a gas chromatograph (GC) using
a  1/8-in. (0.318 cm) packed column  and a  flame ionization  detector  (FID). The organic  vapor
concentrations were high enough to allow the samples to be taken with a sample loop. The samples were
pulled by a diaphragm pump through a heated sample line then to an eight port valve configured with
two S ml sampling  loops and the GC carrier gas. The GC carrier gas was transferred by healed tine to
the injection port of the GC. The GC run parameters were optimized to allow for a  sample time
resolution of 5 minutes.

EVALUATION OF THE SYSTEM PERFORMANCE

Test Procedure
       Several experiments  were conducted to evaluate the performance of the experimental system.
In these experiments, ethylbenzene was used as the air pollutant and was generated in  the source
chamber either by direct injection of microliter amounts of liquid ethylbenzene or flow from  a
permeation oven. The permeation oven contained a permeation device of ethylbenzene and  provided a
flow of constant concentration.  The sink test material used was gypsum wallboard. The sample was
previously painted with a commercially available latex paint, and the edges were scaled with Teflon tape.
       Before starting an experiment, the entire system was purged with clean air overnight  This purge
was used to condition the system to the test conditions (23° C and 45% relative humidity). The next
day, the source chamber was isolated from the clean air purge and a calculated amount of ethylbenzene,
either liquid or standard gas, was injected. The concentration of ethylbenzene in the source chamber was
monitored by  withdrawing  samples  with a gas  syringe and analyzing by  GC-FTO.   When this
concentration reached the intended amount and stabilized, the test was started.  The start of the test, time
zero, is when the two control valves  were turned to allow the clean air to purge the source chamber
atmosphere into the test chamber.  The effluent of the test chamber was monitored by sampling through
the sampling loops.

Source Chamber
    The first experiment was conducted to evaluate the mixing and potential sink effect in the source
chamber. If the air in the chamber is well mixed and the sink effect of the chamber wall is negligible,
the effluent concentration C, should yield an exponentially decaying concentration profile:

                -la                                                                      (1)

where C,Q is the concentration before the purge starts, and k»f j/Vj is the air exchange rate for the source
chamber.
       Before  starting  the  test, air flow  q} was shut off,  and the test chamber was filled with
ethylbenzene vapor from the permeation device. The final concentration (C^ was 10.9 mg/m3. At the

-------
•tart of the test (time zero), the clean air purge was initiated into the source chamber with qt * O.OS2
m3/h, and die outflow was sampled directly to determine the concentration decay rate.  As shown in
Figure 2, the observed outlet concentration followed the semi-log pattern very well (i2-0.989 and n=9),
and the deviation from Equation (1) occurred only after 8 hours when the outlet concentration dropped
to 0.01 rog/m3.

Test Chamber without Sink Samples
      When there is no sink material present, the pollutant concentration in the test chamber depends
•olely on the concentration in the source chamber C, and the flow ratio qt/Q. Due to the dilution of the
bypass clean air, the inlet concentration for the test chamber, Cj,, can be described by:
To save space in further derivation, let's define C^ =» C^ q,/Q. Thus:
The concentration profile for the test chamber can then be described by:

       V2 dC/dt « Q Cfo - Q C                                                            <4>

Substitute Equation (3) into (4) and let N=Q/V2 be the air exchange rate for die test chamber:

       dCMt « N q, e* - N C                                                            <5)

Given that C=0 when t«0, the solution to Equation (5) is:

              NCp       ^    ^                                                       (6)

              

Equation (6) predicts that the  concentration in the test chamber will experience a rising and falling
concentration profile.
    To test whether the  source chamber outlet concentration indeed followed Equation (6), about 5 pi
of liquid ethylbenzene was injected into  the source chamber and allowed to evaporate.  The resulting
initial concentration  was 75 mg/m3.  With q, - 0.036 m3/h and Q - 0.058 m3A, the observed
concentration data from  the test chamber are shown in Figure 3.

Test Chamber with a Sink Sample
       A sink test was  conducted by placing a 0.14 m2 sample of gypsum wallboard into the test
chamber. Ethylbenzene  was again used as the pollutant The test conditions were: Co - 29 mg/m , q}
- 0.023 m3/h, and Q - 0.060 m3/h.  The results are shown in Figure 4. With the sink sample placed
» the test chamber, the concentration peak was suppressed due to strong adsorption in the early stage,
and the tail was extended due to the consequent desorption.
    To further analyze the data, we applied the dynamic sink model4 to the two-chamber system, and
a new form of the sink model was developed.  The dynamic  sink model4 is based on Langmuir'i
assumption that both adsorption and desorption are of fust-order

       Adsorption Rate  - k, C                                                            (?)
                                              47

-------
       Desorption Rate = ^ M                                                             (8)

where k, is the adsorption rate constant, C the pollutant concentration in the air, kj the desorption rate
constant, and M the pollutant content on the surface of the sample.
    Consider an infinitesimal time interval dt in the test chamber.  If a sink sample with area, S, is
present, the mass balance for the pollutant is:

       change of mass = inlet • outlet - adsorption + desorption

or     V2 dC/dt = Q q, e'* - Q C - S k^ C + S kj M                                        (9)

For the pollutant adsorbed on the surface, M, we have:

       change of mass = adsorption - desorption

or     S dM/dt = S It, C - S k,, M                                                         (10)

Let N = Q/V2 be the air exchange rate and L = S/V2 be the loading factor for the test chamber.  Then
Equations (9) and (10) can be rewritten as:

       dC/dt = -(N + Lk,) C + L kd M + N CQ e'*                                          (11)

       dM/dt = kg C - kd M                                                               (12)

Given the initial conditions-C=0 (empty chamber) and M=0(clean surface) when t=0--Equations (11)
and (12) can be solved simultaneously.  The solution for the chamber concentration is:

                Co
       c =	{[P(r2+kHN]exP(rit)
             rl'r2

             - [P(ri+k)+N]exp(r2t) + [P(rrr2)]exp(-kt)}                                      (13)
where:
                                                   /2
                 N / [k (k-N.Lk.-lt,,) + ka N]
       Equation (13) is the special form of the dynamic sink model suitable to the two-chamber system.
By applying Equation (13) to the experimental data shown in Figure 4, we can estimate k, and kg by
means of non-linear regression.  Table I shows that the values of ka and kj obtained from this method
are very close to those reported in the literature. Although there is no equilibrium status involved in this
method, the ratio kg/tj, a measure of the adsorption capacity, is still close to that determined from
equilibrium conditions .
                                             48

-------
                  Table I. Comparison of the Adsorption and Desorption Rate
                      Constants for Ethylbenzene and Gypsum Wallboaid
                         1^ (m/h)            k,, (h'1)             IcAi (m)
This Method
Literature4
0.64
0.45
1.48
1.5
0.43
0.30
DISCUSSION
      Ethylbenzenc was chosen to evaluate the performance of the system  for two reasons: (1) It is
a common component of many organic solvent mixtures, and (2) Its adsorption on several indoor
materials has been reported.  From Figures 2 and 3, we did not find a significant sink effect for the
chamber walls. For even less volatile compounds, however, the sink effect from the system itself should
be examined.  When the adsorption of the chamber walls is significant, compensation methods should
be considered.  The limitation of the system is yet to be determined.
      In this method, the decay rate of the insulting gas is controlled by the air exchange rate for the
test chamber, k^qj/Vj. To simulate a fast decay source, one needs to increase qv  The maximum value
for k is OyVj, when there is no bypass air flow.
      The dynamic sink model based on Langmuir's  assumptions is the simplest sink model.  More
complicated models can be applied to this experimental system even though they may not have explicit
solutions.

CONCLUSIONS
      A two-chamber system has been developed to test indoor sinks under more realistic conditions.
This method complements and supplements the  regular flow-through  chamber method  Preliminary
evaluation of the experimental  system  shows that, for  organic compounds like ethylbenzene, the
adsorption by the chamber walls is not significant.  The comparison of this  method with the previous
work using a steady state exposure method indicates that the results of kj and !cd from these two
experimental methods are comparable.  More important, their ratios, a measure of the sink capacity, are
very close to each other.  Since there is no equilibrium condition involved, this method is less time
consuming and may be suitable for pollutants/materials screening studies. Because the source can be
well characterized and is easy to control, this experimental setup might also find application in biological
exposure studies  where a reproducible transient profile is needed.

REFERENCES
 1.     LJL Borrazzo, C.I. Davidson, and J.B. Andelman, "The influence of sorption to fibrous surfaces
       on indoor concentrations of organic vapor", Proceedines  of 83rd A&WMA Annual  Meeting.
       Pittsburgh, PA, Air & Waste Management Association; 1990, Vol. 5, paper number 90-91.1, pp
       1-14.

2.     U. Kjw  and P.A. Nielsen, "Adsorption and desorption  of  organic compounds on fleecy
       materials/1 in IAO'91 Healthy Buildings. American Society of Heating. Refrigerating and Air-
       Conditioning Engineers. Inc. 1991:285-288.

 3.     T.G. Matthews, A.R. Hawthorne, and C.V. Thompson, "Formaldehyde sorption and desorption
       characteristics of gypsum wallboard," Environ, gci- & Technol.. 21(7)'. 629-634 (1987).
                                             49

-------
4.     B.A. Tichenor, Z. Guo, J.E. Dunn, LJi. Sparks, and M.A. Mason, "The interaction of vapour
      phase organic compounds with indoor sinks," Indoor Air.  l(l):23-35 (1991)
           CUu Air Bypui (Q-q,)

Clt*n Air
Gtntnlor
l±t
1
ll
Control
Vilve
oltutint Injection
7
Vi C,

Source
Chimbcr
±H
.Q-G.
Control
Vilvc

V2,C
Ten
Chtmhtr
                                          Q,C
     Figure 1. The Schematic Diagram
           of the Experimental System
                                                                             D Observed
                                                                            — Theoretical
             234567
                 Elapsed Time (h)

       Figure 2. Ethylbenzene Decay in
                the Source Chamber
                             D Observed
                            — Theoi-etical
                2345
                Elapsed Time (h)
                          D  Chamber Data
                          — Sink Model
                          	 No-Sink Case
               468
               Elapsed Time (h)
 Figure 3. Ethylbenzene Concentration in
      Empty Test Chamber as Compared
       to Theoretical Prediction
Figure 4. The Sink Test with Ethylbenzene
         and Gypsum Wallboard
                                            50

-------
  ADSORPTION AND RE-EMISSION OF ETHYLBENZENE
   VAPOR FROM INTERIOR SURFACES IN AN INDOOR
                     AIR QUALITY TEST HOUSE
                     ZhishJ Guo, Mark A. Mason*, Kevin N. Gunn,
                         Kenneth A. Krebs, and Scott A. Moore
                           Acurcx Environmental Corporation
                    P.O. Box 13109, Research Triangle Park, NC 27709

                                  John C. S. Chang
                 U.S. EPA, Air and Energy Engineering Research Laboratory
               Indoor Air Branch (MD-54^ Research Triangle Park, NC  27711


ABSTRACT
      The adsorption to and consequent re-emissioti of ethylbenzene vapor from interior surfaces was
studied in an indoor air quality test house. Ethylbenzene was delivered into the house at a constant rate
of 0.1 g/tnin for 72 h. The continuous, real-time concentration of this surrogate pollutant in indoor air
was monitored for 1,085 h. Mass balance calculations indicated that the interior surfaces adsorbed a
substantial amount of ethylbenzene from indoor air during 72-h exposure, and that the re-emission was
a prolonged process; at the end of this experiment, the indoor concentration was still 0.02 mg/m ,
jsignificantly higher than ihe indoor background of 0.003 mg/m3. The effects of the interaction between
ethylbenzene vapor and interior surfaces on human exposure are discussed

INTRODUCTION
      The large area of interior surfaces is  one of the most outstanding characteristics of indoor
environments.  Consider an empty 3 x 4 x 3  m3 room. The 36 m3 of air in the room is in direct contact
with 66 m2 of walls, ceiling, and floor. The  importance of the interaction between the surfaces and the
[inreactive pollutants, sometimes known as the sink effect, has been well recognized and is receiving
fncreased attention. Early observations suggested that some symptoms of "sick building syndrome" could
W best correlated to the ratio of the projected area of fibrous surfaces to the room volume1. A chamber
«udy on the adsorption and subsequent desorption of formaldehyde from gypsum board confirmed that
the board has * substantial storage capacity for adsorbed formaldehyde2. An extensive literature^ review
M adsorption and desorption of vapor-phase organic compounds in  indoor environments was given by
Bergjund et al. in 1988*. Since then, more laboratory studies have been reporwdT*. However, few data
are available from specially designed experiments aimed at characterizing indoor sinks in real buildings.
      This experiment studied the sink behavior in a lest house by using ethylbenzene as a surrogate
 wllutant.  We chose this  compound for two reasons:  it is a component of  many  organic solvent
 nixtures used in household products, tsA its. Ntpot pressure fall* flew the middle of (he tangs among
 he volatile organic compounds (VOCs) commonly found in indoor environments.  The primary goals
     to estimate the sink capacity and the effect of surface adsorption on human exposure.
 " Current address: U.S. EPA, Air and Energy Engineering Research Laboratory,
  Indoor Air Branch (MD-54), Research Triangle Park, NC  27711
                                           Materials Eclong Tor
                                           OPPT Lilr-ry
                                           401 M Sir jet, SW (TS-793)
                                           Washington, DC 2-0460

                                         51

-------
 EXPERIMENTAL METHODS

 The Test House
       The  indoor  air quality test  house is  an unoccupied,  unfurnished,  one-story,  wood-framed
 residential building9, having a total volume of 305 m3 and total projected interior surface area of about
 700 m2.  All the  rooms have wall-to-wall carpet except the kitchen and bathrooms.  Carpeted floor,
 gypsum wallboard, and ceiling tile cover about half of the total area. Other surfaces include uncovered
 plastic floors, windows, painted wooden surfaces (doors,  window  frames, cabinets, and closets), and
 kitchen appliances.  A central heating/air conditioning (HAC) system controls the indoor temperature.
 A floor plan is shown in Figure 1.
       During this experiment, all windows and outside doors were closed; all inside doors were open
 including closet doors; indoor temperature control was set to 22.2°C (72°F); and the HAC fan was kept
 on continuously.  The garage was used as working area. An F460  Climatronics weather station in the
 backyard was used to collect local meteorological data.

 The Ethylbenzene Source
       A Perkin-Elmer Series 10 high-pressure liquid chromatography (HPLC) pump was used to deliver
 liquid ethylbenzene into the house.  The pump was calibrated prior to  the experiment and  showed
 excellent stability. Based on 10 flow measurements made in 3 days, the relative standard deviation for
 the flow rate was 0.43%.  To get fast and even evaporation, the end tip of the pump's outlet tubing was
 in contact with a  piece of paper filter.  A biscuit fan was used to generate dilution air to carry the
 ethylbenzene vapor away from the filter  surface.  To ensure proper mixing after ethylbenzene was
 evaporated, the source was placed in the hall, near the air return  grille of the HAC system.  The source
 was turned off and removed from the house after 72 h.

 Air Sampling and Analysis
       Air samples were collected near the center of living room and corner bedroom, 160 cm above
 the floor,  and analyzed for ethylbenzene with  a GC-8A Shimatsu  gas chromatograph. An eight-port
 valve was connected to two 5-mL sampling loops.   This  instrumental setup gave an excellent time
 resolution when ethylbenzene concentration was higher than IS  mg/m3.
       Tenax sampling tubes  were used to measure the ethylbenzene backgrounds and the low-level
 ethylbenzene re-emission.  Air samples were taken  from the same locations, using a DuPont P4LC
 personal sampling pump with sampling flow  set to  1  L per min.  The samples were then thermally
 desorbed and analyzed by a Perkin-Elmer Sigma 2000 gas chromatograph with a flame ionization
 detector.
       Good correlation was found between the two analytical methods in a  high concentration range
 (r2 m 0.984 with n - 18).

 Air Exchange Rate Determination
       The air exchange rate in a building changes from time to time. In order to make mass balance
calculations, we need to know the real time air exchange rate profile.  The short term air exchange rate
 was determined by the tracer gas decay method10. In order to calculate the continuous air exchange rate
profile, indoor temperature, local outdoor temperature, and wind speed were continuously monitored
during the experiment An empirical air infiltration model11 was used to correlate those environmental
parameters to the air exchange rate:

       N = A + B AT + C Wg                                                             (1)

where N is the air exchange rate in h*1;
                                             52

-------
       A, B, and C are statistically determined constants;
       AT is the indoor-outdoor temperature difference in °C;
       W, is the wind speed in mi/h.

RESULTS

Ethylbenzene Delivery Rate
       The actual ethylbcnzenc delivery rate  was 0.0988  g/min.  The total amount of ethylbenzene
delivered in the 72-h period was 427 g.

Real-Time Air Exchange Rate Profile
       Thirteen sets of tracer data  were collected during the test and used to determine  the three
parameters in the air exchange rate model (Eq. 1) by multiple linear regression. The results were: A =
0.204; B m 0.0062 ± 0.0010; C = 0.300 ± 0.0051; and the multiple correlation coefficient» 0.9267. The
average air exchange rate during the test period was 0.28 h"1.  The calculated air exchange profile for
the first 72 h is shown in Figure 2.

Indoor Ethylbenzene Levels During the Test
       There was no significant difference in ethylbenzene concentration between the two  sampling
locations.  Ethylbenzene concentrations found in the living room are given in Figures 2 and  3. Some
statistics regarding indoor ethylbenzene levels are given below:

       Indoor background (2 samples): 0.003 mg/m3;
       Outdoor background (12 samples):  0.002 mg/m3;
       Maximum  indoor concentration:  83 mg/m3:
       First 72-h average concentration: 64 mg/m3;
       Concentration at t - 72 h (072): 72 mg/m3;
       Time for concentration to drop from C^ to 50% C^:  4 h;
       Time for concentration to drop from C^ to 75% C^:  10 h;
       Time for concentration to drop to 1 mg/m3:  100 h;
       Time for concentration to drop to 0.1 mg/m3: 480 h;
       Concentration after 1,000-h decay:  0.02 mg/m3.

       For comparison purposes, the no-sink prediction (using the real-time air exchange profile) is also
shown in Figures 2 and 3.  From Figure  2, one can see that the concentration fluctuation can  be
attributed to the varying air exchange rate—the dynamic feature of real buildings. The three peaks in
the concentration curves corresponded to the three valleys in the air exchange rale profile because the
low air exchange rate caused by calm wind and/or small indoor/outdoor temperature difference favored
indoor pollutant accumulation.

DISCUSSION

Mass Balance for Ethylbenzene
       The mass balance  for  ethylbenzene  was made in two different  ways: one based on  the
accumulation phase, and the other on the decay phase.
       For the accumulation phase, the amount of ethylbenzene adsorbed by indoor surfaces after 72 h
of continuous exposure can be calculated based on the following mass balance:

       Mass adsorbed by indoor surfaces at t  = 72 h (W3) =
                                             53

-------
              Mass delivered by HPLC pump in 72 h (W,,)
              - Mass remaining in indoor air at t = 72 h (Wj)
              - Mass exfiltrated in 72 h (W2)                                               (2)

       Mass delivered by the pump was W0 = 427 g. The amount of ethylbenzene remaining in indoor
 air at t = 72 h is the product of the indoor concentration at t - 72 h and the house volume: Wt = 72
 mg/m3 x 305 m3 = 21,960 mg - 22 g. The amount of ethylbenzene carried out by the exfiltrated air
 in the  72-h period, W2> can be calculated by integrating the concentration curve from time zero to 72
 h:
             72
                CVNdt
                                                                                        (3)
      Iff

W2 -  f CVNdt
where C is the concentration; V the house volume, and N the air exchange rate. In this calculation, we
used the real-time air exchange profile.  The calculated result was W2 = 353 g. We then have the mass
adsorbed by surfaces at t = 72 h:

       W3 = W0 - Wt - W2 - 427 - 22 - 353 = 52 g                                         (4)

       For the decay phase, a similar mass balance equation can be set up:

       Mass adsorbed by indoor surfaces at t - 72 h (W3) =
             Mass exfiltrated during the decay phase (W4)
             + Mass remaining in indoor air after decay(W3)
             + Mass remaining on surfaces after decay (W^
             - Initial mass in indoor air at  t = 72 h (Wj)                                     (5)

By integrating the concentration curve from t =  72 h  to t = 1,085 h, we obtained W4  = 71 g.  At
t = 1,085 h, the indoor ethylbenzene concentration was 0.02 mg/m3. We have Ws = 0.02 mg/m3 x 305
m3 = 6.1 mg - 0.006 g. Since W5 is so small, we can ignore it in the calculation. We don't exactly
know how much ethylbenzene remained on  the indoor  surfaces after 1,000 h decay, but we are fairly
confident that W6 should be much smaller than W3.  By ignoring both W5 and W6, we get:

       W3 = W4 + W5  + W6 - Wt = 71 + 0 + 0  - 22 » 49 g                                 (6)

    The two values for W3, based on the two phases, arc fairly close.  We can say that, after the source
was shut off, about 50 g ethylbenzene was adsorbed by the interior surfaces, and this value is more than
twice as much as the mass remaining in the  indoor air at the same time (W}  = 22 g).

The Effect of Surface Adsorption and Desorption on Human Exposure
    Since the surfaces do not hold the unreactive pollutants permanently, the existence of reversible sinks
does not change the total exposure for a given indoor pollution event  Instead, the interaction changes
the time distribution of human exposure. To show the significance of this  effect, we compared  the
observed exposure with that without sink effect  We first plotted a fitting curve to the data (the solid
line in figure 3), and then used the smooth curve to calculate the daily exposure.  The no-sink case was
represented by simple exponential decay: C = CQ e*Nt  where CQ is the initial concentration, N is  the
average air exchange rate, and t is time.  In our case, CQ = 72 mg/m3, and N  =  0.275 h"1. The simulated
no-sink decay is shown by the dotted line in Figure 3.  Table I compares the two cases.
                                            54

-------
                   Table I. Comparison of human exposure in decay phase.*
                                           Daily Exposure f(mg/m3) day]
                            This Test(A)          No-Sink Case (B)            (A):(B)
Day 1
Day 2
Day5
Day 10
Day 20
Day 50
20.2
4.64
0.889
0.270
0.085
0.020
9.75
0.016
0.003
0.003
0.003
0.003
2.1
290
2%
90
28
7
* Background daily exposure = 0.003 I(mg/mb day].

CONCLUSIONS
      Interior surfaces can adsorb a substantial amount of ethylbenzene. After a 72-h exposure to an
average concentration of 64 mg/ro3 ethylbenzene, interior surfaces adsorbed about 50 g of the pollutant,
roughly twice the amount in the indoor air at the time the source was removed.  In the absence of
•dsorptive surfaces, indoor concentrations would  drop to background levels within 72 h due to the
indoor/outdoor air exchange. The observed concentration, however, was seven times background 1,000 h
after the removal of the  source.   Control strategies designed to prevent long-term, low-level human
exposure to organic pollutants must consider the pollutants' adsorption to and re-emission from interior
surfaces.

REFERENCES
1. P.A. Nielsen, "Potential pollutants, thtir importance to the sick building syndrome, and their release
mechanism." in Proceedines nf the 4th International Confereny* ™ ^Anor Air Quality and Climate, Vol.
2, Institute for Water, Soil and Air Hygiene, Berlin, 1987, pp 598-602.
I T.G. Matthews, A.R. Hawthorne, and C.V. Thompson, "Formaldehyde sorption and  dcsorption
characteristics of gypsum wallboanf," Environ. Sci. & Techno!.. 21(7): 629-634 (1987).
3. B. Berglund, L Johnson, and T. Lindvall, "Adsorption and absorption of organic compounds in indoor
materials," in Proceedings of Healthy Bui]dines '88.  Vol. 3, Swedish Council for Building Research,
Stockholm, 1988, pp 299-309.
4. B. Berglund, I. Johnson, and T. Lindvall, "Volatile organic compounds from building materials in a
simulated chamber study," Environment International. 15(3):299-309 (1989).
5.1. Gebefugi and F. Korte, "Indoor accumulation of scmivolatilcs," iiv Proceedings "f Rfod. A&WMA
Annual Mfflfrg  Air and Waste Management Association, Anaheim, CA, 1989, Vol. 6, paper number
89-86.1., pp 1-9.
6. B.A. Tichenor, Z. Guo, J.E Dunn, LE. Sparks, and M.A. Mason, "The interaction of vapour phase
organic compounds with indoor sinks," Indoor Air. l(l):23-35 (1991)
7. L.E. Borrazzo, C.I. Davidson, and J.B. Andelman,  The influence of sorption to fibrous surfaces on
indoor concentrations of organic vapor," Proceedings of 83rd A&WMA Annual  Meeting.  Pittsburgh,
PA, Air & Waste Management Association; 1990, Vol. 5, paper number 90-91,1, pp 1-14.
8. U. Kjser and P.A. Nielsen, "Adsorption and desorpttan of organic compounds on fleecy  materials,"
to IAO'91  Healthy Building. American  Society of  Heating, Refrigerating and Air-Condi Don ing
Engineeti, Inc. 1991:285-188.
                                             55

-------
9.  B.A. Tichcnor, L.E.Sparks, J.B.  White and  M.D.  Jackson, "Evaluating Sources of  Indoor  Air
Pollution," Journal of Air and Waste  Management Association, 40(4):487-492 (1990).
10. ASHRAE, ASHRAE jlandbook of Fundamentals. American Society of Heating, Refrigerating  and
Air-Conditioning Engineers Inc., Atlanta, 1985, p 22.8.
II. Ibidem, p22.13.
           Master
           bedroom
              Clos
                                 Master
                                 both
                                 Both
                Clos
Corner
bedroom
           ClOS |   Return
                    air

                            xj~Cto,
                     Clos

                     A

                      Utility
                     Middle
                     bedroom
                                                     Den
                                                Kitchen
                                                  Living room

                                                        D
                                                Clos
                                                                    Instruments
                                                              Goroqe
                 = Source Location    o  = Sampling Location
                                                             = register
                  Figure 1.  Floor Plan for EPA Indoor Air Quality Test House
 140


 120
       Air Exchang* Rat* (X400)



V '        \ -              '. .*
        10    20    30    40   50   00   70   80
                 Elapsed Tim* (hrs)
                                             0.1,



                                            0.01;


                                           0.001
                                                         i j"«—NoSlnkD»cay
                                                         !
                                                                   Indoor Background
                                                    200    400     600    800
                                                            Elapstd Dm* (hrs)
                                                                                      1000   1200
   Figure 2. Ethylbenzene Concentration in
            in Living Room  (Accumulation)
                                               Figure 3. Ethylbenzene Concentration in
                                                        in Living Room (Decay)
                                              56

-------
        ASSESSMENT OF INDOOR AIR EXPOSURE TO MEDICAL WASTE
      INCINERATOR EMISSIONS BY EXTRACTIVE FOURIER TRANSFORM
         INFRARED SPECTROSCOPY AND CONVENTIONAL SAMPLING

                                  Eric D. Winegar
                                  Jeffrey B. Hicks
                                Radian Corporation
                             10389 Old PlacervUle Road
                              Sacramento, CA 95827

                                 William F. Herget
                           Nicolet Instrument Corporation
                                 5225 Verona Road
                                Madison, WI  43711
ABSTRACT

      Various methods are used to measure pollutants for indoor air quality investigations.
Conventional industrial hygiene and ambient air methods are limited by long data turnaround,
difficulty in observing contaminant fluctuations over short periods of time, the limited
number of analytes for each method, and relatively high detection limits.

      Recent developments have enabled fourier transform infrared (FTIR) spectroscopy to
collect low digit ppbv concentration data on a near real-time basis for many organic and
inorganic chemical species. This  method can bridge the gap between the need for rapid
information and low detection limits compared to conventional methods.

      This paper describes extractive FTIR used in a six-week field indoor air study for
pollutants that may have entered the building due to emissions from a nearby medical waste
incinerator.  The FTIR results were compared to traditional ambient air methods for selected
pollutants. The advantages and disadvantages of the method will be discussed.

INTRODUCTION

      There arc a wide variety of methods and techniques available to measure the presence
and concentrations of air pollutants in indoor environments.  Methods commonly used for
indoor testing include modifications of the NIOSH  or OSHA methods, the application of
recognized ambient air quality measurement techniques, or development of methods specific
to the non-industrial indoor environment.  While these modern methods are able to generate
useful results at very low chemical concentrations and specific to the pollutants of interest,
they do have limitations. These limitations include a long turnaround time from sample
collection to receipt of analytical results; difficulty in monitoring short-term concentration
changes due to the integrated sample collection period; the limited number of analytes that
may be detectable from one sampling device; limited instrument sensitivity that requires
extended sampling times for some compounds; the  relatively high cost of collecting large
numbers of samples from multiple locations for an  extended period of time; and, the
difficulty in collecting samples during "episode events" that are frequently not predictable.

      In some situations, the traditional sampling  and analytical methods to measure low
concentrations of indoor pollutants fall short of the practitioner's need.  This is especially
                                         57

-------
true when the situation requires a large number of measurements over an extended period of
time.

       The use of fourier transform infrared air (FTIR) monitoring is an evolving technology
that is finding a variety of applications.'  This instrumentation is currently being used for the
measurement of environmental "ambient" air for selected pollutants, automotive exhaust, and
workplace air samples. This technology provides real-time measurement of a wide variety of
air pollutant concentration at relatively low detection limits, and by employing a closed-cell
system with multi-point extraction from the study areas, provides an opportunity to monitor
several different indoor environments simultaneously.

       FTIR was  selected for this study due to the need to monitor for a variety of gases and
vapors over a long period of time.  In addition to the use of FTIR, concurrent monitoring
was also performed during two time periods using conventional sampling and analytical
methods.

       This study was performed to measure selected inorganic gases and vapors that were
believed to be entering an office building from a nearby,  frequently upwind,  medical waste
incinerator.  The study was performed for six weeks. Complaints had been expressed by the
occupants of the office building that on occasion,  during upset conditions in the nearby
incinerator, odors and an apparent "haze" were noticed in the building and attributed to
emissions from the incinerator.  The medical incinerator stack is located approximately 250
feet from the primary outside air intake for the building.  Occasionally, upset conditions
occurred with the medical incinerator requiring the use of a bypass stack that bypasses some
of the pollution control equipment. It was impossible to predict when the incinerator upset
conditions would occur, and when indoor air complaints were expressed by the occupants.

       The building contained several  separated areas and ventilation zones, with openable
windows.  It was  necessary to monitor the different areas of the building to assess the
situation throughout the building.  A closed-cell "extractive" sampling system was designed
and installed.  This system involved the use of a plumbing system employing 1-inch diameter
stainless steel piping that  was oriented to sample five indoor locations and one outdoor
location near the building air intake.  Electronically controlled valves and a pumping system
was employed  so  that each sampling location was sequentially sampled for a 10-minute time
period once each hour. The air was drawn through the stainless steel  piping system and into
the closed cell  for FTIR analysis.  A test of the tubing network with SF6 showed that
approximately 2 seconds were required for transport of sampled gas from the farthest
location into the white cell for analysis.  Purging  of the cell for subsequent sampling points
required 4 minutes.  Figure 1 shows the six sampling locations within the building, and
Figure 2 shows a schematic of the extraction and  FTIR system.  Data was collected nearly
continuously for a period of 53 days, with a data  capture of 80 percent.  Some data
collection time was lost due to instrumental downtime and exhaustion of the liquid nitrogen
supply used to cool the detector.

METHODS

       A Nicolet  Model 740 FTIR interferometer interfaced to a Nicolet Model 620 data
acquisition system was used for measurements. Air was  pumped at a  rate of 2.8 CFM into a
3-meter multiple pass "white cell" from Infrared Analysis, Inc. where the infrared beam was
reflected off a  series of mirrors, giving an effective path length of 72 meters. The co-added
225 FTIR spectra per sampling period were analyzed for 25 different chemicals selected from
a list of approximately  125 compounds, including hydrocarbons, chlorinated organics,  and
                                          58

-------
inorganic gases and vapors. The list of analytes that the FTIR spectra were analyzed for and
their respective detection limits are presented on Table 1.

       Air sampling was conducted during two events using EPA Method TO-14 that
incorporates the use of SUMMA™ polished evacuated stainless steel canisters equipped with a
flow controller so that integrated sampling would be conducted over an 8-hour time period.
Analysis of the collected whole air sample from canister was performed by cryo-focusing an
aliquot of the gas sample and analysis by gas chromatography/mass spectrometry in the SIM
mode for 42 common VOCs.  EPA Method TO-5 was used for ambient air aldehyde
sampling and analysis.  This method employs the use of Sep-Pak cartridges, which contain
silica gel sorbent impregnated with dinitrophenylhydrazine.  Air was drawn through the
sprbent tube that captures and preserves the resultant aldehyde derivatives for high pressure
liquid chromatography analysis.  NIOSH method 7903 was used to measure acid gases.  Air
was drawn through a sorbent tube containing washed silica gel.  Analysis was conducted by
desorption in an aqueous solution followed by ion chromatography. Total suspended
Paniculate and metals were determined by drawing air through a 25 mm  Teflon* filter with
subsequent analysis by x-ray fluorescence.

       For comparison of actual detected concentrations, a Tedlar* bag containing several
gases was emptied into the white cell with its pumping system turned off. After coming to
equilibrium, the FTIR sampled the resultant gas mixture concurrently with obtaining a
canister grab sample.  Table 2 shows the agreement of the FTIR results versus the canister
data.

       Meteorological measurements were obtained at the site during  the FTIR measurement
period by the use of portable meteorological station.  A MET 1* meteorological station was
used to continuously record weather conditions including wind speed, wind direction,
temperature, relative humidity and rainfall.

RESULTS

       Continuous measurement of selected chemical constituents in outdoor and indoor
locations of the facility under study was successful.  Typically, concentrations of the gases
and vapors studied varied only slightly from one location to the next, and from day-to-day.
Many of the pollutants selected for FTIR monitoring were rarely detected.  The most
commonly detected compounds included carbon monoxide, carbon dioxide, ammonia,
methane, ethene, formaldehyde, methanol, benzene, toluene, and chlorobenzene.  Air
Pollutants anticipated to be released during the incinerator episode  events, especially when
the bypass stack was used (i.e.,  bypassing the acid gas scrubber and baghouse), included acid
gases such as hydrogen chloride and hydrogen cyanide.  However, these gases were rarely
detected by FTIR, and not detected by conventional sampling methods.

       Figure 3 contains a series of spectra showing the process of verifying the presence of
a compound by subtracting the spectrum of a period in which the chemical is known not to
be present.  This subtracted spectrum is then compared to the reference  spectrum at the
bottom.

       Throughout the six-week FTIR  monitoring period, only one incinerator "episode"
occurred.  It was  anticipated that the incinerator episodes would occur more than once over
the six-week monitoring period. Daily logs were maintained in which odor or other occupant
complaints were noted. On August 29, characteristic "burning" odors were noted by several
of the building's occupants.
                                         59

-------
      Table 3 presents a daily average from the FTIR measurements conducted at the
facility during an non-episode and episode day associated with incinerator operations. The
episode event occurred when several occupants reported characteristic "burning" odors in the
building. Noticeable increases for some chemicals monitored occurred, especially for carbon
monoxide, carbon dioxide and ammonia, during the episode event.  These results indicate
that none of the chemicals measured exceeded or approached the OSHA permissible exposure
limits during the episode event for the compounds of interest. Figure 4 provides additional
details concerning indoor chemical concentrations on the day the episode was noted.  The
characteristic odor was reported during the morning hours, and this time dependent plot
confirms a peak concentration of CO and benzene at 10:00 AM.  It appears that carbon
monoxide may be a good surrogate indicator for the combustion gases when infiltrating into
the building.

      Table 4 contains the overall average of the indoor versus the outdoor values.  As
expected, formaldehyde in the indoor air is present at higher levels than outdoors.  Several
other compounds -- m-xylene, sulfur dioxide, 1,1,1-trichloroethene, carbon tetrachloride,
trichlorethene,  and hydrocarbons — showed this same characteristic.  With the exception  of
sulfur dioxide,  all these chemicals could have originated from indoor sources.

      The FTIR system proved to be a valuable tool for obtaining a large amount of
concentration data. Indeed this large amount of data provided its own set of problems in
reducing and interpretation of the dataset, though this was seen mainly as an asset, since
many sampling programs suffer from a scarcity of data.  Possible improvements in the
system used would mainly center on logistical concerns such as the construction of the tubing
network. The optical system and chemical analysis method provided near-real time data
collection capability that could not be matched by traditional methods.

CONCLUSIONS

      This study demonstrated the utility of FTIR measurements for indoor air
environments.  The instrumentation is especially useful when measuring selected inorganic
and organic gasses and vapors that are believed to be present on an intermittent basis, and in
which continuous monitoring is required for extended periods of time.  The instrumentation
shows good sensitivity and specificity for the analytes studied during this project.
REFERENCES

1.    Grant, W.B.; R.H. Kaganin; and W.A. McClenny. 1992.  "Optical Remote
      Measurement of Toxic Gases."  Journal of Air and Waste Management Association.
      Vol. 42, No. 1,  pp. 18-30.
                                         60

-------
          OUTSIDE AIR INTAKE
     IT        "a   I   I   U
           FTIR/WHITE CELL LOCATION-UPSTAIRS
                 ... . TIDING NETWORK
 Figure 1. Stanford ESF Building Study Layout
Control
and Data
Reduction
Com put or
Solenoid
 Valves
                         3 Meter
                         White Cell
                         (72 Meters Path)
                              ~-'r— Exhaust
 Figure 2. Schematic of Extractive FTTR System
                    61

-------
                 LOBBY CONCENTRATIONS-FTIR
                           (PPBV)
    800


    700 -


    600 -


    500


    400


    300 1


    200


    100 -


       .
       500
                     1000
                               TIME
                                    1500
                                                   2000
 Figure 3.  Plot of Selected Pollutants During Incinerator "Episode.*
           11  1-TRlCHLOROETHftNE 52.6 PPM-M 750/25
. .
                                                       ' If,
     00    750    800    650    900    350    1QOG   1050
                 Figure 4.  Example FTIR Spectra.
                                62

-------
                                  Table 1
               Compounds and Their Detection Limits Measured
                       by FTTR During Stanford Study
      Compound
MDC (ppbv)  I       Compound
MDC (ppbv)
Water                       MBA
Hydrocarbon Continuum          5
Sulfur hexafluoride             0.2
Carbon monoxide             MBA
Carbon dioxide               MBA
Ammonia                      5
Methane                     MBA
Ethene                        5
Propylene                      10
Formaldehyde                  10
Methanol                      10
Benzene                      75
Toluene                      50
              m-Xylene
              Hydrogen chloride
              Hydrogen cyanide
              Nitrous oxide
              Nitrogen oxide
              Sulfur dioxide
              Chloroform
              1,1,1-Trichloroethane
              Carbon tetrachloride
              Trichloroethylene
              Chlorobenzene
              Freon22
    20
     5
     10
   MBA
    200
    75
     10
     10
     5
     20
     50
     5
MDC = Minimum detectable concentration
MBA = Much below ambient
                                  Table 2
                 Comparison of White Cell FTIR Measurement
                           Versus Canister Sample
                                (Units:  ppbv)
Chemical
Chloroform
1,1,1-Trichloroethene
Ttichloroethene
Toluene
Sulfur Hexafluoride
j Frm
336
10
1.6
270.2
820
I Canister
340
3.9
1.9
280
760
                                     63

-------
                Table 3

FITR Measurement Results - Daily Averages
Chemical .
Carbon Monoxide
Carbon Dioxide
Ammonia
Methane
Ethene
Propylene
Formaldehyde
Methanol
Benzene
Toluene
m-Xylene
Hydrogen Chloride
Hydrogen Cyanide
Nitrous Oxide
Sulfur Dioxide
Methylene Chloride
Chloroform
1,1, 1 -Trichloroethene
Carbon Tetrachloride
Trichloroethylene
Chlorobenzene
Freon 113
Outdoor
Non-episode
(80S)
290
340
34
2,500
2.3
ND
ND
9.3
77
16
ND
ND
ND
220
92
ND
6.4
0.63
ND
ND
45
0.48
Indoor * Lobby
Non-episode
(8/25)
320
350
35
2,500
3.0
ND
8.6
32
60
18
ND
ND
ND
220
104
ND
6.1
1.2
ND
ND
57
1.0
Indoor - Lobby
Episode
(8/29)
490
390
46
2,400
4.9
ND
0.1
34
85
50
ND
1.3
ND
210
162
ND
6.4
1.4
ND
ND
57
0.1
OSHA
PEL
35,000
5x 10*
24,000
NA
NA
NA
1,000
200,000
1,000
100,000
100,000
5,000
10,000
50,000
2,000
50,000
10,000
350,000
2,000
50,000
75,000
1 x 10*
                Table 4

   Comparison of Indoor Versus Outdoor
         Concentrations by FTIR
              (Units:  ppbv)
Compound
Carbon Monoxide
Formaldehyde
Toluene
Xylene
Sulfur Dioxide
1 , 1 , 1 -Trichloroethene
Carbon Tetrachloride
Trichloroethene
Hydrocarbon Continuum
| Indoor
462
11.1
ND
188
123
21.6
18.9
31.5
50.8
Outdoor
516
ND
83.8
ND
78.4
15
ND
ND
23.7
                   64

-------
 Practical Limitations of Multisorbent  Traps and Concentrators for
        Characterization of Organic Contaminants  of Indoor Air

                                    Mark A. Mason
                      Air and Energy Engineering Research Laboratory
                           U.S. Environmental Protection Agency
                       Research Triangle Park, North Carolina 27711

                            Kenneth Krebs and  Nancy Roache
                                  Acurex Environmental
                                    P. O. Box 13109
                       Research Triangle Park, North Carolina 27709

                                    James A. Dorsey
                                        Consultant
                                     124 Indian Trail
                               Raleigh, North Carolina 27609
ABSTRACT
      Practical limitations of two types of multisorbent traps and two  sample preconcentrators were
investigated. A cryogenic preconcentrator trapped and transmitted normal alkanes with boiling points
between -42 and 257°C without apparent loss while a sorbent concentrator was able to trap and deliver
compounds with boiling points between -42 and 316°C.  For multisorbent traps, recovery relative to n-
decane decreased significantly beyond 257°C for n-alkanes desorbed at 250 and 300PC from graphitized
carbon traps and  by 796  and 15%  for n-alkanes with boiling points of 285 and 32CPC from a trap
containing glass beads, TenaxR, Ambersorb", and charcoal (ST032). Sampling an air stream containing
21 contaminants (12 hydrocarbons and 9 oxygenated compounds) resulted in acceptable recoveries
(100+/-25%) of hydrocarbons from all combinations of traps and concentrators with the exception of
cyclohexane from the cryoconcentrator and a-pinene from the sorbent concentrator  which apparently
underwent rearrangement and interfered with quantitation of propylbenzene. Acceptable recoveries of
oxygenated compounds were observed with the ST032 traps  and  sorbent concentrator,  but poor
recoveries were observed for many of the oxygenated compounds from both multisorbent systems using
the cryoconcentrator.

INTRODUCTION
       The observation that concentrations of vapor-phase organic compounds are generally higher
indoors than outdoors, even in relatively polluted locales,  has focussed attention on charactenzation
of sources of indoor  pollutants.1  Sorbent collection of organic vapors and thermal desorption to a
cryogenic or  sorbent concentrator, followed by gas chromatographic  (GC) analysis has been  used
extensively for identification and quantification of organic indoor air pollutants.1-3  Multisorbent traps
containing  several  adsorbents  arranged   in  series retain  a broad range  of organic compounds.
Quantitative recovery should occur if analytes are not altered during thermal desorption, retained by the
adsorbent, or altered by the sample concentrator or transfer system.
       An experiment was conducted to  evaluate two types of  analytical  concentrator units and two
types of multisorbent sample collection systems. Experimental goals were to:  (1) determine the boiling
point range limitations of the concentrator units and sorbent systems and (2) investigate recovery from
                                            65

-------
each multisorbent  system  of a  broad  range of compounds including  alkanes, alkenes, aromatics,
ketones, esters, and alcohols. The boiling points for this mixture ranged from 70 to 170°C.  Therefore,
the second phase  of the  experiment neither examined  recovery  of very volatile  or  semivolatile
compounds nor investigated recovery from sample volumes larger than  3 L.

EXPERIMENTAL METHODS

Analytical Systems
       The two analytical systems used in this project were (1) an HP5890 GC equipped with a mass
selective detector (MSD),a flame ionization detector (FID), and a Nutech cryoconcentrator and (2) an
HP 5890 GC with FID and electron capture (EC)  detectors coupled to  a Unacon 810 (Envirochem)
concentrator.

       The Nutech cryoconcentrator consists of a modified Model 320-02 desorption chamber, 320-01
controller, clamshell oven, and Model 370 temperature controller.  The  desorption chamber houses a
1/16 -in. (0.16 cm) OD nickel stainless cryotrap wound around a heating cartridge.  The system has
been modified by addition of a hot injection port  and four-port valve. The Nutech concentrator is
connected by heated nickel stainless transfer tubing  directly to a 0.32 mm OD by 30 m DB-5 column.
Column effluent is split to  an FID and HP model 5970 MSD.

       The Envirochem system, an automated system designed to permit unattended analysis of up to
16 sorbent traps, includes the Unacon 810 concentrator, Envirochem 815 temperature controller, and
Envirochem 8916 multiple tube desorber.  The Unacon utilizes two sorbent traps to refocus analytes
desorbed from multisorbent traps. A hot injection port permits introduction of analytes directly to the
large bore concentrator trap.  The heated transfer line of the Unacon is connected directly to a 0.53 mm
by 30 m DB-5 (megabore) GC column.  A splitter at the end of the column directs effluent in a 9:1
ratio to the FID and EC detectors.

Multisorbent Traps
       Two different multisorbent systems were utilized.  Traps of each design contained sorbents in
series designed to trap a broad spectrum of organic compounds.

       Graphitized carbon adsorption traps consisted of "front" and "back" cartridges and were
constructed in-house and contained in series approximately 380 mg Carbotrap C, 750  mg Carbotrap*,
and 50 mg Carbosieve SID". Traps were prepared for use by overnight thermal desorption at 300°C
under purified  nitrogen flow of 20 cc per minute in reverse of sampling  direction.  Cleaned traps
were allowed to cool under purge then immediately removed from the desorption manifold. Trap ends
were sealed with 1/4 -in. (0.64 cm) Swagelok* end caps and Teflon/glass ferrules (Supelco, OM-2), and
trap sets were  sealed in Teflon* bags.

       Envirochem ST032 adsorption traps, purchased from T.R.  Associates Inc., are fabricated of
6 mm OD by  203 mm long silanized borosilicate glass tubing and contain approximately 290 mg of
20/30 mesh   silanized glass beads, 85 mg of 20/35 mesh TenaxR TA,  170 mg of  35/60 mesh
Ambersorb XE-340*, and 48 mg of 80/100 mesh activated charcoal.   Sorbent tubes were cleaned by
purging at room temperature for 5 minutes with high purity nitrogen (50 cc/min) then conditioning at
350°C for 15 minutes. Conditioned tubes were placed in glass holders fitted with screw caps.  Tubes
and holders were then sealed in Teflon*  bags.
                                             66

-------
Preparation of Standards
      Normal alkane (even carbon number, C, to C*,) standards were prepared by diluting weighed
aliquots of each compound (Chem Services, West Chester, PA) in hexane (Fisher Scientific). Serial
dilutions of primary standards were used to create working standards ranging in concentration from 2
to 2000 ng per pL.   A gas standard containing nominally 50 ppm each Cj to C5 alkanes in air was
purchased from Air Products, Durham, NC.   The bottled standard was diluted with air from a clean
air generation system to create working range concentrations. Calibrated mass flow controllers were
used to control  flow of  the bottled  standard and dilution air.   Calibration  standards  for  the
Environmental Protection Agency/Health Effects Research Laboratory (EPA/HERL) 21 component
mixture were prepared using the gas bulb technique described by Riggin.4 The compound mixture used
for this standard was a subsample of the mixture used in the exposure generation system. Toluene was
added to the mixture as an internal standard.

Standards Recovery Experiment
      Aliquots of 1 fiL each of the C, to €„ normal alkane mixture were injected by solvent flush into
the hot port of each concentrator unit and trapped on the sample concentrator. Trapped analytes were
flash desorbed to the analytical  column, identified by retention time, and quantified by area counts
obtained from  electronic  integration of the FID response.  Response factors were calculated  for each
compound by least square fit of triplicate injections at five concentration levels.   Recovery of the same
compounds from the sorbent traps was investigated by spiking sorbent traps connected directly to a 1/4-
in. packed column injection port of a Perkin Elmer Sigma 2000 GC and analyzing  spiked traps using
each concentrator. Sorbent traps were spiked with the C, to C, mixture by pulling 100 cc of the diluted
gas through sorbent traps using a Samplair piston displacement pump.

Exposure Chamber Sampling Experiment
      Constant concentrations of 21 organic compounds are generated at the EPA/HERL exposure
chambers by vaporizing a mixture of the compounds in a large glass dilution  system.1 Test chamber
total net concentration for the 21  compounds is maintained at 6.5 ppm as toluene by a feedback control
system utilizing the output from a total hydrocarbon monitor. Concentrations of individual compounds
range nominally from 2 ppb (octene) to 2 ppm (m-xylene and butylacetate). Duplicate samples of 0.3,
1, and 3 L were collected from a port in the EPA/HERL exposure chamber exhaust by pulling air
through carbon and ST032 adsorbent traps.  Samples of 1 and 3 L were collected by pulling chamber
air  at 100 cc/min  through  sorbent traps using a Thomas  vacuum pump and calibrated mass flow
controllers.  Samples of 300 cc were collected using the Samplair piston displacement pump.  Field
blanks were also collected.


RESULTS AND DISCUSSION

Standards Recovery Experiment
       The results of experiments with the n-alkane standard are given in Table I.  Recovery of the Cg
through CM standards from the concentrator trap of the Unacon  demonstrated quantitative recovery
through hexadecane. Recovery  relative to n-decane dropped to 92%  for octadecane and 72% for
eicosane, but relative standard deviation (RSD) for triplicate injections less than 20% indicate that the
system could be used quantitatively to eicosane.
       Desorption of spiked ST032 tubes from the Envirochem 8916 multiple tube desorber at 250°C
resulted in quantitative recovery through tetradecane but a 41 % loss of hexadecane and higher losses
for octadecane and eicosane. Quantitative recovery of propane, butane, and pentane was observed for
the ST032 traps.  Ethane was either not retained by the traps during sampling or not retained on the
                                             67

-------
concentrator traps of the Unacon.
       A 300°C desorption temperature extended the usable range to octadecane for desorption from
ST032 traps; however, a 10% decrease was observed  for the C,0 through CM compounds relative to
recovery from the concentrator trap.  This was observed for both ST032 and carbon sorbent traps and
is consistent with the results of work by Mangani6 that showed a relative decrease in recovery of hexane
and toluene from Carbotrap" at 300°C.  Desorption at 300°C from cartridges packed with Carbotrap C
and Carbotrap* indicated 70% recovery of hexadecane, and 50% recovery of octadecane with relative
standard deviations of triplicate analyses of 30% and greater.
       Recovery of the Cg through CM standards from direct injection to the cryotrap of the Nutech 320-
02 concentrator was (relative to decane) 92% for tetradecane, 77% for hexadecane, and less than 20%
for eicosane.  No significent differences from the direct injection results were observed for recoveries
from ST032 or Carbotrap tubes.  Note that results from this system may be complicated by the effluent
splitter for the FID and MSD: we cannot currently  attribute the losses of higher boiling compounds
solely to the cryotrap.

EPA/HERL Exposure Chamber Sampling Results

       The total volatile organic carbon (TVOC) measured was computed by multiplying the toluene
FID response factor by the net sum of area counts for the 21 compounds.  Concentrations determined
by averaging the three  sample volume results of each system were calculated to be 24.2,24.7, and 23.5
mg per m3 for   cryogenic concentrator/CarbotrapR, cryogenic concentrator/ST032,  and sorbent
concentrator/ST032  systems or 98.5, 100.4, and 95.6% of EPA/HERL's target concentration of 24.6
mg per m3 as toluene.  The precision of the results (RSDs of 3.7 to 5.5%) suggests equivalent recovery
of the 21 compounds  from each system. However, 11 of the  21 compounds comprise 97% of the
pollutant mass and differences in recovery of minor components (0.33 and 0.03%)  will have little
apparent effect on TVOC recovery.
       Compound specific FID calibration factors for each of the 21 compounds were used to determine
the concentration  of each compound for each sample.  Percent recovery for each compound was
calculated by dividing observed individual percent concentration by weight percent in  the mixture.
Averaged results are presented for the three combinations of multisorbent system and concentrator unit
tested in Table II for hydrocarbons and oxygenated compounds.
       Sorbent Conccntrator/STQ32 System!  Recovery of a-pinene decreased  while recovery of
propylbenzene increased with sample volume. Inspection of the mass spectra from GC/MSD analysis
of ST032 adsorbent traps indicated elution of b-pinene  just prior  to propylbenzene.   The lower
resolution of the 0.530 mm diameter column of the  Envirochem/ST032 system may have resulted in
coelution of a-pinene  rearrangement compounds with propylbenzene; however,  this has  not been
confirmed.  No other systematic problems were noted for the hydrocarbons other than erratic recovery
of n-hexane (RSD 23%) and apparent low recovery of n-undecane (80% of expected).  Recovery of
the oxygenated compounds was 20% low for both alcohols but  within 10% of expected for all other
oxygenated compounds.
       Crvoconcentrator/cflrbon Adsorbent System;  Recovery of hydrocarbons from the carbon
adsorbents was acceptable, except for variable recovery of cyclohexane which occasionally coeluted with
3-methyl 2-butanone. No problems were observed with recovery of a-pinene from the graphitic carbon
traps, but recoveries of many (five out of nine) of the oxygenated compounds were suspect. 2-Butanone
was observed to coelute with water and was not quantifiable.   Recovery of alcohols decreased and
recovery of ethoxyethylacetate increased with sample volume,  indicating systematic errors.  Poor
recoveries and reproducibility may be attributed to the sample concentrator rather than the multisorbent
traps since erratic results were observed from recoveries of oxygenated compounds from both types of
traps using  this concentrator.  Further testing will investigate recoveries of the oxygenated compounds
                                            68

-------
from carbon adsorbents using the sorbent concentrator.
      Crvoconcentrator/ST032 Adsorbent System!  Again, poor chromatography resulted in poor
and variable recoveries for  some of the hydrocarbons and most of the oxygenated compounds.
Coelution of 3-methyl 2-butanone and cyclohexane; and nonquantitative recovery of 2-butanone, the
alcohols, and ethoxyethylacetate are indicative of the cryoconccntrator's inability to produce acceptable
chromatography with polar compounds.

SUMMARY AND CONCLUSIONS
      Recovery of C, to  C^ n-alkanes from  two types of multisorbent  traps and GC  sample
concentrators was investigated. A cryogenic concentrator was capable of concentration and quantitive
delivery of C, through CM alkanes, while a sorbent concentrator quantitatively delivered C3 through C,»
alkanes.
      Recovery of Cj to C^ n-alkanes from ST032 multisorbent traps at 300°C from an automated 16
tube desorber decreased from >90% for tetradecane to 76% for octadecanc with RSDs for triplicate
standards less than 10%, suggesting a useable range through n-alkanes with boiling points up to 316
°C with careful calibration.   Recovery from graphitic carbon adsorbents (Carbotrap B and C) at 300
*C with the multiple tube desorber demonstrated significant decrease and variable recovery of n-alkanes
beyond tetradecane.  At desorption temperatures of 250°C, recovery of n-alkane standards from ST032
traps dropped significantly beyond n-tetradecane.  Ethane was not recovered from either trap system.

      Samples of 0.3, 1, and 3 L taken from the outlet air stream of an  exposure chamber using the
two types of multisorbent traps were thermally desorbed to a GC/MSD/FID using a Nutech 320-02
cryoconcentrator to refocus the analytes from the traps.   ST032 traps were also desorbed to a
GC/F1D/ECD  and  analytes refocussed using a 16 tube automated  trap  desorber  and  Unacon
concentrator. The cryoconcentrator effectively trapped and transferred hydrocarbons but was ineffective
with many of the oxygenated compounds.  The Unacon, which concentrates analytes on sorbent traps,
was effective for most oxygenated compounds tested  and all hydrocarbons sampled except a-pinene.


REFERENCES
1.    L.A. Wallace, E.D. Pellizzari, T.D. Hartwell et al.: "Personal Exposures.  Indoor-Outdoor
      Relationships and BreaflLLevelq fpr 355 Persons in New Jersey^*  Atmos. Eviron.  19:1651
      (1985)
2.    B. De Bortoli, H. Knoppel, E. Peccio et al.: "MgflSVremgrit? pf Indoor Air Quality and
      Comparison with Ambient Air^A Study of 15 Homes in Northern Italy." Commission of
      the European Communities Report, EUR 9656EN.  Directorate-General for Science,
      Research and Development, Joint Research Centre, Ispra, Italy (1985)
3.    C.C. Chan,  L. Vainer, J.W.  Martin, D.T.Williams.: "Determination of Organic
       Contaminants in Residential Indoor Air Using  an Adsorption-thermal Desorption, Technique.*
      J. Air Waste Manage.  Assoc. 40:62-67 (1990)
4.    R. M. Riggin: Compendium of Methods for the Determination of Toxic Organic
       Compounds in Ambient Air.  EPA-600/4-84441 (NTIS PB87-168688). USEPA,
       Environmental Monitoring Systems Laboratory, Research Triangle Park, NC (1984)
5.     D. Otto, L.  Molhave, G. Rose, et al.: "Neurobehavioral and Sensory   Tnit^F" Effects of
       Controlled Exposure to a Complex Mixture of Volatile Organic Compounds."
       Neurotoxicology and Teratology. 12:649-652 (1990)
6.     F. Mangani, A. R. Mastrogiacomo:  'Evaluation of the Working  C^iti™" "f Light
       Adsorbents and Thair Use as Sampling Material for the QC Analysis of Organic Air
       Pollutants in Work Areas." Chromatographia 15(11) 712-716 (1982)
                                            69

-------

Multi«otb«niTrtp'
Compound
(Boiling Paint *Q

D«CMM{I74)
Dodecue(216)
TcMdecuw C254)
H«*dec*w(2J7)
Octidecu»(3t6)
EJCOMDC (343)
ST032
Avj*
93.0
92.0
92.0
84.0
76.0
23.0
Carbotnp
B/C
USD
2.6
3.3
2.3
2.8
S.4
S1.2
Avg*
94.0
94.0
91.0
5».0
40.0
3.0
USD
2.4
1.3
6,9
30.0
46.9
6IJ
Cooc*ntntk» Unit Type
Duett
lajecl
SonjcnF
100.0
99.0
102.0
98.0
92.0
72.0

USD
3.2
43
2.9
4.9
7.1
14.4
Direct
Inject
Ctyo*
100.0
96.0
92.0
77.0
46.0
14.0

USD
4.4
4.6
4.5
11.6
29.2
43 .i
], Miihintetf tnpi dwortwd it 300 *C to Untcoa concentrator
2. Unwxm
J. Nutach
Av| " Avenge X recavery
USD • Rdiiive riuxlanl devi*0oti
TABLE n. ttECOVE&Y OF HYDROCARBONS AND OXYGENATED COMPOUNDS


Compound
Scrbtol Conteirintor
ST032Tnpi
Avg*
USD
070 CancealnUir
Onphitic Ciifcon Tnpi
Avg*
USD
Hydrocirboiu
HtMOt
Nonue
Dectne
Und»c«ne
Ocleoe

Cyclahexine
m-XyhM
Ethytb«az«ne
) , 2,4 TrimfibySbenuof
Pnpybcncene
t-Pmcne
11-4.1
114.6
90.5
80.)
103.8
04 a
90.1
102.5
96.4
9JJ
125.6
73.4
22.8
6.2
7.1
5.8
3,4
f. a
7.8
2,4
4.3
l\
20.6
37.7
94.3
105.0
97.1
S7.8
106.9
OR A
100.1
100.2
90J
19.1
95 J
106.0
14.7
9.9
3.1
9.1
9.3
^ <
23.6
3.6
1.8
5.9
3.9
1.5
STQ32 SortwnJ Tnpi
Avj*
USD

106.5
120.5
95.0
89.8
94.1
01 1
115.7
103.9
83.9
»».5
90J
88.8
3.6
8.3
9.4
21.6
1.0
1 1 n
56.5
4.9
19.4
n.t,
7.7
17.2
Oxy|«MUd Compound*
PcaUn*)
HMMMl
2-Praptnol
g|ri«iwJ
2-BuUnoM
J-Mrthyl 1-BuUnooo
4-Methy| 2-Pertuooe
»«utyi AeeUI*
EUwxyeihyUcUU
97.0
96.7
77.8
79.2
90.7
90.8
97.0
102.5
94.6
9.9
7.5
27,9
11.5
!t.8
J.9
4.2
0.9
6.9
93.7
96.2
80.5
84.2
NA
S7.2
103.3
101.8
126.4
11J
12.8
22.2
36.2
HA
65.1
10.3
6.9
34.6
79.6
82.3
78,1
41.5
HA
69J
96.2
106.4
102.3
4.6
66.3
19.4
84.7
NA
76.4
11.2
6.5
92.8
                                                      70

-------
 FUNDAMENTAL MASS TRANSFER MODELS APPLIED TO
      EVALUATING THE EMISSIONS OF VAPOR-PHASE
ORGANICS FROM  INTERIOR ARCHITECTURAL COATINGS
                           Zhishi Guo Acurex Corporation
                                 P.O. Box 13109
                          Research Triangle Park, NC 27709

                                Bruce A. Ticbenor
                                 Indoor Air Branch
                                 U.S. EPA/AEERL
                          Research Triangle Park, NC 27711
ABSTRACT

      Emissions from paints and other coatings can cause elevated indoor concentrations of vapor-
phase organics.  Methods are needed to determine the emission rates over time for these products.
Some success has been achieved using simple first-order decay models to evaluate data from small
dynamic test chambers.  While such empirical approaches may be useful for assessing the emission
potential of indoor sources, a more fundamental approach is needed to fully elucidate the relevant
mass transfer processes. Researcher's at EPA's Air and Energy Engineering Research Laboratory
(Indoor Air Branch) are in the process of evaluating mass transfer models based on fundamental
principles (o determine their effectiveness in predicting emissions from indoor architectural coatings.
As a first step, a simple model based on Pick's Law of Diffusion has been developed. In this
model, the mass transfer rate is assumed to be controlled by the boundary layer mass transfer
coefficient, the saturation vapor pressure of the material being emitted, and die mass of volatile
material remaining at any point in time.  Both static and dynamic chamber tests were conducted to
obtain model validation data. Results of these tests are presented. Comparisons between empirical
and mass transfer models are also provided.
                                       71

-------
 INTRODUCTION

       Indoor concentrations of total VOCs (volatile organic compounds) of several hundred
 milligrams per cubic meter can occur after petroleum based interior coatings are used.1  Small
 environmental test chambers have been used to develop emission rate data for such products.2
 These tests involve placing samples of coated substrates in the chambers and measuring total VOC
 (or individual compound) concentrations at various times as the coatings dry.  The concentration vs.
 time data are then used to determine the parameters of empirical emission rate models.  The first-
 order decay model3 (also  called the R
-------
where, C - VOC concentration (mg/m3) in the bulk air and  6 = apparent laminar boundary layer
thickness (m).  The ratio D,/6 represents the mass transfer coefficient.  To apply this idealized case
to indoor environments, we introduce the concept of "apparent laminar boundary layer thickness. "
It is a normalized length used to represent the mass transfer zone within the source/air interface, and
is defined as the thickness of an imaginary thin  layer of air above the source within which molecular
diffusion is the only mechanism that transfers VOCs from the source surface to the bulk air and vice
versa.  Its value is determined so that the overall mass transfer resistance in that layer is equivalent
to that of the real case that it represents. Substituting equation (2) into (3):

                          rate = - (D,/6)[C - Cv (M/ M0)]                              (4)

    mass balance equation for VOCs in chamber air is:

                         V(dC/dt) =  - QC - S( D,/5)[C -  Cv (M/ MQ)]                    (5)
where, V = chamber volume (m3), Q = chamber air flow rate (m3/h), and S = source area (m2).
The mass balance for the VOCs in the source is:

                          S(dM/dt) - S(D/6)[C - C¥ (M/ M0)]                         (6)

por the initial conditions at t = 0, C = 0 (an empty chamber) and M = MQ.  The solutions of
Rations (5) and (6) give the following expressions for chamber concentration (equation 7) and
emission rate (equation 8):
                          C = {LCJVWr, - r^Hexpfrt) - exp(r2l)]                     (7)

where, L = product loading = S/V (m2/m3) and rt_2 is described by equation (9).

                    R -  -dM/dt = {CvD/[6(r, - r7)]}[(r, + N)exp(r,t) - (r2 + N)exp(r2t)]   (8)

where, N = air exchange rate (h'1), and:

                                    ±  [(N+LD/S+DA/(5Mo))2-4DfNC¥/(SM0)]w}/2     (9)
s'nce the mass transfer mechanisms represented by equations (7) and (8) are controlled by vapor
Pressure and boundary layer effects, we call this model the VB model.


PRELIMINARY MODEL VALIDATION

       There are seven parameters in the VB model: M0, C», Dfl S, V, N, and 6: (he first four are
Properties of the source, and the rest are properties of the environment.  All of them can be
determined or calculated independently. The key parameter is the apparent laminar boundary layer
thickness, 5.  in order to estimate 5 in our test chambers, we applied wood stain to oak boards and
"t the model to the concentration vs. time data.  Five data sets were obtained.  The parameters used
we*e: initial vapor pressure, Cv = 11 g/m3; average diffusivity (based  on the most abundant
compound, decane), Df =  0.0207 mj/h; sample size, S - 0.021  m1; chamber volume, V = 0.053
m ; and air exchange rate, N = 0.5 hr1.  The value of M0 varied from test to test.  The 5 value
obtained through non-linear regression was 5 = 0.00886  ± 0.00169 m.  We have also estimated the
                                             73

-------
5 values at different air exchange rates, and sample sizes.
       Chamber tests were then conducted for polyurethane and liquid wood floor wax using the
same sample substrate (oak boards). These two products contain mixed solvents (mineral spirits)
similar to those used in the wood stain. The VB model was used, with the 5 value obtained in the
wood stain test, to predict the chamber concentration vs. time. Comparisons between model
predictions and chamber data are shown in Figure 1.  Given that we have not adjusted any model
parameters, we consider the  predictions to be very good.
       When the parameters  change, the model adjusts itself automatically to give proper
predictions. Figure 2 shows model predictions for two sets of wood stain data at different air
exchange rates.
       We also compared the emission rates predicted by the VB model and the lyk model with
those directly calculated from chamber data for polyurethane.  Figure 3 shows that the new model
follows the experimental results more closely than the first-order decay model.
DISCUSSION

       One of the major features of the VB model is that all the parameters have clear physical
definitions, and they can be either experimentally determined or calculated.  The other desirable
feature is that each parameter represents a property of either the source or the environment, but not
both.  These features give the model greater flexibility, and it is possible to apply it to different
environments.  We are in the process of validating the VB model in a test house.
       It is recognized that the degree of air turbulence in test chambers may be significantly
different from that found in indoor environments.  Such differences may cause scale-up problems in
the use of chamber-derived emission rates in indoor air quality models.  Thus, a source model
properly validated in test chambers may not be applicable to sources in real buildings.  The
introduction of the apparent laminar boundary layer thickness provides one way  to solve this
problem.  In addition to experimental determination, it may be possible to calculate the value of this
parameter by correlating it with other fundamental parameters such as the Reynolds number (Re),
Sherwood number (Sh), and Schmidt number (Sc).
       When validating the VB model using dynamic chamber data, we used a Cv value of 11 g/m3
for mineral spirits based on static chamber tests.  Since we applied the product to oak boards outside
the chamber with an application time of about 5 minutes, when we closed the chamber door and
started the test,  the source had been emitting for 5 minutes.  This is not the case in buildings where
wet products are applied indoors.  Thus, we recommend a higher vapor pressure value (either
calculated based on  the solvent composition or experimentally determined) for use in those cases.
       The diffusivity of a given compound can be obtained  through theoretical calculations. The
most commonly used equations are: the method of Fuller, Schettler, and Giddings (FGS),  and the
method of Wilke and Lee (WL).4  The values  of diffusivity of consecutive alkanes,  the major
components of mineral spirits, are fairly close: with a molecular weight increase from CgH,g
(octane) to C12Hj4 (dodecane), diffusivity decreases by only 20%.  The average diffusivity for five
alkanes from C8Hlg  to C12HM is 0.0209 mVhr, which is very close to the decane diffusivity of
0.0207 m2/hr.
CONCLUSIONS AND RECOMMENDATIONS

       A fundamentally based model (VB model) has been developed to predict organic emission
rates from oil-based indoor architectural coatings.  Preliminary validation results indicated that the
                                             74

-------
VB model can be applied to different products with similar solvents.  The model provides a better
fit to chamber-derived emissions data than the empirical first-order decay model, especially over the
decaying portion of the concentration vs. time curve.  Further validation of the approach is required.
Test house studies are underway for three products tested in small chambers.  Both chamber and test
house studies are needed for other indoor product categories.
REFERENCES

1. B.A. Tichenor, L.E. Sparks, M.D. Jackson et al., "The effect of wood finishing products on
indoor air quality," in Proceedings of the 1990 U.S. EPA/A&WMA International Symposium on
Measurement of Toxic and Related Air Pollutants. EPA/600/9-90-026 (NTIS PB91-120279),
Raleigh, NC, 1990, pp 968-973.

2. B.A. Tichenor, Indoor Air Sources: Using Small  Environmental Test Chambers to Characterize
Organic Emissions from Indoor Materials and Products. EPA/600/8-89-074 (NTIS PB90-110131),
U.S. EPA,  Air and Energy Engineering Research Laboratory, Research Triangle Park, NC, 1990,
39pp.

3. B.A. Tichenor and Z.  Guo, "The effect of ventilation on  emission rates of wood finishing
materials,"  Environment International. 17:  317-323 (1991).

4. W.J. Layman, W.F. Reehl, and D.H. Rosenblatt, Handbook of Chemical Property Estimation
Methods,  McGraw-Hill, New York, NY,  1982, Chapter 17, pp 9-17.
                                           —   VB Model
                                            -|-   Data (Polyuretbane)
                                            D   Data (Floor Wax)
                 0    2     4    6    8    10    12   14    16   18    20
                                    Elapsed Time (b)

 Figure 1.  VB model predictions for two wood finishing products tested in small chambers.
                                            75

-------

                                                    VB Model
                                               +   Data (N = 0.5)
                                               D   Data (N = 1.0)
                    2    4     6    8    10   12    14    16   18    20
                                  Elapsed Time (h)
Figure 2. VB model predictions for wood stain tested in small chambers at two air exchange rates.
           100000-
                                                —  VB Model
                                                     R0/k Model
                                                 D  Data
                 0          46         10   12   14   16    18   20
                                    Elapsed Time (h)
Figure 3.  VB model vs. R
-------
     EVALUATION  OF THE EFFECTIVENESS  OF SEVERAL
  TYPES  OF AIR CLEANERS  IN REDUCING THE HAZARDS
               OF INDOOR  RADON  DECAY PRODUCTS
                       N. Montasster, PJC. Hopke, Y. Shi, and P. Wasiolck
                                  Department of Chemistry,
                                    Clarkson University,
                                   Potsdam, NY 13699-5810
                                            and
                                        B. McCallum
                                Atomic Energy of Canada Ltd,
                                   Ottawa, Ontario, Canada


ABSTRACT
      The objective of this study was the evaluation of three types of air cleaners, an ion
generator/circulation fan, an electrostatic air cleaner, and a filtration system, on the concentration and size
distribution of radon progeny in a normally occupied house. Using an automated, semi-continuous, graded-
screen array system and a radon monitor, the activity size distribution and radon concentration was
measured every two hours for almost 7 weeks. During one week each, an air cleaner was continuously
operated. The exposure of the occupants of the home to radon and the concentration and size distribution
of airborne decay products could be assessed during the 4 weeks in which no cleaner was in use. The dose
model developed as part of the recently released  U.S. National Academy of Sciences report (National
Research Council (1991) Comparative Dosimetry of Radon in Mines and Homes, National Academy Press,
Washington, DC) was used to relate the exposure to deposited dose in the tissue of the bronchial
epithelium.  Thus, the effectiveness of the air cleaners in reducing both exposure and dose were assessed
and the results of that assessment will be presented.


INTRODUCTION
      A critical factor for the effectiveness of radon decay products in providing dose to the human
respiratory tract is the size of the particle to which the decay product is attached. Air cleaners can
effectively remove most particles and radon decay products from indoor air. Since the air cleaner does not
remove radon, the decay products, particularly short half-lived It$Po (3.05 min), can very quickly be formed
in the air. When the particles are removed,  the "unattached" fraction increases and although there are
fewer decay products, they are more effective in depositing their dose of radiation to the lung tissue. The
increased dose per unit exposure means that there will be much lower dose reduction than there is
radioactive concentration reduction.  Thus, the exact dose impacts of air cleaners are uncertain, and there
are  major uncertainties in the effectiveness of air cleaning to reduce the dose of radiation when there is
simultaneous removal of particles from the air. So, studies are needed to measure the concentration and
size distributions of the radon progeny activities in real living conditions where air cleaners are being
employed.
                                           77

-------
AIR CLEANERS
       Three types of room air cleaners were tested. A NO-RAD Radon Removal System (Model 1000
from Ion Systems, Inc.) is a ionization, filtration and air circulation system developed by Ion Systems, Inc.
A ionizer emit a steady stream of ions using emitter bristles (388,000 ions cm'1 measured at one meter)
that will increase the plateout rate in the room. A three speed fan draws room air through a two stage
filters. In this study,  the fan was set at low speed.
       A F59A console Electronic Air Cleaner (EAC), from Honeywell, includes a 3-speed fan that draws
room air through an electronic cell and activated carbon filter.  High, medium and low fan speed
corresponds respectively to 560, 450 and 270 m3 h'1 ( 330, 265, 160 cfm). The low speed was chosen for
our experiments.  Into the electronic cell, airborne particles pass through an electric field where they
become electrically charged.  Then, they enter a second electric field set up between a series of parallel
plates. Charged particles are then collected to the ground plates. Lastly, odors are absorbed by an
activated carbon filter.
       A Pureflow Air Treatment system from Amway is designed to maximize the filtration efficiency. It
includes a multi-stage filter, three activated carbon filters plus one High Efficiency Particulate Air (HEPA)
filter, and a four fan speed (the highest speed provides about 150 cfm).

HOUSE CHARACTERISTICS AND INSTRUMENTATION
       Experimental data used in this study were collected in a one-story, ranch home in Arnprior,
Ontario, a small village about 60 km northwest of Ottawa. This house has a basement with an approximate
area of 200 m2 while the first floor, presented in Figure 1, has an area of about 210 m2. The house was
occupied by three people, none of whom smoke. Measurements were made from May to July  1991, and no
heating or air conditioning was used during the sample period. The sampler and air cleaners were placed
at the dining room end of the kitchen/dining area (23 m1, Figure 1).
       Measurements of radon progeny size distributions were made using the Automatic Semi-Continuous
Graded Screen Array (ASC-GSA) described in detail by Ramamurthi and Hopke1.  The ASC-GSA system
is a fully automatic device capable of measuring the activity-weighted size distribution of each individual,
short-lived  radon decay product. It uses wire screens for particle segregation and alpha spectrometry for
radioactivity detection.  Samples were taken and analyzed every two hours. A Pylon Passive Radon
Detector (PRD 111), was used for continuous measurements of the radon gas concentration.
       Data were collected for a week long period for each  air cleaner alternating with a week with no ail
cleaner running (Background). Table I summarizes the experiments conditions. The speed of  the fan was
set for living conditions (i.e. as quiet as possible).  However,  in order to set the air cleaners at the same
speed, the Pureflow system was first run at high speed (4). Because it was too noisy, it was subsequently
set at a lower speed (2). The air cleaners were operated continuously during experiments.

RESULTS AND DISCUSSION
Radon Concentration and its Progeny
       Mean values and arithmetic standard deviations of the radon, Potential Alpha Energy
Concentration (PAEC) and equilibrium factors are presented in Table II.  The equilibrium factor was
calculated for each samples; then, mean values and standard  deviations from each experiment were
obtained. As expected, the radon concentration was not affected by the air cleaners; the values were
almost the same for every experiment with a grand mean of 1.1 pCi L"1 ( or 41 Bq m"3). However, a
significant decrease of both PAEC and equilibrium factor was observed  with the air cleaners running.  The
mean value of the equilibrium factor for the background conditions was found in the range of 0.4 to 0.5.
But this value decreased when the air cleaners were running as particles were  removed. From  the
equilibrium factor, one can observe that the NO-RAD reduced the mean PAEC per unit radon by 38%
while the EAC provided 56% and the Pureflow 65% of reduction.
                                               78

-------
Activity-Weighted Size Distributions
       Figure 2 shows the typical bimodal size distributions of radon progeny and PAEC for background
conditions.  However, changes in size distributions (Figure 3) were observed when air cleaners were
working.  A peak in the size range from 1.5 to 5 nm was induced when the NO-RAD was running. The
EAC caused an increase in the activity fraction of the small particles with a distinct peak in the smallest
particle size. Meanwhile, the activity fraction of particles greater than 15 nm decreased.  With the
Pureflow system, experiments 6 and 7 suggest an influence of the fan. When it was set to the medium
speed, the Pureflow system did not seem to change the shape of the size distribution significantly.
However, for high speed, the activity fraction decreased in the size range of 1.5 to 15 nm while the smallest
size fraction increased.  Those differences may be due to increased air cleaner efficiency at  the higher
speed as  indicated by the manufacturer.

Exposure and Dose Estimates
       From the PAEC concentration and activity size distributions and assuming that these limited
measurements  are representative of the situation throughout the year, the annual average exposure, Ep and
the dose  to the bronchial epithelium can be calculated (Table III).  An occupancy factor of 0.68* was used
to estimate Ep.  The dose per unit exposure, for a male adult with a mean breathing rate of 0.74 m! h'1, was
calculated using the most recent dosimetric model (NRC model' modified by James4). In the current model
the dose  to basal and secretory cells is evaluated on the basis of the calculated deposition of activity as a
function  of particle size and breathing rate. As expected, the dose per unit exposure (D/EP) was similar for
the "backgrounds" (between 31 and 37 mGy WLM-1 for the secretory cells and between  15 and 17 mGy
WLM'1 for the basal cells). When the Pureflow was running, D/Ep stayed at the same level; however this
value increased to 44 mGy WLM >  for the NO-RAD and up to 48 mGy WLM'1 for the EAC.  This implies
that the reduction of exposure by both the NO-RAD and the EAC was much higher than the dose
reduction. In fact, experiments 2, 4, 6 and 7 when air cleaners were running compared to the background
(exp 1, 3 and 5, respectively), show exposure reduction per unit radon of 47% for the NO-RAD while the
dose reductions per unit radon were 27%.  The EAC diminished the exposure by 50% and the dose by
33%. A  decrease of 67% was observed for both exposure and dose for the Pureflow system.

CONCLUSION
       The effectiveness of the three types of air cleaner in removing radon progeny and changes in size
distributions of radon decay were investigated in a single family house in Arnprior, Ontario. Radon gas and
radon progeny concentration as well as the radon decay product activity-weighted size distribution were
measured semi-continuously. Each device  decreased the decay products concentration, reduced the
equilibrium factor and consequently the exposure but this decrease depends strongly on the type of air
cleaner used.  Moreover, air cleaners producing a shift of the size distribution towards smaller particle sizes,
like the NO RAD or the EAC, increased the dose per unit exposure. Thus, dose impact of air cleaners
depends  strongly on the way particles are removed.

REFERENCES
!•     M. Ramamurthi and P.K. Hopke, "An automated, semi-continuous system for measuring indoor
       radon progeny activity-weighted size distributions, dB: 0.5-500 nm," Aerosol Sci. Technol.  14: 82
       (1991).

2.     International Commission on Radiological Protection (ICRP). (1987). "Lung cancer risk from
       indoor exposures to radon daughters." ICRP Publ. 50, Ann, of ICRP. Pergamon, Oxford.

3-     National Research Council (NRC). (1991). "Comparative dosimetry of radon in mines and homes."
       National Academy Press, Washington, DC
                                                79

-------
4.      AC. James, D.R. Fisher, T.E. Hui, F.T. Cross, J.S. Durham, P. Gehr, MJ.  Egan, W. Nixon, D.L.
       Swift and P.K. Hopke, "Dosimetry of radon progeny," In: Pacific Northwest Laboratoryj\nnuaJ
       Report for 1990 to the DOE Office of Energy Research. Pt. 1, pp 55-63. PNL-7600, Pacific
       Northwest Laboratory, Richland, Washington (1991).

ACKNOWLEDGEMENT
       This work was support by the New Jersey Department of Environmental Protection under Contract
P32108 and P33444.
                                                   -24.4m-
                GARAGE
                                FAMILY ROOM
                                                   LIVING ROOM
                                                                           BATH
                                                                                 BEDROOM
                                                       AIR
                                                       CLEANER
              LAUNDRY
              AREA
                                  KITCHEN
DINING
ROOM
                               DEN
                                                                            MASTER
                                                                       /\  BEDROOM
                                                                       	6.4m
               Figure 1.  Floor plan of the first floor of test house in Arnprior, Ontario.
 E
3
                                              80

-------
00
                                       _o
                                       a
u.v
0.5
0.4
n i

0.2
01

nn
O



a
0




[-9-
!T| O


u
•7T
O


0


a


-
LJ
„
o


0.5
c
o
= 0.4
?t01
j >,
-^03
04

no
-O



U
o





A H
1

a
&
o



o

o


o^
c




                                              i     10    100
                                              Portklfl Dtametar (nm)
       1     10    100
      Particl« Diameter (nm)
                                    I   I PAEC
                                    m
                                    &
                                    u
u.t
c °'J
a
= 0,1
o
^ rt,
3 0.2
0.1
IYC
1
"o




L]
O
S

fc '
-

_
o


ft
o
p

0
ft

o

u
o"
-
  0.61-1
  D.5 -
 c
= 0.4 -c
!»•
fo.2-
^0.1^
                                                                                    Oi-cn
                                                                    0.0
                                              1     10    100
                                              Parttdfl Diameter (nm)
       1     10    100
      Particute diameter (nm)
                Figure 2.      Average size distributions measured under background
                               conditions with no aii cleaners operating.
                         figure 3.

c
o
2 •*; 0.4
| 0
£ ^ 0.3
H 3>


0.1
0.0



-o

-

.

-
to

y
u



1









..
"

1
10



-


«

a
o


0


«J_

o"

-

1 1 T

c
o
i>
5i S
u ^DJ
* ^
H"o
•<
0.1
OjO
o






D

-O

I
100 1










J
*~ 1
10



-

-
o
0

u

4> «.'


ij

u-

O-

' t '
100
Parfieta Diameter (nm) Porticte Diameter {nm}
1 1 PAEC
&s

5 g 04


•i* -O
S ^ 0.3
a £
I < M
0.1

_o







•a
-V




"
_ *!*_ *«*,_
O Po D Pb









-
^
D*(^ | 1 ]








8
o




O


x-

o
-

05
C

£+ "o

S ^-
'"^

flS0""
0.1




0


•


-D
*










-&T*-
• i i

o tut
•


0


A_

rS-
o

p
o

1
u

O

*


               1      10     100
              PartTcl* Oksmeter (nm)
 1     10    100
Partict« D"ramrt«r (nm)
Average size distributions measured while the air cleaners
were operating.

-------
                                                                         Table I.  Experiments conditions.
Experiment
number
1
2
3
4
5
6
7
8
Sampling period
May 13-21
May 21-28
May 28-June 3
June 3-10
June 10-17
June 28-30
June 30-July 5
July 5-6
Conditions
Background
NO-RAD on (low speed)
Background
EAC on (low speed)
Background
Pureflow on (high speed)
Pureflow on (speed 2)
Background
No. of
samples
77
50
54
77
69
24
52
11
**Rn (pCi L'1)
Mean
1.2
0.8
0.7
1.1
1.7
1.4
1.1
1.1
Standard
deviation
0.5
0.5
0.4
0.6
1.2
1.1
0.7
0.4
PAEC (mWL)
Mean
5.8
2.2
2.6
2.1
7.5
2.1
1.6
5.0
Standard
deviation
ZO
1.1
2.0
1.6
6.2
1.8
1.1
2.1
Equilibrium Factor
Mean
0.50
031
0.41
0.18
0.43
0.15
0.15
0.45
Standard
deviation
0.13
0.14
0.22
0.12
0.19
0.06
0.08
0.13
oo
K>
                                                                      Table II. Exposure and dose estimates.
Exp.
1
2
3
4
5
6
7
8
E»
WLMy1
0.20
0.08
0.09
0.07
0.26
0.07
0.06
0.17
E,/Rn
0.17
0.09
0.14
0.07
0.15
0.05
0.05
0.16
Secretory Cells
D/E, '
mGy/WLM
33
44
34
48
37
32
35
31
D/Rn
5.6
4.1
4.6
3.1
5.6
1.6
1.8
4.9
Basal Cells
D/E,
mGy/WLM
16
20
16
22
17
15
16
15
D/Rn
2.6
1.9
2.2
1.5
2,6
0.8
0.9
2.3

-------
          MEASUREMENT OF INDOOR RADON LEVELS
                       IN  13 NEW FLORIDA  HOMES
                                     James L. Tyson
                                   Charles R. Withers
                                Florida Solar Energy Center
                                    300 State Road 401
                               Cape Canaveral, Florida 32920


ABSTRACT
    The Florida Solar Energy Center has been  involved with the Florida Department of Community
Affairs in  the past year demonstrating radon resistant construction techniques.  FSEC has installed
mitigation  systems in  13 new homes.
    These homes were built on soils containing  up to 20,000 pCi/1 of radon in the soil gas.  Extensive
testing was done on the slabs to determine the amount of cracking, and on the house to characterize the
pressure between the house and the sub-slab and  between closed rooms in the house and the main body
due to the  operation of the air handler.
    Pressure differences between the main body of the house and the sub-slab area of as high as 16.5
pascals have been observed. Changes in this pressure of up to 13.2 pascals have been measured between
natural conditions and system operating conditions.  Radon measurements taken  before and  after
activation of the mitigation system will be compared.  Measurements were made using continuous radon
monitors for a minimum period of 48 hours.
    Causes and remedies for elevated radon levels in Florida homes are discussed. Seasonal variations
in indoor measurements are compared, and results of measurements in one problem house in the project
are presented.

INTRODUCTION
    The Florida Solar Energy Center has for the past year been  involved with the Florida Department
of Community Affairs in demonstrating radon resistant construction techniques in new Florida homes.
    Radon gas is the result of the radioactive  decay  of radium-226,  an element which is found  in
varying degrees in many soils. As a gas it can  easily be transported through soil, and enter homes if
entry  pathways exist.  Damage to the lung cell tissue  can occur when the gas undergoes a series  of
radioactive decays, depending on the concentration of the gas and the length of exposure.
    The state of Florida is developing a radon building code, and is funding this project to accumulate
o^ata on the effects of radon resistant construction techniques on indoor radon levels. The number  of
houses tested to date (13) is too small a number on which to base definitive conclusions, but the project
is on-going, and an additional 17 houses are scheduled to be tested in the current year.

EXPERIMENTAL METHODS
    Data collected can be divided into three areas - soil, slab, and house. Soils were tested to determine
type, permeability, radon and radium content, radium emanation coefficient, and diffusion coefficient.
The house slab was examined to characterize the  crack size and number, and the pressure field extension
under the  slab created by the sub-slab depressurization system was  measured.  The  finished house
underwent extensive testing, including blower door, tracer gas, and duct leak measurements.
                                            83

-------
Soil
     Native soil radon levels were found by driving a probe one meter into the ground and taking a grab
sample of soil gas for analysis.  This was done using a portable radiation monitor with scintillation cell
technology. (Williamson)
     Soil sample analysis by the University of Florida reveal a surprising trend of higher radium content
in the fill soil  than in the native soil in the area of the project  This is probably due to the use of sand
tailings from mining operations in the local area.  The use of high radium fill soils could import a radon
problem onto  a site with low native  radium content, and this situation might lead to government
regulation of the radium content of fill soils.  Table I below presents the soil data.

                           Table I. Radium, Radon and Permeability
House
Number
1
2
3
4
5
6
7
8
9
10
11
12
13
Native
Ra-226
0.7
3.6
2.9
0.9
1.2
0.5
10.8
1.9
6.2
1.0
0.2
8.8
0.4
Native
Radon
(pCi/1)
3,851
3,547
11,055
2,103
902
640
20,858
15,371
4,500
1,179
657
1,790
574
Native
Perm.
(cm2)
6 X 10'*
2 X 10'v
1 X 10'7
2 X 10-'
2 X 10*7
1 X 10"7
2 X 10''
5 X 10'9
6 X 10'8
9 X 10'8
6 X 10'8
3 X 10''
4 X 10"y
Fill
Ra-226
(pCi/g)
10.3
18.8
29.5
16.0
5.6

5.3
0.7
8.5
2.4
5.2

9.9
Fill
Radon
(pCi/1)




475
183

1,100



548

Fill
Perm.
(cm2)
4 X 10"'
9 X 10'1U
9 X 10'10
1 X 10"'
4 X 10''

6 X 10*"

1 X 10-y
6 X 10'7
6 X 10'7
5 X 10' '
8 X 10'8
Slab
    Cracks.  Cracks were characterized by measuring the approximate width of each crack, and the
length of each crack.  Air flow through the cracks was found by sealing a small chamber to the cracfc
taping the crack for one meter in both directions, and applying a negative pressure to the chamber to
draw  through soil gas. (Acres International)2 A grab sample of this air was taken for radon analysis-
Although the vapor barrier remained relatively intact, there were cases of substantial radon being drawn
through the cracks.  It should be noted, however, that the pressure applied to the cracks during the test
was much higher than that normally produced in the house environment. A concentration of 2370 pCi/1
was drawn through a crack in House #7, and 234 pCi/1 from a crack in House #2, but most of the tests
yielded  much smaller levels.
    Pressure Field  Extension.  Sub-slab depressurization systems were installed  by laying dovfl
ventilation matting under the  slab, and  attaching a PVC riser that extends  through  the roof.  Small
diameter plastic tubing was also  laid down at the same time, and run out beyond the slab for later u#
as measurement points.  Pressure field measurements are then  taken by  attaching a fan to the riser afld
measuring the pressure at each tube end.  (Tyson)3  These tubes are also used to measure sub-slab rado"
levels.  The  mitigation systems were activated in 6 of the 13 houses in  the project.
                                               84

-------
    Figure 1 shows an example of the ventilation mat design and the pressure field extensions produced
in the project.
                           Figure  1.  House #4 Pressure Field Extension
                                     (Pascals)

House
     Data collected during house dynamics testing was extensive, including descriptions of the house and
HVAC system, blower door and infiltration data, and  differential pressure data.  Pressure differential
measurements were made between the indoors (in the main body of the house) and the outdoors, subslab,
and various sections of the  house.  Pressure differentials between the house and the subslab region of
up to 16.5  pascals were recorded with the air handler on and all doors closed.  Pressure differentials at
this level will draw soil gas into the house through cracks and slab penetrations in the absence of an
active mitigation system.
     Interior Radon  Levels.  Interior radon  measurements  were taken with a portable radon monitor
using scintillation cell technology.  Monitors were  placed in the main body of the house  and allowed
to run continuously for at least 48 hours.  During this period,  all windows were closed, doors were open,
and the air handler was run continuously.  An effort was made to test each house with the vent stack
for the mitigation system closed off.  This gives a  reading on how  effective the slab is as a barrier to
radon.  The house was then  tested for another 48 hours  with the vent stack uncapped, and the mitigation
system in a passive mode.  If interior readings were still above the EPA action level after this  test, then
a fan was permanently installed in the system, and  another 48 hour  test was conducted.  A level of 3.7
pCi/1 was used for the cutoff, to compensate for the short testing period.  Results from these tests are
summarized below in  Table D.
     An interesting result of these  tests  is the difference in levels noted between winter  and summer
season results.  House #5 dropped its indoor radon  level considerably from the initial winter reading to
the second summer reading.  House #4  also  fell below the  action level in the second  test, also  in the
summer. These differences due to season call into question the use of strict action levels, especially for
new construction, as  it can be argued that seasonal variations  in  the radon source make these tests
unreliable.  Work is being  done in conjunction  with the Florida Department of Community Affairs to
correlate seasonal variations in  radon levels.
                                                85

-------
                                 Table II.  Radon Levels (pCi/1)
#
1
2
3
4
5
6
7
8
9
10
11
12
13
Native
Soil
3,851
3,547
11,055
2,103
902
640
20,858
15,371
4,500
1,179
657
1,790
574
Capped
Subslab

4,986

6,570
614
1,090
5,040
1,483
6,506
1,620
2,900


Capped
Indoor
0.6
4.7
0.7
3.7
3.7
4.4
3.6

1.1
1.1
1.7


Passive
Subslab



2,730
614
883
3,090

6,441
1,350
3,120
7,097
4,032
Passive
Indoor

4.9

4.9
3.7(0.9)
2.2
13.3
3.7
1.1
2.1
1.8
2.0
5.4
Active
Subslab

2,068
2,080
2,200

39
4,554
1,140

2,330



Active
Indoor

2.9

5.4


34.0
1.8




1.8
Second
Test



1.8


4.6






     House #7 is the most interesting case in the project.  In the first post-construction test the indoor
level actually went up when the mitigation system was turned on, with a peak of over 60 pCi/1, which
decayed over a two-day period. This is in contrast to the 24 hour cycle displayed during the passive test,
the results of which are presented in Figure 2 below. The graph starts at midnight, and the first 24 hours
are correct military time.  The radon data are plotted along with the air temperature. A  pattern exists
which indicates  that the weather is playing some part in the elevated indoor radon levels.
                                                                             u
                                           JO   III   41
                                             Tlnw (h)

                                   	RaCan  + Tmp (C)

                            Figure 2.  Radon vs. air temperature (#7).
                                                                           II
                                               86

-------
    Figure 3, shown below, contrasts the passive and active data for House #7. The active mitigation
system reduces the height of the peaks in radon concentration, but does not bring the house below the
EPA action level. It should also be pointed out that the active test was conducted in the summer, and
the passive in the winter. This seasonal difference might account for some of the decrease in radon level
shown here.
                          t   II    IB   ti   M   M   U   41   54   10   M   71
                                              Acflin
                           Figure 3. Active vs. passive control (#7).
CONCLUSIONS
    Mitigation systems were activated in  five of the  13 houses in  the project, and only one house
reniains above the EPA action level at this time. Seasonal variations in the indoor radon levels call into
Question the use of strict action levels, without good correlation between seasonal radon levels.
    The elevated radium content of some fill soils can lead to the importation of a radon problem onto
a site on which radon does not exist   This use of high-radium fill soil could  lead to government
regulation of fill soils.
    The active mitigation system in House #1 did not work as well as theory supposes. This could be
    to the very high levels of radon in the soil on the site.  This house remains above the action level,
     an average of 4.6 pCi/1 indoors over a 4 day period in the latest test.  This house is scheduled to
 6 nstrumented exhaustively to determine the cause of the 24 hour cycle of elevated radon levels found
•n the indoor environment.  (Other houses on the  same street show the same cyclic behavior.)
    Longer term  measurement  periods that  cover whole  seasons are  preferable to short term
Measurements, and a term of one year would average seasonal variations out  Unfortunately, a year long
test period is unworkable, especially for new houses and real estate transactions.  Work is on-going to
 stablish a relationship between the seasons and radon sources and indoor radon levels.
                                              87

-------
REFERENCES

1.  A.D. Williamson, and J.M. Finkel, Stajjdard^easurement Protocols, compiled for the Florida
Department of Community Affairs, 1990.

2.  Acres International Corporation, "Radon Entry Through Cracks in Slabs-On-Grade", Appendix VI
B. of Volume V of the Second Draft Report for the Florida Department of Community Affairs, 1990.

3.  J.L. Tyson and C.R. Withers, "Installation and Evaluation Techniques Used to Measure Pressure
Field Extension from Sub-Slab Depressurization Systems Installed in New Florida Homes", Proceedings
of the 1991 AARST National Fall Conference, pp. 526-545. American Association of Radon Scientists
and Technologists, Rockville, MD,  1991.
                                            88

-------
    EFFECTS  OF VENTILATION ON SMOKING LOUNGE
                                 AIR QUALITY

                P.R. Nelson, R.B. Hege, J.M. Conner and G.B. OJdaker III
             R.J. Reynolds Tobacco Company, Bowman Gray Technical Center,
                              Winston-Salem, NC 27102

                                   Harold E. Straub
                        TITUS Products, Richardson, TX  75081
ABSTRACT
      An experimental smoking lounge (test lounge) was constructed and various ventilation
configurations were evaluated.  The lounge was evaluated at maximal occupancy (14 smokers) and
ventilated at 60 CFM per occupant (ASHRAE Standard 62-1989). Concentrations of CO, CO2,
and RSP were monitored and integrated average concentrations of nicotine, 3-ethenylpyridine, and
RSP were determined. Occupants rated the air quality in the lounge as being acceptable for most
of the configurations. Smoking did not contribute significantly to CO2 concentrations.  Smoking
had a small  effect on CO concentrations; the average  increase was less than  1.5 ppm. RSP
concentrations  ranged  from  365 to 642 ngfm3) and  were consistent with smoking  activity.
Concentrations of nicotine and 3-ethenylpyridine ranged between  80-139 ^ig/m3 and 5.6-12.3 ^g/m3,
respectively.  Overall, ETS concentrations were lowest when the air within the test lounge was well
mixed. Results from the test lounge were compared to those obtained in a smoking lounge in an
office building.  Concentrations of nicotine  and RSP were an order of magnitude lower in the
smoking lounge in the office building under normal occupancy and use conditions than they were
in the test lounge.

INTRODUCTION
      The designation  of specific smoking areas, such as smoking  lounges, can  provide
accommodation for smokers in workplaces  with smoking  restrictions.  Presently, there  is little
information  available to guide construction of  a smoking lounge  with acceptable  air quality.
Perceptions of indoor air quality may be based on a number of factors including odor, irritation,
temperature, humidity and drafts(l-7).  Effective ventilation will reduce concentrations of irritants
and diminish concentrations  of odoriferous contaminants.  Air distribution can  affect both
ventilation effectiveness and comfort parameters.
      ASHRAE Standard 62-1989  recommends that air be supplied to smoking lounges at 60
CFM per occupant in order to achieve  acceptable air quality(8).  However,  the Standard does not
make any recommendations regarding  air distribution. Data which demonstrate effective ways to
ventilate  areas used by both smokers and non-smokers are available(9), but there are no data on
effective  air  distribution for smoking lounges.
      The effect of ventilation (the combination of air supply  and distribution) on air quality
within a smoking lounge was investigated in a specially constructed test room. The room complied
with the  ventilation  rate procedure of ASHRAE  Standard  62-1989.   Short-term  testing was
performed in the test lounge  at maximal occupancy (upper limit smoke concentrations). Air
quality in the test lounge was investigated in terms of occupant acceptability and ETS constituent
concentrations.   ETS concentrations also were monitored  in a  "real-world" smoking lounge  in
order to relate the results obtained at maximal occupancy  to more typical  conditions.
                                          89

-------
 EXPERIMENTAL

 Test Lounge
       The dimensions of the test lounge were 19'4" x 13'H" x 9'.  The maximal occupancy was
 determined to be 14 smokers(lO).  Air supply and temperature were monitored and controlled by
 computer. Total air flow through  the lounge was controlled by an exhaust fan which was vented
 to the outside.  Cooling air (350 CFM) and transfer air (490 CFM) were drawn from adjacent,
 non-smoking office areas.  Brief descriptions of the five air distribution configurations tested are
 given in Table I.  The 1-WAY and 4-WAY ventilation configurations rely on conventional air
 distribution whereas the remaining three configurations were expected to provide displacement
 ventilation.  Three replicate experiments were performed in the test room for each configuration.
 The test lounge is described elsewhere in greater detail(lO).
       Each experiment lasted 80  minutes.  Background concentrations of CO, CO2 and RSP in
 the air supplied to the lounge were monitored during the first ten minutes of each experimental
 run  while smokers were  ushered into the test room and seated.  Immediately following the
 background collection, air was sampled from the test room  for ten minutes. This sampling period
 was used to determine the effect of the smokers, but not their ETS, on CO, CO2, and RSP in the
 lounge.   At 20 minutes, the smokers were instructed  to  begin  smoking together.  All of the
 smokers smoked their regular brand. After smoking the first cigarette, each smoker was permitted
 to smoke ad  libitum for the  remainder of a 50-minute  smoking period.  At the end of the 50-
 minute smoking period, the smokers  extinguished their  cigarettes,  exited the chamber, and
 responded on a ballot to the statement: "The air quality in  the room was acceptable to me. True
 False."  Concentrations of CO, CO2 and RSP in the supply air were then monitored again for ten
 minutes  to verify that background  concentrations did not change  significantly  over the course of
 the experiment. Integrated average samples were obtained  during the 50-minute smoking period.

Field Sampling  Location
       Concentrations  of CO, CO2, nicotine and RSP were determined in the smoking lounge of
 an office building. The smoking lounge was designed to accommodate up to 15 smokers and was
ventilated at 1033 CFM.  The building was ventilated with  *20 CFM fresh air per occupant
during testing.

Table I  Ventilation configurations examined in test smoking lounge.


       Code                                     Description


     4-WAY       Cooling air supplied through two four-way blow diffusers along main axis of room,
                  transfer air and exhaust located along minor axis, (conventional ventilation)
     1-WAY       One-way blow diffusers discharging away  from each other substituted for 4-way
                  blow diffusers of 4-WAY configuration, (conventional ventilation)
     WALLS       Cooling air supplied through low-velocity slot diffusers centered on each wall,
                  transfer air introduced through pairs of grills on two opposing walls. Exhaust
                  located in center of ceiling, (expected to behave like displacement ventilation)
      PLUG       Cooling air and transfer air supplied to sub-floor space. 75% of floor tiles
                  replaced with perforated tile. Exhaust located in center of ceiling,  (expected  to
                  behave like displacement ventilation)
     PLUG2       Cooling air and transfer air supplied to sub-floor space. 50% of floor tiles
                  replaced with perforated tile. Exhaust located in center of ceiling,  (expected to
                  behave like displacement ventilation)
                                            90

-------
Analytical Measurements
      The following analyzers were used to obtain real-time measurements during the test lounge
evaluation: CO -  Thermo-Electron Model 48 CO analyzer (Hopkinton, MA); CO2 - Thermo-
Electron Model 41h CO2 analyzer (Hopkinton, MA); and RSP -   RAM-1 respirable aerosol
monitor  (MIE, Bedford, MA).  Prior  to  each  experiment, the CO and CO2  analyzers were
calibrated using gaseous standards (Sott Specialty Gases, Durham, NC).  The output from the
RAM was calibrated against experimentally determined gravimetric RSP values.  Nicotine and
3-ethenylpyridine were collected on XAD-4 sorbent tubes and analyzed by the method of Ogden
(11,12) and gravimetric RSP was determined using the method of Conner(13). The sample inlet
for the analyzers was located at the center of the lounge in the breathing zone of the occupants.
      Smoking rates were determined in the lounge by counting the number of cigarette butts in
the lounge and dividing by the number of smokers and the length  of the smoking period.  Any
partially  burned cigarettes were counted as completely burned. On average, 3.3 cigarettes per
hour per smoker were smoked in the test lounge.  This rate was considerably  higher than the 1.6
cigarettes per hour per smoker measured in offices(14).
      For the field sampling portion of the study, CO was monitored three  times daily with an
Ecolyzer Model 211 (National Draeger, Pittsburgh, PA) and COZ  was monitored on the same
schedule using a Riken Portable Infrared Gas Analyzer Model  RI-411  (CEA Instruments,
Emerson, NJ). Nicotine (6-7 hr. sample) was collected on XAD-4 sorbent tubes  and determined
by EPA Method IP-2A(15). Gravimetric RSP (6-7 hr. sample) was quantified using the method
of Conner(13).

RESULTS & DISCUSSION

Real-time Measurements
      The presence of smokers  in the test lounge  resulted in  an average increase  in  CO2
concentration to 723 ppm (background = 593 ppm). Smoking did not have any measurable effect
on the CO2 concentration in the lounge.
      Average CO concentrations measured for the 1-WAY, WALLS, and PLUG configurations
are shown  in Figure  1.  CO  concentrations did not  differ greatly between each of the three
configurations illustrated  in Figure 1.   The presence  of a stratification layer located in the
breathing zone of the occupants  in the PLUG configuration was  probably  responsible for the
variable CO concentration observed for this configuration(lO).  The  1-WAY and  4-WAY profiles
closely resembled each other as did the profiles for the PLUG and PLUG2 configurations.
                                                   Real-time RSP concentrations are plotted
                                             in Figure 2.   The lowest RSP concentrations
                                             shown in the figure occurred with conventional
                                             air distribution (1-WAY).   Figures 1 & 2 are
                                             similar  in   that  spikes  observed  for   CO
                                             correspond  to spikes in  RSP concentration
                                             observed for PLUG configuration.  This is due
                                             to the stratification layer formed  in the PLUG
                                             configuration.  As smoke  in the stratification
                                             layer moved  past  the  sampler  inlet, spikes of
                                             both CO and RSP  were detected.  During other
                                             periods, cleaner air was drawn into the detector
                                             and relatively low RSP  concentrations  were
                                             observed. Here again, the 4-WAY and 1-WAY
                                             profiles were substantially the same  as were the
— 1-WAY
WALLS
- PLUG
10     40     M
      Time (mln)
Figure 1 Average real-time RSP concentration for  profiles  obtained for the PLUG and  PLUG2
1.U/AV  u/Arrc r,«^  DIIT/I   -„!,:_,  i~.      "
1-WAY,  WALLS
configurations.
   and  >LUG  smoking lounge  configurations.
                                           91

-------
- 1 -WAY
WALLS
-PLUG
                                                                   44     60
                                                                   Time (mln)
                                                Figure 2 Average real-time CO concentration for
                                                1-WAY, WALLS and  PLUG  smoking  lounge
                                                configurations
Integrated Measurements
       Average  concentrations   of  CO,  RSP,
nicotine,  and 3-ethenylpyridine  determined  for
each  of  the  smoking lounge  configurations  are
presented in Table  II.   Concentrations of CO,
RSP  and  nicotine  obtained  during  the  field-
sampling  portion of the study are included for
comparison.  In addition, occupant ratings of the
air quality in the lounge are incorporated in the
table.
       Occupant satisfaction with air quality in the
smoking    lounge    was   greatest  for   those
configurations which incorporated conventional air
distribution.   The  use  of unusual  ventilation
systems,  such  as  displacement  flow,  was  not
necessary to achieve acceptable air quality in the
lounge.
       The  lowest  RSP concentrations measured  in the  test lounge were  found  in the
configurations which relied  on conventional air distribution technology.  Conventional ventilation
relies upon effective mixing of air within a conditioned space.  Vertical  airflows in the  PLUG,
PLUG2  and WALLS  configurations  were  not great  enough  to  produce true displacement
ventilation.  The low velocity air in these configurations resulted in poor mixing in the lounge and
correspondingly higher RSP concentrations.  The stratification layer  in the PLUG configurations
caused ETS to become trapped in the breathing zone of the occupants.  This probably led to the
unusually high  RSP concentration encountered  for that configuration.
       RSP concentrations  in the test lounge were  measured  at maximum occupant  density.  By
comparison, the average RSP concentration measured in a "real-world" smoking lounge, ventilated
according to ASHRAE Standard 62-89,  was 31 /xg/m3.  The lower concentration in the "real-world"
lounge is due in part to the longer measurement  time; e.g. the concentration is averaged over both
high  and low usage periods. Also, the occupancy  of the "real-world" lounge was less than the
maximum allowed which resulted in a higher  effective ventilation rate.
       The two displacement type ventilation systems utilizing underfloor air supply resulted in the
lowest overall CO  concentrations in the smoking lounges.   However,  the  difference  in CO
concentration between these and the other configurations was small. CO concentrations measured
Table II Occupant satisfaction and analyte concentrations measured in "real-world" lounge (LOUNGE)
and the test lounge (4-WAY . . . PLUG).
         Analyte
                       LOUNGE
4-WAY
1-WAY
PLUG2    WALLS
             Occupant
       Satisfaction (%)
                          ND
  93
  88
  81
  fBkg. subtracted; 'total; ND = not determined
79
         PLUG
TCO (ppm)
*RSP (Mg/m3)
'nicotine (/jg/m3)
*3-cthcnylpyridine
1.1
il
4.3
Mn
1.5
395
127
T1 1
1.2
365
101
01
1.0
435
80
« 6
1.5
481
139
10 1
1.1
642
127
8 1
45
                                            92

-------
in the "real-world" lounge were typically at or below the limit of detection for the analyzer (1
ppm).
       Concentrations of 3-ethenylpyridine and nicotine correlated weakly but significantly with
CO  concentrations in  the  test lounge  (r2=0.47, p=0.005 and rz=.33,  p=.025, respectively).
However, none of the gas phase component concentrations showed significant correlation to RSP
concentrations.  Poor correlations involving  nicotine were not surprising; however, the lack of
correlation between 3-ethenylpyridine  and RSP  was unexpected(16,17).   Contrary to results
obtained at low air exchange rates (<4 ACH), the results of this investigation suggest that accurate
ETS exposure assessment in highly ventilated areas requires that both gas and particulate phase
markers be measured.

CONCLUSIONS
       Acceptable air quality, as defined by occupant satisfaction, can be achieved in a  smoking
lounge using conventional air distribution (4-WAY and 1-WAY configurations) at ventilation rates
suggested by ASHRAE(8). True displacement ventilation was not achieved in either the PLUG
or PLUG 2 ventilation configurations. Although displacement ventilation can be effective for ETS
removal,  such systems must be  carefully  designed to achieve the  desired air flow characteristics.
       Investigations conducted in a test room under maximum occupancy conditions may be used
to determine relative  differences between test configurations and provide  an upper limit on the
ETS concentrations obtainable.  However, ETS component concentrations  measured  in a test
lounge under those conditions may greatly overestimate typical ETS concentrations which would
be found in that lounge under typical operating  conditions.  At high ventilation rates, the removal
rate for gas and particulate phase compounds may be affected by air distribution.  As a result, two
or more indicators may be needed to quantify exposure to gas and particulate phase compounds
in ETS.

REFERENCES

1.     B. Berglund andT. Lindvall "Sensory Reactions to Sick Buildings," Environ. Int., 12,147-159 (1986).

2.     P.O. Fanger "Perceived Quality of Indoor and Ambient Air," in Indoor and Ambient Air Quality.
       R. Perry and P.W. Kirk eds., Selper, London, (1988) pp. 365-376.

3.     D.L.C. Kay, D.L. Heavner, and P.R. Nelson "The Effect of Environmental Tobacco Smoke (ETS)
       on  Selected Eye Parameters," presented at the  44"1  Tobacco  Chemists' Research Conference.
       Winston-Salem (1990).

4.     D.L.C. Kay et al. "Effects of Relative Humidity on Nonsmoker Response to Environmental Tobacco
       Smoke," in Proceedings of the Fifth International  Conference on Indoor Air Quality and Climate.
       International Conference on Indoor Air Quality and Climate Inc., Ottawa (1990), Vol. 1, pp. 275-
       280.

5.     J.J.K.  Jaakkola, L.M. Reinikainen, O.P. Heinonen, A, Majanen and  O. Seppanen "Indoor Air
       Quality Requirements for Healthy Office Buildings: Recommendations Based on an Epidemiologic
       Study," Environ. Int., 17, 371-378 (1991).

6-     R.W. Gorman and K.M. Wallingford "The NIOSH Approach to Conducting Indoor Air Quality
       Investigations in Office Buildings," in Design and Protocol for Monitoring Indoor Air Quality. N.L.
       Nagda & J.P. Harper, Eds., ASTM, Philadelphia (1989) pp. 63-72.

7.     O. Seppanen and J. Jaakkola "Factors That May Affect the Results of Indoor Air Quality Studies
       in Large Office Buildings," in Design and Protocol for Monitoring Indoor Air Quality. N.L, Nagda
       & J.P. Harper, Eds., ASTM, Philadelphia (1989) pp. 63-72.

-------
 8.     ASHRAE, "ASHRAE Standard 62-1989, Ventilation for Acceptable Indoor Air Quality" American
       Society for Heating, Refrigerating, and Air- Conditioning Engineers, Inc., Atlanta (1989).

 9.     K.A. Smola "Removing Environmental Tobacco Smoke:  A Practical Solution for  the City of
       Beverly Hills,  CA," in Engineering Solutions to Indoor Air Problems. ASHRAE, Atlanta (1988),
       pp. 84-98.

 10.    H.E. Straub,  P.R. Nelson, H.R. Toft, "Evaluation of Smoking Lounge Ventilation Designs,"
       Submitted to ASHRAE for presentation and inclusion in ASHRAE Transactions.

 11.    M.W. Ogden,  etal. "Improved Gas Chromatographic Determination of Nicotine in Environmental
       Tobacco Smoke," Analyst, 114. 1005-1008 (1989).

 12.    M.W. Ogden "Use of Capillary Chromatography in the Analysis of Environmental Tobacco Smoke,"
       in  Capillary Chromatographv • The  Applications.. W.G. Jennings and J.G. Nikelly eds., Huthig,
       Heidelberg (1991) pp. 67-82.

 13.    J.M.  Connor, G.B. Oldaker,  and J.J.  Murphy, "Method for  Estimating the Contribution  of
       Environmental Tobacco Smoke to Respirable Suspended Particles,"  Environ. Technol. 11:189
       (1990).

 14.    G.B. Oldaker, W.D. Taylor, and K.B. Parrish "Investigations of Indoor Air Quality at  Four Large
       Office Buildings, to appear in proceedings IAQ Conference and Exposition. Tampa, FL (1992).

 15.    W.T. Winberry, L. Forehand, N.T. Murphy, and A. Ceroti in Compendium of Methods for the.
       Determination of Air Pollutants in Indoor Air. EPA-600/4-90/101, September  1989.

 16.    P.R. Nelson, D.L. Heavner, and G.B. Oldaker "Problems with the Use of Nicotine as a Predictive
       Environmental Tobacco Smoke Marker," in Proceedings of the 1990 EPA/A&WMA International
       Symposium: Measurement of Toxic and Related  Air Pollutants. Air & Waste  Management
       Association, Pittsburgh (1990) pp. 550-555.

 17.    P.R. Nelson, D.L. Heavner, B.B. Collie, K.C. Maiolo, and M.W. Ogden "Effect of Ventilation and
       Sampling Time of Environmental Tobacco Smoke Component Ratios," Submitted to Environ. Sci.
       Technol.
ACKNOWLEDGEMENT
       Without the aid of the following individuals, this project could not have been completed: Gerald
Bash, TITUS; Michael Blubach, TITUS; Fred Conrad, RJR; Joe Hash, TITUS; Bain McConnell, RJR;
David Taylor, RJR; Howard Toft, RJR; Paula Simmons, RJR; Billy Willis, TITUS.
                                             94

-------
          Session 4
Chemometrics and Data Analysis
  Donald R. Scott, Chairman

-------
      AN OBSERVATIONAL BASED ANALYSIS OF OZONE
                   PRODUCTION FOR URBAN AREAS
                            IN NORTH CAROLINA
                         Andrea A. Adams and Viney P.  Aneja
                     Department of Marine, Earth and Atmospheric Sciences
                               North Carolina State University
                             Raleigh, North Carolina 27695-8208
ABSTRACT
      An observational based analysis of ozone production for Raleigh and Charlotte, North Carolina,
was performed for 1981 to 1990.  A trend analysis was done over the ten year period for Raleigh. The
first quartile average for Raleigh indicated a slight upward trend of about half a ppbv per year in ozone
concentration. During 1989, the city area of Raleigh provided an average of 25 ppbv of ozone to the air
advecting over the city area. This is compared to a published value of 30 to 40 ppbv for Atlanta, Georgia,
during 1979 through 1987.  A similar analysis was performed for Charlotte, North Carolina, and the range
of values for ozone provided by the city area during 1984 to 1991 is about 10 to 26 ppbv.

INTRODUCTION
      Ozone (03) is a highly reactive photochemical oxidant that is formed in the atmosphere by reactions
involving hydrocarbons, nitrogen oxides and sunlight Ozone is the most abundant photochemical oxidant
in the atmosphere and many measures have been enacted to control its production.  Ozone is designated by
the Clean Air Act  as a criteria pollutant; and a primary and secondary National Ambient Air Quality
Standard (NAAQS) of 120 pans per billion by volume (ppbv) has been established as a measure for
control.  Recent problems with the compliance of the NAAQS has lead to an increase in concern for the
control of ozone in the Raleigh and Charlotte, North Carolina areas. One can get an idea of the trend in
ozone levels, by performing various analyses on ozone data over many years. This can provide an insight
as to whether the control measures have been effective in reducing ozone, or if adjustments are needed.
Control measures have been enacted because ozone is a major component of photochemical smog, which
can result in reduced visibility and injury to humans and vegetation.
      The nonproportionality in ozone production with an increase in precursors, known as nonlinearity,
can result in problems in formulating control strategies. This relationship has been shown in the Empirical
Kinetic Modeling Approach (EKMA), which was first developed by pimitriades[1977], and show that
ozone production does not increase linearly when the precursors are increased. In studies by Laird et
al.1982] and Gradel et al.[1978] it was shown, using EKMA and other kinetic models that as NOX is
reduced, the  predicted photochemical production of ozone increases.  Earlier, Fox et al.[1975], using
smog chamber experiments reached the same conclusion, that as precursor concentrations decrease ozone
can be formed more efficiently.  More recently, Liu et al[1988] found that ozone production per unit NOX
is actually greater at lower NOX concentrations. Consequently, the better our understanding of the trends
in the ozone levels and its precursors in cities, the better we are able to formulate effective control
strategies.
      The purpose of this research is to discover the trends in ozone concentrations over the past ten
years for the  Raleigh area, and to get an estimate of the contribution to the production of ozone made by
the metropolitan area. This is done by performing various observational based trend analyses on the ozone
data for the Raleigh area from 1981  through 1990. An estimate of the ozone production provided by the
city area is obtained by performing a delta ozone analysis. This ozone production then is compared to
values calculated for Atlanta, Georgia, by Lindsay et al.[1989], and for Charlotte, North Carolina, by this
study.  This comparison is done to contrast the estimate for Raleigh with values for cities with larger
metropolitan areas, and greater photochemical precursor sources. Unfortunately, gaps exist in the data,
consequently comparisons between the delta ozone values for the Raleigh area sites can only be performed
for 1987 through 1990.
      The locations of the sites in Raleigh and Charlotte, North Carolina, are shown in Figures 1 and 2.
These sites are located along the predominant wind directions which are southwest and northeast.  The
monitoring stations in the Raleigh area are the Chatham County (Moncure,NC) site, which is located about
                                            97

-------
43 kilometers southwest of the city area; the sites in Wake County are : the East Millbrook Junior Higb
and Wake Forest sites, which are located around 10 and 26 kilometers northeast of the city are*
respectively. The sites in Charlotte are all in Mecklenburg County, with the Westinghouse Boulevard siW
about IS kilometers southwest of the main city area, while the Plaza Road and Route 29 North sites art
located around 8 and 27 kilometers northeast of the city area.  Figures 1 and 2 show the three monitoring
stations in each city, the major highways entering the regions, with the area of each city outlined, and the
Raleigh-Durham and Charlotte-Douglas International airports. There are suburban areas extending past the
metropolitan area in both cities.  In the Raleigh area, the Chatham County and Wake Forest sites art
considered rural, and only the East Millbrook site as suburban. In Charlotte, the Westinghouse Boulevard
and Route 29 North sites are classified as rural, and the Plaza Road site as suburban.
       The hourly averaged ozone concentrations for the Raleigh and Charlotte sites were provided by the
North Carolina Department of Environment, Health, and Natural Resources. However, ozone data for th«
Chatham County site was available only for 1987 and 1989, and for the East Millbrook Junior High sits
only for 1989 and 1990.  While the Wake Forest and all the Charlotte sites were in operation over th«
entire  1981 to  1990 period.The meteorological data for Raleigh-Durham and Charlotte-Doug!^
International airports was obtained from the National Climatic Data Center, Asheville, North Carolina.

Number  of  Exceedences
       One of the factors the Environmental Protection Agency uses to monitor ozone trends is thf,
number of exceedences of the NAAQS per year. Figure 3 shows the plot of exceedences per year for thj
Raleigh area during 1980 through 1990 at die Wake Forest site. Although there is no discernable upwafli
trend, there were three  exceedences each in 1980, 1983 and 1987, while the worst year was 1988 witfc
thirteen exceedences. The maximum daily ozone concentration measured at Wake Forest for the period;
equalling 1S9 ppbv, occurred in June 1988.  Conversely, 1982, 1984, 1989 and 1990 were characterized
by lower ozone concentrations, with the daily maximum ozone level for these years around 100 ppbv-
While  1981 and  1986 were close to exceedences with daily maximum ozone concentrations of 114 ppW
and 118 ppbv respectively. The sixteen exceedences in 1987 and 1988, which constituted a violation
precipitated the Raleigh  metropolitan statistical area to be classified as out of compliance for ozone.


First quartile trends
       Another factor that can be employed  to follow the yearly trends in ozone is the average of the firs'
quartile of daily maximum ozone concentrations. The  first quartile is the top twenty-five percent of tb«
daily maximum  ozone  concentrations, and by averaging these numbers the parameter is less sensitive to
extreme values.  Figure 4 shows the average of the first quartile values for the Wake Forest site for Jun*
through August of 1981 to 1990. A simple linear regression model was run on the data which indicated '
slight upward trend of about half a ppbv per year for the period. As with the number of exceedences, tltf
values of the first quartile averages were high  in 1983, 1987 and  1988.  Consistent with 1988 being
characterized by anomalously high ozone concentrations, the average of the first quartile of ozone values
for 1988, which was about 124 ppbv, was  greater than the NAAQS of 120 ppbv.  While 1982, 1984,
1989 and 1990 had lower values for the first quartile average.


Delta  Ozone Analysis
       Lindsay et al.[1989] introduced a concept for evaluating photochemical production of ozone in *
metropolitan area. This  concept, which they called delta ozone, is an observational based analysis of the
ozone concentrations in an urban environment When the winds are from the predominant wind direction
(southwest and northeast for Raleigh and Charlotte), the difference between the daily maximum ozoitf
concentration at the downwind and upwind sites should give an estimate of the ozone production over the
area. In the Raleigh area, when there are southwest winds, the upwind site is located in Chatham County
(Moncure.NC), and both downwind sites are located in Wake County (East Millbrook Junior High an**
Wake Forest).  In Charlotte, all  sites are in Mecklenberg County, and the upwind site is  located
Westinghouse Boulevard, and the two downwind sites are located at Plaza Road and Route 29 North.
difference between the two sites gives  an estimate of the concentration of ozone entering and leavin
city area, and hence the  amount of ozone that is produced over the metropolitan area [Lindsay et al.,19
When the winds are from the southeast, the delta ozone estimate is expected to be positive, since the vain*
at the upwind site is subtracted from the value at the downwind site. It follows that when the winds art
from the northeast, the value is expected to be negative. The advantage of using a delta ozone analysis i*
that most of the variations due to meteorological factors are removed, since a certain set of meteorological
conditions are specified. Only days when the wind speed was greater than 2 meters per second, the wit**
                                             98

-------
direction was from the southwest or the northeast, and the ozone concentrations were greater than 60 ppbv
were included in the calculations.

Results
       The delta ozone analysis was performed for sites in Raleigh and Charlotte, North Carolina, and
then compared to values obtained by Lindsay et al.[1989] for Atlanta, Georgia. In the Raleigh area, the
values at Chatham County are available only for 1987 and 1989, and the values at East Millbrook Junior
High are available only for 1989 and 1990.  Consequently, only a limited delta ozone analysis could be
performed for the Raleigh area. Table 1 presents the average delta ozone values calculated for the Raleigh
area sites. There is considerable variation in the delta ozone values, so the standard deviations for the
values are large, but due to the limited amount of data there is a small  number of values used in each
calculation, consequently the statistics are less robust  Since the East Millbrook Junior High (EM) site is
located closer to the city area, and there are few  emission sources between the Chatham County (CH) site
and the city area, the values  for EM - CH are the  best estimators of ozone production due to the
metropolitan area. When the winds arc from the southwest, the average value of the amount of ozone
provided to air advecting over the city area is about 25 ppbv. This is compared to values between 30 and
40 ppbv obtained by Lindsay et al.[1989] for Atlanta, Georgia. The value obtained for Raleigh, even
though only for 1989, appears quite large when compared with the values calculated for Atlanta, which
has considerably more city area. The  delta ozone  value when the winds are from the northeast is only
about 6 ppbv. This is attributed to the Chatham County site being about 43 kilometers from the city
region, consequently the effects of the city on airmasses advecting over the area are considerably reduced
due to dispersion and deposition. The values for WF - CH are expected also to be lower because the sites
are located in rural areas, and due to the great distance between the two sites. The average value of ozone
provided by the city during 1987 for southwest  winds was around 12 ppbv, and for northeast winds was
approximately 5 ppbv.
       The delta ozone estimate for WF - EM is negative for both southwest and northeast winds,
indicating that the daily maximum ozone concentration at East Millbrook Junior High on average was
greater than the concentration at the Wake Forest site. This suggests  that the Wake Forest monitoring site
which is downwind of the urban plume, and the effects of the metropolitan Raleigh area are less influential
on the observed ozone concentrations.  The value  for southwest winds during 1989 and  1990 indicates
that the concentration at the East Millbrook Junior High site is on average around 20 ppbv greater than at
the Wake Forest site.   When  the winds are from  the northeast,  the value is only  about  3 ± 5 ppbv,
suggesting that there is little difference between  the two sites. This results from there being few emission
sources between the sites, and that the effects of the city area is not included in the calculations, since the
airmasses have yet to travel over the metropolitan area.
       The delta ozone results for Charlotte are  shown in Figures 5 and 6. Figure 5 presents the trends in
the annual average delta ozone values for PR - WB from 1984 through 1991 for southwest and northeast
winds. The values of ozone production provided by the city area for southwest winds ranged from around
' ppbv in 1990. to a high of almost 20 ppbv in 1984. The delta ozone estimates for northeast winds
ranged from approximately 2 ppbv in 1984 and 1990, to a high of about 14 ppbv in 1988. The values of
PR - WB for both wind directions are probably much closer together than the EM - CH estimates for
Raleigh, since the distance between the two sites in Charlotte is considerably less than those of Raleigh.
Figure 6 shows the trend in the annual average delta ozone values for MC - WB from 1984 through 1991
for southwest and northeast winds. The delta ozone estimates for southwest winds ranged from about 10
ppbv in 1985, to approximately 26 ppbv in 1991.  The values for northeast winds ranged from about 1
Ppbv in 1989 and 1991, to around 10 ppbv in 1988. The trend in delta ozone values for southwest winds
indicates an upward trend, however the values for northeast winds denote a downward trend. Overall the
delta ozone estimates for Charlotte ranged from about 5 to 25 ppbv, which is quite similar to the values for
the Raleigh area, yet both cities provide a smaller contribution to air advecting over the metropolitan area
than Atlanta, Georgia.
       The value of the ozone provided by the city area was averaged over the entire eight year period to
get an idea of the overall ozone production between the sites.  The value for PR - WB when the winds are
from the southwest was around 14 ± 4 ppbv, and the value when the winds are from the northeast was
about 9 ± 4 ppbv. The values for the different wind directions are believed to be different, because the
distance of the Westinghouse Boulevard site from the city region is almost double that of the Plaza Road
site. The delta ozone value averaged over the entire period for MC - WB, when the winds are from the
southwest was approximately 17 ± 6 ppbv, and the value when the winds are from the northeast was
about 5 ± 3 ppbv. The values for the different wind directions suggests that there are additional sources
other than  the city area contributing to the value for southeast winds.  Since the MC site is further
downwind of the city area than the WB site for their corresponding wind directions, yet the delta ozone
                                              99

-------
value is about three times larger for southwesterly winds. Overall, for both wind directions, the average
delta ozone value for the entire period ranged from around 5 to 17 ppbv.


CONCLUSIONS
       The analysis of the ozone data for Raleigh and Charlotte, North Carolina, from 1981 through
1991, indicates that both cities are providing about 10 to 25 ppbv of additional ozone to air advecting over
the city areas. There appears to be a slight upward trend of about half a ppbv per year in the average of the
first quartile of daily maximum ozone concentrations for Raleigh. The ozone concentrations at the East
Millbrook Junior High site, which is located approximately 7 kilometers northeast of the Raleigh city area,
were typically the highest of the three Raleigh sites. The ozone concentrations were usually lower at th«
Wake Forest site, which  is located about 26 kilometers northeast of the city area, indicating this site is
downwind of the urban plume.  The delta ozone value for 1989 for Raleigh , reflecting the amount of to
ozone added primarily by the city area to air advecting over the region, was about 26 ppbv.  This is
compared to a value of 30 to 40 ppbv obtained by Lindsay et al.[1989] for Atlanta, Georgia, during 1979
to 1987. The overall range of delta ozone values for both wind directions, and for all sites was about 5 tt>
25 ppbv.
       The annual average delta ozone values for Charlotte, NC, during 1984 to 1991 for southwesterly
winds ranged from around 8 to 27 ppbv, and for northeasterly winds ranged from about 2 to 14 ppbv.
The delta ozone value averaged over the entire period for both wind directions ranged from 5 to 17 ppbv.
The average  delta ozone values for Charlotte, NC (PR - WB), for both wind directions was around 9 to H
ppbv, and for Raleigh, NC (EM - CH), the value was about 5 to 26 ppbv. However, both of these values
are less than  those found by Lindsay et al.[1989] for Atlanta, Georgia.

Acknowledgements. This research has been funded through cooperative agreements with the University
Corporation for Atmospheric Research  (S9153) as  pan of the Southern  Oxidant Study (SOS-
SORP/ONA), and the Southeast Regional Climate Center (NA89AA-D-CP037).
                                             100

-------
                           AVERAGE AO3
             EM-CH(1989)      WF-CHfl 987.1989)     WF-EM(1989.1990)
  SW    +25.6 ±12.8 (9)      + 11.9 ± 15.4 (34)      - 19.7 ± 12.6 (23)
  NE
- 5.4 ± 6.1  (6)
-4.9 ±7.6 (18)
-2.7 ±5.1 (18)
                    WikcForca
JT'^Jre ] The locutions of the Rsleigh ara sues and
 : Kaleigh-Durham Iniemarionil liipon with the
c«y area ouiiined
                                                            Hoot 29 Nonh
                                                            (MechJenbui|Cil>Ca>
                                                ~~\T  ~*^£Z5jtV*u*MA
                                 Figure 2 The locations of (he Charlotte sites «nd
                                 the Charlone-Douglas Iniernanooil airpon with the
                                 city area outlined.
                                       101

-------

          M   II   II   1.1   14   IS   I*   IT   II   M   *•
                                 VBAM
        Fi|«« J Tt* malbti at ao*Kttn» « *c W«tc Nam tkt

                                                                                      120


                                                                                      110


                                                                                      100"


                                                                                       •

                                                                                        I9M  IM1  I9t]   IM3  l«4  1913  !9tt  1M7  19M
                                                                                                                                                1990  lf*l
                                                                                                 (knot June » Auftitt lor Wikc
                                                                                                                        dKKiMJu
                                                                                                                        kc Rut*

'


191)    1914    19(5    1916   19f?    ISM    1919    1990    1991    1991
                                 YEAR

             Annul ivmft drill ozone for At PUza Rend ind Wettkifbnnc
              Boulevard uri for icudiweu ind nonheau winds
                                                                                      1913    19M    IMS   I9W    1917    1911   1919    1990    1991    1««
Figure 6  Annual ivtrmgc dclu carat for ihe RouK J                 .
        CabCorapmy) ind WeanflwuK Boukvml DO fa mhweg Md
        nonheui winds.

-------
              STATIONARY SOURCE SAMPLING AND
                          ANALYSIS  DIRECTORY
                        Merrill D. Jackson and Larry D. Johnson
                      Methods Research and Development Division
               Atmospheric Research and Exposure Assessment Laboratory
                         U. S. Environmental Protection Agency
                           Research Triangle Park, NC 27711
                Kim W. Baughman, Ruby H. James, and Ralph B. SpafTord
                               2000 Ninth Avenue South
                              Southern Research Institute
                                Birmingham, AL 35255


ABSTRACT
      Sampling and analytical methodologies are needed by the U.S. Environmental Protection
Agency (EPA), state, and local agencies and by industry for testing stationary source emissions for
specific  lists of chemical  compounds that are included in Title  III of the Clean Air Act
Amendments  of 1990 (CAAA), and  Appendices VIII and IX  of the Resource Conservation
Recovery Act  (RCRA).
      A PC-based directory has  been developed that supplies information on  available
methodologies for each compound in these  lists.   Existing EPA  methods are referenced if
applicable; along with their validation status. The directory is, at present, strongly combustion
source oriented.
      The directory may be searched on the basis of several parameters, including compound
name, Chemical Abstract Service number, physical properties, thermal stability, combustion rank,
or general problem areas in sampling or analysis.    The methods directory is menu driven and
requires no programming ability.
      The information in this document has been funded wholly or in part by the United States
Environmental Protection Agency.  It has been subjected to Agency  review and approved  for
publication.

INTRODUCTION
  j There are a large number of chemical compounds listed under Appendix VIII1 and Appendix
IX of RCRA  and the CAAA of 1990,3 whose emissions are regulated by EPA. EPA has several
sampling and analytical methods that are validated for one or more source type for many of these
compounds. Emissions of other listed compounds may potentially be measured by these methods,
but they have not been validated.  EPA or state permit writers and industry personnel may not be
familiar with each compound and its measurement methodology status; therefore, a directory has
been prepared containing all of these compounds listed, with relevant sampling and analytical
methodology. If the methodology has been validated for a compound, a reference is given; however,
u no method has been validated, the best potentially applicable methods are indicated. Since the
directory was originally developed for use in conducting incinerator trial burns under RCRA, it has
an orientation towards combustion methodology.
                                        103

-------
COMPUTER AND SOFTWARE REQUIREMENTS
     An IBM PC or compatible system with a hard disk using DOS 2.0 or higher is required to run
the directory.  Version 1.0 of the directory requires that dBASE III+  be installed  on the system
and is currently available from the National Technical Information Service (NTIS) under the name
"Problem POHC Reference Directory".* Version 1.0 contains only the compounds listed under
RCRA, Appendix VIII.  Version 2.0 will additionally include the compounds listed  under RCRA,
Appendix IX and Title III of CAAA of 1990, and it is scheduled to be released shortly. It will be
titled "Source Sampling and Analysis Guidance, Version 2.0" and will also be available from NTIS.
We plan to have Version 2.0 in the compiled format so that it will not require dBASE III+ or IV
to run.

DIRECTORY CONTENTS
     The directory provides the  following information for each compound, where available: (1)
name of compound (the Appendix VIII name is listed first followed by either the Appendix IX or
the CAAA name. If there are additional common names, they are also listed; (2) CAS registry
number; (3) chemical formula; (4) molecular weight; (5) compound class; (6) University of Dayton
Research Institute (UDRI) thermal stability class and ranking;4 (7)  heat of combustion; (8)
combustion ranking;* (9) boiling, melting and flash points; (10) water solubility; (11) information
on toxicity; (12) sampling and analysis methods; (13) validation status of the method(s) for that
compound; (14) general and specific problems; (15) a description of the problems; and (16)
solutions (if known).  The directory is not totally complete  plus new information, particularly in
regard  to method validation will  constantly become available; therefore we expect to update it at
regular intervals.

RUNNING THE DIRECTORY
     The first screen shown  upon opening the program is the main menu (Figure 1).
                                      MAIN MENU

              1. PRINT ALL RECORDS IN DATABASE
              2. PRINT A SPECIFIC DATABASE RECORD
              3. LIST COMPOUNDS BY PHYSICAL PROPERTY,
                THERMAL STABILITY, OR COMBUSTION RANK
              4. LIST COMPOUNDS BY NAME AND/OR CAS REGISTRY
                NUMBER
              5. LIST COMPOUNDS BY PROBLEM AREAS
              6. EXIT
              ENTER YOUR CHOICE (1-6) FOR THE ABOVE:	

                    Figure 1.  Main Menu

Selection of an option starts a new sequence.  Option 1 prints the entire directory (Warning: This
takes about 1.5-2 hours). This option need only be used once to provide a complete hardcopy of
everything in the data base; additional copies can be photocopied. Selection of Option 4 prints a
list of all the compounds (first listed name only) with their CAS numbers and  directory record
number. This is a very useful tool to have available since the directory record number facilitates
the use of Option 2.

Selecting Option 2 will bring up the Records  Menu (Figure 2).
                                          104

-------
                       PRINT A SPECIFIED DATABASE RECORD.
                       SPECIFY THE RECORD TO BE PRINTED BY:

                       1. RECORD NUMBER
                       2. COMPOUND NAME
                       3. CAS REGISTRY NUMBER
                       OR
                       4. EXIT TO MAIN MENU

                       ENTER YOUR CHOICE (1-4) FOR THE ABOVE:


                                Figure 2. Records menu.

Upon the entry of choice 1, 2, or 3, the question "DO YOU WANT A HARD COPY OF THE
DATA? (Y/N)" will appear. Selecting "yes" will create a printed copy, where a "no" answer will only
bring the data on screen. The search routine is such that the record number is the fastest way to
locate an entry; however, if you do not know the directory record number, you may search by either
the name of the compound or its CAS Registry  Number. The Records Menu is probably the most
useful since it provides the complete information on any given compound.
      Selecting the third option on the  Main Menu brings up the  Specific Compounds Menu
(Figure 3).  This menu allows searching for compounds on the basis  of their physical properties.
                      LIST COMPOUNDS ON THE BASIS OF:

                      1. UDRI THERMAL STABILITY CLASS
                      2. UDRI THERMAL STABILITY RANKING
                      3. MOLECULAR WEIGHT
                      4. BOILING POINT
                      5. MELTING POINT
                      6. COMBUSTION RANK
                      7. COMBINATION OF ANY TWO PROPERTIES
                      8. RETURN TO MAIN MENU	

                          Figure 3. Specific compounds menu.

After selecting any of Options 1-6, the user will be prompted to input a range for the associated
parameter, then the user must specify whether or not he wants a hard copy. Selecting Option 7 will
result in a request for the two properties and the range for each property. This search and listing
option can be particularly helpful in Principal Organic Hazardous Constituent (POHC) selection
for trial burns, since compounds can be listed by incinerability category and by physical properties.
     The fourth  Option  on the Main  Menu (Figure 1) provides an alphabetical list of the
compounds with the directory record number, that, in turn, facilitates searching with Option 1 of
the Records Menu (Figure 2).
     The Problem Menu (Figure 4) is accessed by selecting Option 5 from the Main Menu.
The first option will list every compound that has a problem listed in its directory record. Problems
can be with sampling or analytical methodology, the compound itself may be reactive or water
soluble.   If the problems are known a decision can be more really made on how to handle the
compound.  The second option brings up the screen  shown in Figure 5.
                                         105

-------
                          1. LIST ALL PROBLEM COMPOUNDS
                          2. LIST COMPOUNDS BY GENERAL PROBLEM
                          3. LIST COMPOUNDS BY SPECIFIC PROBLEM
                          4. RETURN TO MAIN MENU

                          ENTER YOUR CHOICE (1-4) FOR THE ABOVE:
                              Figure 4. Problem menu.
                         1. ANALYSIS
                         2. HAZARDOUS
                         3. SAMPLING

                         SPECIFY GENERAL PROBLEM TYPE (1, 2, OR 3):


                           Figure 5. General problem types.

Selection of 1,2, or 3 lists all compounds with problems in the area selected. The third choice on
the Problem Menu probably is the most useful one since it allows a more limited selection. The
menu which accompanies the third choice is shown in Figure 6.
      GENERAL PROBLEM        SPECIFIC PROBLEMS

      1, ANALYSIS               A. CHROMATOGRAPHY  E. SENSITIVITY
                               B. INTERFERENCE      F. RECOVERY
                               C. WATER SOLUBLE    G. DECOMPOSITION
                               D. BLANK

      2. HAZARDOUS             A, CORROSIVE
                               B. EXPLOSIVE
                               C. INCOMPATIBILITY
                               D. TOXIC

      3. SAMPLING               A. BLANK
                               B. BREAKTHROUGH
                               C. DECOMPOSITION
                               D. REACTIVE

      SPECIFIED GENERAL PROBLEM TYPE (lt 2, OR 3):
                        Figure 6. Specific problem types menu.
                                       106

-------
After the user selects the general type from the Specific Problem Types menu, then the program
prompts the user to select a specific problem type from the selections on the right.
   A sample of printout of the record for benzene showing the type of information provided by
the directory is presented in Figure 7. The sampling and analytical methods have been validated,
and the references are given. The specific problem type is a blank problem, and suggestions are
given on how to overcome this problem.  Since benzene is listed under Appendix VIII, there is an
UDRI  class and ranking.  Only compounds listed on Appendix VIII have UDRI ratings at the
present time.  Many records in the directory do not have complete information in all the data
fields, but the data will be added as we become aware of it.  If sampling and analytical methods
are not shown as validated, they are listed as suggestions  only.  The heat of combustion is listed
for help in determining which compounds in a waste  mixture should be selected as POHCs.

SUMMARY
   A directory listing appropriate sampling and analysis methods and physical characteristics of
each compound listed under RCRA Appendix VIII, is available for use  with dBASE III+.  The
directory provides a single reference for field sampling and analytical procedures for regulatory
purposes.  A second version of the directory  covering RCRA Appendix VIII, Appendix IX, and
Clean  Air Act 1990  compounds will be available in early  1993.  The  second version will  be
compiled eliminating the requirement for any additional software  (i.e.  dBASE III+ or IV) to
operate.

REFERENCES
1.    U.S. Government Printing Office, Code of Federal Regulations. 40 CFR, Part 261, Appendix
     VIH, 1990, pp 90-98.

2.    U.S. Government Printing Office, Code of Federal Regulations. 40 CFR, Part 261, Appendix
     IX,  1990, pp 98-117.

3.    Clean Air Act, Title III, Public Law 101-549, 1990.

4-    Guidance on Setting Permit Conditions and Reporting Trial Burn Results. Volume II of the
     Hazardous Waste Incineration Guidance Series. EPA-625/6-89/019, U.S. Environmental
     Protection Agency, Washington, DC, 1989,pp 105-123.

5-    guidance Manual for Hazardous Waste Incinerator Permits. Mitre Corp.. NTIS PB84-100S77.
     July 1983.

6.    K.W. Baughman, R.H. James, R.B. Spafford and CH. Duffey, Problem POHC Reference
     Directory. EPA-600/3-90/094, U.S. Environmental  Protection Agency, Research Triangle
     Park, 1991.

DISCLAIMER
     The information in this document has been funded  wholly or in part by the United States
Environmental Protection Agency under contract 68-02-4442 to Southern Research Institute. It has
been subjected to Agency review  and  approved for  publication.   Mention of trade names or
commercial products does not constitute endorsement or  recommendation for use.
                                          107

-------
RECORD NUMBER:          77               DATE Off LATEST ENTRY:    12/13/90

COMPOUND»   Benzene


CAS REGISTRY NO:   71-43-2
FORMULA:   C6-H6
MOLECULAR WEIGHT:     78.11
COMPOUND CLASS:    Aromatic hydrocarbon
APPENDIX 8?  Y         APPENDIX 9?    Y      CLEAN AIR ACT OF 1990?   Y

UDRI THERMAL STABILITY CLASS:   1
UDRI THERMAL STABILITY RANKING!     3

BOILING POINT, CELSIUS:   80.1
MELTING POINT, CELSIUS:   5.5
FLASH POINT, CELSIUS:     -11.00
SOLUBILITY, IN HATER:   Sol

HEAT OF COMBUSTION, KCAL/MOLE:         780.96
COMBUSTION RANKING:     47

TOXICITY DATA:  Cancer suspect agent; flammable liquid

SAMPLING METHODS   SW-846 No. 0030 (VOST)

ANALYSIS METHOD*
SW-846 No. 5040 or Draft No. 5Q41(Therm. Desorb./P and Trap-Gc\MS)

VALIDATION STATUS:
The VOST method has been validated for this compound (See "Validation Studies of the
Protocol for the VOST" JAPCA Vol. 37 No.  4 388-394, 1987). (Also see "Recovery of POHCfl
and PICa from a VOST" EPA-600/7-86-025.)

GENERAL PROBLEM TYPE(S):   Sampling

SPECIFIC PROBLEM TYPE{S)s  Blank

DESCRIPTION OF PROBLEMS:
Cancer suspect.
Blank problem with Tenax
Benzene is a common PIC.  This may complicate interpretation of results, and make it
difficult to achieve acceptable DRE with low waste feed concentrations.

SOLUTIONS:
Level of lab blank should be determined in advance.  Calculations should be based on
waste feed concentration to determine  if blank  level will  be a significant problem'
Benzene should not be  chosen  as a POHC at very low  waste  feed  levels because it i*
likely to make blank or PIC problem significant.
                          Figure 7.  Data output for benzene.
                                         108

-------
           Session 5
Effects of Pollution on Materials
    John Spence, Chairman

-------
       POLLUTANT DEPOSITION TO METALS MONITORED
                     USING PRECIPITATION  RUNOFF
                      Stephen D. Cramer and L. Garner McDonald
                     Albany Research Center, U.S. Bureau of Mines
                         1450 Queen Avenue, Albany OR 97321


ABSTRACT
      The Bureau of Mines measured the deposition of acidic pollutants to metal surfaces over
a 33 month period in Washington, DC, as part of the National Acid Deposition Assessment
Program. The chemistry of precipitation and precipitation runoff from large zinc, copper and steel
panels was measured on a monthly basis. A 304 stainless steel panel was used as an inert reference
surface. Mass and ion balances yielded  the wet and dry deposition fluxes.  Corrosion product
losses, which in long exposures are equal to the corrosion rate, were shown to equal the sum of
excess H+ in wet deposition, of SO2 in dry deposition, and of corrosion product solubility in "clean
rain", minus dry deposited basic particulates.  In this model, basic particulates compete with the
corrosion product for acidic species deposited on the metal surface. The R2 for the atmospheric
corrosion model applied to zinc and copper runoff was  >0.%.  Precipitation runoff was show to
be an effective means for monitoring  the impact of atmospheric pollutants on metals damage.


INTRODUCTION
      The Bureau of Mines, in cooperation with the  U.S. Environmental Protection Agency,
studied the impact of acid deposition on metals corrosion damage as part  of the National Acid
Precipitation Assessment  Program.1   An atmospheric  corrosion model was developed  which
quantified the relationship between atmospheric pollutants and the corrosion of galvanized steel
and copper.23  The model replaces the qualitative measures of atmospheric corrosivity ("rural",
"industrial", etc.) with quantitative, site-specific  measures of the  dose of reactive environmental
species that can be obtained from air quality, wet deposition and meteorological monitoring. Such
information is frequently available at  a regional level.
       The Clean Air Act Amendments of 1990 implements new standards for pollutant emissions
in the mid-1990's and requires monitoring to determine  the effectiveness of the NAPAP research
to predict benefits from pollutant reductions. Corrosion damage will be monitored using corrosion
product runoff. In short exposures of several years the  rates of corrosion damage and corrosion
product runoff are proportional.  In long exposures, such as those experienced by monuments and
historical structures, the rates of corrosion damage and  corrosion product runoff are identical.
       A 33 month runoff experiment was conducted in Washington, DC as part of the NAPAP
study.3 The results of this runoff study have been analyzed to include in the atmospheric corrosion
model the contribution of basic particulates to partially  neutralize acid deposition.  This effect is
most clearly manifested when examining acid deposition to inert surfaces.  The results will show
that the impact of atmospheric pollutants on corrosion damage can be effectively monitored with
runoff measurements, that important details of corrosion processes can be determined from runoff
measurements, and that  the major  impacts of  atmospheric species  can be described in an
atmospheric corrosion model based on runoff measurements.
                                         Ill

-------
EXPERIMENTAL METHODS
      The runoff experiment was begun June 1985 on the roof of the West End Library in
downtown Washington, DC, and ended February 1988. The experiment involved simultaneously
collecting the precipitation that washed a surface of known geometry and the incident precipitation.
Runoff was collected monthly from 03x0.6 meter (1x2 foot) panels of rolled zmc(UNS-Z44330),
electrolytic tough-pitch copper(UNS-CHOOO), Cor-Ten A steel, and an inert reference panel of 304
stainless steel. Each panel was mounted in a 7polyethylene runoff collection tray oriented at 30
degrees to the horizon and facing south. The runoff was collected from a tray in a large plastic
bottle connected to the tray by a sealed Teflon tube. The runoff was analyzed for the standard  acid
rain ions (H, Ca,  Mg, K, Na, NH4, NO3, Cl and SO4) and selected metal ions (Cr, Fe, Zn, Cu).
Precipitation was collected monthly using an Aerochem Metrics wet collector and analyzed for the
standard  acid rain ions and, every three months, for the selected metal  ions.
      A number of standard 10x15 cm (4x6 inch) corrosion panels, with the groundward  side
masked by electroplating tape to prevent corrosion, were exposed June 1985 to provide a running
measure  of corrosion  product composition during the 33 month period. Three of these  smaller
panels were removed after 1,3,12 and 33 months, the corrosion product chemically stripped, and
the composition of the corrosion film determined by chemical analysis  of the stripping solution-
Film compositions on a  monthly basis were obtained by interpolation between measured values.
 Particulates were analyzed on  a regular basis by EPA from samples collected in  Hi-Vol  and
dichotomous samplers. Air quality was measured on a continuous basis by the DC Government.
Meteorology was  available from NOAA for National Airport.

RESULTS AND DISCUSSION
      The volumetric collection efficiencies for the runoff collectors were equivalent to that of the
Aerochem Metrics wet  collector despite the  considerable difference in geometries of the  two
collector types.  From a knowledge of monthly corrosion film chemistry, precipitation chemistry and
runoff chemistry, mass balances were used to compute the monthly dry deposition of the standard
acid rain ions to the panels.  Cation/anion (C/A) charge ratios for  the monthly precipitation and
runoff were roughly unity. Cation/anion charge ratios did not balance for paniculate and gaseous
materials dry deposited on the inert stainless steel panel or the zinc, copper and Cor-Ten panels-
These ratios were reconciled by making two assumptions which  are supported by the data.

       1. Ca and Mg are dry deposited in various mineral forms. Some of these are basic and will
      compete with other basic species, i.e., corrosion product,  for hydrogen ions available from
      both wet and dry deposition. Some of these are salts and soluble in precipitation with n°
      basic properties, e.g., CaCI2. Total Ca and Mg paniculate dry deposition will be the same
      for each of the panels.

      2. Dry deposition of sulfur on the stainless steel panel can be partitioned into contributions
      from sulfur dioxide and aerosols using the cation/anion charge ratio.   Aerosol sutfate dry
      deposition  is small because of very low deposition velocities  and will be the same for ea<#
      of the panels. The balance of sulfate deposition to the panels will be from sulfur dioxide-
and Mg containing particulat
account for the quantities of   ' consumed.  Figure 1 shows the total Ca and Mg
runoff on the stainless steel panel.  (Any insoluble Ca and Mg particles remaining are filtered fro*1
the runoff with silica and other insoluble particles prior to analysis of the solution.)  The lowef
curve gives  the amount present as a soluble salt and not reacting with hydrogen ions.
difference between this curve and the total is that which is made soluble by reaction with H*-
                                           112

-------
       Ca and Mg deposited to the stainless panel with a deposition velocity of 1.4 cm/s typical of
coarse particle settling.2 The Ca and Mg flux to the zinc, copper and Cor-Ten A panels is the same
as for the stainless panel. The soluble salt portion is the same for each panel.  The Ca and Mg
that successfully competes for H+ on the zinc, copper, and Cor-Ten A panels can be obtained as
the difference between the measured total, which is different for each panel, and the soluble salt
portion.  An amount of anions equivalent to the H+ reacted with Ca and Mg was included in the
C/A charge ratio to account for the base involved in this reaction.
      The difference between the sulfur dry deposited to the zinc, copper, and Cor-Ten panels and
the sulfate aerosol dry deposited to the stainless panel  is the sulfur dry deposited as sulfur dioxide.
The dry deposited SC^ should be included in  the C/A charge ratio as a neutral species or as
contributing equivalent amounts of sulfate and  H+.
       The C/A ratio was approximately 1.0 for the material dry deposited on each of the panel
surfaces when sulfur, Ca and Mg were treated in  this way.
      The atmospheric corrosion model developed under NAPAP2 contains three terms for runoff
losses representing contributions from rain acidity due to carbon dioxide, i.e., "clean rain", excess
hydrogen ions from strong acids, i.e., "acid rain", and the dry deposition of sulfur dioxide. The first
term is related to the thermodynamic stability of the corrosion product in the runoff. The second
and third terms represent acid/base neutralization reactions/  The three  terms are related in
various ways to temperature, wind speed, humidity, size and shape of a structure, and a factor r (0
$ r £ 1) for the residence time of precipitation on a surface. A runoff experiment measures the
net result of the environment-surface transport processes. Consequently, the atmospheric corrosion
model based on runoff data can be written without defining  these processes and becomes


                         R = rSV + H^consumed)!^ + [SO^ry)]/^                    (1)
where R is the cumulative runoff loss of the corrosion product metal ion, in mmol per unit panel
area; S is the solubility of corrosion product in precipitation in equilibrium with atmospheric carbon
dioxide; V is the cumulative precipitation volume; H+(consumed) is the cumulative hydrogen ion
consumed; [SO2(dry)] the cumulative sulfur dioxide dry deposited; and nt and n2 are stoichiometric
coefficients, n, is 2 and n2 is 1 for zinc and galvanized steel.2-3 Earlier use of this equation with
these values resulted in a  prediction for zinc runoff that was 15 pet higher than the observed
runoff.3  However, inclusion of the Ca and Mg that is dissolved by H+ balances the two sides of
the equation.  Thus, the left side of the equation should include all species that compete for H+
regardless whether the H* is delivered by wet deposition or dry deposition. The atmospheric
corrosion model that includes the effect of dry deposited basic particulates is

                R + (Ca+Mg)s.(dry) = rSV + H'(consumed)/^  * [SO2(dry)/n2            (2)
This equation has only one undetermined parameter, r, the residence time factor representing the
undersaturation of corrosion product metal ion in the  runoff when pollutants are absent. The
quantity rS is the average concentration of the corrosion product metal ion in clean rain.  Equation
2 was fit to 33 month cumulative data for the zinc panel and yielded a value for rS of 56.8 /unol
Zn/L and an R2 of 0.99.  The cumulative contributions of the terms in the atmospheric corrosion
model are shown in Figure 2 with the line (H2O+H++SO2) representing the sum of the 3 terms
and "runoff1 the experimental runoff data. The monthly average concentrations of the zinc in the
runoff are plotted in Figure 3 as a function of runoff pH. The solubility curves for  ZnCO3 and
Zn(OH)2 are also shown on this figure.  The runoff was not, on average saturated in zinc. The
                                            113

-------
value rS, also plotted on this figure, represents the average monthly zinc concentration in the runoff
in the absence of pollutants.  The effect of pollutants on dissolved zinc  is clearly evident with
monthly runoff values typically 2 to 4 times the "clean rain" value and, in one case, 10 times that
value.
       A similar analysis of the copper runoff data yielded a value for rS of 28.6 nmol Cu/L and
an R2 of 0.96.  The monthly copper runoff was close to or at the saturation value for CuO and well
above the "clean rain" value. Excess acidity partitioned out of the Cor-Ten A data using Equation
2 suggests that, while the primary cathodic reaction for atmospheric corrosion is oxygen reduction1!
for steels perhaps 2 pet of the total reaction involves hydrogen reduction.
       Deposition velocities defining the mass transfer from  the  environment to the panels of
reactive gases and atmospheric particulates can be computed using the runoff results, air quality
and meteorological data.


CONCLUSIONS
       Runoff measurements can effectively partition wet and dry deposition to metal surfaces.
They require no assumptions regarding environment-surface mass  transfer processes.  Through a
combination of mass and ion balances, the reactants involved in corrosion product dissolution can
be determined quantitatively.
       An atmospheric corrosion model involving competition between corrosion product and basic
particulates for available wet and dry deposited H* describes with  an R2 of >0.96 the dissolution
and neutralization reactions taking place on corroded zinc and copper surfaces.
       While the primary cathodic reaction for atmospheric corrosion processes is oxygen reduction)
runoff experiments suggest  that perhaps 2 percent of the total corrosion reaction of steel surfaces
may involve hydrogen reduction.
       Calcium and magnesium particulates are delivered to the  panel surfaces with a deposition
velocity of 1.4 cm/s. A portion of these particulates are soluble in water and a  portion are
dissolved by available hydrogen ions.  Competition exists between the basic particulates and other
basic reactants on the metal surface for hydrogen ions.
       Deposition velocities for reactive gases and atmospheric particulates can be computed from
the runoff results, air quality and meteorological data.


REFERENCES
1. E.O. Edney, Effects of Acidic Deposition on Materials. State of Science and Technology Report
19, National Acid Precipitation Assessment Program, 722 Jackson Place, NW, Washington, DC,
September 1990, pp 37-95.

2.  F.H. Haynie, J.W. Spence, F.W.  Lipfert, S.D. Cramer and L.G. McDonald, Atmospheric
Corrosion Model for Galvanized Steel Structures: Evaluation  and Application, Corrosion, to be
published.

3.  S.D. Cramer and L.G.  McDonald,  Corrosion Testing and Evaluation.  ASTM STP 1000, R-
Baboian and S. W. Dean, Eds., American Society for Testing and Materials, Philadelphia, 1990, pP
241-259.

4. J.W. Spence and F.H. Haynie. Corrosion Testing and Evaluation, ASTM STP 1000, R. Baboiafl
and S. W. Dean, Eds., American Society for Testing and Materials, Philadelphia, 1990,  pp 208-224-
                                           114

-------
            100
                                    10       15       20
                                Exposure time, hrs
                                   (Thousands)
25
Figure 1.  Calcium and magnesium dry deposition on stainless steel panel as a function of
exposure time.  The portion that is soluble salts dissolved in water without reaction with
hydrogen ions is shown by the lower line.
                                     115

-------

             350
             300
         E   250


         +   200
         3^

         f  150


         8   100

         T
         C    en
         N
                         10       15

                    Exposure Time, hrs

                        (Thousands)
                                                       20
25
Figure 2. Contributions of hydrogen ions (H + ), dry deposited sulfur dioxide (SO2), and

"clean rain" (H2O) to zinc corrosion product and basic particle dissolution.
            0.01
      o


      c
      Q
      Q
      U
0.001
         0.0001
           1E-05
                                       6

                                  Runoff pH
                                                   8
Figure 3.  Concentration of zinc in 33 monthly runoff samples. Lines are solubility curves

for zinc carbonate and zinc hydroxide. The zinc concentration that would be observed in
the absence of pollutants is rS.
                                     116

-------
                 THE EFFECT OF SPECIMEN SIZE AND ORIENTATION ON THE
                      ATMOSPHERIC CORROSION OF GALVANIZED STEEL


        John W. Spence                                               Frederick W. Lipfert
        U.S. Environmental Protection Agency                           Environmental Consultant
        Research Triangle Park, NC                                    Northport, NY

        Steven Katz
        State University of New York
        Buffalo, NY


INTRODUCTION
        Most of the field data that have been gathered on atmospheric corrosion of metals over the yean were
obtained from standardized test specimens, for example 10x15 cm coupons mounted at 0* to the horizontal facing
south.  This practice can provide useful data on the relative corrosion resistance of alternative alloys and coatings,
but is not particularly useful with regard to deducing the various mechanisms  responsible for these corrosion
differences.  Mechanistic experiments have traditionally been performed  under controlled conditions in test
chambers,' but such controlled conditions are not necessarily representative of the complex mixtures of pollutants
and meteorological conditions that occur in real atmospheres.  The data analyzed in this paper  were intended to
provide mechanistic data for galvanized steel under semi- controlled field conditions at Research Triangle Park, NC,
a site that would be considered "clean"  in the context of much of the corrosion data in the literature.  These
experiments were intended to provide data that would allow surface chemistry and atmospheric processes to be
considered separately.

EXPERIMENTAL METHODS
        The methods used in these experiments and a summary of findings were presented by Edney et al.2 Briefly,
the specimens were exposed for 100 weeks, beginning in June 1987, on a special test rack with a movable rain
shelter.  A moisture sensor activated the covering device, excluding precipitation and thus wet deposition.  Every
two weeks  (nominally), the 'skyward facing" surface of each  specimen  was rinsed with a known quantity  of
deionized water to remove soluble corrosion products  resulting from dry deposition; the quantities of water cor-
responded to annual rainfall of 12-20 cm.  These solutions were then analyzed for their zinc content and for species
pertinent to atmospheric deposition. These data constitute histories of corrosion responses to growth of corrosion
films on the specimens under changing atmospheric conditions.

Specimens Exposed
        The test specimens consisted of 12 new (virgin) samples of galvanized steel and two previously weathered
samples. The new specimens included a 3.5 cm diameter pipe, 68 cm long, exposed vertically; a section of standard
rain gutter 33 cm long exposed horizontally; a section of chain-link fence fabric made from 3.5 mm diameter wire,
exposed vertically; four 2.5 cm square panels exposed at 0°, 30", 60°, and 90* to the horizontal; three 10x15 cm
panels exposed at 0", 30", and 90° to  the horizontal; and two 46 cm square panels exposed at 30s and 90° to the
horizontal.  The weathered samples were exposed vertically and included a 37 cm long section of  10x15 cm I-beam
and a section of similar chain-link fence fabric; the weathered fencing was acquired after the program was under
way and thus was only exposed for about one year.  Each specimen was well rinsed in deionized water before initial
exposure.

Chemical Analysis of the Run-off Solutions
        The biweekly  run-off from each specimen  was analyzed  for Zn and Ca using atomic absorption
spectroscopy and for SO,', NO,'- NH/, HCOO"- CHjCOOr-  CP-  Na+,  and  K+ using  ion chromatography. H*
concentrations were determined by measuring pH.
                                                117

-------
 Atmospheric Data
        The atmospheric data were collected simultaneously at the site, which was located in a grassy field away
 from trees and from pollution sources in the immediate vicinity. Air concentrations of SOj, NO, NO,, and ozone
 were monitored continuously and then reduced to hourly avenges, as were data on wind speed and direction (10
 m. height), dry and wet-bulb temperatures, and solar radiation.  Hourly precipitation amounts were recorded.  In
 order to provide a complete time-series for use in the statistical analyst*, missing aerometric data were "filled-in"
 using data from secondary sources and various interpolation procedures.1  The filled-in data were identified with
 flags in the data base and the relative frequencies of such fill-ins were used in the statistical analysis as a data quality
 parameter (it was not a significant predictor).  The air monitoring program was terminated about six weeks before
 the exposures ended; data were available for only 47 of the SO run-off samples.

 STATISTICAL ANALYSES
        We calculated average run-off concentrations for each specimen and converted these data to units of
 deposition (i.e.. run-off rates) taking the volumes of rinse water and the specimen surface areas into account.  Ion
 (charge) balances were computed  in each case and  the amount necessary  for charge balance (which was' usually
 negative and presumed to be HCO3'  was carried  through the analysis.   The time dependence  and frequency
 distributions of these quantities were noted.  Most  of the  data on NH/, HCOa- CHjCOa- Na*. and K+ were
 below the minimum detectable levels (MDL).
        As a check on stoichiometry, (egression analyses were performed for each specimen,  with Zn as the
dependent variable and all other ions as independent variables.  As expected, the ions below MDLs were usually
 not significant in these regressions.  The terms which were clearly non-significant and those with the wrong
algebraic sign were eliminated and the regressions rerun, in order to derive "robust"  models.
        Hourly relative humidity and dew point values were derived from the dry and wet-bulb temperatures. The
hourly atmospheric data were aggregated into time periods coinciding with the  rinses,  assuming that the  rinse
operation was performed  at 9 AM in each instance. In addition  to the measured parameters, several computed
parameters were similarly aggregated.  These included:

        1. setting all SO, values below the MDL (3 ppb) to 1.5 ppb (in order to eliminate measured "zeroes").
        2. assuming that no dry deposition of SO,  occurred when the relative humidity was below some critical
        threshold (RHJ,  and thus that the effective SO, values for those hours were zero.  RH. values of 65%,
        75%, and 85% were assumed, alternatively.
        3. assuming that SO2 dry  deposition is proportional to the product of SO2 and wind  speed, subject to the
        conditions of 1. and 2. above.

These procedures yielded several different correlating parameters for SO2 dry deposition.

RESULTS

Average Run-off Values
        Table 1 presents average run-off values for each ion and specimen.  Zinc loss was substantially greater for
the weathered specimens  and for those with smaller characteristic dimensions and more horizontal orientations.
SO4" was the most important anion, followed by  NO,' and  €!'•  Ca+ + was the most important cation (after Zn++),
but the contributions of these cations to the overall ion balance were small as were the contributions of NH/ and
the organics. Average pH values were between 5.7 and 6.3.  For most specimens, the magnitude of the "missing"
anion increased with exposure time, which is consistent with the growth of a corrosion film and increased HCO,'
in the run-off.
                                                  118

-------
                            Table 1  Average Run-off Amounts (neq/cnftlay)
    Qwrgt
2JN   «04   »K»
CA   NA  HOOO
                                                                     +
                                                                     K
                                                    H
NH4 CK90OO
2AO4
24x25
24XZS
?«»?«
10x15
10*15
10x15
tt*M
46*46
Ouav
Item
HP*
Might tarn
*WU»no«
0
to
90
80
0
30
00
30
80
0
00
00
00
00
724
764
66.9
484
644
404
41.1
404
27.0
•42
115-8
464
764
232.1
404
344
317
33.4
344
224
1*2
234
144
1&S
072
31JO
802
103.7
10.1
164
104
16.7
162
8.7
12*
64
74
•A
&6
04
ttJ
124
144
U4
134
164
104
84
74
64
74
62
64
64
14/4
104
64
64
44
94
64
4.4
12
64
•4
34
12
24
34
34
24
1J
24
14
14
14
04
14
O4
12
O7
1.1
14
14
14
14
14
24
1.1
14
04
0.7
04
04
3.4
14
14
0.1
14
\A
14
14
14
\A
0.7
1.1
04
i.r
04
0.7
14
1.1
14
14
12
14
12
04
04
0.4
O.7
04
O4
04
04
O2
&7
or
0.7
14
04
04
0.7
04
04
04
0.7
04
04
24
04
O2
04
02
0.4
02
02
0.1
0.1
02
1.1
02
04
04
Surface Chemistry Stoichiomctry
        The regressions derived the following stoichiometric coefficients (averages, ranges and standard errors,
expressed as microequivalents):
        SO/
        NO,'
        cr
1.01 (0.66 to 1.19), with standard errors around 0.08.
1.53 (1.16 to 2.00), with standard errors around 0.34.
0.96 (0.62 to 1.70), with standard errors around 0.40.
Consistently statistically significant coefficients were not derived for any other ions.

        The above findings are consistent with the preliminary findings of Edney et al .J and are as expected except
for NO," We assumed that HNO, was the atmospheric NO/ compound present and that the coefficient should be
1.0.   The consistent finding of higher values therefore suggests a net loss of NO,' (assuming that  the NO,"
measurements are accurate),  which could occur if HjSO4 were subsequently deposited and then interacted with
Zn(NOj)j.4  Since SO] deposition is likely to be more episodic than HNO,, this may be a likely sequence of events.
 The independent role of Cl was also unexpected; note the much smaller values for Na*. which rules out sea salt
as the source of Cl" and suggests the  presence of HC1.

        A 'prediction* equation for the amount of zinc in the run-off would thus be given by:

        Zn*+ = SO/ + 1.5 NO,  + Cl + other terms                                    [1]

This relationship holds for nearly all specimens (the 2.5x2.5-0° had low values for SO/ and NOj" and a high value
for Cl*1 and thus represents the surface chemistry.  The differences in corrosion among types of-specimens must
therefore be related to the rates at which SO/, NO3'- and Cl'are delivered to the surfaces by atmospheric processes.1

Deposition Velocities
        Dry deposition velocities are conventionally defined as the quotient of surface flux and air concentration.
Here we assume that the surface flux of a specific ion is given by the amount in the run-off (nmol/cmMay). These
calculations are carried through for SO/ and NO," only; we have no atmospheric data on Cl*.
                                                  119

-------
         Sulfur Deposition. Sulfur may be dry deposited on structures by SO2 or by SO4" aerosol.  In this paper,
 only SO, was considered. The method of analysis was to compute deposition velocities (VJ from the SO/ run-off
 and the alternative SOj measures listed above, and then to regress these values against various other aerometric
 variables.  A logarithmic transform was used for V4, in order to evaluate power law relationships with temperature
 and wind speed and to suppress any extreme values that might have resulted from dividing by inordinately low SO,
 concentrations. The standard errors of estimates derived by regressing the logs represent percentage confidence
 limits, which are useful in comparing parameters with greatly different mean values.  The analyses reported here
 were limited to four alternative SO, parameters, all of which used the assumption that values below the MDL were
 equal to 1.5 ppb: (a)  all hours (RH. - 0), (b) only hours for which RH > 65 56, (c) only hours for which RH >
 75%, (d) only hours  for which RH >  85%.
        The average V,, values are given in Table 2, and are seen to increase with increasing RH,.  Average values
 are  also higher for the weathered specimens, for more horizontal angles, and for smaller  dimensions.  The
 regression  analysis showed a  strong  effect of exposure time  for the virgin specimens,  a negative  effect of
 temperature, and a positive effect for the log of wind speed mat only reached significance for RH. = 75% and 85%.
 For eight of the fourteen specimens, the lowest V4 prediction errors were obtained with RH.« 0; for the- other five
 cases, it was for RH.  — 65%. Wind speed was not a significant predictor for any of these cases.  ForRH<=85%,
 the regression coefficient for m(wind speed) was around unity, indicating a linear relationship.  When significant,
 the regression coefficients for temperature (°C) were in the range - 0.03 to -0.08. These values are consistent with
 the theoretical rate of dissolution of SO, in surface moisture.  A crossplot of V4 against temperature suggested that
 the increase in deposition was limited to values above freezing, as expected. The prediction errors were such that,
 in the best cases, about 95% of the predicted Vt values would be expected to fall within a factor of two (in either
 direction).  The strong positive effect of exposure time suggests that the build-up of the corrosion film on the surface
 accelerates  the sulfur deposition rates (about a factor of two for one year) and is consistent with the higher rates
 observed on the weathered specimens.
                      Table  2                                              Table 3
  Av'g Sulfur Deposition  Velocities (cm/s)            Av'g Nitrogen  Deposition  Velocities (cm/%)
  RHC-0
75%
85%
NO
NO,
NO.
0.098
0.090
0.080
0.081
0.089
0.060
0.049
0.067
0.036
0.052
0.256
0.089
0.078
0.464
0.230
0.206
0.182
0,177
0.205
0.140
0.107
0.155
0.079
0.114
0.596
0.195
0.171
1.062
0.328
0.294
0.260
0.250
0.295
0.203
0.151
0.225
0.111
0.164
0.864
0.280
0.242
1.475
0.567
0.515
0.456
0.427
0.518
0.364
0.258
0.405
0.188
0.287
1.560
0.487
0.413
2.559
                                                2.5x2.5-0
                                                Z5x2.5-30
                                                2.5x2.5 - 60
                                                2.5x2.5 - 90
                                                 10x15-0
                                                10x15-30
                                                10x15-90
                                                46x46 - 30
                                                46x46 - 90
                                                  Gutter
                                                  I-beam
                                                   Pipe
                                                Virgin fence
                                                Weath.fence
0.026
0.027
0.027
0.026
0.022
0.014
0.017
0.012
0.010
0.013
0.008
0.014
0.031
0017
0.066
0.075
0.075
0.068
0.058
0.043
0.050
0.033
0.028
0.037
0.029
0.045
0.092
0027
0.017
0.018
0.018
0.017
0.014
0010
0.011
0.008
0.007
0.009
0.006
0.010
0.021
0.010
        Nitrogen Deposition.  Since NO,'was the second most important anion, an effort was made to predict its
deposition, even though the stoichiometry was such that the exact mechanisms at work were unclear. Three nitrogen
Vd values were used, based on  NO, NOj and  NO, (NO +  NOj), respectively.  Data on atmospheric HN03 were
not available.  The hourly NO concentration values were noted to be quite episodic, perhaps reflecting the
intermittent presence of plumes from combustion sources in the vicinity; NO,  concentrations were less variable.
The average Vd values for nitrate are given in Table 3. These values are substantially lower than the corresponding
deposition velocities for sulfur, which could reflect either the  reduced solubility of NO and NO] or the fact that
ambient levels of HNO, tend to be a small fraction of NO,.
                                                  120

-------
        A regression analysis was conducted for the logarithms of the three nitrate deposition velocities, following
the methods used for sulfur.  Prediction errors were lowest for V4 based on NO, but R"s were consistently highest
when V, was based on NOj. Temperature was the most consistently significant predictor, with positive coefficients;
this suggests that dissolution is not the operative mechanism but that some surface reactions are occurring whose
rates are accelerated by temperature in an Anheniu* fashion. The avenge coefficient for temperature was 0.082
+/- 0.006 (95% CL for the mean), which corresponds approximately to a doubling of nitrate deposition for an
increase of 10* C. The average coefficient for ln(wiod speed) for  the six significant cases was about 1.1, also
indicating a linear relationship. The prediction errors for nitrate deposition were somewhat higher than for sulfate;
95% of the values would be expected to lie within a factor of 4. The effect of exposure time on nitrate deposition
was equivocal; it was significant (negative)  only  for the  pipe and the I-beam, based on  NO,, and significant
(positive)  for five of the flat specimens based on NO and NO,.


Effects of Specimen Size and Orientation
        A multiple regression of the average run-off rates (nmol/cm'day) on the geometric factors for the 12 virgin
specimens gave a prediction equation of the form:

        ln(Zn run-off) - B» + B, (cos angle) + B, uncharacteristic dimension)

where the angle is defined with respect to the horizontal and the characteristic dimension is taken as me square root
of the  surface area, except for the fence, for which the wire diameter was used.  The values derived for the
regression coefficients B, and Bj are shown in Table 4.


        Table 4 Regression Coefficients for Specimen Orientation and Size (n= 12)
species
Zn
so4-
NO,-
cr
Ca
orientation
B, std. err.
0.39
0.52
0.24
0.15
0.63
0.12
0.12
0.14
0.20
0.30
specimen size
Bj std. err.
-0.22
-0.16
-0.25
-0.23
-0.11
0.041
0.039
0.046
0.06S
0.098
We see that the B, values are significant (p>0.05) for Zn, SO4~, and Ca, and the B, values for all species except
Ca.  The relationship for Zn reflects those of all the other species, since Zn - SO4' -I- 0.5 NO,' + 0.5 Or- Ca.
No other species were evaluated in this way.
         Orientation angle can affect deposition in two ways: for gravitational settling of particles, we would expect
the deposition rate to be proportional to the projected horizontal area, which is given by the cosine of the angle,
and thus B, should equal unity. We would also expect condensation to form more readily on horizontal areas, since
they will cool faster because of a better "view*  of the night sky. These two phenomena explain the findings for
Ca (dust particles) and SO4~ (dissolved SOj), respectively. We note that the angle effect is slightly stronger for Ca
(although not significantly so).  The lack of significance of the orientation angle for NO,' and  CT suggests that
particle deposition is not very important for these  two species.
         Specimen size can affect air-borne deposition by virtue of the Reynolds number effects on the boundary
layers formed on the surfaces.1  According to empirical results with turbulent flow, an exponent of-0.2 is expected
in the absence of surface resistance;1 the regression results above  for NO,* and Cl* match this very closely.  The
finding of  a lower exponent for SO4"  suggests  that  surface resistance must be more  important than for SOj
deposition.
                                                   121

-------
 CONCLUSIONS
         This preliminary  report presents some of (he findings from a unique set of experiments designed to
 elucidate dry deposition mechanisms for galvanized steel specimens of various configurations, and augments
 information presented earlier.3  The run-off data show that SO4~, NO,* and Cl are the most important factors
 controlling zinc dissolution, under these conditions.  Merging these data with atmospheric measurements allowed
 some conclusions to be drawn about atmospheric deposition mechanisms: sulfur deposition was dependent on
 exposure time, temperature (negative), and wind speed (if only the high relative humidity hours are considered).
 Nitrogen deposition was positively dependent on temperature and wind speed. These findings in turn suggest that
 sulfur deposition is limited by the solubility of SO, and nitrogen deposition by the kinetics of some (undefined)
 surface reactions.  It was not possible to study the deposition of Cl' because of the lack of atmospheric data, but the
 presence of HCI was suggested.   The effects of specimen size and orientation were consistent with theoretical
 expectations based on boundary layer theory. The importance of exposure time in these experiments suggests that
 future experimental programs should include weathered test specimens.

 ACKNOWLEDGMENT

 This research was supported by the U.S. Environmental Protection Agency under Contract No. 2D-1140-NATA.
 Steven Katz was supported by the Department of Energy's Division of University and Industry Programs, Office
 of Energy Research, as a Science and Engineering Research Semester Program participant. We would like to thank
 E.O.  Edney, S.F. Cheek,  D.C.  Stiles, and E.W.  Corse for conducting the field exposure study for EPA under
 Mantech Contract 68-DO-6106, and for providing the run-off data.

 DISCLAIMER

 This manuscript has been subjected to the agency review and approved for publication and presentation.  Mention
 of trade names or commercial products does not constitute endorsement or recommendation for use.

 REFERENCES

 1. E.O. Edney, D.C. Stiles, J.W.  Spence, F.H. Haynie, and W.E. Wilson, Laboratory investigations of the impact
 of dry deposition of SO, and wet deposition of acidic species on the corrosion of galvanized steel. Atmos. Environ.
 20:541-548 (1986).

 2. E.O.  Edney, S.F. Cheek,  D.C. Stiles, and E.W, Corse, Impact of Shape, Size,  and Orientation on  Dry
 Deposition Induced Corrosion of Galvanized Steel: Results of a Controlled Field Study, Atmos, Environ, (in press).

 3. R.T. Tang, P.M. Barlow, and P. Waldruff, Material Aerometric Database for Use in Developing Materials
 Damage  Functions,  EPA 600/3-89/031, U.S. Environmental Protection Agency, Research Triangle Park, NC
 (1989).

 4. J.W. Spence and F.M. Haynie, Derivation of a Damage Function for Galvanized Steel Structures: Corrosion
 Kinetics and Thermodynamic Considerations, pp. 208*224 in Corrosion Testing and Evaluation: Slyer Anniversary
 Volume.  R. Baboian and  S.W.   dean, eds. ASTM  STP  1000,  American Society  for Testing and Materials,
 Philadelphia. 1990.

 5. F.W.  Lipfert and R.E.  Wyzga, Application of Theory to Economic Assessment of Corrosion Damage,  in
 P?f fflVltiflff of Materials due to Acid Rain, ed. by R. Babaoian. American Chemical Society Symposium Series 318,
pp.411-432, 1986.
                                                122

-------
          CORROSION OF MONUMENTAL BRONZES
                     John D. Meakin* and Susan I. Sherwood*
            * Mechanical Engineering, University of Delaware, Newark, DE 19716
          ^National Park Service, P.O. Box 37127, Washington, DC 20013-7127

ABSTRACT
       Chemical components of the atmosphere in the form of strong mineral and weak organic
acids accelerate metals corrosion. This paper focuses on the questions of delivery of pollutants to
bronze sculptural surfaces and the influence of changes in precipitation chemistry on the stability
and removal of corrosion products. Three specific NFS research efforts, based on in situ
measurements of environmental exposure and/or corrosion at selected bronze monuments are
described in detail.  The first is a field study of the General Meade Statue at the Gettysburg
National Military Park. Dry deposition was monitored, with a supporting laboratory simulation
study.   Aerodynamic processes controlling the delivery of gases and particles to outdoor
monuments were investigated. The second effort evaluates specific forms and severity of bronze
corrosion (uniform, streaking, pitting) in the context of overall environment exposure and specific
site characteristics, as evidenced by replicates of Kitson's Hiker statue dedicated throughout the
Northeastern United States beginning in the 1920s. The third project investigates the chemistry of
runoff from bronze monuments in a rural environment Runoff from a number of Bronze Brigade
Markers, also at the Gettysburg National Military Park, and parallel rain samples were collected
and analyzed.
INTRODUCTION
        It is  clear from the basic principles of electrochemistry that both strong mineral and weak
organic acids accelerate metals corrosion^. The purpose of this paper is to look more closely at
the role of trace chemicals in the atmosphere in the corrosion of outdoor bronzes and the nature and
results of the corrosion process. The delivery of pollutants to statue surfaces, the corrosion effects
on the surface morphology and appearance, and the removal of corrosion products by runoff are
explored. The physics of how atmospheric chemical stresses are supplied to outdoor bronzes by
pollutants in  the environment is important in understanding how the resulting chemical corrosion
occurs. The delivery of corrosive species, intermittent wetting and drying cycles, and removal by
evaporation and runoff are interdependent processes that influence the concentrations of ions that
are present on outdoor bronze surfaces. The  quantity of pollutants participating in corrosion
processes is not a simple linear function of the concentrations in the air and rain. Changes in the
atmosphere alter the stability regimes of natural and artificial patinas, as well as the durability of
protective coatings. Many of the basic processes are understood and can be quantified in general
terms.  Future research may enable us to quantify impacts for specific monuments.
        Three specific National Park Service research efforts, based on in situ measurements of
environmental exposure and/or corrosion of selected bronze monuments are described. The first
considers aerodynamic processes that influence the delivery of gases and particles to outdoor
monuments^. The second evaluates specific  forms of bronze corrosion (uniform, streaking,
pitting) in the context of overall environment exposure and specific characteristics of the monument
site, as evidenced by the series of replicates  of T. A. R. Kitson's Hiker statue dedicated beginning
in the 1920s4. The third investigates the chemistry of runoff from bronze monuments in a rural
environment^.
                                         123

-------
DRY DEPOSITION STUDY AT THE GENERAL MEADE MONUMENT, GETTYSBURG, PA

        Wu and associates conducted a series of deposition measurements on a equestrian bronze
statue of General Meade during spring and summer seasons at Gettysburg National Military Park,
PA. A complete description of these experiments has been published elsewhere^. The granite
pedestal is 3.4 m high and the top of the statue is 6.7 m above the ground. The statue was selected
to provide a variety of shapes with different aerodynamic characteristics, ranging from the bluff
body of the horse (vertical "flanks", skyward facing horizontal "rump" surface, ground facing
horizontal "belly" surface) to the relatively fibrous slender legs . The microclimate near the surface
of the statue was  determined using wetness sensors, thermistors, and hot film anemometers.
Meteorological data representative of the ambient conditions of the open field setting were obtained
nearby.  Airborne concentrations of acidic and acid precursor materials were measured using filter
packs; precipitation was sampled on an event basis. Particle concentrations were evaluated using
acrodynamically designed surrogate surfaces positioned near the statue. Dry deposition to the
statue was sampled using patches of various materials selected to react aggressively and selectively
with the species of interest. Carbonate impregnated Whatman filter paper was used to collect SO2,
Nylasorb filters were used to measure total flux of nitrogen oxides, and ungreased mylar was used
to collect paniculate sulfates, nitrates, and calcium.

        The deposition fluxes varied greatly with sampling location on the statue, and they also
varied greatly from day to day. The amount of deposition varied with location on the statue. The
sulfate particle deposition in order of diminishing severity was as follows: horse's back, the
windward flank, the leeward flank, and showing least deposition, the belly. The greater fluxes on
the windward side coincided with areas where the statue had developed green corrosion, since its
last waxing in 1981.  In contrast, sulfur dioxide fluxes varied more between sampling periods than
between sampling locations, indicated that the monument is more generally "bathed" in deposition
from SO2 gas. Overall, SO2 fluxes exceeded equivalent sulfate particle fluxes by a factor of about
five. Nitrate fluxes generally exceeded sulfate fluxes by factor of 1.5 to 4.

        A naphthalene sublimation wind-tunnel study was undertaken to evaluate the aerodynamic
characteristics of equestrian statues in general and to assist in interpreting the General Meade
deposition  field study results**.  The technique  utilizes a uniformly thin coating of white
naphthalene over a model that has  been painted black. The coated model is exposed to simulated
wind fields in a wind tunnel  As the naphthalene sublimes, portions of the model become  grey and
then black. The model is  photographed at regular intervals to chart the relative removal of the
transient coating.  Areas where naphthalene sublimates most quickly are those areas where mass
transfer, such as absorption of pollutants, evaporation of dew, etc., will occur preferentially.


      A thorough understanding of the microclimate and aerodynamics of free-standing outdoor
bronzes may lead to conservation treatments that retard corrosion by interrupting the delivery of
pollutants to the metal surface, by altering the condensation characteristics or the  aerodynamic
flow.

CORROSION OF  THE HIKER BRONZE STATUES

      The many replicas of the Hiker statue  that were cast over a sixty year period, and which are
located at numerous sites in the United States, provide a unique resource for assessing the impact
of environmental conditions on the degradation of a monumental bronze. Theo Alice Ruggles
Kitson sculpted the original Hiker and from  1922 to 1965,51 replicas of the statue were cast by
the Gorham Company of Providence, RI. In  1965 the metal masters from which all these castings
were presumably made, were themselves assembled and erected in Washington, DC, as the final
copy of the Hiker series.
                                         124

-------
       Analyses have been conducted on the composition of the alloy in actual statues  the overall
     •es of the corrosion patterns, the composition of the corrosion layers and the morphologies of
         s surfaces in the as-corroded state as well as for statues after conservation treatments. A
complete description of the techniques used and the results to date is in press4.
       Microscopic and surface characterizing techniques are much more readily carried out in the
       3ry than at outdoor Hiker sites. Some photography can be carried out in the field but this is very
  mited in the enlargement that can be achieved. Accordingly a replica technique was developed and
applied to selected features on a number of statues.

       The replicating material is a vinyl  polysiloxane, widely used for dental purposes and
     •  i   £"1      supply houses. The two components are mixed by hand to yield a putty like
    snal which can be pressed firmly against the surface to be replicated. At normal temperatures
        nal sets up to a firm, but slightly elastic solid which can be peeled from the surface.  Areas
 )f about 20cm2 have been routinely replicated on more than half of the Kitson Hikers.

       Various regions of the statue were considered for replication but the location selected for
me  majority of studies was the rifle barrel under the front sight. This region is well exposed and
     : complex run off effects. Furthermore over a relatively short distance the surface goes from
   lost horizontally up to horizontally down. A surface profilometer was used to give line profiles'
   ng a horizontal line. Representative profilometer traces of the surfaces of various statues are
               .  The Montgomery statue has been in a museum and shows an essentially smooth
       [the peaks are surface detritus) as does the Washington statue which is the most recent and
     een well maintained. In contrast the Lynn, MA statue dedicated in c!923 reveals pits up to
             Hie Fitchburg, MA, statue is almost as old as the Lynn statue but was walnut shell
       and waxed just before the replica was taken. The pits appear more rounded than those on
                  A number of statues have received aggressive surface  treatments such as
     :use which has  been  sand blasted. The  trace shows  numerous sharp asperities in contrast to
the profile of the Fitchburg statue.

       A Preli™nary analysis of pit depth against the age of the statue has resulted in the plot
                 rhree  statues that are known to have been aggressively conserved and coated
  tow surprisingly shallow pits in view of their age.  Further investigation is needed but it seems
          >tner older statues showing shallow pit depths have also been similarly treated.
                                               0.5 -r
                                               0.4 • - •
                                s\f\     *«•
                                            Q
                                            O
                                               0.2 • •
                                               0.1  .-
                                                    a    •
                        Syricuia
                                          1920     1930     1940     1950    1960

                                                     Dedication  Year

              Figure 1                                 Figure 2
       Profiles for various statues.          Pit depth vs dedication year. Hollow symbols
Note vertical scale change for Syracuse.      are for statues known to have been conserved.
                                           125

-------
 RUNOFF MEASUREMENTS AT GETTYSBURG NATIONAL MILITARY PARK

       To assess the effects of corrosion product stability on bronze under current environmental
 conditions, an experiment was designed to analyze the chemistry of runoff from openly exposed
 bronze monuments*. The Gettysburg National Military Park is in a rural area of Pennsylvania
 although  there is  substantial vehicular traffic created by the over one  and a half million
 visitors/year.  In about 1906 a series of Bronze Brigade Markers  were erected at numerous
 locations throughout the Park.  These markers are cast bronze plaques with raised letters and are
 mounted at 30° to the vertical on granite supports. They appear to have been cast by Bureau Bros.
 of Philadelphia and according to a letter to the War Office dated October 6th,  1906, were to be
 made of "Government Standard Bronze Metal of the best quality"?. Qualitative EDS analysis
 indicates a copper alloy containing small amounts of Sn, Zn and Pb suggesting that these markers
 are ounce  metal, nominally 5% Zn,  Sn and Pb in Cu, the same alloy that was used for the Hiker
 statues.

       A collection systems was designed to sample the runoff solution following a rain event.
 Parallel rain samples at two locations in the park were collected between 1986-88. Analysis of the
 runoff and rain samples included measurements of pH, Cu and Zn content, and various ion species
 typical of rain.

       Three markers were selected for measurements and were fitted with a channel device that
 fed into acid-leached polyethylene sample bottles. Park staff and volunteers mounted the collection
 systems when a rain event was anticipated.  In the event that rain did not occur in 12 hours the
 collection  bottles were re-cleaned to avoid contamination. Laboratory analysis was conducted
 using atomic absorption and ion chromatography; the techniques yield compositions to an accuracy
 of about 5% relative.

       Computer based files are available that contain the results corresponding  to 35 rain events
 and the associated rain and runoff analyses for the three bronze markers. Initial correlations have
 been tested for zinc versus copper, the concentration of copper versus sulfate ion and the copper
 versus nitrate ion concentrations. The ratio  between copper and zinc was found to be 20:1 in
 accord with the anticipated composition of the bronze. The copper versus sulfate correlation is
 shown in Figure 3.  The correlation is high with a coefficient R2^ of 0.90.  The line has a slope of
0.62, close to the  value of 0.66 which  would be  expected for dissolution of CuS04.   The
correlation of copper versus nitrate  ion is not so high, R^ = 0.5, and the least square line has a
slope of 0.82, substantially different from the value of 0.51 that would correspond to dissolution
ofCu(N03)2.
                                      50           100

                                       Sulfate ppm
ISO
                                          Figure 3
                            Copper vs Sulfate concentration in runoff.
                                         126

-------
CONCLUSIONS

        The impact of pollutants on bronze corrosion depends on the chemical nature of the
atmospheric agent and the extent of exposure.  The research on the General Meade statue has
shown that areas  of sculptures with an open sky-view are exposed to the greatest amount of
deposition, as well as to the greatest range in temperature conditions. Corrosion in these locations
is expected to be the most severe.  If these areas are not well drained, such that moisture and snow
can accumulate, the corrosion is further increased

       The effects of acid precipitation on the corrosion of the Hiker series of statues has been
studied by a number of techniques and a molding system developed to characterize the surface
profile of corroded regions.  Substantially different degrees of attack have been recorded. The
technique will permit monitoring of corrosion over a period of time and will also contribute to
quantifying the effect of conservation treatments.

       Runoff studies on bronze tablets at the Gettysburg National Military Park have indicated
that the dissolution rate is controlled by the availability of sulfate ions. There appears to be little or
no correlation between the acidity of the runoff and the acidity of the rain falling on the tablet Dry
deposition between rain events are concluded to dominate the acidity of the runoff.

        As the environment continues to change, consideration should be given to the chemical
stability of materials exposed to  the elements. This applies to "original" surfaces, weathered
surfaces, and those subjected to protective treatments. Ideally, a treated surface will be at least as
resistant to attack by pollutants as an untreated, corroded surface.  Conservation treatments that
diminish the potential for electrochemical reactions will reduce the deleterious impact of pollutants.

        In the long run, the most efficient solution is to eliminate the causes of the problem. In
addition to the projected reductions in sulfur oxide emissions, in the future it may be possible to
disrupt the pollutant delivery process by altering the condensation cycle and/or the aerodynamic
flow conditions near the surface of bronze monuments.

ACKNOWLEDGEMENTS

       The research summarized  here encompasses work carried out by a substantial number of
workers in cooperation with the National Park Service under the auspices of the National Acid
Precipitation Assessment Program. We trust that the text reflects the efforts and views of the
researchers at the Gettysburg National Military Park, the Illinois State Water Survey, Carnegie
Mellon University, The National Ocean and Atmospheric Administration, The University of
Delaware, the Winterthur Museum and the National Park Service. We take full responsibility for
errors and faulty interpretation.
                                           127

-------
REFERENCES

1.    W. D. Richey, "Recent Advances in Corrosion Science", Science and Technology in the
      Service of Conservation, N. S. Bromell and G. Thomson,  eds. Preprints of the
      Contributions to the Washington Congress, 3-9 September 1982, International Institute for
      the Conservation of Historic and Artistic Works, London, pp. 108-118,1982.

2.    Susan I. Sherwood, "The Greening of American Bronzes -  the Role of Atmospheric
      Chemistry in the Corrosion of Outdoor Bronzes", Dialogue/89 - The Conservation of
      Bronze Sculpture in the Outdoor Environment:  A dialogue among conservators, curators,
      environmental scientists and corrosion engineers. T.D. Weisser ed. pp. 37-72,1992.

3.    Y.  L. Wu, C. I. Davidson, D. A. Dolske, and S. I. Sherwood, "Dry Deposition of
      Atmospheric Contaminants: The relative importance of aerodynamic, boundary layer, and
      surface resistances", Aerosol Science and Technology, Vol 16, pp. 65-81,1991.

4.    J. D. Meakin, D. L. Ames, and D. A. Dolske, "Degradation of Monumental Bronzes",
      presented at the International Conference on Acidic Deposition: Its Nature and Impacts,
      Glasgow, Scotland, September 16-21, 1990; Atmospheric Environment, to be published,
      1991.

5,    D. A. Dolske  and J. D. Meakin, "Acid Deposition Impact on Historic Bronze and Marble
      Statuary and Monuments"., Materials Performance, Vol.  30, pp.53-57,1991.

6.    R. P. Hosker, J. R. White, and E. A. Smith, "Dry deposition to structures:  configuration
      considerations", Presented at: International Conference on Acidic Deposition: It's Nature
      and Impacts,  Glasgow, Scotland, September 16-21, 1990; Submitted for publication to
      Atmospheric Environment, 1991.

7.    National Archives and Records Administration (1906) Letter from Gettysburg National
      Park Commission, October 16,  1906, to The Secretary of  War in 7393/46.
                                        128

-------
          REMOVAL OF CaCOa EXTENDER IN RESIDENTIAL COATINGS BY
                        ATMOSPHERIC ACIDIC DEPOSITION
                   W.C. Miller, R.E. Fornes, R.D. Gilbert and A. Speer
                            North Carolina State University
                                 Raleigh, NC 27695

                                 J. Spence, U.S. EPA
                           Research Triangle Park, NC 27711
ABSTRACT
      The removal and fate of CaCCg extender in latex and alkyd paints upon exposure of paint
films to UV and atmospheric pollutants generated in a large environmental chamber were studied
using optical and  scanning  electron microscopy  in combination  with energy dispersive
spectroscopy. X-ray mapping of film cross sections was used to examine migration of calcium to
the film surface, and X-ray diffraction and Energy Dispersive Spectroscopy (EDS) were employed
to determine crystalline nature of surface deposits. Crystals of various forms of calcium sulfate
formed on paint surfaces. Surprisingly, migration of calcium to the paint surface occurred in the
absence of liquid water in the form of dew.

INTRODUCTION
      Previously we investigated the effects of U.V. and SO2 in the presence and absence of
moisture on the structure of the base polymer in acrylic-type latex paints (1,2,3). Here we extend
the studies to the removal of CaCOs pigment in latex and alkyd paints upon exposure of the paint
films to U.V. and atmospheres  generated in a large environmental chamber located at North
Carolina State University. The chamber essentially consists of a stirred tank reactor equipped with
U.V. lamps into which SO2, NO, propylene and water can be combined at various levels with
clean air, which under the influence of U.V. generate mixtures of SOj, NOX, 03, PAN, HiSO*,
HNO3, formic and acetic acids. These pollutants are circulated, under turbulent conditions through
channels having a total of 48 4"x6" film sample holders. The films are mounted on stainless steel
plates through which refrigerant can be circulated to produce, if desired, dew on the films. There
is provision for collecting dew run-off samples.  The films can be irradiated with U.V. light dunng
atmospheric exposure. The concentrations of pollutants and temperature may  be continuously
monitored. The circulating smog was operated at a temperature in the 25-30C range.

EXPERIMENTAL
      Two latex-based paints and two alkyd-based paints were used in the study. One latex-
based paint contained a butyl acrylate/vinyl chloride/vinyl acetate copolymer prepared by UCAR
Emulsions.  The other latex paint contained  a butyl acrylate/methyl methacrylate copolymer
prepared by Rohm and Haas. Each copolymer contained small (1-2%) amounts of acrylic or
methacrylic acid and each paint contained CaCOs and TiOa pigments. Likewise the alkyd paints
were prepared by Rohm and Haas and Union Carbide and each contained CaCOs and TiO^.
      Films were cast onto release paper at a thickness of 10 mils using a draw down bar, dried
at R.T. for 2 hours and then heated under vacuum at 40° for 48 hours and then were stored under
vacuum prior to use and after exposure.  The films were exposed to (1) U.V.; (2) pollutants; (3)
U.V. and pollutants; and (4) U.V., pollutants and  dew for a maximum  of 94 days.  Small
specimens were also taken from each sample after exposure for 29,51 and 73 days.
      Film samples (1/8" x 1/4") were mounted on an SEM stub with a carbon disc using double-
sided masking tape, and carbon coated. SEM micrographs and EDS spectra were obtained with an
Amray 1000 electron microscope with a corresponding EDS system, which operated at 30 kV and
                                         129

-------
was located at EPA in Research Triangle Park. North Carolina.  Several micrographs and EDS
spectra were obtained for each sample. Film cross sections were obtained by freezing the films in
liquid N2 and then impacting them against a sharp edge.  The fractured samples were carbon
coated, mounted on an aluminium block and an SEM micrograph obtained.
       Samples (1/2" x 1/2") were attached to glass  slides specifically designed for X-ray
diffraction studies using the particular paint as the adhesive, and exposed in a Rigaku Denki Max B
X-ray diffraction instrument.  The resulting patterns were then compared to patterns published in
the Joint Committee on Powder Diffraction Standards.
       Film samples were viewed optically with a Nikon reflecting microscope.  Selected optical
micrographs were taken using a Polaroid camera and Polaroid 667 film.

RESULTS AND DISCUSSION
       In each case the SEM photomicrographs and EDS spectra showed that the CaCOs pigment
was converted to  CaSO4  when the paint films were exposed to pollutants alone, to U.V. and
pollutants,  and to U.V., pollutants and dew.  For  example, Figure la shows the  SEM
photomicrograph and corresponding EDS spectrum of an unexposed UCAR latex paint film and
Figure Ib is for the paint film after exposure to pollutants alone  for 94  days.  Significantly, the
calcium and sulfur levels have increased substantially and calcium sulfate crystals are  apparent on
the surface. On exposure to UV and pollutants, CaSO4 again appeared on the surface at the paint
film as illustrated in Figure 2 for the Rohm and Haas latex paint  However, on exposure to UV,
pollutants and dew no CaSO4 was apparent on the exposed film surface as shown by Figure 3
(Rohm and  Haas latex paint film after 94 days exposure).
       The alkyd paints showed similar behavior. That is, CaSC>4 crystal formation occurred on
film surface as illustrated in Figure 4, which shows the SEM photomicrograph and EDS spectrum
for the Sherwin Williams alkyd paint film after exposure to UV and pollutants for 94 days.
       Reflectance optical microscopy confirmed the presence of CaSO4, in the form of gypsum
after exposure to pollutants. In several cases different types of twinned gypsum crystals formed as
illustrated in Figure 5.
       X-ray  diffractograms of the exposed paint films showed the presence of partially hydrated
(hemihydrated) CaSO4 and gypsum as well as TiO2, as expected.
       Examination of the freeze fractured surfaces of the paint films after exposure to pollutants
by SEM suggest that mass transport of calcium from the interior of the  paint film to the surface
occurs during exposure. When dew was present the calcium was  removed from  the film surface.
Corresondingly the greatest amount of mass transport occurred in the presence of dew as illustrated
by Figures 6 and 7.
       Xu  and Balik (4) exposed paint films containing CaCO3 to aqueous SO2 and showed
calcium diffused out of the water-swollen films (either as Ca** or CaSOa). We have no direct
evidence that an H2SO4 aerosol evolved in the reaction chamber but it could be formed  by
             SO2 + H2O2      hv      ^ H2SO4.
It is not known if Ca++ ions migrated to the surface, reacted on the paint surfaces with H^SO4 to
form CaSO4, or whether SO=4 anions diffused into the paint film and reacted with CaCOs and the
resulting CaSO4 migrated to the film surface. Certainly the freeze-fracture results confirm there
was mass transport of calcium (either as Ca++ or CaSO4) to the paint film surface, even the
absence of moisture, but in the presence of dew the CaSO4 is removed from the surface.
       Our previous studies (1,2,3) demonstrated that SO2 has  a synergistic effect on the
photodegradation of paint films.  The present results suggest CaCO} pigment may protect paint
films from photo degradation initiated by SO2 in acid rain by the SC*z complexing with CaCX>j.

DISCLAIMER
       This paper has been in accordance with the U. S. Environmental Protection Agency's peer
and administrative policy for publication.  Mention of trade names of commercial products does not
constitute endorsement or recommendation for use.
                                         130

-------
5
                                          < . I      ( . I
                                          I»EmOT (EC*)

CJt
"•• 1 I
TT 1 1 • I
cjrii.U . • «•,

tl

1 It X*

                                                          *.* -  1C . e
                                                                           0.9     1.0

                                                                                                                             >: c:
                                                                                                                        I
                                                                                                                        —
                                                                                                                              It
i
                                                                                                                          2  a?.
                                                                                                                                s
     £
                                 a.     Control Sample                              b.    Exposed to Pollutant Only

                                 Rgure 1.  SEM Micrographs and Corresponding EDS Spectra of Union Carbide Latex Paint
      CO

-------
—
M

e*
- ii m,d • i
c* "I 1 i i"
II 1 *^ -*-^- -- * T
t , o z1. • »'. a
u
1
('.0 •'. • 10.1
                          Figure 2.  Groups of Crystals on Rhom and Haas Latex Paint     Figure 3.  Rohm and Haas Latex Paint Exposed to UV, Pollutant
                                   Films Exposed to UV and Pollutant-Viewed on                 and Dew for 94 Days. Areal EDS Scan.
                                   Side Opposite of Exposure. Areal EDS Scan.

-------
                                                                                                    *-iJ
                                                                  Nfe,
Figure 4.  Sherwin Williams Alkyd Paint Exposed to Pollutant     Figure 5.  Sherwin Williams Alkyd Paint Exposed to UV, Pollutant
         Only  for 94 Days. Area! EDS Scan.                           and Dew for 94 Days with Gypsum Crystals Shown.

-------

RH Latex P,UV _    S M»P
Ca Map
                                                               RH Latex Control  j S Map
                                                             RH Latex P,UV, Dew  S Map
  Figure 6.  Rohm and Haas Latex Paint Exposed to Pollutant
           and UV for 94 Days. Extensive Depletion of the
           Calcium Carbonate Particles is Indicated.
                       Figure 7. Rohm and Haas Latex Paint Exposed to UV,
                                Pollutant and Dew for 94 Days.

-------
        A STUDY OF THE EFFECTS OF  ACIDIC POLLUTANTS
                        ON AUTOMOTIVE FINISHES

           Naraporn Rungsimuntakul, Douglas White, Raymond Fornes,
                          Richard Gilbert, Chunshan Zhang
                       Physical and Mathematical Sciences Research
                             North Carolina State University
                          P.O. Box 8209, Raleigh, N. C. 27695

                                    John  Spence
                    Atmospheric Research and Assessment Laboratory
                      United States Environmental Protection Agency
                          Research Triangle Paric, N. C. 27711


ABSTRACT
      Automotive finishes of various compositions on metal substrates were exposed vertically in a
smog chamber to UV and acidic atmospheres that were generated from combinations of SC>2, NO,
propylenc, water and air.  Dews of different compositions were generated and collected for spot
testing.  Spot tests were performed by placing drops (lOOuL) of dews on the surfaces of the paints
and heating in an air-circulating oven at 90 °C for 24 hours. Visual observation, reflection optical
microscopy, profilometry, SEM and EDS were used to examine surface damage. Various degrees
of damage occurred depending upon the dew composition and surface properties.  In general, the
damage areas were in the form of rings with diameters smaller than the original drop. After rinsing
and buffing, the damage was still visible.  Microscopy and SEM revealed that the rings consisted of
numerous small areas of damage and that swelling, pitting blistering and cracking had occurred.
EDS showed aluminum and sulfur at the damage surface, while the surrounding area did not. Since
the base coat contained Al flakes, this suggested that the acidic dew had penetrated through the top
coat into the base coat

INTRODUCTION
      Environmentally-related damage to automotive finishes (paint coatings on metal substrates)
has been observed.  Weather and acid resistance  of materials have concerned coatings and
automotive manufacturers and government agencies. Paints exposed to acidic pollutant atmospheres
are typically subjected to UV light, oxygen/ozone, temperature and humidity. Understanding the
damage characteristics and the influencing factors and mechanisms of photodegradation of materials
in an acidic environment will provide highly useful information and guidelines, possibly leading to
the development of the acid resistant materials.
      Paint damage can occur at the macroscopic level, such as darkening or fading of the
pigments, decrease  in gloss, chalking1'2 pitting, blistering, peeling and cracking2'3-  It can also
occur at  the microscopic level, such as increased crosslinking, adsorption or film component
dissolution2.
      McEwen et al.1 studied accelerated weathering of automotive paint using xenon-arc and
quartz filtered ultraviolet light and compared the results with materials exposed to Florida sunlight
They used gloss meter analysis and attenuated total reflectance infrared spectrometry (ATR-IR). The
ATR-IR gave useful information about the degradation and indicated that some surface oxidation
occurred. However, the paint film had to be peeled away from the metal substrate in order to be
characterized using the ATR-IR.
      Simson  and Moran2 discussed the effects of UV radiation and oxygen/ozone on the
degradation of  the polymer films. They stated that UV excitation of sufficient energy caused
excitation of oxidants resulting in free radical formation. Free radical reaction with polymer films
could induce crosslinking or chain scission of the polymer. If the backbone of a polymer chain were
                                         135

-------
          significant degradation could result.  They also discussed the effect of the presence of
moisture and stated that it could result in some swelling of the polymer film and lead to increased
permeation of pollutants.
       Campbell et al. used six techniques to assess air-pollution damage to three kinds of paint on
steel:  alkyd industrial maintenance paints, coil coating finishes and automotive refinishes (titanium
in nitrocellulose/acrylic).4 The techniques used were:  erosion rate, ATR-IR, gloss and sheen,
surface roughness, tensile strength and scanning electron microscopy (SEM). They concluded that
the combination of the gravimetric erosion rate, ATR-IR and SEM analysis gave the most useful
information in assessing the damage.  SEM micrographs showed that the automotive refmish
exposed for seven months at Chicago, Illinois and Leeds, North Dakota were unaffected, but that
the paints exposed to 1 ppm of SC*2 had slightly greater surface roughness. The erosion rate
appeared to be linearly related to (SOj or 63) concentration.
       White and Rothschild3 found dark spots of several millemeters in diameter on cars exposed
in Israel.  Some spots were in the form of shallow pits in the paint films. They reproduced the
appearance of die  spots by leaving drops of strong nitric and sulfuric acid on the paint for some
time.
       Wolff et al.5 studied the damage to automotive finishes exposed outdoors in Florida
(subjected to heat, UV radiation, wind, rain, dew and air pollution) for five weeks.  The damage
occurred as circular, elliptical or irregular  spots that appeared as deposits or precipitates.  They
summarized that wetting events such as rain and dew were a prerequisite for damage to occur. The
damage was enhanced without exposure to additional wetting events when the deposits remained on
the test panels  for several days while exposed to daytime heating, sunshine and cooling.  Their
electron dispersive spectroscopy (EDS) data showed that the precipitate associated with the ringlet
shaped spots was composed mainly of calcium sulfate (CaSO4).  When the surface was washed,
most of the CaSO>4 was removed but the surface remained scarred.
       Simson and Moran reviewed Edney's work (EPA report 1988) on an oil-based maintenance
paint,  which they exposed in a smog chamber containing mixtures of CsHg/NOx/SC^, under wet
and dry conditions for 21 h.2 The pollutant concentrations used were: 722ppb of  SO2,230 ppb of
03 ,180 ppb of NO? , 380 ppb of HCHO and 7ppb of HNC>3 . The results indicated that this paint
was fairly inert at this exposure condition.
       The extent of damage to polymer films caused by acidic pollutants depends on many factors
such as the type and concentration of pollutants, the exposure temperature and time and the presence
of UV radiation, ozone and humidity.  Jellinek et al. reported  that chain scission took place in
poly(methyl methacrylate) when the polymer was exposed to UV/O2 and UV/O2/SO2-6 Sankar et
al.7 reported the results of elemental analysis, x-ray photoelectron spectroscopy (XPS) and 13C
magic angle spinning nuclear magnetic resonance (I3C MAS NMR) studies of a UV/SO2/H2O
exposed acrylate copolymer and a teipolymer of n-butyl acrylate, vinyl acetate and vinyl chloride
films.  There was clear evidence of the incorporation of sulfur into the polymers and there was
significant loss of the acetate group in the teipolymer.  The results suggested a synergistic interaction
between SO2 and UV leading to rapid degradation.

EXPERIMENTAL
       We developed our spot test to simulate the outdoor damage process of automobile paint
exposed to precipitation followed by heating from the sun. In this study we exposed automotive
finishes in a smog chamber for one week, followed by dew exposure in the form of a spot test at
90 °C for 24 h. (Note that the outdoor temperature  of the automobile body can  surpass 90 °C6.)
The spot test was performed by placing 100 nL drops of the dews onto the surface  of the paints,
followed by heating the samples in an air circulating oven at 90 °C for 24 h.  The samples were
analyzed using reflection light microscopy, profilometry, SEM and EDS.

Samples
                                          136

-------
      The paint samples' dimensions were 10 cm x 15 cm x 0.058 cm. They were prepared in a
manner that is consistent with the method of the preparation of automobile paint coatings. Two
kinds of paints, white and metallic grey, were studied. The white sample consisted of a layer of
titanium dioxide in an acrylate blend topcoat on a metal substrate.  The metallic grey sample
consisted of layers of an acrylate blend topcoat and aluminum flakes on an acrylate blend base coat
on a metal substrate.  The samples were rinsed with dcionized water and lightly buffed with a
chamois before each exposure to remove dust

Chamber Exposure
      Samples were positioned vertically and exposed to UV  light and pollutants in a smog
chamber at  North Carolina State University.  Pollutants such as SO2, NO and propylenc were
introduced into the chamber and mixed with dry clean air and deionized water. The chamber was
surrounded by banks of UV light which simulated the UV component of the sunlight spectrum. The
chamber was operated as a continuously stirred reactor in which NOX, ozone and various acids were
formed.  Each sample holder was placed on a chiller plate so that sample could be chilled below the
dew point temperature to generate a wet surface, i.e., dew.
      The samples were exposed at approximate average pollutant concentrations of 300 ppb of
NOX, 460 ppb of C3H6, 90 ppb of SO2 and 120 ppb of 03 for one week, under the cycle of 5 h wet
-2 h dry - 5 h wet -  12 h dry surface conditions. The sample temperatures under dry deposition and
wet deposition were about 30 °C and 5 °C, respectively.  The samples were removed from the
chamber, observed for  surface change and stored in a desiccator. For the spot tests, dews werje
generated on teflon films placed on the chiller plates and the run-offs were collected twice  a day and
kept in amber glass bottles under refrigeration. The pH and composition of the dew were  measured
by using a Fisher pH meter  and a Dionex Ion Chromatograph model 201 Oi, equipped with  an
lonPac column AS-10.

Dew  Exposure
      Three drops of filtered chamber dews (100 ^1 each) were pipetted onto the surface of the
samples. The samples were kept at room temperature for 1 h and then placed in an air-circulating
oven at 90 °C for 24 h. Finally, the samples were rinsed with deionized water and lightly buffed
with a chamois before surface analyses were performed.

Surface Analysis  of  the Painted  Samples
      A reflection light microscope (Zeiss model AXIOMAT) was used to examine the damaged
surface areas. An Alpha Step 200 profilometer manufactured by Tencor Instruments Co., with a
stylus in the shape of a 60° cone rounded at the end to a spherical tip of 12.5 |im radius was used to
measure the depth or height of the damage by dragging it across the surface. An SEM, (JEOL 840)
equipped with an EDS (Kevex model 8000) was used to examine the details of the damage and the
elemental composition of the surface.

RESULTS AND  DISCUSSION
       From visual observations, there was no significant change of the surface appearance on
either of the chamber exposed samples.  The samples were then subjected to spot testing  using two
chamber dews with pH 3.35  and 3.50, respectively. The composition of the dews are shown in
Table 1.

Tah|g I   nfl and composition of  the chamber dews.
Chamber.         pH                  Ion Concentration (mg/L)
DeW#                     F-        Cl-      S04-     NOr   CH3COa      HCOO-
                335      L21      O54    2O51     1014     20.49         1.83
                3.50      1.59      0.99    14.91      7.99     23.07 _ 33.81
                                         137

-------
       The samples with dew drops placed on their surfaces were placed into an oven and heated at
90 °C.  The behavior of the drops was essentially the same as reported by White8.  From the
damage size and shape, it appears that at a critical concentration the acidic chamber dew attacks the
painted surfaces.
       Previously, the damage was found to be more pronounced when the exposure temperature
was increased from 54 to 90 °C, and when the exposure time was increased from 1 to 24 h8. This
also suggests that the extent of the attack directly depends on the exposure temperature and that the
attack continues with the exposure time.
       Various degrees of damage occur depending upon the dew composition and the surface
properties.  For the white paint (#7), reflection light microscopy reveals that the damage is in the
form of a ring with some damage in the middle.  Some surface cracking also occurs (Figure la).
The corresponding surface profile of this damage (Figure Ib) shows that the damage is a blister with
a height of 0.8 mm. (Note that the 4.5 urn value in the figure represents the height of the deposits or
reaction products.)  The white paint (#7B), which was exposed to pollutants in the smog chamber
for one week prior to the spot test, has a larger damage area and a slightly higher blister (0.9 mm)
than #7, as shown in Figures 2a and 2b, respectively. When drops of acidic dew containing various
acids such as HiSCM, HNOs, HCOOH, CHsCOOH, were dried, deposits were left on the paint
surface. It appears that they penetrated the top coat and caused swelling and cracking of the paint.
       The chamber exposed (#1B) and unexposed metallic grey paint samples (#1) were subjected
to spot tests using chamber dews #91-3 and #91-6.  The height and depth of the damage area are
reported in Table 2. The damage on the chamber exposed samples is greater than on the unexposed
sample. The chamber dew #91-3, pH 3.35, causes more damage than the chamber dew #91-6, pH
3.50.

Table  2    Maximum height (H) and  depth (D) of the damage on the  paint samples
exposed to chamber dews  at 90 °C for 24 h, measured by  profilometry scans
CEambTr pH
Dew#
#91-3
#91-6.
3.35
3.50
Palnt"S 1
H D
0.90, -0.1
0.33 --
" Taint #2
H D
2.60
1.57
Palm
H
0.86,
NA
itt
D
-0.90
NA
Paint 14^
H D
0.90
0.60
-0.80
-0.94
      Microscopy and SEM reveal that the ring shaped damages on paint #1 and #1B consist of
many small areas of damage and that swelling, pitting, blistering and cracking occurred. The EDS
spectrum of the damage surface on paint #1B shows aluminum and sulfur (Figure 3a), while the
surrounding area does not (Figure 3b). This suggests that the chamber dew has attacked the top coat
and penetrated through cracks into the base coat, exposing the aluminum in the base coat.  It also
suggests that the sulfuric acid in the dew may have reacted with the acrylate polymer.

SUMMARY
      This preliminary study of the effects of acidic pollutants on acid resistant automotive finishes
showed that one week of exposure to moderately high concentration of pollutants in a smog chamber
does not visually damage the paints.  However, the spot test at 90 °C for 24 h using a chamber dew
containing various organic and inorganic acids causes blistering and cracking of the top coat. EDS
data provide evidence that the acidic dew can penetrate through the top coat into the base coat.
Further studies are underway in an attempt to understand the mechanism of the attack.

REFERENCES
1. D. J. McEwen, M.H. Verma and R.O. Turner, "Accelerated Weathering of Automotive Paints
Measured by Gloss and Infrared Spectroscopy", J. Coat. Tech.. 59f755V 123 (1987).
2. T.C. Simson and P.J. Moran, The Johns Hopkins University, Baltimore, MD, personal
                                         138

-------
communication, 1990.
3. J. White and W. Rothschild/'Defects in the Finish of Motor Cars." Metal Finishing. 85(5), 15
(1987).
4.  G.G. Campbell, G.G. Schurr and D.E. Slawikowski, "A Study to Evaluate Techniques of
Assessing Air Pollution Damage to Paints,"  EPA-R3-73-040, U.S.Environmental  Protection
Agency, Research Triangle Park, 1972.
5.   G.T Wolff, W.R. Rodgers,  D.C.  Collins,  M.H. Verma and C.A. Wong,"Spotting of
Automotive Finishes from the Interactions Between Dry Deposition of Crustal Material and Wet
Deposition of Sulfate," J.Air Waste Manage. Assoc.. 40(12), 1638 (1990).
6.  H.H.G. Jellinek,  F. Flajsman and F.J. Krymn,"Reaction of SC«2 and NC>2 with Polymers,"
LAppl. Polvtn. Sci..  13, 107 (1969).
7.  S.S. Sankar, D.Patil, R. Schadt, R.E. Fomes and R.D. Gilbert,"Environmental  Effects on
Latex Paint Coatings. H: CP/MAS 13C-NMR and XPS Investigations of Structural Changes in the
Base Polymer," J. Appl. Polvm. Sci..41. 1251  (1990).
8.  D.F. White,"Investigations of Techniques to Assess Physical Damage to Polymeric Automotive
Coatings on Metals by Acidic Deposition," M.S. Thesis, North Carolina State University, (1992).

DISCLAIMER
      This paper has been reviewed in accordance  with  the U.S. Environmental  Protection
Agency's peer and administrative policy for publication. Mention of trade names of commercial
products does not constitute  endorsement or recommendation for use.
Figure 1.
                  Horizontal Distance
                           (b)
Paint#7, spot tested with chamber dew #91-3,90 °C, 24h.
a. Optical micrograph        b. Surface profile of the damage
                                          139

-------
                                              1 mm



+-»
"S "
-o •


i

V^\)



\
1
•


(£



\J
V
I)


,A
/ i
' A
i e£
\ /





•
                               Horizontal Distance (Jim)
                                         (b)

Figure 2.     Paint #7B, one week chamber exposed and spot tested with chamber dew #91-3,
             90 °C, 24 h.
             a. Optical micrograph             b. Surface profile of the damage.
.

"i

1
j
K^*«i

1
in. *««
>X^>»_^J
4- 0 MA «.-,. II .r» k*v it li» -»
                          (a)

Figure 3.     EDS spectra of Paint #1B, one week chamber exposed and spot test with chamber
             dew #91-3.9()0C, 24 h
             a. EDS spectrum of the dew exposed area
             b. EDS spectrum of the unexposed area
                                          140

-------
    PHYSICAL DAMAGE FORMATION ON AUTOMOTIVE
      FINISHES DUE TO ACIDIC REAGENT EXPOSURE
                      Douglas White, Raymond Fornes
                     Richard Gilbert, J. Alexander Speer
                         North Carolina State University
                                  Box 8202
                       Raleigh, North Carolina 27695-8202

                                John Spence
                  United State Environmental Protection Agency
             Atmospheric Research and Exposure Assessment Laboratory
                   Research Triangle Park, North Carolina 27711
ABSTRACT
    Several types of automotive finishes with clear coatings were exposed to drops of acidic
reagents at 54 C. Surface damage was examined using visual observations, reflection opti-
cal  microscopy, SEM, EDS, and  profilometry. Reflection  microscopy was  the most useful
technique for  observing surface  damage.  Scanning electron microscopy  provided sulfur
mappings through the use of an EDS attachment.
    A chamber dew with pH level of 3.4 created in a smog chamber designed to simulate real
environmental conditions was highly detrimental to the finishes with damage concentrated
in a ring with a diameter less than the original drop size. The form of this damage suggests
a. free energy minimization process favoring a concentration of the damaging reagent at
the edge of the evaporating drop  where stable nuclei are thought to form. Continued heat-
ing of the samples after the drop  evaporation resulted in damage that increased with time,
with most of the visual damage located underneath material deposited from the evaporated
drop.

INTRODUCTION
    Environmental damage to  automobile paints has been observed recently. This damage
if generally in the form of circular, elliptical, or irregular spots that cannot be removed by
Cashing1. The major automotive manufacturers in the U. S. and other countries have some
concern regarding the effects of  acidic pollutants on automotive paints2.  It is suggested
that newer automotive  paint formulations which contain  unpigmented surface clear coats
are highly susceptible to acidic pollutant caused damage3.
    Our studies have attempted to reproduce this type of damage through exposing several
types of automotive paints to a variety of acidic  reagents with the objective of obtaining a
                                     141

-------
better understanding of the paint degradation process. We also were interested in evaluating
techniques to assess the paint's surface damage.  Such information would be helpful in
formulating paints that are more resistive to acid precipitation.
    J. White and W.  Rothschild linked acidic deposition/acidic pollutants to automotive
paint damage3. They observed spotting and in some cases pitting in locations on automobile
paint surfaces when vehicles were exposed in the field in Israel. They were able to reproduce
the color changes of the field exposed paints by spotting the specimens with either nitric
or sulfuric acid.
    The natural environment is very complex and it is difficult to  isolate the effects of
acidic pollutants from other variables for field exposed paints. It is also difficult to deter-
mine which  techniques and parameters are optimum for determining the damage levels of
paints after exposure. Here we extend the  spotting type tests done  by White and Roth-
schild and others by using acidic reagents that closely resemble environmentally produced
precipitation.  In an environmental research chamber at North Carolina State University,
it is possible to prepare complex mixtures of acid dew  of varying composition, which are
representative of dews formed in real atmospheres. The composition  of these dews can be
easily controlled making them useful for the damage analysis of paints.  Several types of
automotive paints  with clear coatings were exposed to these chamber dews and a variety
of other acidic solutions. In the study reported here, emphasis was on characterizing the
physical surface damage and proposing a possible model for the damage process.

EXPERIMENTAL METHODS
Paint Samples Studied
    Several types of paint samples on sheet metal substrates were supplied by an automo-
tive paint manufacturer. All samples were 10 cm by 15 cm with a total thickness (substrate
plus paint) of about 0.84 mm.  The  paints were the same except for differing clear coat
compositions.  Based  on information provided by the company, the  most likely composi-
tions were determined. All  the paints had a black pigmented base coat which consisted of
an hydroxyl-containing acrylic resin crosslinked with melamine formaldehyde.

Exposure Procedures
    The paint samples were first washed with deionized water and then buffed lightly with a
chamois before heating in order to remove dust from the surfaces of the sample. Then three
30 /iL drops of a pH 3.4 chamber dew produced  in a smog chamber designed to reproduce
real environmental conditions were pippetted onto the surface of the  plate equal distances
apart. Unless otherwise indicated, the plates were then placed into an oven and heated at
54 C for 50  minutes.  After exposure, the plates were removed from the oven, allowed to
cool, and then rinsed with deionized water and hand buffed immediately to remove surface
deposits.

RESULTS AND DISCUSSION
    The exposure  method used  in this study simulates the outdoor damage  process of
                                        142

-------
automobile paints due to exposure to precipitation followed by heating from the sun. Tem-
peratures during outdoor exposure  can  commonly  exceed 90 C1.  In these experiments,
exposures at 54 C for 50 minutes were used in order to observe damage level* under mod-
erate exposure conditions. A spot type teat was used to simulate the damage process that
occurs after rain or dew exposure to  automobile paints. Beading of water on the paint sur-
face occurs during the drying process after rain or dew exposure which forms drops on the
paint  surface. The exposure of the paints to reagent drops in the spot test simulates this
type of exposure and this type of test also permits  comparisons with adjacent unexposed
areas  of the paint.

Reflectance Microscopy Observations
   Ring shaped blistering damage was observed on all the paint surfaces. Figure 1 is  of
a paint surface with a clear coat  having an hydroxyl containing acrylic resin crosslinked
with diisocyanates and melamine formaldehyde.  The dear coat appears to be separating
into layers, and fracturing of the ring can  be observed. This is a result of the dew being
absorbed into the paint coating followed by the dew  reacting with the paint surface. As
the dew reacts with the clear coat,  the elasticity of the paint coating decreases resulting
in splitting of the  surface.  The  ring shaped form  of the damage suggests a free  energy
minimization process favoring a concentration of the damaging reagent at  the edge of the
evaporating drop. This process will be discussed in  a separate section of this paper.
Scanning Electron Microscopy Observations
    Scanning Electron Microscopy permitted the obtaining of qualitative sulfur concentra-
tions on the surface of the damaged areas through X-ray compositional sulfur mapping.
Damage to a paint with a clear coat composed of an acrylic resin containing hydroxyl
groups, modified with a polyester resin and  crosslinked with melamine formaldehyde ob-
served  using SEM is shown in Figure 2. To the left is a sulfur mapping of the damaged area.
The lighter a particular part of the map, the higher the concentration of sulfur (probably
in the form of SOj~ } in that particular part of the damage area. On the right is an image
of the damaged area. The part of the image indicated by arrows is not a damaged area, but
is a scratch identification mark. Deposition of sulfur is generally located in a central area.
These samples were rinsed and  buffed after exposure, so either the sulfur had chemically
combined with the paint, or  was in some other form resistant to buffing.

Profllometry Observations
    Profilometry was also used to assess damage levels. This technique can give quantitative
comparison of damage amounts between samples since it measures the actual sice (width,
height, or depth) of the damaged areas. Unfortunately, due to the unevenness of the paint
coatings, the background noise was high which limited the precision and usefulness of this
technique for studying the samples.  Figure 3 shows a profile of damage formed on a paint
                                        143

-------
         Figure 1   Chamber Dew #7 Damage - Paint #2
                   50 Minute Exposure at 54 C
         Figure 2   Chamber I)<-w //6 Damage   1'aint $7
                   50  Minute Exposure at 54 C
        (EDS Sulfur map on left; Photomicrograph on right)
(Arrows indicate scratch marks for identification of damage location).
                              144

-------
with a clear coat having an acrylic resin containing hydroxyl groups and crosslinked with
diisocyanates. A crater shaped blister was formed with wall heights up to 0.6 micrometers.
              Figure 3   Profile of Chamber Dew #7 Damage -  Paint #4
                             50 Minute Exposure at 54 C
    Results from inspection of the profilometer analysis and photomicrographs of the ex-
posed paints indicate that the damage areas are not necessarily etches as would be expected
from acid attack. What seems to be occurring is instead a separation of the clear coat into
layers. The acidic dews at elevated temperatures generally form an uplifted crater on the
paints. The center of the crater is approximately the same height as the rest of the paint.
However, the sides of the crater are higher than  the  rest of the paint.

Chamber Dew Evaporation  Process on Paint  Surface
    Visual observations of the evaporation process of the chamber dews on the paint surfaces
show  that no change of the clear coat surfaces of the paints tested occurs until a critical
drop  size is reached.  At this critical size, deposition of material from the drop begins
and continues until the drop has completely evaporated. After this evaporation, an area of
deposition can be observed which is much smaller than the initial drop size with  the highest
levels of deposits located in a circular ring.  After washing  and buffing,  a circular ring of
damage is observed which is located at the same places on the surface where deposits were
formed.
    Deposition of material from  the reagent drop occurs only after the drop reaches a criti-
cal size or concentration. Once this concentration is reached, precipitation occurs, resulting
in material being  deposited on  the paint  surface with the highest levels occurring at the
edge of the drop.  This location appears to be the most favorable for the creation of nu-
cleating  centers  of the depositing material to form.  Favorable locations for nucleation  in
solutions occur at the surface  of solutions (the drop  surface  in our case), or at the walls of
the vessel containing the solution (the drop-paint interface  in our case)1. These locations
                                         145

-------
are favorable because the inteifacial free energy of a nucleating center is lowered in these
locations.  A nucleus located at the edge of the drop exists at both favorable locations
simultaneously, resulting in a further decrease in the free energy of formation compared
with either location alone or the interior of the solution.

CONCLUSIONS
    The results from these investigations indicate that acid deposition causes considerable
damage to automotive coatings with clear coat surfaces. The chamber dews formed uplifted
craters on the paints. The center of the crater is approximately the same height as the rest
of the paint, but the walls are higher. The visual damage on the paint surface appeared to
occur as a result of the interaction at elevated temperature between the deposited material
from the evaporated drop and the clear coat surface with the damage levels on  the paint
surface increasing as the time of heating increased. The ring shaped damage produced by
the dews appeared to be a result  of a nucleation process which favored the deposition of
the damage producing material at the edge of the evaporating drop.
    Reflection microscopy, scanning electron microscopy, and pronlometry were found to
be useful techniques to evaluate the damage on the paint surfaces. Reflection microscopy
and pronlometry were helpful in determining the physical structure of the damage to the
paint surface. Scanning electron microscopy was most useful for obtaining sulfur mapping
of the paint surfaces through the use of an EDS attachment to the SEM.

REFERENCES
1. G. T. Wolff, W.  R. Rodgers, D. C. Collins,  M. H. Verma, and C. A. Wong, "Spotting
of Automotive Finishes from the Interactions Between Dry Deposition of Crustal Material
and Wet Deposition of Sulfate," J. Air Waste Manage. Assoc. 40(12): 1638-1648(1990).
2. T. C. Simpson and P. J. Moran, The John Hopkins University, Baltimore, MD, personal
communication, 1990.
3. J. White and W. Rothschild, "Defects in the Finish of Motor Cars," Metal  Finishing
85(5): 15-18 (1987).
4. D. Elwell and H. J. Schell, Crystal Growth from High-Temperature Solutions, Academic
Press, London, 1975, p.100.

DISCLAIMER
    This  paper has been reviewed in accordance with the U. S. Environmental  Protec-
tion Agency's peer and administrative policy for publication.  Mention of trade names of
commercial products does not constitute endorsement or recommendation for use.
                                        146

-------
        Diffusivity, and  Chemical  Reactivity of  Sulfur

                     Dioxide with an  Alkyd  Paint
 W. H. Simendinger and C. M. Balik, Department of Materials Science and Engineering, Box
 7907, North Carolina State University, Raleigh, NC. 27695

 ABSTRACT
   Sorption-desorption studies were conducted with a representative alkyd paint using sulfur
 dioxide as the penetrant gas. During the course of the investigation evidence of a chemical reaction
 was noted. DSC sol-gel analysis, and FTIR studies were conducted to determine the nature and
 site of the chemical reaction. Results showed that the SO2 reacts with the drying oils and competes
 with the normal auto-oxidative curing  mechanism responsible for crosslinking the binder. A
 gravimetric technique was used to measure the chemical reaction rate of the drying oils and the
 SO2, from this data the reaction rate constant for the system was determined.
 INTRODUCTION
   The formulation and  application of paint  coatings to protect man made structures is a
 multibillion dollar per year industry. Consequently, significant economic losses could result if
 increased levels  of atmospheric $62 appreciably shortened the lifetime of a paint coating.
 Additionally, the  underlying substrate  may be damaged by the corrosive nature of the gas,
 especially in combination with water.1'3  Determination of the rates at which SO2 diffuses through
 paints, its equilibrium solubility in the paint, and whether it reacts with any component of the paint,
 are important fundamental issues relating to this problem.
   Previous work conducted by other members of this group on latex paints that have  a similar
 composition of fillers and extenders (i.e. Ca(X>3, TiO2, and mineral clay) has shown that the fillers
 act simply as  impenetrable barriers around which the penetrant gas must diffuse4. Other studies
 using aqueous SO2 systems determined that the aqueous solution tends to leach the CaCOj from
 the polymer binder. Leaching of the CaCO3 occurs relatively quickly and accelerates as the pH is
 reduced.
   Holbrow has exposed alkyd paints to atmospheric levels of pollutant gases in industrial and
 suburban sites.5 He noted that exposure to SOj can cause  delays in drying (curing) time due to the
 reaction of S02 with certain drying oils.  He also noted the formation of crystalline blooms due to
 attack on pigments when SO2 is incorporated with water5.
   Reactions  of the drying oils were studied by Wexler. He determined that the mechanism for
 crosslinking of the drying oils occurs via an  auto-oxidation reaction involving the formation of
 hydroperpxides at the allylic hydrogen adjacent to the double bond of the oils6. In this study drying
 oils consisting of oleic acid, linoleic acid, and linolenic acid were examined.
   Sorntion  Measurement A gravimetric technique was employed to measure the sorption-
 dcsorption characteristics of SO2 in the alkyd films. This was accomplished by the use of a Cahn
 2000 electrobalance, which was contained inside a glass vacuum system. Data was  transferred
 from the electrobalance  to a computer for  manipulation and storage.
   DSC Measurements.  A Perkin Elmer differential scanning calorimeter was used to record
 the thermal behavior of the samples. Samples were scanned over the temperature range of 300-500
 K using a heating rate of 10°C/min.
   Sol-Get Studi^. Samples of the alkyd  film were weighed  and  placed in acetone for 24
hours to remove any uncrosslinked organic material. The solution was then washed and filtered
and the remaining material was weighed to determine the amount of crosslinked material present in
the sample.
   FTIR Studies. FTIR spectra of the fatty acids were obtained by smearing the liquid acids on
a sodium chloride crystal and collecting the spectra in transmission mode. Samples were exposed
to S02 by placing the neat liquid in a vacuum chamber and backfilling the chamber with the gas.
Unexposed samples were taken directly from the bottle and placed in the FTIR.
                                         147

-------
  SO2  Diffusion
    Sorption — desorption studies were initially conducted using a series of pressures ranging from
 100 to 700 ton of SO2. The samples were first exposed at 100 torr and the pressure was raised in
 increments of 100 ton, until 700 torr was reached. Typical sorption-desorption kinetics curves for
 a sample exposed to 501.4 torr of SO2 can be seen in Figure 1. The data has been plotted as total
 mass uptake vs. the square root of time.
    From Figure 1, several important pieces of information are obtained. First, the initial linearity
 of the curve shows that the diffusion behavior at this pressure is Fickian in nature.  From the
 plateau region, the equilibrium concentration of S02 for the experimental pressure and temperature
 can be obtained. It can be also noted that the plateau value for the desoiption curve is slightly lower
 than that of the sorption curve. This occurs because a fraction of the SO2 reacts chemically with the
 alkyd film, and consequently does not diffuse out of the film. This fraction has been termed the
 "residual" and will be discussed below in more detail . Finally, the diffusion coefficient can be
 calculated from the slope of the initial linear part of the curve, using  the following equation for
 diffusion into thin films at short times
where Mt is the amount of gas sorbed or desorbed at time t and M^ is the maximum amount sorbed
or desorbed. D is the diffusion coefficient, 1 is the film thickness, and t is time7. Figure 2 is a plot
of the average of the sorption and desorption diffusion coefficients versus pressure, from this D0
was found to be 7.2x1 0"9 cm2/sec.
S02  Reactivity
    The sorption-desorption experiments confirmed the presence of residual amounts of SC<2 in the
alkyd films. A second series of experiments were conducted to confirm that the SO2 was reacting
with the binder material. These experiments included DSC, sol-gel analysis, FTTR and low
pressure sorption experiments.
    Differential scanning calorimetry was conducted on the same types of samples used in Figure
1, which provided further evidence of a chemical reaction with SC>2. Figure 3 is a DSC plot of two
alkyd samples cured at 25°C, however, one sample has been exposed to SO2 at 760 torr prior to
being placed in the DSC, and  the other sample has had no exposure to the gas. The exothermic
peak in Figure 3 can be associated with the crosslinking reaction that occurs in the sample not pre-
exposed to SO2. Consequently, the absence of this peak in the sample exposed to S02 indicates
that the reaction is not occurring during the DSC scan. Second scans revealed no exothcrms for all
samples, indicating that the chemical reaction had gone to completion in the DSC.
    The reduction in the magnitude of this exotherm can be attributed to SO2 reacting with the
binder, and either promoting or preventing the crosslinking reaction.  In either case, a reduction in
the exotherm would be expected  Sol-gel analysis was carried out on fresh samples that  were
treated in the same way to determine if exposure to S02 caused an increase in the degree of
crosslinking.
    For the sol-gel studies, samples were cured at 25, 100, and 150°C and then exposed to either
vacuum, air, or SO2 for a period of 24 hours. Results of the sol-gel analysis (see Table 1) showed
that samples exposed to vacuum had  a much lower degree of crosslinking, indicating that the
absence of oxygen prevented the crosslinking reaction from occurring. However samples exposed
to air or SO2 had about the same degree of crosslinking. Curing temperature did affect the degree
of crosslinking in the samples  exposed to vacuum, but its effect was not as prevalent in samples
that were exposed to SO2 or air. These results showed that the SO2 was indeed crosslinking the
polymer binder.
    Since two different kinetic processes (diffusion and chemical reaction) are occurring during the
sorption of SO2 into these samples, one would expect to see a deviation from Fickian diffusion in
the  sorption kinetics (e.g. Figure 1). However, at sufficiently high SO2 pressures, the chemical
                                          148

-------
reaction rate would be high, due to the (relatively) high concentration of SO2 in the polymer.
Thus, diffusion is the rate-limiting step in the overall sorption kinetics, and analysis of this data
based on Fickian kinetics is entirely acceptable.  Conversely, at low pressures, the chemical
reaction rate slows to the point where its rate becomes comparable to diffusion, and deviations
from ideal Fickian behavior can be seen. Figure 4  shows two low pressure sorption  runs
conducted at 5 and 10 torr.  These curves show an initial rapid uptake region (essentially Fickian
diffusion), followed by a protracted region where the sorption kinetics are appreciably slower.
This latter pan of the curve is probably indicative of the kinetics of the chemical reaction between
the paint and S02. The plateau region of these curves  is never reached in the time scale of the
experiment  Given an extended period of time, the SC>2 would eventually  react with all of the
available sites in the binder and the sorption curves would reach their solubility limits. The lowest
SO2 pressure at which no significant deviation from Fickian behavior occurred was approximately
40 torr.
    The components  of the binder material were examined to determine a  possible site for the
chemical reaction. The alkyd binder contains phthalic anhydride, a polyfunctional alcohol, and
soya (also referred to as a drying oil) as its main components. The possibility of a reaction between
SO2 and the anhydride/acid/polyol functional groups was eliminated because this reaction occurs
when the binder i& manufactured. Soya contains a series of saturated and unsaturated fatty acids.
The unsaturated fatty acids arc most likely to react with S02; these include oleic, linoleic, and
linolenic acid. These acids all consist of a straight chain of eighteen carbon atoms with a carboxylic
acid group at one end. They differ primarily in  the number of double bonds they contain; oleic
linoleic and linolenic acid having 1,2, and 3 double bonds respectively. Previous work has shown
that a reaction between the SO2 and the drying oils is possible; these were considered to be the site
of the S02 reaction5.
    The possibility of SO2 reacting with these acids results from the extended period over which
drying (crosslinking) of the acids occurs. The samples were exposed to SO2 after drying and
curing (requiring a total of 48 hours). Typical drying times range from 8 to 15 hours in the
presence of a drier catalyst, or up to 4 or 5-days without a catalyst.* Due to the length of these
drying times it is quite possible that sites for chemical reaction with SO2 arc available even after the
paint film has been cured for 48 hours.
    Crosslinking of the drying oils in the presence of oxygen occurs via an auto-oxidative reaction
by the formation of a hydroperoxide at the allylic hydrogen.8 The presence of the neighboring
double bond activates this hydrogen and facilitates  the reaction. Consequently, we think these
allylic hydrogens are the most probable site for the SC^ reaction. Crosslinking of adjacent  acid
molecules could occur via a reaction similar to sulfur vulcanization of rubber. The SO2may also
react with a hydroperoxide to form a sulfate ester, which may then react  again to form an -OSO3-
bridge.
    Sol-gel studies tend to favor the first reaction (resulting  in an -SO2- bridge) because the
polymer gel fraction still increases when exposed to SC^ in the absence of oxygen (see Table 1). In
this case, there would be no additional hydroperoxide groups available for formation of a sulfate
ester. The lack of formation of significant amounts of hydroperoxide groups while under vacuum
is indicated  by the low gel fractions in Table 2 for unexposed samples  (at 25 and 100°C).
Preliminary infrared studies indicate the presence of sulfur-oxygen compounds, however, the exact
structure has yet to be determined Yet another reaction could be copolymerization of S02 with the
double bonds in the acids. Copolymerization of SO2 with alkenes has been reported.9
   Samples of oleic, linoleic, and linolenic acid were obtained to study the nature of the chemical
reaction, and to determine the chemical reaction rate. A gravimetric technique was employed to
measure the chemical reaction rate. However mis technique was complicated by the fact that the
samples are liquids, and the experimental equipment is designed for measuring sorption  in solid
films. This problem was overcome by dispersing a measured amount of the drying oil into a latex
tcrpolymer of butyl acrylate, vinyl acetate, and vinyl chloride.  This particular latex was selected
because previous work showed no chemical reaction between the latex and SC^.The suspension
                                          149

-------
 was  then  cast on glass and allowed to dry as a film. The films were then placed  in the
 electrobalance and sorption studies were conducted to measure the reaction rate. Figure 5 is a
 sorption curve for linolenic acid in latex which amply demonstrates diffusion of SO2 into the film
 followed by gas uptake due to chemical reaction. Figure 6 shows the chemical reaction portion of
 the curve only. We propose the following reaction rate mechanism:

                        Reaction Sites  +  SO2 —>  Crosslinked Polymer              (2)
 and the rate follows as:
                        Rate = k [sites]  [SOJ                                         (3)

 where k is the reaction rate constant and the reaction sites are the allylic hydrogens. If we assume
 that the concentration of SO2 does not change because as SO2 is consumed more will diffuse into
 the film from the surroundings, and only  the number of sites decreases as the reaction proceeds,
 then we obtain pseudo-first order reaction kinetics. The solution for this is expressed in  equation
 4.
                        Cl = C0(l-exp(-kCdt))                                       (4)

 where Q is the amount of SO2 reacted at time t, C0 is the SO2 saturation value for the reaction, Cd
 is the concentration of SO2 in the film due to diffusion, t is time, and k is the reaction rate constant
 normalized for SO2 concentration. Using numerical regression on the data in figure 8 k and C0
 were determine to be 6.922 x 1O5 (mol acid/mol SO2-sec) and 0.0341 (mol SO2/mol  acid),
 respectively, the solid line is the numerical regression fit to the data.
    DSC studies were conducted  on the latex/linolcnic acid films. Figure 7 shows samples that
 have  been and have  not been exposed to SO2. Again, as with the paint films,  there is a large
 exothermic peak for the sample that has not been exposed to SO2 indicating the thermal promotion
 of the auto-oxidative reaction in  the DSC. The sample exposed to S02 displayed no exothenn
 which implies that the SO2 had reacted with the allylic hydrogen responsible for the auto-oxidative
 reaction.
    Pure linolenic acid samples exposed to SO2 and unexposed were studied using FTIR.  Figure 8
 is the spectrum for the unexposed sample and figure 9 is the exposed sample. There are two main
 features in these spectra, the first being  the  new peak at 967 cnr1  and the second being the
 reduction in the magnitude of the peak at 722 cm-1. The peak at 967 cm'1 corresponds  to the
 presence of a trans conformation about  the double bond  of the molecule. Likewise the reduction of
 the peak at 722 cm*1 can be attributed to the reduction in concentration of the cis  structure.These
 results are important because changes from  the cis to trans structure may occur during the auto-
 oxidation process, and indicate a chemical reaction involving the allylic hydrogen8. Several other
 new peaks occur at 483, 539, 1170, 3619,and 3693 cm-1. These peaks can be associated with
 various sulfur oxygen compounds. The exact structure  of the sulfur-oxygen bridge has not been
 determined, but the FTIR data docs provide evidence of a chemical reaction. The presence of cis
 and trans bonds indicates the double bond is still intact after exposure, suggesting that  the SOj
 does not react with the double bond but is reacting at the allylic hydrogen.
    These experiments provide strong evidence for the chemical reaction between SO2 and the
drying oils. NMR experiments are currently being conducted with the individual fatty  acids to
determine the exact site and nature of this reaction. Reaction rate studies are also underway with
oleic acid and linoleic acid to determine their reaction rate constants
SUMMARY
    From the data obtained it was determined that the overall sorption kinetics of the alkyd/SOj
system is Fickian in nature at higher S02  pressures, (40-700 torr) but tends to deviate from this
behavior at lower pressures. The diffusion coefficient is  exponentially dependent on pressure, and
has  a limiting  (zero-pressure) value of 7.2 x 10'9 cm2/sec. A residual amount of S02 in the film is
the result of a chemical reaction in which SO2 crosslinks the polymer, competing with the normal
                                          150

-------
auto-oxidative crosslinking mechanism.  DSC analysis, low pressure sorption kinetics data, sol-gel
studies, and FTIR provided additional evidence for this chemical reaction. Using a gravimetric
technique the reaction rate for linolenic acid and SO2 was measured and found to be 6.022x10'5
(mol acid/mol SO2-sec).
   The authors gratefully acknowledge the support of this work by the U.S. Environmental
Protection Agency through Cooperative Agreement #CR-814166-01-0.
REFERENCES
1) J.W. Spence and F.H. Haynie, /. Paint Tech.,44, No. 574, (Nov. 1972).
2) J.W. Spence, F.H. Haynie, and J.B. Upham, /. Paint Tech., 47, No. 609, (Oct 1975)
3) G.G. Campbell, G.G. Schurr, D.E. Slawikowski, and J. W. Spence, /. Paint
Tech., 46, No. 593, (June 1974)
4) B.J. Hendricks and C.M. Balik, /. Appl. Polym, Sci., 40, 953-961 (1990).
5) G.L. Holbrow, /. Oil Colour Chem. Assoc., 45 No. 11, 701-718 (1962).
6) H. Wexler, Chem. Rev., 64 No.6, 591-598 (1964).
7) J. Crank and G.S. Park, Eds., Diffusion in Polymers, Academic, New York, 1968
8) Oil and Colour Chemists' Association, Australia, Surface Coatings, Vol I Raw Materials and
Their Usage, Tafe Educational Books, NSW, Australia, 1974
9) Zbigniew Florjancyk, Ewa Zygado, and Dorota Raducha, Macromolecules, 23,2901-2904
(1990).
      Table 1
      Sol-Gel Analysis
Cure     Exposure
Temp. °C
25
25
25
100
100
100
150
150
150
Environmejil
air
vacuum
S02
air
vacuum
SO2
air
vacuum
S02
Gel Fraction
0.747
0.262
0.707
0.754
0.279
0.716
0.806
0.717
0.763
Figure 1
    Sorpiion Daorption Cnrvri for SO; in Alkvd
          Piinl 11 Stl.i icrr SO2 "
Figure 2
          Dirtmiiiiy of SO; in Altvd Piinl vi. Pretlurr
                                        Figure3
                                                            :oo      'oo     too     tut

                                                                 pressure florr h
     DSC Suns of Alkjd r.lnl nimi E.powd in SO,
               •nri Uneip0s«d
                                         151

-------
Figure 4
      S«rpnotl Curv.i  |.r  SO. If
                im It Terr SO.
    Figure 5

     Sorpiion  Curve;  20% Linolenic acid in  Lalex
                      20 Ton- SO2
                                                     :

                                                            0-t-
                                                          0.00  10*    1.75 10*   3 50 10*   525  10*   7.00  10*
                                                                            •limt  (src)
Figure 6
  Figure 7
          Reaction Curve Linolenic  Acid and  SO
    0 03S
'=   0016
      0.00 10    1.50 10    3,00 10   450 10    600 10s  •• i-fs	,-;	—
Figure8
Figure 9
                                                                                 .. ?«• l_, 10,
                                                  152

-------
MONITORING THE EFFECTS OF BUILDING - INFLUENCED MICROCLIMATE VARIATION ON THE DRY
DEPOSITION OF SULFUR DIOXIDE

Donald A. Dolske. Office  of Air Quality. Illinois State Water Survey, 2204 Griffith Drive. Champaign,  Illinois
61820.

                                             ABSTRACT

The urban setting of the historic Philadelphia Merchants' Exchange (built 1830s) has resulted in varying degrees
of surface erosion, discoloration, gypsum crust development, and loss of marble Integrity at various locations around
the building.  The complex microclimate of the building presents a variety of environmental exposures.  These
exposures, In turn, significantly affect the rate of dry deposition of pollutants, especially sulfur dioxide. This study
had a primary objective of examining deposition processes which may Impact marble deterioration.  The approach
was to coordinate monitoring of a) the diurnal of wetting and drying cycles (which are known to occur In different
patterns on selected parts of the building) and b) the airborne concentrations of sulfur dioxide In the vicinity of the
building.  A surface and near-surface microclimate sensor array controlled a constant-flow air sampling system, to
collect air samples segregated on the basis of  surface moisture conditions.  The monitoring methods developed
in this work may also be applicable to case studies of dry deposition of water-soluble pollutants to any surface
exposed to the environment.

INTRODUCTION

The marble weathering at the Merchants Exchange differs significantly between the facades of the building (McGee.
1992; Coe, et al., 1992). It has been observed (Camuffo. et al., 1982) that deterioration of stone building exteriors
occur by different processes and at greatly differing rates on various parts of a building.  An in situ pollutant and
microclimate monitoring system was installed in early 1988 to evaluate the exposure parameters for comparison
with independent measures of marble deterioration.   The general physical and chemical processes of marble
weathering and deterioration  are relatively well-known (Amarosso and Fasslna, 1983) performance of stone in a
building facade is far more complex and Is affected by highly variable pollutant deposition patterns.  The design
of an  individual building, neighboring structures, and location within a city are all important determinants of the
facade's exposure (Sherwood, et al.. 1990).  The ambient range of meteorological conditions places limits on the
conditions a building facade might experience over time.  However, within those limits, variations  in the magnitude
and timing of temperature, insolation, moisture, and other environmental cycles can be large enough to significantly
affect pollutant deposition.  Subsequently, facade deterioration may show great variability In rate and differences
in process.  Therefore, understanding  the microclimate of the Merchants Exchange must be a key element in
formulating management of the historic fabric represented by the building facade.  The principal objective of this
research has been to monitor the impact of a possible correlation between the diurnal timing of wetting and drying
cycles and the also temporally-varying  airborne concentrations in the vicinity of the building.

This principal aspect of the ongoing research, i.e., microclimate - deposition interaction, provides a description of
how pollutant deposition and moisture cycling varies from point to point on a single building. A  second series of
measurements Is also ongoing, In which the soluble surface deposits have been sampled  as a function of location
on columns near the pollutant deposition monitoring sites. These surface samples were collected at several sites
on the building, selected with reference to direct exposure to rain and differences in visible surface accumulation
and discoloration.   In  addition, continuous measurements are made of ambient meteorological conditions,
precipitation amount and chemical composition.

Mlcrometeorologlcal Measurements

Pollutant and microclimate Instrumentation are  attached to two columns on the north and south sides of the semi-
circular colonnade on the east facade, approximately 12.5 m above the ground (Figure 1).  Identical  arrays of
microclimate sensors are glued to each of the marble column shafts about 2.7 m below the cornice, Including:
visible solar radiation Intensity (silicon pyranometer), stone surface temperature (copper-constantan thermocouple),
and stone surface wetness (bi-metallic grid  painted with a salt-laced white latex). Instruments are mounted about
20 cm radially away from the column  at the same level to monitor air temperature (thermistor probe), relative
humidity  (capacitance sensors), and horizontal wind velocity (magnetic reed closure cup anemometer).  A digital
datalogger scans all sensors every 10 seconds, computing and storing the mean values on magnetic tape once
                                                  153

-------
 each hour.  The  stone  surface wetness sensors and  datalogger control the switching  of pollutant samplers
 described below through a solid-state relay system and solenoid valves In the air sampling Intake line.
     Air inlel
  Windspeed-0
Temperature/
humidity IRH)
                                NORTH
                               COLUMN
  Surdce itmpenlore
       wetness.
     solar ndnnon
                                                               /    J      V
                                                                           INLET
                                                                           IUM
tr*lure. /    I—jf
i
                                                                       TO
                                                                       FLOW
                                                                    CONTROLLED    COWIROLLEO
                                                                      VACUUM
                                                                      SOURCE
 Figure 1.  Instrumentation used  in monitoring  building microclimate and  pollutant exposure conditions at the
 Merchants' Exchange, Philadelphia, PA.

 A set of meteorological sensors is installed atop a mast on the roof of the building.  Air temperature, relative
 humidity, wind direction and velocity, and rainfall rate are measured continuously. The meteorological data provide
 a general characterization of conditions at the site, relatively unaffected by the building itself. Also, a wet-only semi-
 automatic precipitation sampler (Vermette and  Drake, 1988) is located on the roof.   Samples are collected tor
 individual rain events.  Volume, pH and major ionic species (including SO4", NO,', Cl",  NH,*, Ca~, Mg**, Na*. and
 K') are determined by ion chromatography for all precipitation samples  with sufficient volume. Exposure to rain
 exhibits significant variation, because of sheltering by architectural features and a strong dependence of rain volume
 on wind  direction as shown in Figure 2 (Dugan  and Dolske, 1991).
               Total Volume, mL
                                                Hydrogen ion,  mg/L
Figure 2.  Rain volume and rain pH measured at the Merchants' Exchange by wind direction
                                                  154

-------
    Selected microclimate measurements shown in Figures 3 (summer) and 4 (winter) illustrate the overall seasonal
    trends and differences within the building facade.  The difference between air and stone surface temperature is
    greatest for the north side in the summer, as compared with the south, where the maxima is in mid-winter. These
    differences relate to the seasonal pattern of solar radiation input to vertical walls.  The stone surface Is cooler than
    the air more frequently on the north side than the south, where the temperature differences are much greater and
    more variable. The stone surface moisture data indicate that in general the south side tends to be somewhat wetter
    than the north side.  There is also a seasonally to the wetness.  The largest differences between south and north
    occur in the autumn, while In the winter and spring, there is little difference. It is apparent that surface temperature
    differences control the differential evaporative drying of building surfaces.
                        Midnight
                                                   a
                                                                              Midnight
                                                 S AM « PM
                        UWnlfht
«PM
                                                                              MMnlgtit
                                                 6 AM 6
                                                                                                       8 AM
                                                                                                      -South
                                                                                                      -North
    Figure 3.  Plots of the daily summer means in a) solar radiation (Wans/meter*), b) surface temperature and c)
    surface - air temperature difference (°C). and d) time of wetness (percent of total hours observed) for the period
    May through August,  1988-1091.
                                                    155

-------
                     Midnight
                                               a
                                             6 AM  6
                                                                                                   « AM
                    MMfMQrlt
                                             e AM «
                                                                                                   6AM
                                                                                                  ••out*
                                                                                             MPil -Nortli

Figure 4  Plots of the daily winter means in a) solar radiation (Watts/m*), b) surface temperature and c) surface -
air temperature difference (°C). and d) time of wetness (percent of total hours observed) for the period December
through February, 1988-1991.

Airborne Pollutant Concentrations

A four-stage series filtration, "filterpack". method is used to measure the airborne concentrations of paniculate SO4'
and NO, as well as HNO, and SOS gases (Dolske and Stensland, 1983).  Each sampler controls two filtration unite,
one of which is connected to the sampling air stream when the surface is wet; the other is in line when the surface
Is dry.  Air intake rate is controlled using electronic flow controllers (one for each column) ahead of a vacuum
pump. The flow controllers compensate for variations in pressure drop In the sampling system due to filter loading.
humidity changes, and so on,  keeping the flow rate constant (approximately 1/2 percent) at a nominal set point
of 3.0 liters / min.  The filters are mounted in 47 mm in-line polycarbonate plastic multiple - filter aerosol - sampling
                                                 156

-------
holders. Pairs of holders with quick-release fittings and flow-dividing tubing are prepared in the Illinois State Water
Survey (ISWS) laboratory to facilitate efficient handling by field site operators.  Four types of filters are used In
series within the holder, separated by polycarbonate support screens and sealed with silicons o-rings and flat
gaskets.  The first filter is an 8.0 urn pore diameter polyester membrane,  which  collects large aerosol particles
(diameter > 2.5 um), while allowing smaller particles to pass through to the second stage filter (Cahlll, et al., 1077).
The second  fitter Is a 1.0 um Teflon membrane, which retains the remaining small particles with a very high
collection efficiency. These first two stages are made of materials which are relatively unreactrve with the gaseous
pollutants. The third filter is a 1.0 um nylon membrane filter which selectively adsorbs nitric add vapor (Goldan,
et al.,  1983). The sum of paniculate nitrate from the first two filters and nitric acid from the third filter Is reported
as total ambient nitrate concentration. The fourth and last fitter is a double layer of cellulose fiber paper which is
doped with 25 percent (by  volume) glycerol In water, saturated with K,CO,.  The fitters   are dipped Into the
carbonate solution and then dried In an oven at 90°C for a few minutes before loading Into the fllterpack.  This
treated-fitter stage is used to selectively absorb sulfur dioxide (Johnson and Atkins. 1075).
                 10

                  8

                  e

                  4
     O -' south    r
     • - north
                                                                         10
                                                                               11    i*
                 25

                 20

                 16

                 10

                  5

                  O
                                                                    (b)
                                                                          10
                                                                               11    It
                                                                                          IS
             O*
             CO
28

20

15

10

 6

 0
                                                                          10    11   II    1S
                                                    MONTH
Figure 5. Pollutant concentrations at the Merchants Exchange. The trend curve plots a one-month moving average
(four-way mean ol wet and dry surface condition at both north and south column locations).
                                                  157

-------
 Each sampler controls two filterpacks, one of which is connected to the sampling air stream when the surface Is
 wat; the other Is In line when the surface is dry. Wet and dry surface conditions are defined electronically by the
 stone surface wetness sensor and then measured relative to the humidity of the air. The bi-metaJlte grid sensors
 do not respond with absolute accuracy to the moisture content of the stone; however, the presence of moisture at
 the stone surface sufficient to affect pollutant deposition should be reasonably well  represented by this surrogate
 sensing technique. Thus, for each week, two measurements of pollutant concentration are made at each location:
 a "wet* period average concentration and a "dry* period average concentration.  Using surface wetness condition
 to control collection of the pollutant concentration data allows a more accurate computation of dry deposition to the
 marbles, particularly for sulfur dioxide.  8Ot deposition rate to a wet marble surface is an order of magnitude or
 more greater than deposition to a dry surface under otherwise comparable circumstances (Spiker, et al..  1992).

 An overview of the airborne pollutant concentration data for three species: total nitrate (paniculate NO,' and HNO,),
 paniculate sulfate, and sulfur dioxide is shown in Figure 5.  The open and filled  symbols represent the mean values
 for the north and south columns, respectively, combining the wet and dry measurements at each sampling location.
 The curve traces a one-month moving average ol an overall mean value for the building. These concentration data
 illustrate that the air quality at the Merchants Exchange is typical of large American  cities, with significant week to
 week variability and some degree  of seasonaltty evident.  It is also noteworthy that there  are at times significant
 differences between concentrations measured at the two locations on the same building. Differences on the order
 of 50% or more have been observed, although side by side operation of these sampling systems result In measured
 concentrations reproducible to about 5% (Dolske and Stensland, 1983).  Thus, the observed differences are most
 likely explained by variation in pollutant exposure. The north column faces a pedestrian plaza approximately 300m
 by 100m, whereas the south column abuts Walnut Street, a busy thoroughfare and city bus  route. Recently, buses
 have been permitted to Idle on east side of the plaza, about 100m from the north column  sampling station. This
 may explain the increased tendency for the nitrate concentrations to be greater at the north sampling location in
 1991.

 DRY DEPOSITION TO MARBLE SURFACES

 Relative dry deposition velocities, v^ were derived from runoff chemistry from a Carrara  and Pennsylvania blue
 marble obelelisks at Gettysburg National Military Park. Gettysburg, PA {Dolske and Sherwood, 1992).
  Monument
Pennsylvania marble Obelisk
Carrara marble Obelisk
  concentration in runoff (mg/L):
       sulfate
       nitrate
   1.12
   0.83
                                                                           0.56
                                                                           0.61
  airborne concentrations (jig/m*)
       nitrate
       sulfate
       sulfur dioxide
   0.978
   1.389
   1.31
   0.979
   1.389
   1.31
  dry deposition velocity (cm/s):
              nitrate
  (both SO, & SO/) sulfate
  (SO, only)      sulfate
  (particle SO/)  sulfate
   0.43
   0.10
   0.15
   0.40
   0.20
   0.03
   0.05
   0.13
Table 1. Values of parameters used to estimate dry deposition velocities to Carrara and Pennsylvania Blue marble
obelisks at Gettysburg. PA.

Mean values for the various parameters used to compute the vd's are shown In Table 1. A difficulty of Interpretation
arises because sulfur In the runoff sample  occurs as sulfate, which need to be related to distinct airborne
concentrations of SO, and sulfate aerosol. Thus, three sulfur v, values are presented: the first assumes that SO,
                                                  158

-------
 and participate SO/ contribute to sulfate in the runoff, the second assumes all sulfate in runoff stems from SO, dry
 deposition, and the third assumes paniculate SO/1« the only contributor. This complexity is not present for nitrate.
 aa the airborne measurements aggregate the gas and aerosol concentrations. These results suggest that the type
 of marble strongly Influences the dry deposition of sulfata and nitrate.

 Estimated deposition to the Merchants' Exchange merMse

 Using the estimated vt values from Table 1 and the measured airborne concentrations, a suHurdry deposition flux
 to the marbles was computed for each bi-weekly air concentration measurements. The calculation assumes that
 a rain event flushes all the sultate from the marble surface; thus the flux estimates represent recent deposition of
 sutfate, not an aggregate accumulation. A fixed period between rain events (5 days) wax selected based on the
 long-term regional average to slmpllfylhe calculation of sulfate accumulation forthese preliminary estimates. Future
 calculations will be based on the actual intervals between rain.  The algorithm also assumes that the deposition
 velocity during dry surface conditions Is 10% of the vtf for wet marble, by analogy wlh laboratory determinations
 of vd tor Vermont marble and Indiana limestone (Splker. et al., 1992; Upfert. 1980). Table 2 presents the long-term
 average of the estimated sulfur deposition. The results In Table 2 demonstrate that a relatively small difference In
 wetness (see Figures 3 and 4} has a large influence the deposition of SO* with the south side receiving about 60%
 more deposition to wet surfaces than the north side.

percent time
surface wet
SO, WET
(ug/m3) DRY
marble type
v« wet
vddry
SO, Flux, wet
ng/cm1 dry
total
North Side
11.1
1.0
11.1
Carrara
0.15
0.017
7,2
71.8
79.0
Pennsylvania Blue
0.45
0.05
21.6
210.0
231.8
South Side
16.7
1.8
1Z3
Carrara
0.15
0.017
17.3
75.2
925
Pennsylvania Blue
0.45
0.05 .
51.8
222.0
273.8
Table 2.  Estimates of sulfur flux to the Merchants' Exchange marbles,

As expected from the 1:3 ratio of the v^'s, the net sulfur flux to the fine grained Carrara marble Is about one-third
that to coarse-grained Pennsylvania blue marble.  The sulfur flux estimates indicate that while deposition to wet
marble fe more efficient, the bulk of sulfur Is deposited when marble Is dry.

Surface accumulation of pollutants

Washdown procedures use deionized water to remove accumulated soluble pollutant deposits from a defined area
of a marble surface.  The architectural details of the Merchants Exchange provide two relatively similar, easHy
definable, concave areas on the vertical flutes of the coarse-grained column marble and on the lower foliage of the
fine-grained Carrara capital  (Figure 6). One column adjacent to each of the microcllmate/polutlon sensors was
selected for bi-weekly or monthly collections during warm weather.

Four faces or "exposures* at the two columns are sampled as shown In  Figure 8s. The protected face of the
capitals are  partlafly sheltered from  rain by projections from the upper capital, while the exposed  face of the
columns are fully washed by rain. This distinction applies to a lesser degree to the east and west sample locations,
where both columns and capitals can be partially exposed or sheltered by their postton within the colonnade with
                                                   159

-------
 respect to the incoming rain.  The protected column and capital sample locations are both fully sheltered from rain.
 The chemistry of the washdown solutions  indicate the relative accumulation  of water-soluble pollutants on the
 various marble surfaces.  The  observed concentrations reflect both the  amount of material deposited to the
 outermost layer and the relative solubility of the mineral salts into which the pollutants have been incorporated.
 Multiple collections at the same location show diminishing concentrations  of sulfate and nitrate in the leachate.
 decreasing the nitrate value to 9% of the first washing, and the sulfate to 18% after 3 subsequent washings.  This
 indicates  that the technique  removes some  fraction of the soluble surface deposit, a fraction  that cannot be
 determined at this time.
                      MCBOCUMATE-POU-UTIOH SENSORS
Figure 6.  Washdown protocol, a) Plan view of washdown locations, or exposures; b) Cross-hatching indicates the
areas of marble washed.

The chemistry  of the washdown solutions  indicate the relative accumulation of water-soluble pollutants at the
various locations. The observed concentrations reflect both the amount of material deposited to the outermost layer
and the relative solubility ol the mineral salts into which the pollutants have been incorporated. Multiple collections
at the same location show diminishing concentrations of sulfate and nitrate in the leachate. decreasing the nitrate
value to 9% of the first washing, and the sulfate to 18% after 3 subsequent washings.  This indicates that the
technique removes some fraction of the soluble surface deposit, a fraction that cannot be determined at this time.
 Table 3 presents average sulfate concentrations in the washdown solutions based on 14 collections for 16 different
locations.  The mean sutfate at all four exposures for both stone types at the South column is significantly greater
than those observed at the North column, confirming the influence of the increased sulfur exposure on the street
facade of  the building.   Further, sulfates are more concentrated in the Carrara leachate than in the comparable
Pennsylvania marble solutions, except for the South exposed location.

Table 3 also presents predicted washdown concentrations based on recent sulfur accumulation using the method
described above.  The predicted values lor the blue marble columns are within 20% of the observations  lor the
overall average, which is much closer than for the Carrara marble capitals.  The better agreement is explained in
part because the simpler geometry (and thus aerodynamics) of the columns is more similar to the obelisks from
which the deposition velocities were derived. More importantly, the columns are more fully washed by rain, fulfilling
the assumption in the prediction algorithm that the surface is flushed clean by rain every 5 days. In contrast,  sulfate
leached from the Carrara marble is 3-5 times greater than predicted, with the largest underpredictions found for the
protected  sampling locations, whore sulfate readily  accumulates.  The difference between the predicted and
observed sulfate concentrations increases as the degree of protection from rain increases.
                                                  160

-------

Sulfate in wash- down
(median)
protected, mg/L
exposed, mg/L
overall mean, 4
exposures, mg/L
predicted, mg/L
North Capital
Carrara

22
15
10
5.3
North Column
Pennsylvania

18
10
14
15.5
South Capital
Carrara

32
20
26
6.2
South Column
Pennsylvania

16
28
22
18.3
Table 3.  Sulfate concentrations In marble washdown solutions.

CONCLUSIONS

The air quality at the Merchants Exchange is typical of large American cities, with seasonal patterns, as well as
week to week variability. The relatively small Increase in time of wetness on the south side of the building causes
SOS deposition to wet marble be about 60% greater than to tha north side.  The sulfur flux calculations Indicate that
although  deposition to wet marble Is more efficient, under these exposure conditions, the bulk of the sulfur is
deposited when  the marble is dry. The net sulfur flux to Carrara marble Is about 30% of that to the Pennsylvania
blue marble. Sulfate levels in washdown solutions from the south column are greater than those observed for the
north column, correlating with the increased time of wetness and exposure to atmospheric sulfur.  The predicted
values of sulfate in the washdown from the Pennsylvania blue marble columns fall within 20% of the observations
for the overall average. In contrast, sulfate leached from the Carrara marble Is 3-5 times greater than predicted,
with the largest underpredictions  found for the protected sampling locations, where sulfate readily accumulates.

ACKNOWLEDGEMENTS

This research has been conducted with support provided by the National Park Service, Cooperative Agreement CA
0424-6-8002. as part of the National Add Precipitation Assessment Program. We appreciate the conscientious and
thorough work of Independence National Historic Park staff, especially Frank Doyle, for on-she assistance. Anett
Andersen of the National Park Service prepared several of the graphics.

REFERENCES

AMOROSO AND FASSINA, 1983.

CAH1LL,  TA, LL ASHBAUGH. J.B. BARONE,  RA ELDRED.RA, P.J.  FEENEY, R.Q. FLOCCHINI. C.
GOODART. D.J. SHADOAN, and Q.W. WOLFE, 1977: Analysis of resplrable fractions in atmospheric paniculate
Via sequential filtration.  J. Air Poll. Control Assoc.,  27,  675-681

CAMUFFO, D., M. DEL MONTE, C. SABBK3NI. and O. VITTORI, 1982. Wetting, deterioration, and visual features
of stone surfaces In an urban area.  Atmoa. Environ, 16, 2253-2259.

COE, JA S.I. SHERWOOD, J.A. MESSERICH, C.L PILLMORE, AA ANDERSEN, and V.G. MOSSOTTI, 1992:
Measuring stone decay with close range photgrammetry- In Proceedings of the Vlr* Congress on Deterioration and
Conservation of  Stone, Usboa. Portugal, 15-18 June.

DOLSKE, DA and G.J. STENSLAND, 1083: A Comparison of Ambient Airborne Sulfate Concentrations Determined
by Several Different Filtration Techniques, Proc. ol 3rd Had. Symp. on Recent Advances In Pollutant Monitoring
of Ambient Air and Stationary Sources, Raleigh, N.C., 3-6 May, 1983.

QOLDAN, P. D.. W.C. KUSTER, D.L ALBRITTON,  F.C. FEHSENFELD, P.S. CONNELL, R.B. NORTON.and B.J.
                                               161

-------
 HUEBERT. 1963: Calbratlon and tests of the Illter-collectlon method for  measuring clean-air ambient HNOr
 Atmos. Environ.. 17,1083,1355-1364.
 JOHNSON. DA and D.H.F. ATKINS, 1075: An altbome system for the sampling and analysis of sulphur dloxlds
 and atmospheric aerosols. Atmos. Environ.. 9.1975, 825-834.
 LIPFERT, F.W., 1989: Dry deposition velocity as an Indicator of SO, damage to materials. J. Me Pollution Control
 Assn., 39. 446-452.
 MCGEE. E.S.. 1992: Mention oft Ma*te Building: Contributions from Exposure.  In Proceedings of the VII*
 Congress on Deterioration and Conservation of Stone, Lteboa, Portugal, 15-18 June.
 SHERWOOD, S.I., D.F. GATZ. R.P. HOSKER, Jr., C.I.DAVIDSON, B.B. HICKS, R. LINZEY. E'.S. McGEE, R.L
 SCHMIERMUND, DA DOLSKE, D. LANGMUIR, F.W. UPFERT, V.G.  MOSSOTTI,  and E.G. SPIKER, 1990.
 NAPAP Report 20: Processes of deposition to structures.  National Acid Precipitation Assessment Program,
 Washington DC.
 SHERWOOD, S.I. and DA  DOLSKE, 1992: Add Deposition Effects on Marble Monuments at Gettysburg. In
 proceedings of the VII* Congress on Deterioration and Conservation of Stone, Lteboa, Portugal, 15-18 June.
 SPIKER.  E.C., R.P. HOSKER,  S.I. SHERWOOD, and V.J.COMER. 1992: Dry Deposition of SO, on Limestone
and Marble; Role of Humidity. Atmos. Environ, in press.
VERMETTE. S.J.. and J.J. DRAKE, 1988: Modifications to the M"Master wet-only rain collector. Atmos. Environ,
 22 (5), 195.
                                             162

-------
                Session 6
            Personal Samplers
James Mulik and Petros Koutrakis, Chairmen

-------
The  Passive Sampling Device  as  a  Simple Tool  for  Assessing
Ecological Change - An Extended Monitoring Study in Ambient Air.

James D. Hulik and Jerry L. Varns
U. s. Environmental Protection Agency
Atmospheric Research and Exposure Assessment Laboratory
Research Triangle Park, NC 27711 USA

Petros Koutrakis and Hike Wolfson
Harvard School of Public Health
Department of Environmental Science and Physiology
Boston, Ma 02115

Dennis Williams, William Ellenson and Keith Kronmiller
Mantech Environmental Technology, Inc.
Research Triangle Park, NC 27709


ABSTRACT

     Passive sampling devices  (PSDs),  normally associated with
personal  monitoring  were  studied  as less  costly alternate  or
supplemental methodology  for  the  Environmental Monitoring  and
Assessment Program  (EMAP).  PSD sampling results were compared to
methods  used at  one  of  the remote  sites  in  the national  Dry
Deposition  Network  (NDDN).   At the  1991 EPA/AWMA  Symposium we
presented data  comparisons from six months  of  testing that were
very encouraging.  This inter comparison of methods, now extended for
an  entire  year,  better  demonstrates  the  effects  of  seasonal
temperature and humidity.

     This report specifically provides data from November 1990 to
October 1991 at the  NDDN  site in Prince Edward State Park, VA.  The
following analytes were monitored on a weekly basis:  0,,  NO,  N02,
SO2,  HNOj, HONO, NH3, SO4,  and NOj.  Some of these  analytes were also
measured by  annular denuder-filter  pack systems (ADSs) that were
operated under  identical PSD sampling intervals*   The ADSs were
housed  in the  same shelters used  for protecting the  PSDs from
direct rainfall.  Cost comparisons  of using PSDs and ADSs  versus
current KDDN methodology will be discussed.

INTRODUCTION

     Last year, we reported on a successful six months evaluation
of passive  sampling  devices  (PSD*) and  annular denuder systems
(ADSs) as potential  cost saving alternatives to the methodology now
in use at the National Dry Deposition Network (NDDN)  site in  Prince
Edward, VA.  (i).  The Prince Edward site is only one of 50 sites
now operated by the NDDN.  At an annual cost of $60K per site to
operate,  this  effort  becomes prohibitive,  particularly with the
need  to expand the number of  sites to  375.    Therefore,  it is
imperative  that  less expensive  methods  be developed  wherever
possible. We selected passive  sampling devices for  remote site
                                165

-------
sampling because they are inexpensive, require no power and can be
easily deployed.  ADSs were also evaluated as a potential alternate
methodology   because  they   can  provide  information   on  those
pollutants  that cannot be measured  with PSDs.   The ADS is  also
relatively  inexpensive but  requires  a power source.  The  results
from  the  first six  months  were very  encouraging because of  the
close agreement that was  obtained between the PSDs, ADSs  and the
NDDN methodology.   As a result, the study was continued for  the
remainder  of  the  year to  determine  the  effects  of  seasonal
temperature and humidity changes.

     This paper provides weekly data from November 1990 to October
1991 from the Prince Edward, VA study  for  the  following analytes:
03,  NO,  NO2,  and  SO2.   Data  collected  on  HNO3,  HONO, NH3  and
particulate nitrate  and sulfate will be reported  elsewhere.

EXPERIMENTAL

     The instrumentation,  analytical procedures and description of
the  NDDN  site  at Prince Edward,  VA  were provided  in the  1991
EPA/AWMA  Proceedings  (1).   PSDs  from Ogawa  Inc.,  USA,  Pompano
Beach, FL were used for O3 ,  NO and NO2.  The SO2-PSDs were obtained
from  Scientific  Instrumentation  Specialists(SIS),  Inc.  Moscow,
Idaho. The  initial  purchase  cost  of  the Ogawa-PSD is $38 with an
analytical cost of  approximately  $25 per pollutant.  The  cost of
the SIS-PSD is $250 with a analytical cost  of  $25  for S02. Both PSD
types used in this study are reusable.  The more costly SIS-PSD was
used  for  SO2  because  it  offered  a  higher  sampling  rate  and
sensitivity needed to quantify the extremely low concentrations of
S02  at the Prince  Edward site.

     Two different  ADSs, both  available from University Research
Glass  (URG),  Carrboro,  NC,  were  also  used during  this  study.
Unheated ADSs were deployed in triplicate  by Harvard researchers.
An additional ADS,  a heated  aluminum prototype from URG was  also
tested during a portion of this study.  PSDs and unheated ADSs  were
housed  together  in  shelters used to  protect them  from  direct
rainfall. The PSDs and ADSs were operated  under the  one-week  NDDN
sampling intervals.

RESULTS AND DISCUSSION

OZONE AND SULFUR DIOXIDE

     The 0}  data in Figure I  graphically compares the Ogawa O3-PSD
to the TECO real time ozone monitor  for weekly ozone samples  from
November 1990 to October 1991.   The PSD data represents  the weekly
time weighted average of three PSDs.  The  real time ozone monitor
data is the  average of 168 hourly average readings. The  overall
ozone average for  the PSD was 34.8  ppb ( with a standard deviation
of  +/-  2.4  ppb)   for the  51  week  study.  The  overall average
                                166

-------

         PRINCE EDWARD VA SITE
      9  13 17  21 25  29 33 37 11  45 49
      51 WEEKS BEGINNING OCTOBER 16, 1990
   Heai T i me
   MonI tor
                           Passive
                           Sampler
Passive
Monitor.
 '    caparison  of  ozone  values using
 Sampling  Devices   versus  Real  Time
concentration  for  the
real  time  monitor  was
32.7  ppb.   The   ozone
concentrations   during
this  time period varied
from  13  ppb  to  50  ppb
using  the  UV  monitor
(see  bar graph)  and the       2
weekly  average PSD data       .,
ranged  from 12 to 51 ppb
(see  solid line).   The
averaged    difference
between weekly  PSD  and
UV monitor readings was
only  10  percent.  These
data  indicate excellent
agreement over this year
long  period  and exceeds  S^?Uf*
the   goal  of   +/-   20
percent   considered
necessary   for   trend
analyses.

      Comparisons of  the SO2-PSD data and the ADS  data  [heated EPA-
ADS (A)  and unheated Harvard ADS  (B) ]  with the NDDN S02 filter pack
are shown in  Figure  2  and Figure 3, respectively.
                                                 SO/2. PPB
      The PSD data points are               SIS-PSD vs NDON FILTER PACK
the average  of six weekly PSD
readings.  The data points for
the   unheated  ADSs   are  the
average of triplicate  weekly
samples whereas the heated ADS
data  were from  single  weekly
determinations. No significant
difference  is  noted  between
the heated and  unheated ADS
systems at  this  site.  High                   „;, Pllta,  f'mct
values  Of the coefficient of  Figure 2.  Comparison  of SO, Values Using
determination were obtained in  Passive sampling Devices versus NDDN site
all cases. However,  the PSD  Filterpack.
readings  show  more  scatter
than the ADS readings at midrange, e.g. at the 4 ppbv value for the
NDDN  filter  pack.   This is too  great to be due  to  the  inherent
scatter (typically +/-  15% about  the mean value for a set of six
PSDs).   Since  the  PSD  uses  a  different  collection  chemistry
(triethanolaroine)  than  the ADS (sodium carbonate), it is possible
that an  unknown  interference exists for the  PSD collection.
167

-------
             SO/2, PPB
          EPA-AOS vi MUM F4 lt«r Pick
    SO/3, PPB
>*rwd ADS v.  WON Fl Itv l
                                         •s
                                                   IBM riit.r nek
              mm Mlttr p«c»
Figure 3.  Comparison of Sulfur Dioxide Values Using NDDN Filterpack Versus (A)
EPA-ADS or (B) Harvard-ADS.

     These  data suggest that  both ADS samplers  and  the PSDs can
provide SO2  data comparable to the NDDK filter pack. To expand this
comparison  , a  study  has been  planned at four additional
sites  in different areas of the U. S. A.  This study,  beginning
August of  1992, will analyze  biweekly PSD and  ADS  samples for a
full year.

     The heated ADS costs about  $1500 whereas the URG  unheated ADS
cost is  $700.  These prices do not  include  the  cost of the pumps.
A  new,  and significantly  less  expensive  ADS  developed  by the
Harvard  School  of Public Health, will also be  evaluated in 1992.
This unit costs only  $500.

     The  Ogawa PSD  data  for  NO  and  N02  showed   a  very  low
concentration  range of  2  to 10  ppb  for both pollutants  for the
entire year. Because an NOX real  time monitor was not available for
such low concentrations, we were not able to verify their accuracy
however, the high  precision among the  six weekly NO/NO2-PSD values
indicated that placement in different shelters was not a  factor. We
will pursue the accuracy of  NO and NO2 data from the Ogawa PSD in
anticipation of its future application in the CASTNET program.

CONCLUSION

     The Ogawa  ozone-PSD demonstrated a +/-  10  percent agreement
with a real time ozone monitor when these  data were  collected
weekly for  a full  year  at a  remote NDDN  site.  The versatility of
the Ogawa-PSDs  was further demonstrated  by  promising measurements
of low ppb levels of NO and N02.  Research on this PSD for NO and NO2
continues because currently  there are  no inexpensive  alternate
methods available.  The SIS-PSD for SO2  also  performed quite well
and its comparison with the  NDDN filter pack S02 data resulted in
a correlation coefficient of 0.90. The scatter in a portion of the
SIS-PSD data for SO2 will be investigated.
                                168

-------
     In conclusion, these data  presented herein strongly suggest
that a combination of passive sampling devices and annular denuders
can offer alternative,  less  costly methodology than is currently
being used for the pollutants now being measured  in national air
monitoring networks.

     We also  suggest that  the passive  sampling  devices  now be
considered as  a  rapid  inexpensive means for  site  selection and
saturation monitoring.   This  approach should augment EPA's ability
to meet the mandates set by the 1990 Clear Air Amendments.

     The research described  in  this article  does  not necessarily
reflect the views of the Agency  and no official endorsement should
be inferred. Mention of  trade names or commercial products does not
constitute endorsement or recommendation for use.

ACKNOWLEDGEMENT

     We appreciate the year-long dedication and care shown by Gene
Brooks, the NDDN  site operator at Prince Edward, VA for all aspects
of sampling during this project.

REFERENCES

1.   J. Kulik,  J. Yarns, P. Koutrakis, M. Wolfson, D. Williams and
     K. Kronmiller  "  Using  Passive Sampling  Devices  To  Measure
     Selected  Air  Volatiles For  Assessing   Ecological  Change1*
     Proceedings of the 1991 EPA-AWMA International Symposium on
     Measurement of Toxic and Related Air Pollutants, VIP-17, Air
     and Waste Management Association, Pittsburgh, Pa. 1991 pp. 219
     - 226.
                               169

-------
                 PERSONAL EXPOSURE MODELS FOR SULFATES AND
                              AEROSOL STRONG ACIDITY

                     Helen H. Suh, John D. Spengler, Petros Koutrakis

                             Harvard School of Public Health
                                   665 Huntingdon Ave.
                                   Boston, MA 02115
ABSTRACT
       Personal exposure models for sulfates (SO4") and aerosol strong acidity (H*) were
developed using data collected from a personal monitoring study conducted in Uniontown, PA,
during Summer 1990.  Models were based on time-weighted microenvironmental exposures and
incorporated indoor and outdoor concentration and time-activity information for 24 children
living in Uniontown.  Models were validated using data collected from a second, larger
monitoring study conducted in State College, PA, during Summer 1991.
       Personal exposure models that included a correction factor (It,) were found to predict
personal exposures to SO4" well, representing a substantial improvement over outdoor
concentrations alone. Similarly for H+, models predicted personal exposures better than
outdoor concentrations, particularly when a correction factor and a neutralization term were
included in the model. Model validation showed that models can be used to predict personal
SO4" and H+ exposures for children living in State College and similar areas.
INTRODUCTION
       Several controlled laboratory studies have demonstrated that exposures to acid aerosols
may compromise the respiratory system (1-7).  Results from epidemiologic studies have been
inconsistent and less definitive, but suggest that acid aerosol exposures may result in decrements
in pulmonary function, increased hospital admissions for asthma and other respiratory ailments,
and possibly excess mortality, as experienced during the 1952 London fog episode (8-12).
       These health studies underscore the need to characterize personal acid aerosol
exposures.  Characterization of personal exposures will help identify factors, such as housing
characteristics and activity patterns, that influence acid aerosol exposures.  Once identified,
these factors can be incorporated into exposure models, which then can be used to obtain
unproved estimates of health risks when only limited exposure information is known.
       In this paper, we evaluated the ability of outdoor measurements and time-weighted
microenvironmental models to estimate personal exposures to sulfates and aerosol strong
acidity.  Models were developed using data collected in a personal monitoring study conducted
in Uniontown, PA, during Summer 1990 and were validated using data collected  from a second,
larger personal monitoring study conducted in State College, PA, during Summer 1991.

METHODS

Sampling Plan - Uniontown, PA and State College, PA
       In both Uniontown and State College, simultaneous indoor, outdoor, and personal acid
aerosol samples were collected for daytime periods  (8am-8pm).  Monitoring was conducted at
home sites and at stationary ambient monitoring (SAM) sites.  Home sites were  located at the
                                         170

-------
homes of 24 and 47 children in Uniontown and State College, respectively. A SAM site was
centrally located in Uniontown, while in State College, it was located 10 km outside the
residential area.  In total, 48 sets of indoor, outdoor, and personal samples were collected in
Uniontown as compared to 224 sets for State College.
       Indoor samplers were placed in the living room and outdoor samplers were placed in the
backyard of each home.  Samples were collected at a flow rate of 10 LmuV1 using the Harvard-
EPA Annular Denuder System (HEADS) (13-16). Personal monitors were carried by the
children throughout the sampling period on the shoulder strap of a backpack. Personal samples
were collected at a flow rate of 4 Limn'1 using the Personal Annular Denuder System (PADS).
PADS preparation, sampling, and analysis procedures are similar to those for HEADS.
       For each day of sampling, children also were asked to record in a notebook the location
and time of each new activity. Using these notebook entries, field technicians completed an
activity diary together with the child and parent during every evening visit. Diaries grouped
activities to give the primary location and activity level for each half hour  of personal sampling.

MlcroenvlnHunental Exposure Models
       Time-weighted exposure models of personal SO4" and H* exposures were developed
using concentration and activity data collected in Uniontown.  These models were based on
exposures from two microenvironments, "indoor" and "outdoor" (17-19):

                               E - fjC,  +  foC0                               (1)
where E is the mean exposure for a 12-h period, f, the fraction of time spent indoors, C, the
indoor concentration, ^ the fraction of time spent outdoors, and C0 the outdoor concentration.
Concentrations for all indoor environments, including those for automobiles, were assumed to
equal those measured inside the child's home.  Concentrations for all outdoor environments
were assumed to equal those measured at the stationary ambient monitoring site. Models were
evaluated using univariate regression analysis with "no intercept". The slope of the regression
line of estimated on measured personal exposures and the root mean square error (RMSE)
were used as indicators of the accuracy and precision of the model, respectively (20).
       Final models for both SO4* and H+ were validated using concentration and activity data
collected in State College.  Again, the accuracy and the precision of the models were evaluated
using the slope of the regression line (assuming "no intercept") and the RMSE, respectively.

RESULTS AND DISCUSSION

Personal Exposures
       In Uniontown, personal SO4" exposures were less than their corresponding outdoor
concentrations (mean ratio- 0.73 ±024)and greater than indoor concentrations (mean ratio
- 1.15±0.95). Outdoor and indoor SO4" explained a high percentage of the variability in
personal exposures, accounting for 80% and 87% of the variability, respectivery (Table I) (15).
Despite this, outdoor SO4' was unable to predict personal exposures accurately, as personal
SO4" differed from outdoor concentrations by as much as 60% (Figure 1). For H*, personal
exposures measured in Uniontown were higher than indoor (mean ratio- 2.53 ±4J5)and lower
than outdoor levels (mean ratio -0.22 ±0.19). Personal exposures displayed considerable
interpersonal variability, differing by as much as 300% from associated outdoor concentrations.
Outdoor and indoor acid levels accounted for only 42% and 11% of the variability in personal
H+, respectively (Table 1).  Both were poor estimators of personal exposures (Figure 2).

SO4" Exposure Model
       For SO/, the microenvironmental model (RMSE -21.74) estimated personal exposures
better than outdoor concentrations alone (RMSE -35.52) (Table II).  Model estimates, however,
                                          171

-------
were consistently higher than measured personal exposures, resulting in a slope of 1.13 (±0.02)
when compared to measured values. High personal exposure estimates may be due to under-
collect ion of SO4"  by the personal monitor.  Since the accuracy and precision of the personal
monitor have been verified under stationary conditions, under-collection would occur only if
movement or placement of the personal monitor next to the child's shoulder impairs the ability
of the monitor to sample its surrounding air.  Alternatively, personal exposures may actually be
less than would otherwise be expected from the microenvironmental model.
       To account for the observed "loss" in personal SO4" measurements, the model was
amended to include a correction factor
                                + f0C0)  -  [(f^ + f^CJ  »  kp]                (2)
                          '-time-weighted-'    ' — correction term - '
                          concentration

where E is the revised mean exposure. The correction factor (kp) was determined to equal
0.115 through an optimization procedure which determines the value of kp at which the slope of
the regression of estimates on measured personal exposures equalled unity. As shown on Figure
3, the revised model improved personal exposure estimates, with an RMSE of 19.24 (Table II).

H+ Exposure Models
       For H+, the microenvironmental model (equation 1) improved predictions of personal
exposure (RMSE=6t,07) over outdoor concentrations alone (RMSE= 170.07); however, it
overestimated personal H* exposures substantially (m= 1.62±0.19)(Table II).  Since essentially
all H* is associated with SO4", the correction factor estimated for SO4" (k=0.115)  also should
apply to H+,  When this factor was added to the model, improvements in the model were slight
(Table II).  Results suggest the existence of additional loss mechanisms, the most likely being
the neutralization of H* by NH3.
      The model was amended to account for neutralization by NH3 through the addition of an
NH3 reaction rate:
     E  =  (fA +  f0C0) -  [ftq + tCJ'kp] - [(fA + foCJ'INHJp'k™]    (3)
         kime-weighted-1   "—correction term — '   ' - ammonia reaction term - '
          concentration

where kp the correction factor 0.115, [NHj]p the NH3 concentration measured by the personal
monitor, and [NHJp'kNHs the reaction rate of H* with NH3. The reaction rate is first order
with respect to NH3 (21). The value for kf^ was estimated to be 0.005 ppb'1 by determining
the value at which the slope of the regression of personal exposure estimates on measured
values equalled unity.  As shown on Figure 4, the revised model improved predictions of
personal H* exposures, reducing the RMSE substantially to 39.60 (Table II).  Model errors may
result from heterogeneity in H+ concentrations or from inaccurate estimation of H*.

Model Validation
       To validate these models, concentration and activity information collected in State
College were inputted into the SO4" and H* exposure models developed above. Model
estimates were then compared to personal exposures measured in State College.  Results from
these analyses show that the models are able to  predict personal SO4" and H+ exposures for
children living in State College with a high degree of accuracy. Regression of the estimated on
measured personal exposures yielded a slope of 0.96 (±0.01)and an RMSE of 23.26 for SO4"
and a slope of  1.00 (±0.04)and an RMSE of 21.77 for H+.  These results are similar to those
                                           172

-------
obtained when models were fitted to data collected in Uniontown. A summary of results for all
models are presented in Table II.

CONCLUSIONS
       Personal exposures to both SO4" and H+ of children living in Uniontown exhibited
considerable interpersonal variability. Outdoor concentrations were unable to capture this
variability and consequently were poor estimators of personal exposures.  Microenvironmental
models increased our ability to predict personal SO4" and H+ exposures over outdoor
concentrations.  For SO4", the model with the best accuracy and precision included a correction
factor, kp, while  for H+, it included both a correction factor and a neutralization term.  The
precision of the  804" model was better than that of the H+ exposure model.  This difference
may be due to greater variability in H+  and NH3 concentrations.  Model validation showed that
the models' correction and neutralization terms were stable, indicating that the models may be
used to estimate personal exposures for children living in similar,  semi-rural environments.

.ACKNOWLEDGEMENTS
       The field study was funded by the Electric Power Research Institute (EPRI) under
contracts #RP1630-59 and RP-3009-04. Also, support for data analysis was provided by the
Environmental Protection Agency (EPA) under a cooperative agreement  #CR816740.  A special
thanks to the project managers Dr. Janice Yager and Mrs. Mary Ann Allan from EPRI and Mr.
Robert Burton from EPA for their contributions to the project.

LITERATURE CITED
 (I)   Utell, MJ, Morrow, PE, Sneers, DM, Darling, J, and Hyde, RW. Am. Rev. Resp. Dis.
       1983,128, 444-450.
 (2)   Koenig, JQ, Pierson, WE, and Horike, M.  Am. Rev. Resp.  Dis. 1983,128,221-225.
 (3)   Avol, EL, Linn, WS, Anderson, KR, Shamoo, DA, Valencia, LM, Little, DE, Hackney,
       JD. Tax.  Ind Health 1988, 4, 173-184.
 (4)   Koenig, JQ, Covert, DS, and Pierson, WE. Env. Health Persp. 1989,79, 173-178.
 (5)   Utell, MJ, Morrow, PE, Hyde, RW, and Schreck, RM. Arm. Occ Hyg. 1988,32, 267-272,
       Suppl 1.
• (6)   Spektor,  DM, Yen, BM, and Lippmann, M. Env. Health Penp. 1989, 70,167-172.
 (7)   Schlesinger, RB, Chen, LC, Finkelstein, I and Zelikoff, JT. Env. Res.  1990, 52, 210-224.
 (8)   Ayres, J,  Fleming, D, Williams, M, and Mclnnes, G. Env.  Health Persp. 1988, 79, 83-88.
 (9)   Thurston, GD, Ito, K,  and Lippmann, M. Env. Health Persp. 1988, 79, 73-82.
(10)   Bates, DV and Sizto, R. Env. Health Persp. 1988, 79, 69-72.
(11)   Raizenne, ME, Burnett, RT, Stem, B, Franklin, CA, and Spengler, JD. (1989).  Env.
       Health Persp. 1989, 79, 179-185.
(12)   Bates, DV, Baker-Anderson, M, and Sizto, R. Env. Res. 1990, 51, 51-70.
(13)   Brauer, M, Koutrakis, P and Spengler, JD. (1989)  Env. ScL Tech. 1989,23,1408-1412.
(14)   Koutrakis, P, Wolfson, JM, Slater, JL, Brauer, M, Spengler, JD, Stevens, RK, and Stones,
       CL.  Env. Set Tech., 1988, 22,  1463-1468.
(15)   Brauer, M, Koutrakis, P, Wolfson, JM, and Spengler, JD.  Atmos. Env. 1989,23,1981-
       1986.
(16)   Koutrakis, P, Fasano, AM, Slater, JL, Spengler, JD, McCarthy, JF, and Leaderer, BP.
       Atmos. Env.  1989,25, 2767-2773.
(17)   Fugas, M. Proc. of the Int. Symp. on Env. Monitoring 1975,2, 38-45 (1975).
(18)   Duan, N. SIMS Tech. Report No. 47, Stanford University Dept. of Statistics. Palo Alto,
       CA, 1981.
(19)   Duan, N. Env. Inter. 1982,8, 305-309.
                                           173

-------
(20)   RMSE is a measure of the variability in personal exposures that is not explained by the
       regression line.  It is essentially the average error of the prediction from the regression
       line.
(21)   Huntzicker, JJ, Cary, RA, and Ling, CS.  Em. ScL Tech. 1980,14. 819-824.
TABLES AND FIGURES
DEPENDENT
VARIABLE
Personal H+
Personal SO/
INDEPENDENT
VARIABLE
Outdoor H+
Indoor H*
Outdoor SO4"
Indoor SO4"
N
40
39
42
40
R2
0.42
0.11
0.80
0.87
SLOPE
0.25 ±0.05
0.45 ±0.21
0.69 ±0.05
0.79 ±0.05
INTERCEPT
-1.79 ±10.91
22.28 ± 8.43
9.03 ± 10.59
20.36 ± 7.84
Table I. Summary of results from univariate regressions of personal H* and SO4" exposures on
dairy indoor and outdoor concentrations.  N denotes the number of samples included in the
analysis.
POLLUTANT
SO4": + OUTDOOR
+ INDOOR, ACTIVITY
+ CORRECTION FACTOR (kp)
MODEL VALIDATION:
H+: + OUTDOOR
+ INDOOR, ACTIVITY
+ CORRECTION FACTOR (kj
+ REACTION RATE ([NHJp'kNHj)
MODEL VALIDATION:
N
42
39
39
211
40
36
36
36
197
RMSE
35.52
21.74
19.24
23.26
170.07
61.07
54.05
39.60
21.77
SLOPE (m)
0.73 ±0.03
1.13 ±0.02
1.00 ±0.02
0.96 ±0.01
0.25 ±0.03
1.62 ±0.19
1.43 ±0.17
1.02 ±0.13
1.00 ±0.04
TABLE II. Summary of personal exposure model results. Models were developed using data
from Uru'ontown, PA and were validated using data from State College, PA. A plus sign (+)
indicates the addition of variables to the models.  RMSE is the root mean square error. Slopes
were calculated using "no-intercept" univariate regression models. For models with slopes forced
through 1, the RMSE and the standard error of the slope provide estimates of model precision.
                                          174

-------
  ^  300
  rt
  E
                  zoo
FIGURE 1,  Personal vs.  outdoor SO4".
Open circles represent children living in air
conditioned homes.  Plot shows 1:1 line.
     3 SO


     300


     210


     200


     150


     100


     50


      0


     -SO
           100  JOB   300   400   900   100

               OUTDOOR (nmo!M/in3)
FIGURE 2.  Personal vs.  outdoor H+.
Open circles represent children living in air
conditioned homes. Plot shows 1:1 line.
       0   10   100  ISO  ]00  2M  100  JM

               MEASURED (nmol.i/mj)
                                                               i  tDO
                                                                                         I
                                                                                              I
      -50   0    SO   100   ISO   504   2SO

               MEASURED (nmol>l/n3)
FIGURE 3.   Estimated  vs.  measured
personal SO4". Model includes correction
term, k_. Open circles denote homes with
air conditioning. Plot includes 1:1 line.
FIGURE 4.   Estimated  (with k,,  and
^NKs'ENHsJp) vs. measured personal H+.
Open circles are air conditioned  homes;
solid line is 1:1 line).
                                                 175

-------
A NATIONAL  PILOT  STUDY  ON OCCURRENCE  OF  AIRBORNE  VOCs  IN RESIDENCES
                     - DESIGN AND  PROGRESS  -

            Rein Otson1,  Philip Fellin2,  Roy Whitmore3

1 Health and Welfare Canada, Room B-19,  EHC,  Tunney's Pasture,  Ottawa*
Ontario, Canada K1A OL2, a concord Environmental corporation, 2  Tippett
Rd., Downsview, Ontario, Canada M3H 2V2,  3 Research Triangle Institute,
Research Triangle Park,  N.C.  27709, U.S.A.

ABSTRACT
     A study was conducted to determine the distribution of 26 airborne
volatile  organic compounds  {VOCs)  in  typical  Canadian  residential
dwellings.  The sampling program was designed to allow  statistical
inferences  to  be  made  regarding the  study population.  Detailed  field
procedures  were developed to ensure systematic and reproducible  field
operations. The design  and  implementation of the  study  are discussed
together  with  comments  on  other  considerations  and  observations.
Preliminary information  on  VOC occurrence and  the  precision  and
accuracy of measurements are reported.

INTRODUCTION
     There  is  a  concern for the  potential  human health effects of
airborne  VOCs  in  Canadian  buildings,   especially  in  relation to
potential exacerbation  of  VOC  levels that  may be caused  by  various
energy conservation  measures, activities and materials  in  homes.  The
paucity of  data,  largely due to the  lack  of suitable and  economical
sampling and analysis methods, has been a disadvantage in assessment of
the  exposure and risk  of  Canadians  to residential  VOCs.  Recently*
analytical  procedures1,  incorporating the use of  the OVM 3500  passive
sampler, were developed to facilitate  collection of VOC data. To aid in
establishing a strategy for collecting data, a literature  review and
limited preliminary studies  were also  conducted. Then a pilot survey of
VOCs in residences was initiated as an important step in the Health aiw
Welfare Canada program.  The  study was conducted to provide preliminary
information on  the  nation-wide  occurrence  of   26   selected  VOCS/
including some Canadian priority substances2,  and to provide information
necessary for a more complete statistical design of future surveys. The
survey also provided an  opportunity to conduct additional evaluation of
the sampler's performance.

STUDY SCOPE AND DESIGN
     An initial budget  estimate of  ca.  $ 300,000  for contracting the
work and limited  in-house human resources placed  a limit on the  scop6
and nature  of  the study.  The study criteria were  to: collect  data on
single family dwellings; be national  in  scope; be  without temporal of
geographic  bias;   be  based  on  random selection processes;  allo*J
statistical  inferences;  ensure confidentiality of information  about
participants   and;   include  a   simple   questionnaire  on  buildin?
characteristics. The latter  conditions and availability of the  passive
sampling  method  for 24  h integrated  measurements  influenced  the
respondent  burden  and   home occupant  participation  rates.  It  *»<»
estimated that the  requirements and  available methods  and  resources
would allow examination of 500 to 1000 homes. Little information  about
the occurrence of the target VCCs in Canadian homes was  available to
                                  176

-------
assist with the study design.

     One of the first steps required  the establishment of the sampling
frame, i.e. the  list from which sample units  are  selected.  The most
comprehensive list was the Statistics Canada (StatsCan) census database
(7.5 million  residences in the  1986 Census),  but this  list  is only
updated on a five year schedule.  Lists provided by marketing organiza-
tions, such as southam Business Information  (4.8  million "verified"
mailable addresses),  are of uncertain accuracy3. Another option was the
random-digit-dial (ROD)  approach4  which  employs blocks  of telephone
numbers compiled in convenient units  (e.g., 100)  from recent national
listings of area  codes  and prefixes. The  use of  registered telephone
directories and randomized  selection of telephone  numbers for sample
frame construction and use of a single or multistage process was also
considered. The RDD and  telephone directory approaches were discounted
due to absence of geographical  information (ROD),  unlisted telephone
numbers (directories), costs associated with long distance calls, and
the anticipated poor response to telephone solicitation.  The use of a
sampling frame based  on postal  codes was  rejected because geographic
boundaries associated with rural  postal  service areas are not well
defined and identifying locations of homes would have been difficult.

     Several options  for execution of the survey were considered.  An
approach  based  on   mailing  of  samplers to  residents  was  deemed
unacceptable due  to  the anticipated  low5  participation rates  and the
uncertain quality in reporting and handling procedures.  Piggy backing
on an  existing survey,  such  as  a  StatsCan labour force  survey, was
explored. However, this option was  too expensive, required training of
many field operators  and required  at least one year  of  lead  time to
organize. After considering the  alternatives,  the  most recent (1986)
StatsCan census database was chosen to provide the sampling frame for
selection  of   homes.  To  enhance  participation  and  the quality  of
results, it was decided  to conduct face-to-face visits for interviewing
and monitor placement and retrieval.

STATISTICAL DEBION
     Area household sampling methods6 were used to choose a probability
sample of approximately 800 residence-days for monitoring in single-
family, permanent residences throughout a 1-year data collection period
beginning in mid-January, 1991.  Forty-eight census subdivisions (CSDs)
were selected  at  the first stage  with probabilities  proportional to
1986 census counts of regular,  private dwellings  from 6009 available
CSDs. Military bases,  Indian reserves and  the  Yukon and Northwest
Territories were excluded due to difficulty with access and to reduce
travel costs.  The CSD  sample was stratified to ensure representation of
all  major  regions of the  country.  Four  sample  CSDs were  randomly
assigned to each  month  for  data  collection in a  manner that assigned
samples from each geographic region evenly throughout the year.

     Four census  enumeration areas  (EAs)  were selected  within each
sample CSD with  probabilities proportional to 1986 census counts of
regular,  private  dwellings.  The  EAs  were  stratified  to  ensure
proportional representation of urban/suburban and rural single-family
dwellings and representation of different types of housing. Within each
selected EA,  the current residences were listed by field staff and an
                                  177

-------
 average of about 6.5 sample residences were selected. The actual number
 of  residences selected depended on the amount of change since the 1986
 census  and was designed  so that all  single-family dwellings  in  the
 sampling  frame  had  the same probability  of  selection.  In the temporal
 domain,  5/7ths of  the sample  residences were  randomly assigned  to
 weekday data  collection.  The remainder were assigned  to weekend data
 collection  to permit assessment  of weekday/weekend differences.  The
 probability sampling design is  described in more detail elsewhere7.

 FIELD AND LABORATORY PROCEDURES
      One bilingual French/English technologist conducted  the  entire
 survey  although  two  others also had  been  trained.  The  training
 encompassed instruction on sampler  handling, acquisition of auxiliary
 information (temperature, relative humidity, air exchange), administra-
 tion of the questionnaire, data recording, reporting frequency to home
 base  (Toronto)  and  a review of the  information packages for  the  48
 CSDs. The packages  consisted of detailed EA maps,  population counts,
 enumeration lists and  control forms,  sample listing forms,  question-
 naires and bilingual (French/English) letters. A "dress rehearsal"  of
 field operations was conducted  in a residential community  in Toronto
 just before initiation of the survey.

     Typical tasks  executed during each one week CSD  sampling  survey
 are described below. An  initial drive around the selected  EAs  within
 the CSD  was used to define the  geographical  boundaries. A detailed
 house count allowed updating of the 1986 census information and random
 selection (proportional to housing  count) of subareas  within an EA i?
 the  enumeration  list  exceeded  ca.  300 residences.  The  next  step
 required  detailed listing of homes in the EA or subarea and calcul*"
 tion of the number of hones to be visited. The  survey design was based
 on solicitation of 6.5 residences/EA on average and 62  % participation
 rates (based on experience with  the TEAM  study*) to yield ca. 770 hones
 (i.e., 6.5 ho»es/EA x  0.62 x 48  CSDs x  4 EA/CSD). Actual  numbers  ot
 target residences  in each  EA were  adjusted by  the use of  the field
 counts compared with census data  counts.  However, upper  and  lower
 bounds, typically 10 and 2, were placed on the number  of  residences
 solicited within each EA. An upper  bound was used to limit the  effect
 of  intracluster correlation which results  in  less  information p*r
 residence as the number of residences per cluster increases*. Selection
 of homes within EAs was based on systematic sampling6.  This eliminates
 the potential for field operator bias  in  the sample selection process-

     Initial contact was made  by delivery of a bilingual  letter  to
 selected  residences to  notify occupants about  the  survey and th*
 impending visit of the field technologist. Approximately 24 h later tW
 selected  homes  were  visited  in  an  attempt  to  gain  access  tot
monitoring. Each home was  visited until either refusal or acceptance ot
participation was provided  by the occupant or until a  maximum of five
visits with no answers were made. Each visit was recorded on a  uniqu*
control form for the home. The occupant, when encountered, was provide"
with a brief written description and an authorization number  of
survey,  a telephone number  for verification, and an identification
the sponsoring agency.

     The  home  monitoring was  initiated by completion  of  a
                                  178

-------
history form and  administration of a questionnaire  comprising eight
items. Information was  collected on home age  and  type,  ventilation/
heating  systems,   occupancy,   and  activities  such  as  renovations,
painting and acquisition of new items such as carpets or furniture. In
addition,  measurements of temperature and relative humidity were made
inside the home and outside the  home at  the beginning and end of the
sampler deployment period.  Samplers were  placed in  living areas of the
home. Kitchens,  bedrooms and  bathrooms  were  avoided. Samplers were
placed near the center  of  the room, at ca. 1.5 m  from the floor, at
least 0.5 m from any walls, and at least 1 m from corners, windows or
sources of direct  ventilation to avoid stagnant zones  or direct drafts.

     Field procedures to assess data representativeness, precision and
accuracy  included:  collection of field  blank samples in  each CSD;
collection of  non-colocated (different rooms) and colocated passive
method samples  in 5 %  of  homes; and collection of  reference method
samples  (charcoal sorbent  tubes and pumps;  colocated with passive
samplers)   in  5  %  of  homes.  All  samples  were  transported  to  the
laboratory and analyzed within 21 days of sampling  to minimize storage
effects. At the laboratory,  samplers were extracted in situ with 1.5 mL
°f carbon  disulfide.  The extraction solvent was pre-spiked with 4.5
Mg/sample  of  i,2-dichloroethane-d4  (internal reference  standard).
Extracts were analyzed by injection of 1 pL into a gas chromatograph-
mass spectrometer  operated in the selected ion monitoring mode.  One
target ion and  two confirmatory ions were monitored. Analytical quality
assurance measures included pre-analysis of the extraction solvent, and
analysis  of  laboratory blank  sample  extracts, extracts  of sorbents
spiked with target VOCs, six standard VOC calibration solutions at the
beginning and end of each batch of samples,  the solvent and a standard
solution at  10 sample intervals and reanalysis of one in ten sample
extract solutions. In addition,  40 randomly selected sample extracts
were provided to a second laboratory for quality assurance analysis.

PRELIMINARY RESULTS
     The project schedule was maintained, except for an interruption to
sampling  during  a blizzard  in October in  Saskatchewan where missed
areas  were  sampled  in December. The  field study  design,  field
execution, analysis and home base support functions of the project were
accomplished with a total budget of ca.  $420,000 (Canadian).  Partly due
to the method selected  to conduct the study design, this exceeded the
original estimate of $300,000. Travel and accommodation accounted for
§38,ooo and  $75000 was  spent on  study design  and  census  data tapes.
When these items  are excluded,  the cost of the program  for ca. 750
homes was $410/home.  The cost included reanalysis of 200 of the  samples
*or total volatile organic hydrocarbons (TVOC) and determination of air
exchange rates in  23 of the homes by the perfluorocarbon tracer method9.

     Because of the survey design and the use  of passive samplers the
respondent burden was judged to be low and a  high response rate was
anticipated. The  participation rate in the survey was determined by
comparison of  the number of residents  solicited (1447) to the number
that participated  (757). Of the  1447, 277 refused  to participate, 316
«id not respond primarily due to  absence and 97 did  not participate for
other  reasons  such   as scheduling  difficulties.  A  gross positive
response rate of 52.3. % or 15.8 homes/CSD on average was achieved. If
                                  179

-------
 the "no answer"  hones are removed from consideration the participation
 rate was 66.9  %. These data are  similar to values achieved in the TEAM
 study* which was of similar sample size but was conducted on a smaller
 geographic scale.

      In general,  the  survey was received  positively by  the public.
 However, verification  of the  survey  authenticity and  technician's
 credentials was  frequently  requested  by  residents.   No  accurate
 statistics on  requests  are  available since  the telephone service used
 to  provide  confirmation did not  keep  reliable  records.  Based  on
 response for CSDs within the telephone area code 416,  as many as 20 %
 of residents requested  confirmation of the survey's  authenticity in
 some areas. The field  technologist  was  detained,  once by  municipal
 officials  in  Drumheller, Alberta,   and  once  in Vancouver,  British
 Columbia,  while his identity was checked by the  RCMP.  Some residents
 called  to complain about the nature  of the survey,  but  most of these
 participated  after some explanation about  the  survey's  objectives.
 Although provincial representatives had been notified about the survey,
 there were  verification  inquiries  from public officials  in  some
 provinces. The frequency of verification requests by survey populations
 has been much lower in similar U.S. surveys according to the experience
 of one  of  the  authors  (R.W.  Whitmore).

 Table I.  Preliminary  (first  10 months)  results for  maximum and mean
         concentrations  (/ig/m3) of target VOCs in dwellings.
              Max.   Mean
                                                         Max.
Mean
n-decane
hexane
benzene
m-xylene
o-xylene
p-xylene
a-pinene
toluene
chloroform
naphthalene
styrene
p-cymene
d-limonene
6460
1570
68
1470
320
280
1450
1200
69
250
115
277
940
50.4
15.7
7.4
18.2
7.6
8.1
26.4
36.1
4.1
11.9
2.9
4.7
23.2
tetrachloroethylene
ethylbenzene
p-dichlorobenzene
1,3, 5-trimethylbenzene
pentachloroe thane
m-dichlorobenzene
trichloroethylene
1 , 2 -dichloroe thane
hexach 1 or oe thane
dichloromethane
1,1,2, 2-tetrachloroethane
1,2, 4-tri»ethy Ibenzene
1 , 2 , 4-trichlorobenzene
313
540
1140
640
66
9.4
165
27
11
1690
11
1920
20
5.1
11.1
15.7
5.8
4.0
1.8
1.4
1.8
2.1
16.3
1.8
15.5
2.6
   Some preliminary results for VOC occurrence are presented in Table
I. Comparison of the passive sampler results with those  obtained with
the active sampler charcoal  tube  reference method indicated  that the
correlation coefficient (R2)  was 0.998  or better  and  linear  regression
of the pooled results for 20  pair* of samples and 26  compounds yielded
a slope of  1.08 and an intercept at  0.14  fig/*3- The pooled  standard
deviation value for sets of measurements obtained for 22  pairs of non-
colocated samplers was 2.4 jig/m3 (mean concentration 8.1 Mg/»3) *°r all
26 VOCs and  was similar to the value  of 2.2 fig/*3  (mean,  6.7 M9/* )
obtained for 35 pairs of colocated passive samplers  in the  same hones
as the non-colocated samplers. These results suggested that the spatial
variation of VOC concentrations in the homes was not  large. The range
                                 180

-------
of other field  measurements for the study were:  air exchange rates,
0.03 to 4.9  changes/ h;  indoor temperature, 15.5  to  30.5 °C; outdoor
temperature, -22 to 33 °C; indoor humidity, 10 to 79 %RH; and outdoor
humidity,  19 to 100 %RH.

ACKNOWLEDGEMENTS

Assistance in this study by L.  Landry,  S.E. Barnett,  C. Mills and M.J.
Goddard and partial  funding  by the  Panel  on  Energy  Research  and
Development are gratefully acknowledged.

REVERENCES

1. Otson,  R., "A Health and Welfare  Canada program to develop personal
exposure monitors for airborne organics at jig/m3," in Proceedings of the
1990 EP*/AtWMA  International Svmnosium  on Measurement  of  ToXJcand.
Related ftjr  Pollutants.  VIP-17, Air & Waste  Management Association,
Pittsburgh, PA, 1990,  pp. 483-488.

2. Canada  Gazette, Part  I,  February  11,  1989,  "Priority Substances
List", Supply and Services Canada, Ottawa.

3. Whitmore, R.W., Mason, R.E.,  Hartwell, T.D., "Use  of geographically
classified  telephone  directory  listings  in multi-mode  surveys,"  in
         statistical  Association 1983 Proceedings  9f  the Section on
Survey Rfffearch Methods. 1983, pp. 721-726.

4. Waksberg, J., "Sampling methods for random digit  dialing", J. Amer.
Stat. Assoc., 73: 40  (1978).

5. Dillman,  D., Mail  and Telephone Surveys: The Total Design Method-
Wiley, New York, NY,  1978.

6. Kish, L. , Survey sampling. Wiley,  New York, NY,  1965.

7. Whitmore, R.W., Williams, S.R., Fellin,  P., Otson, R.,  "Design  of a
national  study of  residential  air  quality in  Canada,"  in American
Statl^^ai  Association  1991 Proceedings of the  Section on Statistics
and th? Environment..  1992, in press.
8.  Wallace,  L.A. , The Total Exposure  Assessment Methodology  fTEAM)
Study;  summary and Analysis; volume  T.  EPA/600/6-87/002a. Office of
Research  and  Development,   U.S.   Environmental  Protection  Agency,
Washington, D.C, 1987.

9. Dietz, R.N. , D'Ottavio, Goodrich, R.W., "Seasonal effects on  multi-
zone  air infiltration in  some  typical  U.S.  homes using a passive
Perfluorocarbon  tracer technique," in Proceedings  of  the CLIHA  2QQP
Horld  congress  on Heating.  Ventilfltinq and  Mr Conditioning,  P-O-
Fanger, Ed., WS Kongress-WS Messe,  Copenhagen,  1985, pp. 115-121.
                                   181

-------
                INDOOR DISPERSION MODELLING OF TOLUENE

                           Claude S. Davis1 and Rein Otson2
                          'Concord Environmental Corporation,
                     2 Tippett Road, Downsview, Ontario, M3H 2V2
                     2Healtb and Welfare Canada, Room B-19, EHC,
                      Tunney's Pasture, Ottawa, Ontario, K1A OL2

ABSTRACT
             A portable  gas chromatograph was used to measure levels of airborne toluene
which resulted from the introduction of a toluene source of known strength into a house. Air
exchange rates were measured by means of a tracer technique. Dispersion measurements with
C0|2 were made to establish the degree of mixing within die house and to establish the validity
of treating the house as a single room. The U.S. EPA INDOOR model was applied to the data.
For six time periods distinguished by factors  such as the presence or absence of the toluene
source, and air exchange rates, during which the toluene concentration was measured, excellent
agreement between the monitoring data and model predictions was obtained.

INTRODUCTION
             Improvements in building design and building materials, the introduction of new
consumer products and continued emphasis on energy efficiency will lead to increased emphasis
on indoor air quality. Indoor contaminant sources and house characteristics are important factors
in determining indoor air pollutant levels. Dispersion models for predicting indoor contaminant
levels require information on  source and building  characteristics,  thus the compilation of
information on source strengths of consumer products and building materials and the development
of indoor models are expected to play a greater role in estimating human exposure in homes.

             The determination of human exposure to indoor contaminants requires knowledge
of the variation of contaminant concentrations with time and the activity patterns of individuals.
Reliable dispersion modelling provides a cost effective means for estimating indoor levels since
indoor monitoring of a  large number of homes is relatively expensive.  Indoor dispersion models
require information on  sources and sinks, as wen as accurate representation of the diffusion,
transport,  sorption/desorption  and chemical transformation of contaminants throughout the
building. Also, concentration-time profiles of contaminants are required to evaluate die model-

             In this paper, we describe die application of an indoor model to measurements
made in an air tight home.  The measurements were obtained while conditions of ventilation and
deployment of an artificial indoor source of toluene were changed.
                                        182

-------
EXPERIMENTAL
             The test house in which monitoring was conducted is a sinfle family structure of
approximately 5500 square feet, consists of a main floor and a basement, and is *^«ip«^ to be
air tight Le., <&1  air changes per hour (ACH). The heating, ventilation and air conditioning
(HVAC) system consists of a heating system which has a fprhr"^Miltg fan in the electric furnace
with duct work to every room in the house, and a manually operated air exchange system which
has a separate ducting system and two fans (NnTech-Lifebreath System) that allow the exhaust
of bouse air and the introduction of fresh air from outside. The fresh air is introduced into the
furnace room about two feet from a return air vent in die recnculating duct work connected 10
the  furnace.

             Measurements of COj levels that resulted from  the release of the gas  from a
cylinder of pure COj (Medigas Inc. Toronto, Ontario) were used to establish die degree of
mixing within die boose. The CO* concentrations were measured at two locations on the main
floor selected to be distant from the furnace room (in the living room and at the end of a hallway
bom on the main floor).  The COj was released in the furnace room in the basement whfle the
furnace  "^'milatJng fan *r*i die air exchange fun* were all on.  After 43 iniimiri, COj was
measured using a  Fuji Electric Model ZFPSYAZ1 Analyzer at the  two  locations. The COj
malyzer was calibrated by use of a gas cylinder containing 1 500 ± 30 ppm of CO/COj (certified
quality, Matbeson  Gas Products Ltd., Whitby, Ontario).

             Airborne toluene was measured using a HNU Model 321 GC (HNU Systsns,
Newton, MA) equipped with a programmable couroUa. a Ci^ gas samptiag valve (Modd 5621
Mini MK-IQ housed in a dark model 4300 thermosaned valve oven (Hack Co, Loveland, CO),
and a flame ionintion detector.  A Chrontrol CD-4 timer (Cole Partner Int, Montreal) provided
power and contact closures for switching die Carle valve and starring the GC The cyde time
wis set to obtain a measurement every 15 minutes.  The GC was operated isothennaDy at S7*C
A 30 m by 0-53 mm ID. by 10 \un film thKkmrt, DB  wax rosed silica capillary column (J &
W .Snfmific Inc., Folsom. CA) was used widi a nitrogen (UHP) carrier gas flow me of 10
mUninandanmjectkMporttonperatureof 150°C The GC was calibrated by manual injection
of a certified gas standard (Matbeson Gas Products UL, Whitby. Ontario) which contained
bexaae (1.7 ± O09 ppmX benzene (15 ± 0.13 ppmX and totnene (23 ± 0.12 ppm).

             An artificial source of toluene, two flatware plates each mmahtmg 25 ml of
•ohiene (ACS grade) deployed 1.5 ft from the ah- return intake vent in the furnace room, was
introduced into die house in order to provide a sufficiently high concentration for
with the portable GC. The «t«^ *iy| fan pf tV> tofacne roiKmtration **%> f"u"fr ""d *• **
room after two sepanse introductions of die source. During the first series, aD home windows
were closed and the furnace fan was on. In the second series of measurements, the air exchange
frm «me tamed «m rt>g»Ay »nf^i\^g f^f hf "ff "^ ftffh •*»• ***" mttitm. b drfS mode. hOUSC
sir was nhatrnrrl and fresh air was delivered directly into the furnace room about 2 feet from
the sources.  The temperature inside the boose varied from 22 to 26 *C during the i
                                        183

-------
             Prior to deployment of the toluene source, background measurements (over a 1.5 h
period) of the toluene concentration in the house were made with a portable GC.  The entire
period over which monitoring took place was divided into six periods (Phases I to VI) whose
duration are indicated in parenthesis as follows: Phase I (345 min) - sources present, all windows
closed, air exchange fans off; Phase n (135 min) -  sources removed; Phase m (360 min) -
windows opened; Phase IV (120 min) - fresh sources deployed, windows closed, air exchange
fans turned on; Phase V (330 min) - windows remained closed and air exchange fans still on but
a different source strength was assumed; Phase VI (375 min) - monitoring for additional 105 min.
Measurements of airborne toluene were obtained every 15 minutes except failure of the cycle
timer on the GC during Phase I  and during electrical supply power  failures during  electrical
storms (Phase m, V and VI).

             The emission (evaporation) rate of toluene from the plates used in the house test
runs was determined in the laboratory by measuring die weight of the plate plus toluene at
different times (initially and after  181 and 408 minutes) during a total period which was similar
to  the duration of deployment of  the plates in the  house.  Measurements were made in a
laboratory with a room temperature of 24°C, as compared with test house room temperatures
which varied between 22 and 26°C

             A passive perfluorocarbon tracer (PFT) technique1 developed at Brookhaven
National Laboratory (BNL) was used according to instructions to measure the infiltration rate and
the air exchange rate for the test house.  The PFT sources and samplers were deployed for 24
hours in the family room, living room and a bedroom. The passive monitors were returned to
BNL for analysis and reporting of infiltration and air exchange rates.

RESULTS AND DISCUSSION
             Carbon dioxide concentrations measured 45 minutes after the introduction of the
C0j2 source were 950 ppm at the location farthest  from the point  at which  the CO2 was
introduced and  1020 ppm the other location near the  other end of the  main floor.   The
measurements which differ by about 7 % indicate that the air in the house was well mixed after
45 minutes (with the air exchange fans on) and thus the house could be considered as a single
room for indoor modelling. The PFT measurements in the three rooms had a relative standard
deviation of 10.5%, supported the notion of a well mixed house and confirmed the very tight
construction of the house since die infiltration rate was 45.4 m3 h*1 corresponding to an overall
air exchange rate of 0.068 ACH.

             Figure 1 shows the toluene concentration data obtained in the living room of the
house.  The measurements were segregated into six phases based on the source and house
characteristics.  The increase in toluene concentration (Phase I) and the subsequent decrease
(Phase n) are consistent with the deployment and removal of the source. The period of more
rapid  decline in toluene concentration (Phase HI) occurred because windows were open during
this period.  When a fresh toluene source was introduced with the air exchange fans turned on
                                         184

-------
                                                          OBSERVED

                                                          PREDICTED

                                                          PHASES     - VI
  Figure  1.
    T-     -i-     -T-    -T-     T-
   240      480      720      960     1200     1440
                      MINUTES
Observed  and predicted toluene concentrations
and windows remained closed, the increase in the toluene concentration (Phase IV) was less than
in Phase I when the air exchange fans were not on. The toluene concentration then decreased
even while the source was present but  was almost depleted (Phase V).  The resumption of
measurements after the  disruption due to electrical power failure indicated  that  the toluene
concentrations had decreased to levels near background.

            The U.S. EPA INDOOR model2 was used to simulate the toluene concentration
data as a function of time.  The INDOOR model is a personal computer (PC) based model used
to describe the dispersion of an indoor contaminant into a well mixed single or multiroom house.
Based on the CO2 and PFT measurements, the house was treated as a single room.

            Application  of the model  required  assumptions regarding the number of rooms
modelled,  toluene evaporation  rates (source strength)  in each phase, the volume  of the
recirculating fan, the ventilation between the indoor and outdoor environments and the behaviour
of sinks.   In order to select  values for these model  input parameters, sensitivity runs were
performed in which the  source strength, the rate to sink  term (the first order  rate constant for
deposition/reemission  of toluene in the house) and the air exchange raie  were varied one at a
time.  The sensitivity tests were used to select the optimum model  input parameters.  Where
possible, the values selected were compared with  available  measurements.
                                        185

-------
             The series of measurements was separated into the various phases in order to
delineate periods with different house characteristics and as constant an emission rate for the
source as possible.  Thus in the second deployment of the source, two emission rates were
defined - one for the earlier period after deployment and another for a time period when most
of the toluene had evaporated  The source strength (emission rate) depends on the surface area
of the toluene which is expected to change most rapidly when the source is nearly depleted. The
measured source strength. 7,350 ± ISO mg/h were essentially constant for 52% depletion of the
source. Source strength values ranging from approximately 50% to 200% of the measured value
were used in sensitivity tests. For Phase I, the source strength value that provided a good fit to
the observed data was 8,997 mg/h which is about 22% higher than the measured value.  The
agreement is good considering the measurements were made at 24°C in the laboratory while the
house temperature ranged from 22 to 26°G  A source strength of 13,450 mg/h was used as the
model input for Phase IV when the air exchange fans were on. During Phase IV the source was
deployed only 0.5 m from the air intake for a return air vent in the heating system and thus
would experience enhanced evaporation due to air movement over the plate in which the toluene
was contained.  A source strength of 5380 mg/h was used as the model input for Phase V - the
period  when the toluene had nearly completely evaporated.

             The volume of the recircukting fan was estimated to be 1 m3 which is the nominal
model input value recommended for a residential air handling system. The model inputs for the
ventilation rates associated with the separate recirculating and air exchange  systems were as
follows.  The air recirculating system which remained on throughout the measurements was
assigned a constant air exchange rate of 0.05 ACH.  The ventilation rate attributable to open
windows and to infiltration not attributable to the recirculation of air was arbitrarily assigned to
the air exchange system. For the air exchange system, the model inputs for the ventilation rates
were 0.4 ACH with the air exchange fans on and windows closed, 0.035 ACH with the fans off
and windows closed, and 0.068 ACH with the fens off and windows open. The measured overall
air exchange rate with the recirculation fan on and windows closed was 0.068 ± 0.01 ACH.
             The sink was assumed to be a pure $i«k which means font toluene was not re*
emitted after absorption. The rate to sink term was varied in sensitivity tests from 0 to 0.7 nVb
and a value of 0.7 m/h was found to provide a reasonable fit  No measurements of the rate to
sink term are available for comparison.

             There  was  good  agreement  between the predicted  and  observed toluene
concentrations for all phases of the measurements which are illustrated in Figure 1. During Phase
I, the model underpredicts somewhat The discrepancy between the predictions and observations
is  most marked for  the measurements towards  the end  of Phase I when presumably  the
assumption of a constant source strength is least valid.  A  higher source strength or lower air
exchange rate could result in better agreement towards the end of Phase I but  could result in
overprcdiction of the earlier measurements in Phase L The generally good agreement between
predictions and observations for Phases n and in suggests that the values for the sink terms and
                                         186

-------
the air exchange rates are reasonable.  Opening of the windows (Phase HI) had little effect on
the rate of decrease in concentration between Phases n and m, but it should be noted that die
air exchange rate was nearly doubled (0.035 in Phase n and 0,068 in Phase DO).

             The air exchange fans (Phases IV and V) were effective in lowering the highest
concentration achieved during the deployment of a fresh source similar to that in Phase L The
agreement between the model predictions and observations became progressively worse during
Phase V.  This could be due to underestimation of the sink term. Additional measurements made
during periods when a source is removed or over a longer period of time with a constant source
present would be required in  order to better characterize the sink term. The model predictions
after the middle of Phase V must be regarded as nominal only since the ventilation characteristics
of the house would have been  altered  by the electrical power failure (air exchange  and
recirculation fans off).  The  predictions made for periods with power failure were based on
ventilation values which would have been applied with power on.

SUMMARY
             In general, the INDOOR  model predictions reproduced the  measured indoor
concentrations over a wide range of conditions characterized by source strength and air exchange
rates. The assumption that equated the house to a single well mixed room was justified based
on measurements of the distribution of CO2 introduced in the house and also on the consistency
in air exchange rates measured by the perfluorocarbon tracer method in different rooms in the
house.  The  measured source  strength and measured air exchange rates were found to be
comparable to the values used in model inputs mat gave good agreement between measurements
and Observations. Rgttftr rb*T»M*riT*tinn nf th* dnlf Tfrm .10^ in fly TTWH fo yffnmmmfed fnr
future studies.

ACKNOWLEDGEMENTS
             The cooperation and assistance of Mr. P. Fellinis acknowledged. This project was
funded by the Panel on Energy Research and Development and  Concord Environmental
Corporation.

REFERENCES
1. RJ*. Dietz, T.W. D'Ottavio, and R.W. Goodrich, "Multizooe Infiltration Measurements in
Homes and Bmldinys determined with a Passive Perflunmcaihnn Tracer Method." in Proceedings
of the A^nCTJcan Societv of Heatinc Refnmatinft and Air fV»Hifionfng BrmiiiMn' Semiannual
Mafia*, Honolulu. HI, U.S.A., 1985, 38 pages.

2. L£. Sparks, Indoor Air  Model  Version 1.0..  EPA  600/8-88-097a, U.S. Environmental
Protection Agency. Research Triangle Park. NC 27711 (1988).
                                         187

-------
FIELD TEST AND LABORATORY EVALUATION OF A LIGHTWEIGHT, MODULAR DESIGNED,
PERSONAL SAMPLER FOR HUNAN BIONARKER STUDIES

Ron Williams and Lance Brooks
Environmental Health Research and Teating, inc.
RTP, NC 27709

Virgil Harple
MSP, Inc.
Minneapolis, MN 55455

Robert Stevens and Joellen Lewtas
U.S. Environmental Protection Agency
RTP, NC 27711

      The U.S. EPA is currently evaluating a lightweight, modular designed,
personal sampler for use in human biomarker studies.  This sampler has direct
application for capture of polynuclear aromatic hydrocarbons (PAHs),
environmental tobacco smoke (BTS), as well as particles and vapor phase
components from a variety of pollution sources.  This adaptable sampler consists
of an inert inlet that allows for the collection of both 2.5 micron as well as
larger particles, a three stage filter pack for particle collection, a denuder
for vapor phase capture of select species as well as a resin chamber for
collection of secondary vapor phase analytes.  All sections of the sampler are
interchangeable, allowing for their addition or removal as dictated by the study
design.  Storage of collected analytes directly within the samplers' sections
are possible due to inert sealing plugs.  The samplers' sections are constructed
out of aluminum or teflon with all contact surfaces fabricated out of teflon,
deactivated stainless steel or borosilicate.  A small personal sampling pump has
been found to match the sampler, permitting the field testing of complete units
weighing less than 700 grams.  Sampling periods as long as 24 hours are possible
under certain conditions.  The inlet and impactor assemblies were found capable
of 2.5 micron particle cut points at flows as low as l.O L/min.  Particle losses
were negligible for particles larger than 2.0 micron.  Field evaluation results
from capture of select particle and vapor phase species is presented along  with
a discussion on the versatility of the design.
INTRODUCTION

     The U.S. EPA is currently involved in a number of studies where personal
biomarker data is essential for exposure assessment.  Capture of environmental
tobacco smoke (ETS), polynuclear aromatic hydrocarbons (PAHs), acid aerosols,
and vapor phase species allows exposure data to be correlated with monitoring of
human biomarkers. These include DMA adducts, urinary metabolites, respiratory
effects, etc.  Personal monitoring is generally necessary to document individual
microenviromnents.  These efforts require use of active or passive monitors
which are either direct reading or require chemcial extraction or analysis.
Choice of sampling devices is generally guided by expected analyte
concentration, availability of sampling equipment and comfort factor of the
respondent wearing any device.
      An effort was undertaken to develop a lightweight, modular sampler having
flexible capabilities.  Key parameters of the device included fabrication of *»
acceptable flow acceleration jet, a respirable and non-respirable particle
collection system, a multistage filter pack, resin chamber for capture of vapor
phase species, a denuder assembly , inert sealing plugs to isolate captured
species and finally a pump connection port.  Fabrication prototypes had to be
                                       188

-------
modular (using male and female threaded ends) BO that various assemblies could
be interchanged as required by any biomarker study.  Inertnese of all contact
surfaces would have to be assured for sampling-integrity and module sealing
plugs capable of both abort and long term storage were required.


MATERIALS AND METHODS

      Key components chosen in the minipersonal samplers' design are displayed
in Figure 1.  A teflon coated aluminum inlet having a particle elutriator and an
acceleration jet was developed.  Aluminum was utilixed for the inlet and proved
to be a strong, durable, lightweight material capable of being milled out to
exact tolerance of dimensions and angles.  Teflon coating of the inlet was
needed to achieve inertness using a  special bonding process.  The elutriator
aection was 23.0mm long with an i.d. of 6.3mm.  The acceleration jet was 9.5mm
long with an i.d. of 2.0mm.  A distance of 5.0mm between the end of the
acceleration jet and the impactor surface is maintained upon connection of the
inlet to the impactor assembly.  All design tolerances were found to be within
0.5mm.  The theory behind the design of the inlet and impactor has previously
been discussed.1'2  Fabrication using the above dimension* allowed for a face
velocity of S.lcm/sec to occur when a flow rate of 1.5 t/min was pulled through
a 2.5cm circular filter downstream.
      A teflon impactor assembly, sealed within a molded bakelite thermoplastic
threaded sleeve allowed this module to be securely positioned downstream of the
inlet at a reproducible distance.  A 4.5mra borosilicate porous glass impactor
disc (removable) elides into a compression cavity within the impactor assembly.
The surface of this disc is coated with a solution of polyethylene glycol (PBG)
(400/600) dissolved in dichloromethane. Calculations were employed in the
production of the impactor assembly so that when a flow rate of 1.5 L/min
occurred, particles with an aerodynamic particle *i«* of less than 2.Sum would
be diverted past the impactor plate to an awaiting filter surface.  The
dimensions and theory behind these calcultions has been reported.3   Four flow
portals, aerodynamically designed and centered around the impactor plate diverts
these fine particles toward the filter pack assembly.  Large particles (>2.5) urn
are focused onto the center of the impactor disc where they are retained by the
PEG oil.
      Annular denudere were designed as a part of the sampler.  These devices
have been successfully used to capture vapor phase inorganics.1"2  Vossler et
al.,2 has fully explained the principles behind a larger version of  the
approach we employed in denuder technology.  A modification of the above was
utilized in that a second annular was placed within the denuder assembly to
augment its ability to serve as an analyte sink.  Annular denudere were prepared
from open 11.0 cm sections of borosilicate glasa  (15.Omm o.d., 10.0cm i.d.)
complete with male threaded ends.  Two annular rings were affixed within each
tube.  The length of each ring was 7.0cm.  There was a 1.0mm space between both
the inner wall of the the tube and the outer annular as well as between each
annular ring.  Annulars were prepared using open 8.0mm o.d.  (outer ring) and
aolid 4.0mm o.d.  (inner ring) borosilicate glass rods.  A teflon coating of
either 25mm  (inlet) or 20mm  (exit) was applied to the tubee open cylindrical
space to allow entering gas to expand uniformally and thus flow evenly through
the annular*.  Teflon coating provided an inert surface ao that this portion of
each denuder would not act as an analyte sink. The threaded end* permit more
than one denuder to be used in series when an inert bakelite
thermoplastic/teflon coupler i* used.  These ends al*o permit simple connections
to filter pack*, resin chamber*, etc to be performed.  Teflon lined threaded
cap* seal* the denuder *o that reactant coating,  analyte extraction or simple
dry etorage can be performed.  A complete description on denuder coatings and
                                       189

-------
 analyta recovery has bean reported elsewhere.2  The denuder deacribed here is
 presently undergoing laboratory evaluation and no data will be discussed here.
      A two piece threaded teflon filter pack was fabricated so that a minimum
 of three 25mm diameter  filters could be housed simultaneously.  The filter pack
 inlet is connected via  thread* to either the inlet, impactor, denuder,etc.
 Flow enters the pack through an open 9mm i.d. portal which immediately flairs
 out to a 45° angle to allow for particle expansion to ensure uniform filter
 disposition. The lower  section of the filter pack contains a 26.0 cm recessed
 housing which allows for alternate layers of teflon O-rings, filters, and
 paasivated (teflon coated) stainless steel support screens to be utilized.  One
 to three filters may be used with compression and sealing provided by the O-
 rings upon closure of the upper and lower portions.  Threaded teflon caps permit
 the filter pack to be sealed before or after sampling.
      A 5.0 cm3 chamber (1.0cm wide X 5.0 cm length}, cored out from a solid
 teflon block is the central component of the resin chamber.  A volume of this
 size was chosen from internal data which revealed that 24 hour samples
 (82.0L/min) using XAD-2 would not experience analyte breakthrough in most indoor
 air environments.  The  resin chamber has a built in lower stainless steel
 retaining screen which  is utilized to allow resin loading into the unit to be
 contained during loading.  The threaded upper unit also contains a removeable
 stainless steel screen  which permits the introduction of resin into the chamber.
 Resin containment takes place when the two halves are threaded together with a
 viton O-ring providing  an additional sealing mechanism.  All flow contact
 surfaces are inert and  were designed so that solvent desorption of captured
 analytes could take place within the original collection assembly.  Even the
 resin itself can be extracted and made ready for use by simply loading and
 sealing the chamber followed by solvent extractions, resin drying,etc without
 ever having to remove resin from the holder. Air flow (vacuum) is supplied to
 the resin chamber or any chosen component by means of a teflon hose barb
 connected to a threaded cap.  A compressible teflon O-ring assures good
 connection of the hose  barb to any module.
      The inlet, impactor, denuder tube, and filter pack assemblies were tested
 for particle collection efficiency using a vibrating orifice monodispersed
 aerosol generator (VOMAC).  Monodispersed particles of  fluorescent uranine dye
 tracer added to oleic acid were brought into a completely assembled unit using a
 flow rate of 1.5 L/min.  Trapped or adhered particles were removed separately
 from various contact surfaces (inlet, impactor, denuder,etc) using a wash of
 0.001 N sodium hydroxide.  Quantitation of fluorescence intensity of each wash
 allowed for collection  efficiencies, and aerodynamic particle cut points to be
 determined.  Evaluation of the filter pack and resin chamber in field trials i*
 discussed later.

 RESULTS AND DISCUSSION

      Collection surfaces and particle losses associated with aerodynamic
 particle sice are shown in Table 1.  Using a flow rate of 1.5L/min, 81.7% of
 0.9um sice particles were captured by the filter pack.  There was some adhesion
 of particles on the impaction and denuder assemblies (8.3 and 10.0%
 respectively).  An overall loss of 10.0% total particles occurred under the test
 conditions.  Incremental testing of larger particle sizes revealed that a sharp
 cut point between 1.5 and 2.Sum existed. This is evident in Increasing higher
 collection values for the impaction surfaces with decreasing values for the
 filter assembly.  Data  at 2.58um revealed that 98.2% of the particles entering
the sampler were collected by the impactor with only a 0.2% loss overall. This
was expected due to the theory utilized in the prototypes' design.  Figure 2
reveals the collection  efficiency versus aerodynamic particle diameter at 50%
 (dpso)  for flows of 1.0, 1.5, and 3.0 L/min.  Sharp cut points were established
at 2.1,  1.7,  and 1.2um  at these flows respectively.  The above evaluation
                                       190

-------
indicated that design of the inlet, impactor, and filter pack successfully net
all fabrication criteria.
      Evaluation of the filter pack in a field environment waa aleo perforated.
Figure 3 ehowa the recovery of vapor phase nicotine (bound to a filter surface)
versus collection using a passive  (diffusion) sampler as part of a monitoring
effort of ETS.  The example given reveals daily nicotine concentrations of a
single smoker monitored 24 hours/day for one week.  His daily exposure is seen
to flunctuate with an overall average of 2.30ug/m3 nicotine free base.  This
compares favorably to the passive diffusion monitor worn for the same period by
the individual (2.6ug/m3). The filter pack was found easy to use with loading
and unloading of the assembly quickly accomplished.
      Field testing of the minipersonal sampler has also included its use in
occupational monitoring to supplement human biomarker studies.  Respiratory
particle levels within a Czechoslovakian coke oven can be seen in Figure 4.  Ho
personal protection (filter masks) was worn by the workers even though
respiratory sized particles were found at levels as high as 1000ug/m3.  This
figure reveals the difference encountered by workers who are heavily exposed
(topside battery locations) as opposed to those who are located at other parts
of the plant (mechanics for example).  Personal data like this allows for direct
correlation with biomarker (such as DMA adducts from blood) that would not be
possible if stationary monitors were used only.  Even among the topside workers
there is a wide variation in exposure directly resulting from employment duties.
      Figure 5 gives an indication of field evaluation of the minipersonala'
resin chamber.  A mass of 1.9 grams XAD-2 was loaded into the chamber as part of
12 hour shift monitoring at the above plant.  Priority 16 PAH exposures were
totaled for 12 workers from both filter (particles) as well as vapor phase
(resin chamber) capture.  Ratios of vapor phase to particle PAR concentrations
vary depending upon worker assignment.  Workers 1,2,8,9,10,11, and 12 have jobs
requiring them to work on the topside battery itself.  Concentration of vapor
phase PAHs are extremely high here(50-274 ug/m3) due to ambient temperatures
exceeding 33°C with open air release of vapors associated with the use of coal
in the coking process.  The plant has no worker or environmental engineering
control systems.  Efforts are in process to possibly correlate these ambient air
exposures with urinary PAH metabolite biomarker data.
      Laboratory evaluation and field tests have shown that EPAs' minipersonal
sampler can effectively meet sampling requirements for biomarker studies.  An
•ntire unit consisting of an inlet, impactor, filter pack, denuder, loaded resin
chamber and a personal sampling pump capable of 24 hour operation at 1.7L/min
weighs less than 1.5 Ibs.  Storage and closure systems using teflon caps have
proved to be reliable. Durability of each device has been tested where units
were worn by individuals for 14-21 continuous days with only change in filters
and XAD-2 resin, and pump batteries necessitated by the study design.  Use of a
modular approach has reduced  fabrication cost and has eliminated the need of
adapters, tubing,etc to be required to connect multielement sampling trains for
personal monitoring.
     WLEOOEMEMTS

      This work was supported by U.S. EPA contract 68-010148 to BHRT, Inc.
Authors wish to thank Jason Meares and Betsy Crownover for their technical
assistance and Charles Stone of University Research Glassware for prototype
manufacture and technical assistance with the design.
      NCES
j.  v. Marple, K. Rubow, H. Turner, J. Spengler,*Low flow rate sharp cut
iapactors for indoor air samplingidesign and calibration* JAPCA 37s1303 (1987).
                                       191

-------
2.   T. Voaaler, R.  Stevens, R.  Paur, R.  Bauogardner,  J. Pell,"Evaluation  of
Improved inlets and annular denuder systems to measure inorganic  air pollutant*"
Atmoa. Environ. 22:001  (1983).
3.   0. Radar,  V. Marple,  "Effect of ultra-stokasian drag and particle
interception on impaction characteristics" Aerosol sci. Technol.  4(141  (1985).
                             Table I. Particle collection of impartor and other nufacei.


                               COLLECTION EFFICIENCY (ImpaclOr t Accesiorln)

                                   Mtt•
                               Dp   iimi. n»atuo« 0«iudw« ^^  Colirton  Total
                             (microns)
                              0.91    0.0    13    104   117    9.3   10-0

                              1.50    1.0   M.e    4.9   0*3   M.6    «J>

                              1.M    2.1   710    0.»   tta   TU    2.4

                              2.K    0.0   H.1    04   11.S   OL1    0.0

                              LIB    0.0   M.2    OJ    1.6   9U    OJ

                              5,00    0.0   »90    0.1    OJ   M.4    0.1
                                            192

-------
  INLET      IMPACTOR
      ANNULAR DENUDER

              ll	I \ \ \l
FILTER PACK
RESIN CHAMBER      HOSE BARB
 Figure 1.  Simplified schematic of EPAs1 minipersonal sampler.
                          193

-------
                      0 • 10 lpo»
                             Q.I 51pm


  • I     •*  u   U     1      III
         Anodynwnto Pwllc* Domain, mknxu
        Dp (SO)    • 3 0 I/mm • i .2 rraoww
                0 1 Stmvn • l.Tmloonc
                010 l/m(Tt .21 mlawu

F«ure 2.  Coll«lion efTiciency venui pulkfc diuncttr.
                                                            PERSONAL NICOTINE EXPOSURE
Figure J.  Cipcurt of nwrounc by Ihc fillM pick inanbly
                                                          PARTICLE AND VAPOR PHASE PAH CONCENTRATIONS
     FINE PARTICLE EXPOSURE
           OSTHAV* COKE PLANT WOOKER5
  Fifure4.  Field capture of cake oven pinkuluc miner.
                                                               Tigurc S  Field cmplurt of pirticle and vapor phmie PAHl.
                                                  194

-------
       Session 7
   Source Monitoring
Joseph Knoll, Chairman

-------
            DEVELOPMENT OF A TEST METHOD FOR
             CHLORINATED ORGANIC COMPOUNDS

            Bruce A. Pate, Max R. Peterson and R.K.M. Jayanty
      Research Triangle Institute, Research Triangle Park, NG 27709

                              ABSTRACT

        A method was developed for the measurement of stationary source
emissions of chlorinated organic compounds as chloride. A modified volatile organic
sampling train (MVOST) was used for the collection of samples.  The MVOST was
tested in the laboratory and at a field site.
        An extensive laboratory evaluation was conducted to determine which were
most suitable for the adsorption of chlorinated organics. Supelpak-2 (an XAD resin)
was chosen as the primary sorbent because it gave a high percent recovery for the test
compounds. Carboxen 563 was used as a backup due to its affinity for highly volatile
compounds (e.g., vinyl chloride).  Based on the laboratory evaluation results, it was
recommended that an impinger containing  a 0.1N NaOH solution be used for the
removal of inorganic chloride, hexane be used as the desorption solvent, and an
electrolytic conductivity detector be used to measure the chloride.
        A field evaluation of the MVOST was performed on the emissions from a
scrubber vent. The sampling matrix consisted primarily of chloromethanes, with
chloroform  and carbon tetrachloride as the major constituents. Four MVOSTs were
run in parallel for 12 runs (48 samples total). Statistical analysis of the samples
demonstrated an excellent precision among the four trains. The difference of each
train  as a percentage of the mean was less then 5% with a standard deviation that
also was below 5%. The method was found to be sensitive down to the low ppm range.

                            INTRODUCTION

        A modified volatile organic sampling train (MVOST) was developed to
measure stationary source emissions of chlorinated organic compounds as chloride.
This method is designed to sever as a screening test to determine if further, more
elaborate testing of a source is required. If a plant is required to reduce chlorinated
organic emissions by a specified amount, this method can be used to determine if the
lower emission level has been met.
        The MVOST  is based on the volatile organic sampling train (EPA Method
0030). A heated probe is used to collect gaseous emissions from a stationary source.
The sample is first bubbled through a sodium hydroxide solution to remove inorganic
chloride. Organochlorine compounds are then trapped on sorbent beds of Supelpak-2
and Carboxen 563. The chlorinated organics are desorbed in hexane and analyzed
with an electrolytic conductivity detector (E1CD).
        This method has been evaluated in the laboratory and sampling parameters
have been established. The results of both laboratory and field studies are discussed
in this paper.
                                    197

-------
                      LABORATORY EVALUATION

Laboratory Apparatus

        The laboratory apparatus used to evaluate the method is shown in Figure 1.
The organochlorine and diluent nitrogen flows were controlled by Tylan mass flow
controllers. The diluent nitrogen was bubbled through a flask containing deionized
water. The HC1 flow was set using a regulator. The gases were mixed in a 1-L Kimax
dilution flask and passed through a 3-port manifold. The dilution flask and manifold
were enclosed in an insulated box which could be heated to the desired temperature.
        Sampling conditions similar to the VOST method, i.e., 1.0  Lpm for 20
minutes were tested. These runs were performed using Thomas diaphragm pumps,
and when possible, a MVOST unit.  The MVOST can be seen in  Figure 2.  MVOST
sorbent tubes were used for most of the work. A MVOST sorbent tube is identical to a
standard VOST tube except one end has a #7 Ace-thred joint.  These tubes were
developed to expedite the packing of the sorbent tubes.

Inorganic Chloride

        The primary inorganic chloride species  of concern is hydrogen chloride.
Several chloride traps were tested for their ability to remove HC1 while not adsorbing
any organics.  The first series of tests examined  solid  lithium hydroxide, sodium
bicarbonate and calcium hydroxide. None of these three traps were suitable because
they removed organics while allowing HC1 breakthrough.  Iron and zinc shavings
were also tested but allowed significant breakthrough. Impingers filled with
deionized water and 0.1N sodium hydroxide were compared.  The NaOH solution was
selected because it removed 100% of the HC1 whereas the deionized water removed
only 90-100% of the HC1 present.

Sorbents

        Several sorbents were tested for their trapping efficiency of chlorinated
organics. The sorbents tested were carbotrap, Tenax, Supelpak-2 (a purified form of
XAD-2), petroleum based charcoal, and Porapak Q. A mixture of dichloromethane,
methyl chloroform and trichloroethylene was used as the test gas and was fed into the
dilution system (Figure 1) where a concentration of 25 ppm Cl was established. The
sorbents were desorbed in hexane and the desorption solution was analyzed. Since
only a four-foot section of capillary column was used, no separation of the organics
was observed, resulting in the data being reported as total chloride.  Carbotrap and
Supelpak-2 had the highest trapping efficiencies at  about 90%. However, Supelpak-2
was selected as the primary sorbent since it had a larger breakthrough volume.  Two
sorbents, Carbosieve S-III  and Carboxen 563, were tested as a possible backup to the
Supelpak-2. The purpose of the backup sorbent was to collect highly volatile species
                                    198

-------
that may be present at a site.  While neither sorbent had satisfactory recoveries by
solvent extraction, the Carboxen 563 was selected because its recovery was slightly
higher.

Detector

         Two modes of detection, electron capture (ECD) and electrolytic conductivity
(E1CD) were used for this study. Both detectors gave satisfactory results in most
cases, but some problems did arise with the use of the ECD. The most serious
problem was that the response of the ECD was compound dependent, i,e., different
compounds had different response factors on the ECD. This problem does not occur
with E1CD  since all chlorinated organics are converted to the same species, HC1,
before analysis. The analytical system employed consisted of a gas chromatograph
injection port (from a Perkin-Elmer 3920} attached directly to the reactor assembly of
an QIC 4420 electrolytic conductivity detector.  The injection port was wrapped in
heating tape to ensure rapid volatilization.

                          FIELD EVALUATION

         The test site was a vent (6  inch ID) from a process where chlorinated
organics were vented from three holding tanks. The gas stream was approximately
90° Fahrenheit. The major constituents of the gas stream were carbon tetrachloride
and perchloroethylene. No inorganic chloride was observed since the sampling port
was downstream from a sodium hydroxide scrubber.
         Four modified volatile organic sampling trains were run in parallel for
twelve runs (48 samples total).  MVOSTs VI and V7 were run as one pair and
MVOSTs V2 and V9 were run as a second pair. The two probes of each pair were
taped together and placed perpendicular to the vent and to the other pair at the same
location.  A pre-survey at the site indicated that the chlorinated organic levels were
very high (700-1000 ppm Cl). To help prevent breakthrough, the sampling volume,
normally 20 L, was reduced to 10 L by  decreasing the sampling rate from 1.0 Lpm to
0.5 Lpm.
         The field test results shown in Table 1 indicate a significant difference
between the two pairs. The data for the first pair, consisting of MVOST trains VI and
V7, showed excellent agreement as one would expect from replicate samples.
However, the data  for the second pair of trains, V2 and V9, showed very poor
agreement. After the tenth run, it was observed that the probes for the second pair
were not positioned correctly. The probes had been accidentally knocked out of
position prior to the first run so that the probes tips were sitting near the lip of the
sampling port for runs one through ten. This positioning led to a significant amount
of ambient air being collected resulting in the lower than expected concentrations.
The positioning problem was corrected after the tenth run, and in runs eleven and
twelve the second pair produced results similar to those of the first pair.
                                    199

-------
                       FIELD TEST CONCLUSIONS

         The results from the first VOST pair indicate that this method has very
good precision. However, there were two shortcomings of the field test (apart from the
poor data of the second pair) which will be addressed in the next field test. First, the
accuracy of the method needs to be determined by alternately spiking each MVOST
pair (in accordance with EPA Method 301), Secondly, a source containing inorganic
chloride  needs to be tested to determine what effect it may have on the MVOST
method.
          Nitrogen
                                                           . Sampling
                                                           " Ports
                   Hydrogen
                   Chloride
                   In Nitrogen
                                             Chlorinated
                                             Organics in
                                             Nitrogen
                    FIGURE I.   LABORATORY APPARATUS
                                    200

-------
             Inlet
    Knockout Trap •-
Supelpak-2/Carboxen
    (Sorbent  Tube)
       Supelpak-2
    (Sorbent Tube)
 Silica Gel  Drier
                         1
      To Sample Pump
• NaOH(aq) Impingers
  FIGURE 2.   MODIFIED VOLATILE ORGANIC SAMPLING TRAIN
                                                         MRP, MVOSTOS.CDR. 6I2U92
                               201

-------
TABLE 1. FIELD TEST RESULTS
          VOST PAIR VI AND V7

Run
1
2
3
4
5
6
7
8
9
10
11
12




Run
1
2
3
4
5
6
7
8
9
10
11
12


Gas Concentration
(ppmCl)
Train VI Train V7
168.00
241.31
207.04
333.74
396.62
326.37
310.21
376.20
374.89
278.54
169.79
220.28



Gas Concentration
165.72
240.28
205.57
335.54
419.04
347.19
322.32
366.66
383.90
291.58
174.38
219.25
average
std. dev.
VOST PAIR
(ppmCl)
Train V2 Train V9
48.53
64.89
32.73
66.68
233.33
142.77
51.56
42.92
30.04
69.40
200.58
214.35


124.91
169.55
119.05
188.80
329.84
231.19
129.15
184.59
109.05
138.33
211.80
241.85
average
std. dev.
Difference
(V1-V7)
2.28
1.03
1.47
-1.8
-22.42
-20.82
-12.11
9.54
-9.01
-13.04
-4.59
1.03
-5.70
9.44
V2 AND V9
Difference
(V1-V7)
-76.38
-104.66
-86.32
-122.12
-96.51
-88.42
-77.59
-141.67
-79.01
-68.93
-11.22
-27.50
-81.69
34.36
Difference as
% of Mean
1.37%
0.43%
0.71%
0.54%
5.50%
6.18%
3.83%
2.57%
2.37%
4.57%
2.67%
0.47%
2.60%
1.94%

Difference as
% of Mean
88.08%
89.29%
113.74%
95.60%
34.27%
47.29%
85.87%
124.54%
113.61%
66.36%
5.44%
12.06%
73.01%
38.32%
            202

-------
    FIELD VALIDATION OF TWO CALIFORNIA AIR RESOURCES BOARD
               (CARB) STATIONARY SOURCE TEST METHODS
                             Catherine Dunwoody Lentz
                                Cynthia Castronovo
                                   Gloria Lindner
                                 Angus MacPherson
                            California Air Resources Board
                          Monitoring and Laboratory Division
                                   P.O. Box 2815
                               Sacramento, CA 95812


ABSTRACT
     Field validation tests were conducted by the California Air Resources Board (CARB) staff
for two proposed stationary source test methods, CARB revised Method 429, "Determination of
Polycyclic Aromatic Hydrocarbons (PAH) Emissions from Stationary Sources" and CARB draft
Method 436, "Determination of Multiple Metal Emissions from Stationary Sources". The United
States Environmental Protection Agency (EPA) has proposed Method 301, "Reid Validation of
Emission Concentrations from Stationary Sources" for conducting such field validation tests. The
field validation tests conducted by CARB staff differed from EPA Method 301 requirements in
several aspects. Precision was estimated for both methods.  Accuracy and stability were estimated
for Method 436.
     Precision values for revised Method 429 ranged from ±7% for 2-methylnaphtbalene to ±64%
for benzo(ghi)perylene.  Precision values were less than ±50% for 11 of the 18 compounds for
which precision values could be calculated. Precision values for Method 436 ranged from ±17%
for selenium to ±80% for chromium. Precision values were less than ±35% for 6 of the 7 metals
for which precision values could be calculated.  Method 436 samples were determined to be stable
for 45 days after sampling. Method 436 samples did not demonstrate a statistically significant bias
based on anaryte spiking results.

INTRODUCTION
     The California Air Resources Board (CARB) staff have conducted validation tests for two
proposed stationary source test methods, CARB revised Method 429, "Determination of Porycydic
Aromatic Hydrocarbons (PAH) Emissions from Stationary Sources" and CARB draft Method 436,
"Determination of Multiple Metal Emissions from Stationary Sources'. CARB staff plan to propose
these test methods for CARB adoption in  Fall 199Z  The validation tests were designed to meet
the requirements of the Federal Environmental Protection Agency's (EPA) proposed Method 301,
"Field Validation of Emission Concentrations from Stationary Sources*.
     EPA Method 301 describes several test designs for determining the accuracy and precision
of results from stationary source emission tests. Several modifications to the test designs were
necessary to achieve CARB objectives. The  objectives of CARB staffs tests were to validate
CARB test methods prior to adopting the methods as California regulations, and to determine the
feasibility of conducting validation tests  using EPA Method 301.
                                        203

-------
 EPA METHOD 301 REQUIREMENTS
      EPA Method 301 provides three approaches for validating emission measurements.  The
 approach used depends upon the characteristics of the test method to be validated.  The first
 approach is isotopic spiking. This approach can be used for gas chromatography/mass spectrometry
 methods when isotopically labeled target analytes are available.   Either  six paired or three
 quadruplicate sampling trains are required. Accuracy of the test method is determined by the
 recovery of the labeled material.  Precision is determined by comparing the  replicate runs.
      The second approach is to compare the proposed test method to a validated test method.
 This approach can be used when a validated test method  exists.   Either  nine paired or four
 quadruplicate sampling trains are required.  Accuracy is determined by comparing the proposed
 test method  results to the validated test  method results.   Precision is determined using the
 differences between the proposed test method and the validated test method results.
      The third approach is analyte spiking. This approach is used when the  first two  approaches
 are not feasible.  Six quadruplicate trains, half  spiked with the target analyte,  are required.
 Accuracy is determined by subtracting the results of the unspiked trains from the spiked trains and
 comparing the resulting value to the known concentration of the spike. Precision is determined
 by comparing the results of the unspiked pairs.

 CARB TEST DESIGN
      CARB  staff chose to run the field validation tests at an oil-fired steam generator in Taft,
 California.  This source was selected because it is  known to  emit both metals and PAH in
 detectable quantities and because the source owner was willing to cooperate by allowing CARB
 staff on site for the four week duration of the tests.  Due to the configuration of the source and
 the resultant space limitations, it  was not feasible to maneuver a quadruplicate sampling train-
 Therefore, CARB staff were not able to follow the exact procedures outlined in EPA's proposed
 Method 301,  which requires quadruplicate sampling trains for analyte spiking.  CARB staff used
 paired trains, configured with  one probe slightly longer than the other so that  the filter boxes were
 staggered and therefore the probe assemblies could fit inside a 6" diameter  port. Samples were
 collected at a single point within the stack (no stack traverse).

 Revised Method 429
      CARB  staff did  not use the approaches outlined in EPA Method 301 to determine bias for
 revised Method 429.  Instead, a laboratory analyte spiking study was conducted to estimate the
 accuracy of the method.  Although the  isotopes  needed to conduct  field  isotopic  spiking are
 available for the target PAH, they  cannot be  used for this purpose because they  cannot be
 distinguished from the quantitation standards required by the revised Method 429 isotope dilution
 technique.  The isotope dilution technique, which uses isotopically labeled analogues of the targe*
 PAH to quantify the target PAH, provides a significant advantage over other  internal standard
 techniques in that there is an  automatic correction for extraction and cleanup losses. CARB stafl
 were not able to compare revised Method 429 against a validated test method because no validated
 test method exists for the target PAH. Analyte spiking was not used to determine bias because this
 would have required an additional six paired sample trains, and budget constraints restricted the
 number of field tests and analyses which could be  conducted.
     Revised Method 429 precision was determined using six paired trains. Two field blanks were
 taken. Field  blanks are an important requirement  of CARB test methods because they provide a
 check of background and/or contamination levels  of the target analytes.
     The laboratory analyte spiking study was conducted by spiking XAD-2  resin cartridges with
 aliquots of native PAH target  analytes and isotopically labeled surrogate standards. Zero air was
sampled through four  sampling trains in the laboratory. The objectives of this study were to
                                           204

-------
determine how effectively the sampling train retains the native PAH spike added to the XAD-2
resin prior to sampling and how accurately the recovery of the labeled surrogate standards reflects
actual recovery of the target PAH. Although actual accuracy is likely to be different in a field test
where sample matrix effects are a factor, the laboratory study was designed to allow CARB staff
to isolate the two factors identified above under laboratory conditions.

Draft Method 436
     A total of 14 paired sampling trains were used for the draft Method 436 validation test. Six
paired trains were used to determine precision. Analyte spiking of four paired sample trains was
used to estimate bias.  The analyte spiking was conducted using filters spiked with two levels of
metals  (corresponding to  EPA's audit filters for metals) and a mercury impinger  spike.  A
corresponding  field  spike (no emissions sample drawn) was conducted in conjunction with the
analyte spike sampling runs.  A stability  study was conducted on four paired sample trains  by
analyzing one  sample  train in each pair immediately after sampling and analyzing the second
sample train in each pair one month later. Two field blanks were taken to check for background
leveb of metals or contamination.
     Four paired trains each were used for the bias and stability studies instead of six (as required
by Method 301) because of time and budget constraints. Although no validated test method exists
for multiple  metals, CARB staff did compare draft Method 436 to seven currently adopted CARB
single metal methods in a field validation program conducted over the past two years.  Through
this program, source testers conducting tests for California's Air Toxic "Hot Spots" program were
allowed to use draft Method 436 if they agreed to conduct parallel tests using a  single  metal
method. These results have been presented previously1.

RESULTS-Revised Method 429
     The percent relative standard deviation (%RSD) results for the six paired sample trains are
presented in Table I. These results were calculated using Equation 1. It is important to note that


                           USD = = x 100,
 Equation 1
                                   _
                                   X = Average Concentration
                                   d - difference between pairs
                                   n * number of pairs

13 compounds had an average field blank value  greater than 50% of the average field sample
value.  Revised Method 429 requires that data be flagged if the field blank value is greater than
20% of the field sample value.  Based on the results  of a laboratory resin blank, CARB staff
determined that the high field blank values were primarily due to resin contamination. CARB staff
plan to evaluate a resin cleaning procedure and require such a procedure in revised Method 429.
     Percent RSD was less than 50% for 11 of the 18 compounds for which %RSD could be
calculated.  Three of the %RSD values were greater than  100%, but two of  these values were
calculated using less than 6 pairs of data. One compound, acenaphthylene, had a %RSD of 175%.
This was due to one sample pair which demonstrated an order of magnitude difference. Without
this  sample pair,  the  %RSD value is 62% (n =  5,  average  concentration = 8J  ng/dscm).
Unfortunately, results for the laboratory  analyte spiking  study were  not available prior  to
publication of this paper.
                                           205

-------
RESULTS-Drafl Method 436
     Percent RSD values for 7 of the 15 metals (As, Cr, Cu, Mn, Ni, Se, Zn) are presented in
Table II.  Percent RSD could not be calculated for 5 metals (Ag, Be, Cd, Sb, Tl)  because the
results were below the detection limit. Percent RSD was not calculated for the remaining 3 metals
(Ba, Hg, Pb) because of high reagent blank corrections.
     Results for the analyte spike samples and the field spikes are presented in Table III.  Biases
(determined from the analyte spike samples) could be tested for statistical significance for only 7
metals where precision values could be calculated.  Silver demonstrated the lowest analyte spike
recovery at 8%, yet the field spike recovery was excellent at 104%. GARB staff has no explanation
for the apparent loss of silver.  Because silver is not currently a concern as a toxic metal, CARB
staff may remove silver from the multiple metals method before the method is adopted.  The
analyte  spike recovery was also  low for selenium (37%) while the field  spike recovery was
acceptable (86%).  Selenium is of concern as a potentially toxic metal, however, and therefore will
be retained in the final version of Method 436 as there is no alternative method at this time. A
statistically significant bias was detected for arsenic. However, data collected from CARB staffs
field validation program using source test contractor results1 was updated to add  9 additional
arsenic data pairs collected over the past year and demonstrated that arsenic results obtained using
draft Method 436 samples are not significantly different from arsenic results obtained using the
currently adopted CARB Method 423 (Determination of Inorganic Particulate and Gaseous Arsenic
Emissions-similar to EPA Method 108).
     Results for the stability study tests are presented in Table IV, Percent differences between
samples digested and analyzed  10 days after sampling and samples digested and analyzed 45 days
after sampling were less than 10% for 6 of 10 metals.  Lead demonstrated a -117% loss (Le., a
117% gain) in concentration. However, this value was significantly affected by one data pair which
demonstrated a 14-fold increase in concentration over  the storage period and which was likely
affected by contamination.  Using a Student's t-test, none of the average differences  between the
first and second sample analyses were statistically different from zero at the 95% confidence level

CONCLUSIONS
     Analyte spiking is the only field validation approach that could be used for CARB revised
Method 429 and draft Method 436. The use of quadruplicate sampling trains as required by EPA
Method 301 under this approach was not feasible in CARB staffs field validation studies. CARB
staff modified the Method 301 analyte spiking approach to use paired trains. This modification
requires a greater number of sampling runs in order to gather both bias and precision data.  Du*
to budget constraints, it was not possible to determine revised Method 429 bias using field studies.
     CARB revised Method 429 demonstrated acceptable precision values (less than ±50%) for
11 of 18 compounds.  However, only 13 of the 18 compounds had average field blank values greater
than 50%  of the average field sample  value.  Therefore these precision values  may not be
representative of precision values for field samples with higher concentrations relative to the field
blank. Because the high field blanks were primarily due  to resin contamination, CARB staff plans
to evaluate resin cleaning procedures and incorporate such a procedure into revised Method 429.
     CARB draft Method 436 demonstrated acceptable precision values (less than ±50%) fof 6
of 7 metals for which precision values could be calculated. Percent recovery for the analyte spike
samples was greater than 60% for 11  of 15 metals.   Draft Method 436  analyte spiking tests
demonstrated no statistically significant bias for 6 of 7 metals. Arsenic demonstrated a statistically
significant bias, however a comparison between draft  Method 436  arsenic results and CARB
Method 423 results showed no statistically significant  difference.  Draft Method 436 samples
remained stable over a 45 day period after sampling.
                                           206

-------
REFERENCES
1  C Castronovo and C Dunwoody Lentz, "Development of a California Air Resources Board
(CARB) Multiple Metals Source Test Method/ in Proceedings of the 1991 U.S. EPA/A&WMA
International Symposium on Measurement of Toxic and Related Air Pollutants. VIP-21, Air &
Waste Management Association, Pittsburgh, 1991, pp 887-892.


TABLE I                    Percent RSD for Revised Method 429
                  COMPOUND               AVG CONC1     RSD2
                                                (ng/dscm)        (%)
Naphthalene
2-Methylnaphthalene
Acenaphthene
Acenaphthylene
Fluorene
Phenanthrene
Anthracene
Fluoranthene
Pyrene
Benzo(a)anthracene
Chrysene
Perylene
Benzo(b)fluoranthene
Benzo(k)fluoranthene
Benzo(a)pyrene
Benzo(e)pyrene
Benzo(ghi)perylene
Indeno(l,2,3-cd)pyrene
Dibenz(a,h)anthracene
915
119
13.93
15.13
17.5s
76.6*
103J
17.2
15.7
1.3
4.5
0.6
4.5
1.5
0.84
5.9
7.4
1.5
NC7
18.9
6.6
25.7
1754
36.0
233
100s
14.1
51.5
22.9
14.8
216*
23.7
54.8
52.4
33.9
64.2
38.6
NC
1 Avenge field bUnk > 50% of average field Munple concentration link** otheiwiie noted
2 Bated on to. paired sampling train*, unlett otheiwiie noted
3 Average field blank < 50ft of avenge field sample eoncentntion
4 %RSD « 62 after removing one sample pair
5 Based on four paired sampling trmins
6 Bated on three paired sampling trains
1 Not calculated: only one pair > LOD
TABLE II                   Percent RSD for Draft Method 436
                 As       Cr        Cul        Mn       Ni        Se        Zn
Avg. Cone.
Gtg/dscm)
s Oig/dscm)
% RSD2
1 Avenge field blank
2 Calculated using Ea\
3.9 43
0.9 33
24 80
52
1.1
22
12.2
4.0
33
2247
507
23
27.8
4.7
17
712
21.0
29
> average field sample concentration
nation 1
                                            207

-------
TABLE IV   Results of Draft Method 436 Analyte Spike Samples and Field  Spikes
Metal

Ag
As
Ba
Be
Cd
Cr
Cu
Hg
Pb
Mn
Ni
Sb
Se
TI
Zn
Avg. Spike1 Avg. %2
(/tg) Recovery
12.4 8
14.1 53
31.1 133
30.8 103
37.0 78
37.8 61
36.4 110
161 102
188 79
37.4 97
155 951
6.0 72
8.6 37
5.9 55
145 115
Avg. Bias3 Sig* at
(/xg/dscm) a = .95?
NC6 NA7
-2.0 yes
2.0 NA
NC NA
NC NA
-1.9 no
-1.1 no
1.0 NA
-10 NA
-0.2 no
210 no
NC NA
-1.9 no
-0.8 NA
5.5 no
Field Spike5
(/*g)
12.4
16.7
56.1
55.8
62.0
63.3
61.7
162
352
62.4
280
6.0
11.2
6.0
171
1 Average spike amount on filter or impinger (Hg only) for analytc spike sample trains
%
Recovery
104
41
64
91
84
94
117
108
88
92
93
60
86
64
93

2 Percent recovery =[(spiked-unspikcd)/spikeamt]*100 ,
3 Bias (jig/dscm) = spiked - unspikcd - spike amount (dscm of spiked train used to calculate spike amount in pg/dscm). CalcuW1
in pg/dscm in order to conduct t-te*t using i calculated in /ig/dscm from precision runs (Table II).
4 Results of Student's t-test comparing average bias to zero, n=4, a=0.95
S Field spike amount on filter or impinger (Hg only); no sample gas drawn through train
6 NC=not calculated due to less than detection limit results
7 NA=not applicable: average bias not calculated or precision not available for use in l-test
TABLE IV Results of Draft Method 436 Stability Study
As Ba Cr Cu Hg Pb Mn Ni
Avg. Cone.
(/xg/dscm) 43 36.3 9.0 7.9 0.4 13.3 18.6 2022
Avg. Diff.1
(/xg/dscm) 0.3 -0.6 -2.7 3.1 0.14 -15.6 -0.8 -86.3
(Mg/dscm) 0.4 4.8 4.5 1.6 0.35 28.4 1.5 107
%Diff.2 7.0 -1.7 -30 39 35 -117 4.3 -4.3
Sig?(95%)3 no no no no no no no no






Se 2n

31.4 55.8

0.4 2.1
1.1 4.6
1.3 3.8
no no
1 Average difference between samples digested and analyzed immediately after sampling and one month after sampling.
2 Percent difference = (avg. diff./avg. conc.)*100
3 Results of Student's t-test comparing average difference to zero, n=4, a=0.95
                                                208

-------
     PBQPOSgP SAMPLING MBTHOn 3O6-A FOR THE
                  AMD AMQPIZIMG
                           By
                       Prank Clay
                        U.S. EPA
                Research Triangle Park, N. C.


     In  1989,  the   Emission   Hea«ure»ent  Branch  developed  a
simplified  sampling   train  for the determination  of hexavalent
chromium  emissions   from  electroplaters  and  anodisers.    Tne
apparatus  is  currently  undergoing validation  pursuant  to the
Environmental Protection Agency's Method 301 -  "field validation
of Emission  Concentrations  from Stationary Sources*, 40 CFR Part
63. Appendix A.

     Before considering the sampling train in detail, however, it
is worthwhile to discuss the emission standard for electroplaters
«nd anoditers  that will be  proposed by the U.  S.  Environmental
Protection Agency in July 1992  since it has had some  effect on the
simplified sampling  method.   Several forms of  the standard were
taken into account before choosing  the one to be proposed.  Among
these were control  device efficiency,  milligrams  per  amp-hour
•mission rate,  and chromic acid  concentration in  the  stack gas
•missions.
     Analysis of test data showed that the outlet emissions fi
source  remained constant  despite variations in inlet loadings,
h«nce, the control device efficiency varied.  Furthermore, inlet
sites that meet Method I criteria are almost impossible to find.
Further analysis of the test data showed that milligrams per amp-
hour of chromic acid emitted from the plating tank ranged from 2 to
26 milligrams with an average  of 10, thus the emission rate from
the plating tank is not highly correlated with the number of amp-
hours used.  The standard chosen was a concentration standard since
outlet emissions remained constant despite fluctuations in inlet
loadings.
     The concentration standard will vary with the type of
operation (hard plating,  decorative plating,  or anodiiing).  For
•xisting  hard chromium  electroplstars  (where a  thick coat of
chromium is applied to a  surface)  the allowable emission rate will
be  0.03  milligrams  per  dry standard  cubic  meter.   For newly
constructed  large  hard  platers,  the  standard  will  be 0.015
•illigrams per dry  standard cubic meter.   The emission  rate for
•xisting  decorative platers (whers  a  thin  protective coat of
chromium  is  applied)  will be  less than  0.01  milligrams  per dry
standard cubic meter.  Mew medium and large sise decorative  platers
*ill be  required  to use  trivalent  plating instead of hexavalent
plating which is used presently.  The standard for anodisers will
be less than 0.01 milligrams  per dry standard cubic meter.   Exactly
                                209

-------
how much less than 0.01 milligrams per dry standard cubic meter for
decorative electroplaters and anodizers has not yet been decided.


     When  the   standard  is  in  place,  many  electroplating  or
anodizing facilities will  have to be tested to  show compliance.
This can be  done using  one of two  sampling methods:   Method 306,
which is an isokinetic sampling method, or Method 306-A, which is
the simplified  sampling method that uses  a constant sampling rate.

     The isokinetic method (Method 306) is somewhat sophisticated
and requires a  certain level of testing proficiency to conduct.
Such testing would more  than  likely  be  performed by a consulting
firm; the cost  of such  a test  could equal the quarterly profits of
some small plating  facilities.   The  EPA ,therefore,  developed a
simplified sampling method (Method  306A)  to provide an alternative
testing procedure  for  small  electroplating entities  which would
allow these  regulated  entities to obtain the  required  test data
without  compromising  applicability  or  compliance  assurances.
Although the samples would still be analyzed by a laboratory, the
simplified method  would  provide  a  means  for an electroplating
facility to perform its own testing at a presumably lower cost.

     The analysis technique chosen  for both sampling methods is the
same and  is  atomic  absorption using a  graphite furnace.   This
analysis  gives  total  chromium which  is the  sum of  hexavalent
chromium and trivalent chromium.  The assumption is made that all
emissions  are  hexavalent  chromium,  but  if  an  analysis  for
hexavalent chromium  only is desired, ion  chromatography  using a
post column  reactor  is  acceptable.   The  number of labs with this
capability at present are limited;  however,  comparative analyses of
both methods on chromium  samples  taken  in the  field  have given
similar results.

     The prototype train developed in 1989 consisted of  6 basic
components:

     1.   A piece of  1/4 inch  l.D.  glass  tubing bent at 90 degrees
on one end to              form a  nozzle/liner  combination.  This
piece of tubing             was enclosed in a  1/2 " l.D. piece of
metal tubing.

     2.  Flexible clear plastic tubing to connect the nozzle liner
         assembly to the impinger assembly as well as to connect
         other parts of the sampling train.

     3.  The  impinger set.  In the  prototype, this was a standard
         Greenburg-Smith set of impingers.

     4.  A critical orifice to control flow.

     5.  A rotary vane vacuum pump.

     6.  A dry gas  meter.
                                210

-------
     The siBplified sampling train maintains a constant flow rate
through the train (approximately 0.75 of a dry standard cubic foot
per minute) and varies the sample  time at  each  point in order to
obtain a proportional  sample.   This differs from  the Method 306
isokinetic  sampling  train which  would  sample  each point  for a
specified amount  of  time and  would extract a  certain  volume of
sample at each point  based  on the  flow rate at that point.  The
constant sampling rate of the Method 306A train requires that the
sampling time be  varied  at  individual points in order  to sample
approximately the same volume at  each point  as  the isokinetic
train.

     Several changes  have been  made in the original simplified
train, the most important being  the impingers.   The cost of four
Greenburg-Smith impingers with connecting glassware and clamps is
nearly  as  much  at  the  entire  simplified  sampling train with
peripheral equipment.  The Greenburg-Smith impingers were replaced
with fabricated  impingers.   Initially, two fabricated impingers
were used,  one for reagent and one  for silica gel. These were made
from one quart Mason jars and 1/4 inch ID glass tubing or plastic
water supply line. Inlet and outlet impinger connections were made
with flexible plastic tubing.  The first impinger tips had four 1/8
inch holes drilled horizontally to  create bubbling of the impinger
solution.

     Test data that compared this type of impinger with Greenburg-
Smith impingers showed that the Mason jar  impingers were not as
efficient at collecting  chromic acid.  A more  vigorous bubbling
action was obtained by changing  the impinger tip to duplicate as
•uch as  possible the  tip on  a  Greenburg-Smith impinger.   This
produced better bubbling but  also  created  a problem when part of
the first impinger reagent  was carried over into  the silica gel
impinger. This situation was alleviated by adding a blank impinger
with a tip that was about 1 1/2 inches above the  bottom of the jar.
Sample catches now appear to be similar to catches where a set of
Greenburg-Smith impingers have been used.

     The need for rigidity in the nozzle/liner apparatus was also
reviewed. As a result, another change that improved the use  of the
train  occurred.    The change was  the  reduction  in length  and
material rigidity of the nozzle/liner assembly.   The initial 1989
train used a long length  of  1/4 inch I.D. glass  tubing to make the
nozzle/liner, and this was placed inside a piece of 1/2 inch metal
conduit to make  the  probe assembly.  The long  rigid tubing used
inside the conduit made sample recovery cumbersome, and the glass
tubing could easily be broken.

     A technical  assessment revealed that a shorter piece of glass
tubing or comparable water supply line,  approximately 8 inches in
length, allowed an acceptable  right angle bend  to be mode at one
«nd forming a total  nozzle  head.   The sample head could then be
connected to the  clear flexible  plastic tubing  that runs through
the conduit to the  first impinger.   The  new  sampling  head is
centered in the conduit by using  3/4 inch wide electrical tape (or
                                211

-------
equivalent).  The  tape  is  wrapped around the tubing close to the
right angle bend and makes  a collar  that insures a snug fit inside
the conduit.  A second tape collar at  the point of  flexible tubing
connection  to  the  sampling  head insures  alignment  with  the
longitudinal axis of the conduit.


     An additional advantage was realized.  Since  the majority of
the assembly from the nozzle to the impingers is flexible tubing,
sample  recovery is  considerably  easier.   The remainder  of  the
Method  306A  sampling  train  remains  unchanged  from  the  1989
configuration.

     Simplification  of  the  calculations was   required  due  to
milligrams per dry standard cubic meter being chosen as the units
of  emission  standard.   It  is  no longer necessary to know  the
volumetric flow rate of  the outlet location, nor is it necessary to
know the moisture content of the stack gas.  The only measurement
taken from the stack is the differential pressure  (stack delta p).

     Specifically, the  average of  the sum of the square roots of
the  delta p values  is  ratioed  with the  square root  of  the
individual delta  p values.   The  result is then  multiplied  by 5
minutes to get  the sample time at each  point.   Decimal parts of
minutes are converted to seconds to facilitate sampling.

     After the sample has been collected and the analysis has been
performed, a simple  equation is  used to get  the concentration
number for the test run.  The equation is:
           mcr x (Tm + 460)
     Cs = 	
           499.8 (Yin) (Vm) (Pbar)

     Where:

             Cs   = chromium in milligrams per dry standard cubic
                    meter
             mcr  = total micrograms of chromium collected
             Tm   = temperature of dry gas meter in degrees F.
             Ym   = correction factor for dry gas meter
             Vm   = volume of dry gas meter at standard conditions
             Pbar = barometric pressure in inches Hg

     In Hay 1991, a Method 306A field testing  program was conducted
in accordance with the protocol  for method validation specified in
Method 301.   Using a quad probe  assembly, a comparison was made
between the Method 306 isokinetic train which was accepted as the
validated train, and the Method  306A simplified  train that used
Mason jar impingers and sampled at a constant rate.  Data from this
                                212

-------
test  indicated  that  the  Method   306A  train  results  were  of
acceptable  precision but  unacceptable  as  far  as accuracy  was
concerned.  Chromium values obtained were approximately 40% lower
than those from the Method 306 isokinetic trains.  After the method
validation  protocol  sampling,   the  simplified  train  was  also
operated on a  source  test concurrently with an isokinetic train.
Both trains  traversed the  outlet  location at  an  electroplating
facility.   Again,  the  simplified  train provided  lower emission
results than the isokinetic trains.

     A  corrective  measure was  formulated  resulting  in  a  new
impinger  tip  design  for the Mason jar  impingers to  mimic  the
Greenburg-Smith impinger  tip.  The tip opening and the height of
the tip above the bottom of the Mason  jar are the same as the tip
opening and impaction plate height of  a Greenburg-Smith impinger.
Subsequent  tests at electroplating  facilities where this  new
impinger  tip was  used indicate that the new  design results  in a
collection  efficiency  nearly  identical  to  the  Greenburg-Smith
impinger.

     A  new validation  test is  planned.   The  same  quad  probe
assembly  will  be used,  and the  simplified train  will  use three
Mason jar impingers instead of two.  The impingers be in the same
sequence as described previously.  Assuming  successful validation,
Method  306-A  will be  proposed  in  July  1992  with the chromium
standard.
                                213

-------
       INNOVATIVE SENSING TECHNIQUES FOR MONITORING AND
      MEASURING SELECTED DIOXINS, FURANS, AND POLYCYCLIC
                AROMATIC HYDROCARBONS IN STACK GAS
                                Dfj Jeffrey A. Draves

                                 Radian Corporation
                                  P. O. Box 201088
                              Austin, Texas  78720-1088

                                Mr. Dave-Paul Dayton

                                 Radian Corporation
                                   P. O. Box 13000
                     Research Triangle Park,  North Carolina  27709

                                Mr. Thomas J. Logan

                         U.S. Environmental  Protection Agency
               Atmospheric Research and Exposure Assessment Laboratory
                      Methods Research and Development Division
                         Source Methods Development Branch
                     Research Triangle Park,  North Carolina  27711
   The U.S. Environmental Protection Agency has determined the  need to  develop
continuous or semi-continuous emissions monitoring techniques for  the dioxins, furans, al1
polycyclic aromatic hydrocarbons emitted  from municipal solid waste incinerators and othtf
sources.  These  species present great potential public health risk due to their low associate
exposure limits.
   This paper discusses twelve innovative optical sensing techniques that were evaluated to
application to continuous monitoring approaches. The ability of each of the techniques to
as a continuous  emissions monitoring system is discussed. Two techniques, Ultraviolet
Measurement and  Fluorescence Measurement, appear to have the most potential for su
application. Development of these two techniques as continuous emissions monitoring systems &
discussed.  Vapor  phase ultraviolet spectral data for selected dioxins, furans, and poty^0
aromatic hydrocarbons are being generated.

INTRODUCTION                                                                 .^
   Dioxins and furans are formed as byproducts in combustion processes and certain indust
chemical processes  involving chlorine (e.g., paper bleaching and pesticide production). The to*
of these compounds makes them a great human health concern.  Another class of compo111}^
polycyclic aromatic hydrocarbons (PAHs), is also associated with combustion processes. A nuintfce
of the PAH compounds are highly mutagenic and/or carcinogenic.  A potential emission sou*
of dioxins, furans, and PAHs is  municipal solid waste (MSW) incinerators.               .^
   Current measurement techniques for dioxins and furans involve the collection of sample > u '
U.S. Environmental Protection Agency (EPA) Method 23.  Once collected, the dioxins and W  ,
are identified and quantified using high resolution gas chromatography (HRGC) coupled with
                                        214

-------
resolution mass spectrometry (HRMS).  Approximately 2 months of processing time is required
between Method 23 sample collection and data reporting. Due to the acute and genetic toxicity
of these compounds, the U.S. Environmental Protection Agency has determined that a continuous
technique for monitoring dioxins, furans, and polycyclic aromatic hydrocarbons in stack gas is
needed1.   There are currently no technologies at a state of development to allow continuous
quantitation or monitoring of these compounds or other trace organic constituents of stack gas.
Therefore, a fundamental research and development project is being conducted to address the need
for continuous monitoring of dioxins, furans, and PAHs.
   The EPA has specified that the monitoring technique should provide for the following:

   •      Vapor phase measurements (continuously or semi-continuously);

   •      Capability of achieving a detection limit of 100 nanogram/normal cubic meter (ng/Nm3)
          of total dioxin (the detection limits for the furans and PAHs were not specified);

   •      Paniculate phase measurement (if feasible); and

   •      Speciated quantitation (if feasible).

Overview of the Research and Development Project
   The research and development project is being conducted in five separate steps.  These steps
are as follows:

   •      Step I - Feasibility Study;

   •      Step II - Spectral Measurements;

   •      Step HI - Instrument Design and Fabrication;

   •      Step IV - Pilot Scale Testing; and

          Step V - Full Scale Field Testing.

The primary objectives of Step I, the Feasibility Study, were:

   *      To conduct a technology investigation to identify  and evaluate  applicable candidate
          measurement techniques; and

   •      To provide a plan for development of the technique(s), which would have the greatest
          potential for successful application as a continuous emissions monitoring system.

   Step II,  Spectral Measurements, is  designed to obtain measurements  of the vapor phase
absorption  spectra  and measurements  of the  fluorescent  lifetimes,  and to determine  the
fluorescence profiles of three of the 75 chlorinated dibenzodioxins, two of the 155 chlorinated
dibenzofurans, and one representative PAH species. Candidate compounds are as follows:

   •      2,3,7,8-tetrachlorodibenzo-p-dioxin;

   •      1,2,3,7,8-pentachlorodibenzo-p-dioxin;
                                           215

-------
   •      Octachlorodibenzo-p-dioxin;

   •      2,3,7,8-tetrachlorodibenzofuran;

   •      Octachlorodibenzofuran; and

   •      Benzo-a-pyrene.

   These six compounds present a representative cross-section of these classes of toxic species
were chosen because of their likelihood of being emitted and their overall toxicity.  Step II is *"
progress.
   Step III involves the actual design and fabrication of the monitoring instrumentation.
   Step IV  involves testing the instrument produced in Step HI, at a small well-characterized
emission source or simulated emission source.
   Step V involves refinement of the instrument based on information obtained during Step IV and
then performing a field evaluation at a full scale operating emission source.
   This paper specifically presents the results of Step I and the objectives of Step II of the research
and development  project.

Optical Sensing Technique Evaluation
   The term optical sensing (OS), as used in this paper, refers to the interaction of light
matter (i.e., molecules, atoms or  aerosols/particulate) to yield qualitative and  quantitative
information  about that matter. The OS techniques are, for the most part,  common laboratory
spectroscopic techniques which are being applied to environmental monitoring.  The advantage*
of OS techniques over conventional analysis methods include real-time data analysis, structural
specificity, and in many instances, in-situ monitoring capacity.

Requirements of Optical Sensing Techniques
   During the course of the investigation, desired minimum performance criteria of OS
were determined to  ensure both accurate and rapid monitoring of dioxins, furans and PAHs
categories for which instrument performance was evaluated were:

   •      Frequency of Measurement:  Indicates whether the instrument  is  a continuous
          semi-continuous monitor.  The more often a measured value is obtained the higher tb
          frequency of measurement.  The evaluation is expressed in measurements per hour-

   •      Sensitivity: Indicates whether the instrument can meet the desired 100 ng/Nm3 detect0
          limit and distinguish between individual dioxin and furan isomers, and PAH c
          The 100  ng/Nm3 sensitivity level was  specified  by the U.S.  EPA as the
          sensitivity necessary for preliminary technique consideration.  The 100 ng/Nm3 is
          on the measured  emissions from MSWs  currently in operation.   However,    .
          regulations require that newly constructed  MSWs meet a 30 ng/Nm3 emission leyej
          While the techniques selected for further investigation will likely meet the 100
          sensitivity level, their actual detection limits are uncertain since no  vapor phase
          of the compounds of interest are currently  available. Once  the measured spectra
          obtained, a more accurate assessment of the minimum detectable  limits will be

   •      Constraints (Analytical and Physical): Development of the measurement capabilities^
          the instrument to  achieve the objective of the continuous monitoring.
                                           216

-------
         constraints refer to the need to develop computer control software. Physical constraints
         refer  to development  required  to  enable the  technique  to be  used in  a suck
         environment. Evaluation is expressed in person-years required to complete development

         Paniculate Matter  Indicates whether the instrument is able to measure the compounds
         of interest on paniculate matter.

         Ease of Use: An estimate of the amount of training necessary to operate the instrument
         on a day-to-day basis. The evaluation is expressed in person-hours required to complete
         training.

         Maintenance:   An estimate of the amount of routine maintenance expected to be
         required bv the instrument.   Maintenance includes  down-loading of  data,  optics
"•J"HnMHnT7   /\U CMU1U11C Ul MIC «U11UUU* IFI iimuuv  iimm»«. !•»••«> » -y^»»»^». >v
required by the  instrument.   Maintenance  includes down-loading of data, opt
alignment, diagnostic checks, etc.  Evaluation is expressed in person-hours required
optics
   to
         perform maintenance.
   •     In-Situ Monitoring: Indicates whether the instrument is able to measure the compounds
         of interest in the stack as opposed to extracting samples from the stack for measurement.

         Cost:  Is an estimate of the expected  associated cost of the instrument  (based on a
         combination of the prototype and production costs of the apparatus only).

Optical Seasiag Techniques Considered for Investigation
   Twelve OS techniques were considered for dioxin, furan, and PAH monitoring application. The
*«chniqttes were selected for evaluation by reviewing available literature and through discussions
*ith experts in OS applications.  The structural properties of the compounds of interest were also
"aed as criteria for selection. The techniques arc  presented in Table 1, divided according to their
spectral region of operation. Most  of the OS systems considered operate using cither ultraviolet
<* wfrared light Two techniques, photoacoustic spectroscopy (PAS) and Multiphoton lonizaoon
tMPj), are  listed  as  'consequence' techniques because the result of the absorption of light is
""onitored and not the increase  or  the decrease of the light intensity itself.
   Table II presents  possible operating configurations (e.g^ extractive and/or in-situ) for each of
u* techniques presented in Table I. Figures 1 and 2 illustrate conceptual operating configurations
      systems m ctti^ctivc a°d  in-situ monitoring modes.  In either operating configuratiofl. the
    beam is multipassed to extend the measured path length.
           Cmuidcred for Further Investigation
     Each of the techniques presented in Table I was evaluated with respect to the performance
       categories listed above.  The results of this evaluation are given in Ttbte EL
       techniques were ranked for each category on a scale of 0 to 10, with ten indkating the best
       The scores from the individual categories were then summed. The two techniques having
    highest summed scores were selected for further consideration.   When summed, the highest
       techniques were ultraviolet (UV) absorption and laser induced fluorescence (UF), The
         of operation of each of these methods are described below.
                      Spcctitucopy
   The UV absorbance spectroscopy is conventional absorption spectroscopy using an appropriate
   ad-band excitation source such as a Xenon arc lamp . The technique is w*H developed and
'equires about  1 minute or less, depending on the signal to noise ratio (S/N), to identify and
                                           217

-------
quantitate the concentration of a single species. Use of laser light sources is also possible (e.g., an
excimer pumped dye laser as the source). The laser techniques are not, however, as well developed
as the broad-band technique.  Typically, UV provides better sensitivity than IR because the UV
band strengths are greater and light sources are more intense.  However, not all compounds are
observable in the UV region. Further investigation will be necessary to evaluate possible dioxin or
furan detection in the UV or near visible region.
   The literature review and feasibility study yielded no  vapor  phase UV spectra for the
compounds of interest.  However, liquid phase spectra2 and subsequent detection limits do e*5*
for several furan compounds. Extrapolation of the liquid phase detection limits to the vapor phase
has been performed.  The extrapolation is difficult for  the following reasons:

   •      The type  of solvent employed  can have a  large effect on  both  the position of the
          absorbance peak and its intensity,

   •      The solvent interacts with the dioxins, furans, and  PAHs  to  hinder rotational motioA
          causing significant changes in the width and  intensity of the spectral features.

   •      The temperature difference between vapor and liquid phases can significantly increase
          the population of higher rotational states causing the peak intensity to decrease and the
          spectral feature to broaden. However, the lower frequency  of collisions in the vapof
          phase will lead to longer lifetimes and narrower absorption features.  The overall result
          of  these two processes is difficult  to predict a priori, but a factor of 10  increase i*
          intensity is possible.

   Although  not exact, these extrapolations  give insight into the  order of magnitude of &*
detection  limits that can be expected in the vapor phase for the compounds of interest.        ,
   As is shown in Table IV, the expected UV detection limits  increase as the molecular weigh* °l
the furan  increases.  Over a 100 meter (m) path, the detection limits range from 18.6 ng/Nffl f°r
dibenzofuran to 2,353 ng/Nm3 for the heptachlorofurans. The detection limit for the most to»c
isomer, the tetrachlorodibenzofuran is 25.6 ng/Nm3.  Considering the increase in spectral intensity
(about an order of magnitude in most cases) upon going from the liquid phase to the vapor
detection  limits of 1.86, 235.3, and 2.56 ng/Nm3 can be expected for these three furans.
detection limits, while only an order of magnitude estimate at best, are encouraging and fall
the required detection limit of 100 ng/Nm3 for several  of the  furans.
   In the  UV region of the spectrum background interferences are minimal.  While water vap°
and CO2 can significantly hamper IR detection limits they have negligible effect in the UV.
compounds present  in the stack gas may interfere with UV  detection.  Potential inte
compounds include dioxins,  furans, PAHs not of interest, and other  compounds attached to
surface of the paniculate matter. The lack of spectral information on dioxins, furans, and
makes exact identification of interferants impossible at this  time.

Fluorescence
   Fluorescence  relies on  the excitation of the molecule of interest to a known state by ®*
absorption of a photon from a light source (e.g., Xenon arc). The photon is either emitted at tn
same frequency or more likely at a lower frequency.   The frequency of the photons emitt«J-
monitored by  a spectrometer. The response  times generally will be  similar to those for the u
absorbance.  However, because the  emission of photons  can take on the order of
investigation of the fluorescence  spectra and lifetimes will be  necessary.
                                           218

-------
   As with UV absorption the sources are capable of accommodating long path lengths, but the
fluorescence volume and, therefore, the solid angle relative to the detector is important and must
be considered.  The amount of fluorescence is governed by the following equations:

                            F =  2.3*I(0)*f(6)*g(v) ' A(v)

where:    1(0)   =     the incident light intensity
          f(B)   a     solid angle of irradiated volume falling on the detector
          g(v)   =     the response of the detector
          A(v)  =     the Beer's  Law absorbance of the sample.

Replacing A with the components of Beer's Law gives:

                         F = 23 * 1(0) * f(6) " g(v) • a(v) * c * 1

where:    a(v)   =     the molecular absorbance strength
          1      =     is the path length
          c     =     concentrations

   No vapor phase fluorescence spectra of the compounds of interest  were found during the
literature review. However, liquid phase detection limits do exist. In this case, extrapolation of
the liquid phase detection limits to the vapor phase is difficult for the same reasons stated above
and for the following additional reasons:

   •      The limits of detection are not solely dependent depend on the path length but also
          upon the solid  angle of the excitation volume visible to the detector.

   •      Species that could absorb the emitted photon by being location between the emitting
          species and the detector may exist.

   •      The emission of light requires a finite amount of time.  The species emitting the light
          are moving, both up the stack and out of the original excitation volume. This motion
          may require the detector to be placed up the stack from the source. Diffusion out of the
          excitation volume will  make the detection  limits higher as  the excited  volume is
          increasing.

Expected fluorescence detection limits are presented in Table V.
   Trace components such as  the PAHs, the polychlorinated biphenyls (PCBs) and other dioxins
and furans may interfere with the fluorescence technique. The measurement of a single compound
will depend upon its fluorescence lifetime.

   .Laser Induced Fluorescence. The LIF technique is conceptually similar to the fluorescence
technique described above. The LIF technique uses a carefully tuned laser to excite the molecule
of interest This careful  tuning allows for very  specific excitations and more specific  compound
identification. As with the fluorescence technique above, the emitted photon can then be monitored
as a function  of frequency with a spectrometer of appropriate resolution.  This gives the ability to
°oth selectively excite and selectively detect the compounds of interest.  The LIF technique has
been  shown to be very sensitive for PAH compound detection.
                                           219

-------
   The advantages of LIF over fluorescence are twofold.  The first advantage is that a laser light
source is much more specific in terms of which species are excited.  Consequently, the species will
be excited to a narrow band of states, making  the emission spectra less complicated and easier to
interpret. The second advantage is the increase in light intensity obtained using a laser source.
Since fluorescence is directly related to the intensity of the light source, lasers offering greatly
increased light intensity at the  specific wave length of  interest will cause an increase in the
fluorescence.
   As with the  fluorescence technique discussed  above there is no vapor phase information
available concerning the compounds of interest. This lack of information makes identification of
the appropriate laser source difficult.  The frequency of measurement will again depend on the
fluorescence  lifetime but should be similar to UV absorption,  on the order of 1 minute or less,
depending on the S/N ratio, per species.
   Actual vapor phase absorption spectra, emission spectra, and emission lifetimes must be
obtained to better characterize  the ability of these  techniques to measure the compounds of
interest.

Measurement of Vapor Phase Spectra
   One of the limiting factors in  the feasibility study was the absence of vapor phase spectral data
for the dioxin, furan, and PAH compounds.   Lack of spectral information not only made tbe
identification of the appropriate OS techniques difficult but also will effect implementation of the
technique since reference spectra are generally needed to identify and quantify species.
   Vapor phase spectral data  are being obtained, in a temperature range typical of incinerator
stack emissions, for the  six selected dioxins, furans, and PAHs presented above.
   The measurement program consists of measuring  the UV absorbance cross-sections for each
of the selected compounds.  The absorbance  spectra  will be used to identify features for use &
detection, as well as  to pick the appropriate laser excitation sources for LIF measurements.  Tbe
fluorescence  wavelengths and  cross-sections will then be identified.  Finally,  the fluorescence
lifetime will be measured for each selected compound.

CONCLUSIONS AND FUTURE STEPS
   The feasibility study yielded two techniques, UV absorption and LIF, that have the potent^
to be applied to real-time monitoring  of  dioxins, furans  and PAHs.  The lack of vapor p"886
spectral information precludes narrowing  the field further.  Further information is needed *°
definitively specify the most applicable technique.
   A program designed to obtain vapor phase spectra! information for selected compounds o*
interest is presently  on-going.  The spectral information obtained will consist of measured
absorbance spectra, LIF spectra,  and fluorescence lifetimes.

REFERENCES
   1.    J.A. Draves,  D-P.  Dayton,  and J.T. Bursey,  Innovative Sensing
         Monitoring and  Measuring  Selected  Dioxins.  Furans.   and Polvcvclic
         Hydrocarbons  in  Stack Gas. Final Report.   DCN No.  91-275-065-10-09,
         Corporation, October 1991.

   2.    E.B. Gonzalez,  R.A.  Baumann,  C Gooijer,  N.H.  Velthorst,  and  R.W.
         Chemosphere, 16 pp 1123-1135,  (1987).
                                           220

-------
                Table I. Spectral regions of the optical sensing techniques.


	Ultraviolet	Infrared	Consequence


 UV Absorbance             Fourier Transform Infrared        Photoacoustic
                              Spectroscopy  (FTIR)         Spectroscopy (PAS)

 Fluorescence                  Matrix Isolation/FTIR      Multiphoton lonization
                                   (MI/FTIR)                   (MPI)

 Laser Induced                 Gas Chromatography/
 Fluorescence (LIF)           MI/FTIR  (GC/MI/FTIR)
 Shpol'skii Spectroscopy           Laser  Absorbance
 (SS)

 Laser Induced Breakdown      Gas Filter Correlation
 Spectroscopy (LIBS)                  (GFC)
                                      221

-------
Table II.  Extractive and non-extractive techniques.
Category
UV Techniques




IR Techniques



Consequence Techniques

Technique
UV Absorbance
Fluorescence
LIF
SS
LIBS
GC/MI/FTIR
MI/FTIR
FTIR
Laser Absorption
PAS
MPI
Extractive
X
X
X
X
X
X
X
X
X
X
X
In-situ
X
X
X

X


X
X

X
                   222

-------
                                                                    Table OL. Summary of techniques.
K>
Ui
Technique
UV
Absorbance
Fluorescence

LIF

SS



LIBS

FTIR

MI/FTIR

GC/MI/FTIR


GFC

Laser
Absorbance
PAS

MPI

MS/MS

Frequency of
Measurements
[Number/Hour!
«0

60

60

25







300

6


—



60

60

300

Sensitivity"
Within
specifications
Within
specifications
Within
specifications
Within
specifications


Out of
specification
Out of
specification
Possibly within
specification
Within
specification

Out of
specification
Out of
specification
Within
specification
No information

Within
specification
Analytical and Physical
Constrain
None

Needs analysis software

Will need stabilizers for
optics; analysis software
Sampling and separation will
need to be developed as will
solvent mixing system. Also
needs analysis software.




Needs development of a
separation method
Needs development of
software for control and
timing




Needs sample delivery
system; computer software
Needs sample delivery
system
Need downsizing and sample
delivery system
Paniculate
Matter
No

Yes

Yes

No







No

No






Yes

No

No

Ease of Use
(Person-
Hour]
8

8

40

40







12

40






40

40

40

Maintenance
JPerson- In-
Hour/Month] Situ
2 Yes

2 Yes

5 Yes

10 No







10 No

10 No






15 No

10 No

12 No

Capital
Costs
(Thousands)
250

250

200

300







200

250






150

300

300

                   "Ability to meet a 100 ng/Nm3 detection limit and distinguish among various congeners.

-------
                         Table IV.  Expected UV detection limits.

Species
DF
DF2
DF4
DF5
DF6
DF7
Path
"g
0.008
0.038
0.11
0.11
0.44
1.01
Length [M]:
tng/L]
400
1900
5500
5500
22000
50500
0.0047
Oig/Nm3]
400
1900
5500
5500
22000
50500
100
[ng/Nm3]
18.64
88.54
256.3
256.3
1025.2
2353.3
100
[ppt]
02.7
09.1
20.5
18.4
66.8
140.5
DF = Dibenzofuran. Number after "DF indicates number of chlorines.
                                      224

-------
                 Table V.  Expected fluorescence detection limits.

Species
Dibenzofuran*
1,2,3,4
2,3,7,8
Dibenzodioxin
1,2,3,4
1,2,7,8
1,3,7,8
2,3,7,8
1,2,3,7,8
1,2,4,7,8
1,2,3,4,7,8
1,2,3,4,6,7,8
1,2,3,4,6,7,8,9
Wavelength
Excitation
285 246
292 252
307 257

230
230
232
235
232
232
230
232
232
[nm]
Emission
316 327
338 407
340

342 418
346
343
343
342 416
343
340 409
343 405
341
LOD
[ng/ml]
0.02
0.015
0.025

2
0.07
4
1.3
1.8
5.5
4.5
0.5
2.5
100 M
(ng/Nm3)
0.2
0.15
0.25

20
0.7
40
13
18
55
45
5
25
100 M
[ppt]
0.03
0.01
0.02

1.52
0.05
3.04
0.99
1.23
3.77
2.81
0.29
1.33
The numbers in the column indicate the chlorinated positions.
                                      225

-------
DataAquteftion
                                      Moisture
                                      Removal
                                            Heated
                                         Partteuiate Filter
                                                                               Sample Stream
                                                                                   From
                                                                              — Incinerator
                                                                       Heated Sample Una
                        Sample
                          In
                                        Optics
                                                                             Heated White Cell
  [SOUK*
  [Detector
 t*-"^
n-
                               Sample
       F\Qute A.   Conceptual configuration o* an optical sensing system in an extractive mode.

-------
                                                                                                        DataAqulaltfon
K>
                                    Figure 2.   Conceptual configuration of an optical sensing system in an in-situ mode.

-------
 DETERMINATION OF TOTAL GASEOUS HYDROCARBON
     EMISSIONS  FROM AN ALUMINUM ROLLING MILL
        USING METHODS 25, 25A, AND AN OXIDATION
                               TECHNIQUE
                                Sucha S. Parmar'
                                  Michael Short
                                 William Powers
                         ENSR Consulting and Engineering
                               1220 Avenida Acaso
                            Camarillo, California 93012
ABSTRACT
      A simple, cost-effective method for sampling and analysis of total gaseous hydrocarbons
described.  The method entails measurement of  total hydrocarbons as  carbon dioxide 3ft
oxidation through a furnace at 900 °C. Carbon dioxide present in the test mixture before oxidation
is subtracted and the net C02 value is related to the hydrocarbon concentration. This method
compares very well with Method 25A both in the laboratory and in the field stack emission tests
from an aluminum rolling mill where oil is used as a lubricant during the rolling process.  1° ^
tests performed, the ratio of GC/HD (Method 2SA) results to the net CO, values was found to &
close to one.  A comparison of Method 25 with Method 25A and the oxidation technique
attempted.
INTRODUCTION

      For the past  twenty years, ambient air has been analyzed for its volatile content bV
concentration on adsorbent trapsu or by cryogenic concentration from whole air314 using continuous
analyzers  or gas chromatographs. However, measurements from these instruments have bee.11
shown to  be unreliable, particularly at low concentrations, due to a variety of characteristic
problems. These problems include the indirect nature of the measurement process employed  »
nonuniform per-carbon  response for different compounds due to  oxygen  interference,  ^
interference from water vapor*.

      Method 25 was developed in the mid-1970s as a means of determining the total amount o
volatile organic carbon (VOC) emissions from stationary sources. After stack sampling and samp1*
trap recovery, the quantitative measurements of this method  are performed  on an instruioefl
known as total carbon  analyzer (TCA).   VOC is measured  as methane  and  nonmetbaO
hydrocarbons using this methodology. This unit is an oxidation/reduction gas chromatograph v&*c
    To whom til comtpoodencc ibould be •ddnaed
                                      228

-------
separates permanent gases (methane, CO, and COj) from hydrocarbons so that a total hydrocarbon
concentration may be determined.  This is not the only method that applies to the measurement
of total gaseous hydrocarbons.  Direct measurements of an effluent gas with a flame ionization
detector (FID) are appropriate with prior characterization of the gas stream and the knowledge
that the detector responds predictably to the organic compounds in the stream (e.g., Method 25A
Cor alkanes, alkenes, and aromatic hydrocarbons).

      In this study, we have  introduced a simplified  technique for the measurement of total
gaseous hydrocarbons from an aluminum rolling mill where oil is used as a lubricant during the
rolling process.  This technique works on the principle of total combustion of hydrocarbons in air
at approximately 900°Q followed by carbon dioxide measurements taken with a continuous  COj
monitor.  The amount of COj in the gas stream prior to combustion is subtracted, and the net C02
concentration is related to the total gaseous hydrocarbon emissions.  A similar technique (Method
15A) is recommended by the U.S. EPA for the determination of total reduced sulfur emissions
from petroleum refineries.


EXPERIMENTAL

      Gaseous hydrocarbons were sampled using three different procedures: 1) EPA Method 25A,
determination of total gaseous organic concentration using a flame  ionization detection; 2) an
oxidation furnace (at 9000C)/Cfl(2 analyzer method (oxidation technique); and 3) EPA Method 25,
determination of total gaseous methane and nonmethane organic emissions as methane.  Figure
1 provides a schematic of the sampling systems.

      Gaseous hydrocarbons were measured by EPA Method 25 A as follows: A 3-liter per minute
(1pm) gas sample was drawn through a heated Teflon line to a Ratfisch RS55 total hydrocarbon
(THC) analyzer from the back of a Method 5 filter housing. The temperature of the heated  line
was maintained at 150* C. A three-way connection at the heated line inlet allowed the introduction
of calibration gases before and after each sampling run.  The instrument was operated at 100 ppm
foil range using propane as the calibration gas (80.1 ppm). Hydrocarbon free air was used as the
zero gas. Zero and span drift checks were conducted at the beginning and end of each sampling
run.

      In the oxidation fumace/COj analyzer method, a second gas sample was drawn from the
Method 5 filter housing. This sample was routed through a heated stainless steel line to a quartz-
lined oxidation furnace maintained at 900 °C All hydrocarbons were converted to COj and H20 in
the furnace.  Carbon dioxide  was measured upstream and downstream of the  furnace using a
1000 ppm full scale Horiba CO, analyzer. The difference in these two CO, measurements permitted
accurate measurement of hydrocarbons in the sample. VOC (Method 25A) and CO, concentrations
were recorded at five-minute intervals on the field data sheets, and the analyzer outputs were also
continuously recorded on a strip chart recorder.

      A third gaseous sample was collected from the Method 5 filter housing by EPA Method 25.
Immediately after the start of each sampling run, an evacuated Summa* canister was opened to
allow the sample to flow at 0.1 to 031pm through a stainless steel trap (packed with quartz wool)
at -80«C. Upon leaving the trap, the sample gas entered the Summa* canister.  The trap  and
canister were analyzed for methane and nonmethane hydrocarbons according to EPA Method 25.
                                          229

-------
       Laboratory validations between the three methods described here for the measurement of
total VOC were also carried out using certified standards of propane and hexane. The response
factor for rolling oil was determined relative to hexane by making direct injection (0.3/d) into a
modified GC/FID. The analytical column was replaced with a 24-inch fused silica tube to permit
quantification of the analyte as an unseparated single component.
RESULTS AND DISCUSSION

      Propane and hexane standards in pure air were used for the laboratory validation tests for
Methods 25, 25A, and the oxidation technique.  The results in Table I present the relative
performance of each method.  Continuous monitor GC/FID readings are in good agreement with
the known concentration of the standards, whereas Method 25 and the oxidation technique were
off by approximately 10 percent.  These three techniques were further tested in the field during
hydrocarbon emissions testing at the inlet and outlet of a control unit installed on the outlet
ductwork of an aluminum rolling mill.

      Due to technical problems, we do not have the data for Method 25 during all field tests.
The results  for all field validation and comparisons between Method 25A and the oxidation
technique are  given in Tables U through V.  In three tests out of four, the  continuous monitor
GC/FID readings taken every five minutes were very close to the total hydrocarbon measurements
as C02 from the oxidation technique (Tables n through IV). In one of the tests (Table V), the total
hydrocarbon concentration from the oxidation technique was off by 20 percent.

      Overall, the agreement between these two methods is excellent, and either method can be
used for the measurement of total hydrocarbons as long as samples contain alkanes, alkenes, of
aromatic hydrocarbons. However, a complication arises when stack samples contain oxygenated
or halogenated organic compounds. In such situations, GC/FID cannot produce reliable data due
to nonlinearity in per-carbon response  for  the  sample, as propane is  normally used  in ^
calibrations. In this study, the FID response factor of mill oil was determined relative to hexane
on a per-carbon basis. This response factor was found to  be close to one, both in the laboratory
and in the field.

      The oxidation method, on the other hand, does not suffer from response factor variation5*
as all organic compounds will be oxidized to COj. Method 25, in principle, can yield reliable 
-------
CONCLUSIONS

      A simple and accurate method for the measurement of total hydrocarbons has been
validated.  All types  of hydrocarbons, Le., alkanes, alkenes, and oxygenated and halogenated
compounds, can be accurately measured with this technique.  We recommend the use of the
oxidation technique for all stack emissions testing, either as a single source of accurate data or as
a cross check of Methods 25 or 25A.
ACKNOWLEDGEMENTS

      The authors are thankful to Ms. Luda Ugarova, Ms. Donna Lei, and Mr. Fred Pretorius for
providing assistance in sampling and analysis, and Ms. Vera Cerny for typing the manuscript.


REFERENCES

1.  A Zlatkis, H.A Lichtenstein and A. Tishbee, chromatographia. 6:67 (1973)

2.  E. Pellizzari, J. Carpenter, E. Bunch and B. Sawicki, Rwffnn  Sci TechnoL 2:551 (1975)

3.  H.B. Singh, J.L. Salas, H. Shigeishi and E. Scribner, Science. 202:899 (1979)

4.  F.F. McElroy, V.L. Thompson, D.M. Holland, W.A. Lonneman and R.L Sella, J.AP.C.A
      26:710 (1986)

5.  J.W. Harrison,  M.L.  Timmons, R.B. Denyszyn and  C.F. Decker, "Evaluation of the  EPA
      Reference Method for the Measurement of Non-Methane Hydrocarbons," U.S. EPA-600/4-
      77-033. June 1977

6.  F.W. Sexton, R.M. Michie, F.F. McElroy and V.L. Thompson, "A Comparative Evaluation of
      Seven Automated Ambient NMOC Analyzers," U.S. EPA-600/54-82-046. August 1982

7.  H.G. Richter, "Analysis of Data Gathering during 1980 in Northeast Corridor Cities," U.S. EPA-
      450/4-83-017. August  1983.
                                         231

-------
VALVE
            METHOD 25A

            HEATED SAMPLE LINE
        SAMPLE TO
        IMPINGER
        TRAIN
                                                       EVACUATED
                                                       SUMMA
                                                       CANISTER
                  Figure 1.  Gascons hydrocarbon sampling systems.
                                       232

-------
       TABLE I.  Laboratory validation tests.
Sample
Concentration
and Type
80.1 ppm propane
753 ppm propane
JJ5 ppm hexane
40 ppm hexane
Total Measured Concentration as Methane (ppm)
Method 25A
GC/FID (A)
240
2256
510
240
Method 25 (CH« + non-CH4)
(B)
Canister
271
3117
120
119
Trap
58
42
367
103
Total
329
3159
487
222
Oxidation
Technique
HC as C02 (C)
265
-
555
256
Average RF (A/C) = 0.93
TABLE IT.  Total gaseous hydrocarbon measurements.
Sample Time
_ (Minutes)
0
_ 	 5
	 10
_^15
, 	 20
. 	 25
	 _30
Total Gaseous Hydrocarbon Concentration, ppm as CH4
Method 25A
GC/FID
51
51
57
48
48
48
48
Oxidation Technique
HC as CO,
50
53
56
56
46
48
54
FID Response Factor
RF
1.02
1.04
1.02
0.85
1.04
1.0
0.89
	 Average RP = 0.98
                       233

-------
TABLE m. Total gaseous hydrocarbon measurements.
Sample Time
(Minutes)
0
5
10
15
20
25
30
35
Total Gaseous Hydrocarbon Concentration, ppm as CH4
Method 25A
GC/FID
69
60
54
51
45
45
43
42
Oxidation Technique
HC as CO,
74
61
50
52
47
44
41
44
FID Response Factor
R,
0.93
0.98
1.08
0.98
0.96
1.02
1.05
0.95
Average RP = 0.99_
TABLE IV.  Total gaseous hydrocarbon measurements.
Sample Time
(Minutes)
0
5
10
15
20
25
30
35
Total Gaseous Hydrocarbon Concentration, ppm as CH4 __
Method 25A
GC/FID
42
42
42
48
51
45
45
42
Oxidation Technique
HC as CO,
41
45
45
45
45
47
45
45
FID Response Factor
Rr _-
1.02 	 .
0.93 	
0.92 	
1.06 	
1.13 	
0.96 ___
1.10 	 _
0.93 _____
Average RF =J>.99,
                      234

-------
TABLE V. Total gaseous hydrocarbon measurements.
Sample Time
(Minutes)
0
5
10
15
20
25
30
Total Gaseous Hydrocarbon Concentration, ppm as CH4
Method 25A
GC/FID
75
99
93
87
84
54
54
Oxidation Technique
HC as CO,
64
75
69
70
70
46
55
FID Response Factor
Rr
1.17
1.30
1.34
1.24
1.20
1.17
0.98
Average RF • 1.20
                       235

-------
   DEVELOPMENT OF AN  ANALYSIS METHOD FOR TOTAL
  NONMETHANE  VOLATILE  ORGANIC CARBON  EMISSIONS
                    FROM  STATIONARY SOURCES


                Merrill D. Jackson, Joseph E. Knoll, and M. Rodney Midgett
                      Methods Research and Development Division
                     Atmospheric Research and Exposure Laboratory
                         U.S. Environmental Protection Agency
                      Research Triangle Park, North Carolina 27711

           Samuel C. Foster II, James F. McGaughey, and Raymond G. Merrill Jr.
                                 Radian Corporation
                                   P.O. Box 13000
                      Research Triangle Park, North Carolina 27709

ABSTRACT
     The accurate measurement of the total nonmethane volatile organic carbon emissions fro*
stationary sources is critical to characterizing of many  industrial  processes and for regulates
according to the Clean Air Act.  Current  methods are difficult to use and  the ability to d.
performance audits has been marginal, especially at low concentrations (50 parts per million °
carbon, ppmc).                                                                     (
     One of the key elements for  an ideal measurement technique would be a detector w"*
responds to all  classes of organic compounds equally, based  on the number of carbon
present.  A commercially available catalytic flame ionization detector (CFID) has shown P
in this area.  Laboratory  studies with a CFID were performed to determine the response *>
compounds with various functional groups. These classes included brominated, chlorinate*
nitrogenated, oxygenated, aromatic, and non-aromatic compounds.   The response of
compound is compared to the response of an alkane with the same number of carbon atoms.
paper will discuss this phase  of  the experimental work.  Future  work with this detector
incorporate an approach for sampling, sample recovery, and field tests for comparison to the
Method 25.

INTRODUCTION
     The accurate measurement of the total nonmethane volatile organic carbon emissions
stationary sources is critical to the characterization of many industrial processes.  Current metnjj
are difficult to use especially at low concentrations (50 ppmc).  One of the key elements f°r ^
ideal measurement technique  would  be a  detector  that responds to all classes of
compounds, equally based on the number of carbon atoms present. The flame ionization
(FID, the detector of choice for most of the analytical methods) responds to unsubstituted      f
in this manner.  However,  when functional groups are added or when the structure (arornati*'
cyclic) changes, the response no longer follows this pattern. A commercially available cal1
flame ionization detector (CFID)  has shown promise in this area.
     The CFID uses a  ceramic source coated with  a nickel/aluminum oxide to act
combination ignitor, polarizer, and catalytic surface in an H2/air flame environment. The  r  .
ceramic catalyst temperature is controlled through a power supply that is adjustable from 0.0 to •
amperes (amps). Increasing the current to the catalyst raises the source temperature. A
between the catalyst temperature and the  detector temperature is essential  to the c
combustion  of organic compounds. Generally, the catalyst temperature can be varied from
800°C, and the detector temperature can be varied between 100 to 400^.'               ..$
     The detector's performance was evaluated by analyzing organic compounds with van ^
functional groups (halogen, oxygen, nitrogen, and aromatic). Functional groups were evaluate  ^
different currents and fuel ratios until an optimal current and fuel ratio was found that gaV
                                        236

-------
universal response. Once the optimal conditions were determined, the performance of the CFID
was compared to the performance of an FID. The overall performance of the CFID was evaluated
by analyzing 61 organic compounds. The response ratio for each compound was compared to the
response ratio of straight-chained alkanes.  All of the response ratios are based on the number of
nanomoles (nmoles) that were injected on column.


EXPERIMENTAL METHOD
     A CFID and power supply available from DETector Engineering & Technology, Inc. (DET)
was installed on a Varian 3600 gas  chromatograph (GC).  The power supply current was variable
from 0.0 to 4.0 amps. The FID was a Varian FID installed on a Varian 3400 GC. The analytical
column, used for all analyses, was a DB-5,0.54 millimeter x 30 meter, fused silica capillary column.
A PE  Nelson  3000 series Chromatography Data  System was used for data acquisition and
processing.
     The detector  tower  temperature  was set at 310°C  for all  of the experiments.   The
temperature limit for the column,  as indicated  by the manufacturer, was 350°C. The operating
conditions were well below the limits of the column.
     The fuel/air ratio, as recommended by DET for the CFID, was a 1:10 mix of hydrogen and
air. To minimize source deterioration, DET recommended that the flow of hydrogen not exceed
25 mL/min and the flow of air not exceed 250 mL/min. The maximum flows were chosen for the
initial studies, and a different ratio was later evaluated.
     A mix of  four aliphatic hydrocarbons was prepared at a concentration of 1.0 milhmoles
(mmole) each in dichloromethane. This mix was used as the baseline for evaluating the detector
response to the number of carbon atoms present. A solution of dichloromethane, tnchloromethane,
and tetrachloromethane (single carbon chloroalkanes) innonane was prepared with each compound
at 0.12 mmol.  The chloroalkane solution was analyzed on the CFID with the current set at 0.0 and
on the FID for comparison.  The  chloroalkane solution was  then analyzed on the CFID at six
different currents: 0.0,2.0,2.4,2.8,3.2, and 3.6 amps, to find the optimal current for the chlorinated
compounds.  A mix of six aliphatic hydrocarbons was prepared at a concentration of 0.013 mmol
in dichloromethane.
     Different mixtures containing compounds of specific functional groups were then prepared.
The standards were prepared at a nominal concentration of 500 /*g/ml. An internal standard (IS),
nonane, was added to each solution at a concentration of 115 jig/ml.  The standards were analyzed
at the optimal current, and at a higher current to determine the effects on the different functional
groups.
     The response factor (RF) for each compound was calculated using equation 1. The response
factor to nmol was plotted against  the number of carbons in each compound.

 RF - (Compound area/IS area) * (1/nmoles of compound injected)            (1)

A "least-squares-fit"  was applied to the data points from each functional groups with the slope,
intercept, and  correlation  coefficient calculated for each of the generated lines. The linear
regression information was compared to the results for the aliphatic hydrocarbons. The number of
carbons that each compound deviated from the aliphatic line was calculated using equation 2.

 No. Carbons Deviated = No. of carbons in compound -                       (2)
     [(RF of compound - intercept of  base line)/(slope of base line)]

The average  number of deviated carbons was calculated for each  class of compounds  for
comparison to the aliphatic hydrocarbons.

RESULTS AND DISCUSSION
     A mixture of  four straight-chained  alkanes (heptane,  octane, nonane,  and decane) was
analyzed on the CFID and compared to the FID as a preliminary test of detector linearity.  The
                                          237

-------
CFID was comparable to the FID, with both detectors showing linearity with increasing carbon
number for the aliphatic hydrocarbon mix.
      Chlorinated compounds were chosen for the initial experiments because of their low response
on FID, as compared to alkanes. Single carbon compounds (dichloromethane, trichloromethane,
and tetrachloromethane) were selected so that the only difference between the compounds was the
number of chlorines present. With 0.0 amps of current applied to the detector, the chloroalkanes
responded similarly, on a molar basis, when analyzed on the CFID.  When the chloroalkanes were
analyzed  on  the FID,  the response decreased  as the number of chlorines increased.   The
chloroalkane standard was then analyzed at 0.0, 2.0, 2.4, 2.8, 3.2, and 3.6 amps to determine the
optimal current for this class of compounds. As the current was increased, the sensitivity increased*
but the baseline became increasingly noisy.  The best compromise between sensitivity, unifonU
response,  and baseline stability was found to be at a current setting of 2.4 amps.
      A mixture of six  aliphatic hydrocarbons (hexane, heptane,  octane, decane, tetradecane,
hexadecane) was prepared from stock standards four times and analyzed in duplicate using the
CFID with the current set at 2.4 amps (Figure 1). The RFs were averaged and a "least-squares-fit
was applied to the data points (Table I). The aliphatic hydrocarbons responded linearly on the
CFID with a correlation coefficient of 0.992, and the resulting line was used as the baseline f°r
comparison with the  other compound classes.
      Separate  mixtures of  compounds from five functional groups  (aromatic, brominateOi
chlorinated, nitrogenated, oxygenated) with nonane as  the IS were  prepared and analyzed at 2.*
together based on the predominate functional group.  Additional studies were performed  .   .
currents for the aliphatic, aromatic, chlorinated and oxygenated compounds in an attempt to
improve linearity and sensitivity.
      Figures 1  through 6 provide a graphical representation of the CFID response versus carbon
number for the six functional  groups studied at 2.4 amps.  For comparison purposes,  a 1&&'
squares-fit" was performed on each data set that generated a value for the slope and correlation
coefficient. The two values for each data set were compared to those generated for the alipnat ,
compounds, which was used as the target or theoretical situation.  The data from the "least-square*'
fit" for the aliphatic compounds and the RF calculated for each compound associated  with tn*
other functional groups were used to calculate the number of carbon atoms for each compou1} ^
This experimentally determined value for the number of carbon atoms was then compared to tB
actual number of carbon atoms in each compound (Table I).
  The plotted slopes for the nitrogenated and oxygenated compounds (Figures 5 and 6) are ^
to that for the aliphatic compounds, which indicates that the responses increase with the nu
of carbon atoms (as expected for normal alkanes).  However, the magnitude of the responses
less than that for the aliphatics, making the experimentally determined carbon number for *".
nitrogenated  compounds, on the average, low by approximately 0.5 carbon and the oxygenaW
compounds low by approximately 1 carbon.
     The slopes for the aromatic and brominated (Figures 2 and 3) compounds were greater
that for the aliphatics. This shows that the CFID response increases as carbon numbers
but at a greater magnitude than for aliphatic compounds.  The experimentally determine
number for the aromatics was found to be high, on the  average, at  0.4 carbons, whereas, Jj'
experimental number of carbons for the brominated compounds  was found to be equal to tn
number of actual carbons.                                                             . e
     The slope for the chlorinated compounds was less than for the aliphatics, indicating that tn
CFID response  increases as the number of carbons increase, but at a magnitude less than that i .
the aliphatics. The  experimentally determined number of carbons was high, on the average, by ^
carbons. The correlation coefficients were all greater than 0.93. This indicates that all of the d9
points lay on or near the resulting line.                                               >    j
     Several functional groups were analyzed at a higher current to possibly improve linearity
sensitivity. Aliphatic, aromatic, oxygenated, and chlorinated compounds were analyzed at
Table II shows the resulting linear regression data for the compounds that were analyzed.
was not improved  with the correlation coefficients less than 0.96.  Sensitivity toward
                                           238

-------
carbon numbers increased slightly for the oxygenated compounds, compared to the slope of the
lines at 2.4 amps and 3.2 amps, and the experimentally determined number of carbons, on average,
increased by 0.4 carbons.  Sensitivity did not increase for the chlorinated compounds, with the slope
increasing and the experimentally determined number of carbons, on average, increased  to 2
carbons.
     The oxygenated compounds were of special interest, since they are  a major component of
many Method 25  analyzes.  They showed a reduced response,  as  compared  to the aliphatic
hydrocarbons, therefore it was important to closely examine this class of  compounds. As noted
above, increasing the current did not change the overall response of the compounds. The fuel-gas
mixture was changed  to 40 mL/min for hydrogen and 250 mL/min for air.  The CFTD did not
behave well at this fuel ratio. The baseline was erratic, and the signal dropped below the baseline
after the solvent peak passed through the column. The CFID behaves better at  a 1:10 gas ratio;
therefore the ratio cannot be changed to achieve better sensitivity towards a functional group.
     As a confirmation  of the response of the  CFID toward the oxygenated  compounds, the
oxygenated compounds were analyzed with aliphatic hydrocarbons on the  CFID  at 2.4 amps and
the FID.  The CFID  response to the oxygenated compounds was the same as the FID response.
Table III lists  the compounds analyzed and the response on the CFID and the FID. The number
of carbons deviated from the target aliphatic line was calculated and the results are listed in Table
III. The average number of carbons deviated from the target response was -1.25 for both the CFID
and the FID.
     There were 61 compounds analyzed on the CFID.  Figure 6 shows all of the  compounds
analyzed on the CFID, and Table IV lists all of the compounds that were analyzed in order of
increasing response factor. The compounds show that the CFID response increased as the number
of carbons increased.  The response for the compounds that are showing a low response are only
low, on average, by 1  carbon atom.

CONCLUSIONS
     The CFID is a detector that acts as a carbon counter, in that the response to compounds
increases linearly as the number of carbons increases.   Oxygenated compounds did not respond
as well as the other functional groups but did respond linearly with increasing carbon number. For
halogenated compounds,  the CFID out performed the FID with a response that was unaffected by
the number of chlorine atoms and responded linearly with increasing carbon number.  The CFID
at 2.4 amps results averaged one carbon number or less deviation when compared with aliphate
compounds. The CFID has remained stable after over 6 months of continuous use. The CFID is
a versatile detector that is able to overcome some of the selectivity problems of the FID.  The
CFID appears to be a good choice as a universal  detector that may increase the overall detection
limit of current stationary source analyses methods.

DISCLAIMER
     The information in this document has been funded wholly or in part by the United States
Environmental Protection Agency (EPA) under contract 68-D1-0010 to Radian Corporation. It has
been  subjected to  Agency review and  approved for publication.  Mention of trade names or
commercial products does not constitute endorsement or recommendation for use.

REFERENCES

      Theory and Operation of the TIB / CFID Detectors. FTP Detector. Remote FID Detector.
     ei^ TTP  Detector. FID Detector: DETector Engineering & Technology, Inc.,  1991, pp 1-2 -
1-6.
                                          239

-------
Table I. Linear Regression for Compounds at 2.4 amps.
Functional    No.      Slope
Group    Compounds
           Analyzed
               Intercept     Corr, Avg Deviation
                           Coef.  From Target
                                 ( No. Carbons )
Aromatic
Brotninated
Chlorinated
Aliphatic
Nitrogenated
Oxygenated
7
3
20
6
8
17
0.0611
0.0501
0.0401
0.0435
0.0477
0.0456
-0.1028
-0.0011
0.0461
0.0154
-0.0380
-0.0349
05872
0.9990
0.9642
0.9964
0.9771
0.9711
0.41
0.07
0.40
0.01
-0.50
-0.90
Table II. Linear Regression for Compounds at 3.2 amps.

Functional     No.      Slope  Intercept     Corr.   Avg Deviation
Group    Compounds                     Coef.   From Target
           Analyzed                            ( No. Carbons )
Aromatic
Chlorinated
Aliphatic
Oxygenated
 7
15
 3
 4
0.0453  0.0159
0.032S  0.1345
0.0155  0.2447
0.0490  -0.0293
0.9284
0.8968
0.9538
0.7969
 0.33
 1.99
-0.10
-0.49
Table III,  CFID at 2.4 amps vs FID for Oxygenated Compounds.

Compound
              RF
             CFID
                RF
                FID
   CFID DEV.
   CARBONS
       FID DEV.
       CARBONS
4-Methyl-2-Penlanone        0.1482     0.1479      -30
p-Tolualdehyde             0.3234     0.3291      -0.9
2-Butanone                 0.1438     0.1457      -1.1
Acetone                    0.0898     0.0902      -1.3
Ethyl Ether                 0.1410     0.1480      -1.1
Methanol                  0.0394     0.0363      -0.5
Propanol                   0.1114     0.1075      -08
Ethyl Acetate               0.1253     0.1215      -1.5
                                               -3.0
                                               -0.8
                                               -1.0
                                               -1.3
                                               -1.0
                                               -0.5
                                               -0.9
                                               -1.6
                                   240

-------
Table IV.  Organic Compounds Analyzed on CFID.
Aliphatic
Hexane
Heptane
Octane
Decane
Tetradecane
Hexadecane









Aromatic
Benzene
Toluene
o-Xylene
Ethylbenzene
Brominated
Dibromomethane
1,2-Dibromoetfaane
Bromobenzene

m-Xylene
p-Xytene
1,2,4-TrimethyIbenzene


















Chlorinated
Methylene chloride
Chloroform
Carbon tetrachloride
1,1-Dichloroethylene
1,2-DichIoroethane
1,1,2-Trichloroethane
1,1,2,2-Tetrachloroethane
Trichloroethylene
Tetrachloroethylene
1,2-DichIoropropane
1,2,3-Trichloropropane
Hexachlorocyclopentadiene
2-Chlorophenol
1,2,4-Trichlorobenzene
Dichlorobenzene
4-Chloro-3-methyI-phenol
o-Chlorophenol
1,4-Dichlorobenzene
4-Chlorotoluene
Chlorobenzene
Nitrogenated
4-Nitrophenol
2,4-Dimtroaniline
2,4-Dinitrotoluene
4-Nitroaniline
1,4-Dinitrobenzene
2,6-Dinitrotoluene
1-Nitronaphthalene
Diphcnylamine









Oxygenated
Methanol
n-Propyl Alcohol
Acetone
Methyl ethyl ketone
Ethyl acetate
Ethyl ether
2-Butanone
Valeraldehyde
Hexanal
1-Butanol
Phenol
4-Methyl-2-pentanone
Benzalaehyde
p-Tolualdehyde
Acetophenone
1-OctanaI
Isophorone




-------
OS-
0.7-
0.6'
0.5-
OJ.
OJ
02
or
  0-
06
O.7-
0.8
0*
0.4-
CL>
0.2-
0.1-
                      8     9     10    12
                        Number o
-------
0.8-

as-
                    6     6    10    12
    MbognixtKl DOM
                      Twgat
                                         NHrogenJtod Utw
                                                                                                   e     a     10    12
                                                                                                     Number of Cwtxxw
                                                                         F%>rc 6. Oiyteuled at 2^4 •

0.7-
I08'
1 0.5-
| 0.4-
| 0.3
0.2-
0.1-





^
•>




S
•



-H




!
Jf




^










^




^





^











! 4 6 8 10 12 14 18 18
Number dCwbora
» 610rg«lics 	 Fhfl. o* Aliph»«e» I


                                   Fig.rt 7. «1 Ot(»ia >1 2/4 ••]».

-------
  SOURCE CHARACTERIZATION OF AIR  TOXICS FROM
                        ROCKET ENGINE TESTS
                              Jerry L. Downs
                              Brad L. Boyes
Stephen L. Pierett              Nancy A. Wellhausen           Robert W. Melvold
ABB Environmental Services    ABB Environmental Services     Rocketdyne Division
39255 Country Club Drive       4765 Calle Quetzal             Rockwell International
Farmington Hills, MI 48331      Camarillo, CA 93012           Canoga Park, CA 91303

ABSTRACT
      ABB Environmental Services designed  a monitoring system to characterize the
emissions during the testing of rocket engines fueled with kerosene (RP1) and liquid oxygen-  \
source characterization was performed in fulfillment of compliance requirements for Califo^
Air Toxic "Hot Spots" Information and Assessment Act of 1987 (AB 2588).   This paper deScn,S
a source characterization requiring the measurement of volatile organic compounds  (»O  ^
polynuclear aromatic hydrocarbons (PAHs), aldehydes, phenol, and metals.  Method develop^6
was required for both the aldehyde and phenol sampling.  Sampling for metals, PAHs, and VU
involved standard EPA ambient sampling methods  with some modifications for extreme s^P^
conditions. Sampling units were located directly in  the plume exhaust at a sufficient distance ff
the engine to minimize damage to the sampling units but sufficiently close to characterize
plume dimensions for calculating plume volume. The paper describes the sampling configuratl. f
the sampling methods, data acquisition, and the methods for determining the plume
each engine test.

INTRODUCTION
      This paper describes air sampling and chemical analyses performed for the Santa  u
Field Laboratory of the Rocketdyne Division of Rockwell International Corporation. The purP 5
of the sampling and analyses was  to provide quantitative estimates of atmospheric emission f*
from rocket engine testing of species of interest in the context of the California Air Toxics
Spots" Information and Assessment Act of 1987 (AB 2588).                              _j
      Sampling was done in the plumes resulting from static testing of Atlas main stage MA-1
MA5A engines. These engines burn kerosene (RP1) and liquid oxygen. The rocket eflgines ^
mounted vertically  on a test stand and exhausted  downward. The exhaust from each test  -
deflected horizontally by a water-cooled flame deflector.  The test stand was at the north s1   >
a small canyon.  The exhaust plume moved horizontally across the canyon, impacted  the
surface on the south side of the canyon and was deflected upward. The plumes from rocket en§
tests were quite visible and had fairly well defined  visible boundaries.                    ^
      Engines were of two types,  boosters and sustainers. The booster fuel consumption rate  4
about five times that of sustainers. Test durations ranged from 20 to 40 seconds for boosters. ^
from 120 to 300 seconds for sustainers.  The plumes from sustainer tests appeared quite  dif*e ^
than those from booster tests. The flame deflector on the test stand was cooled with wateI"Luef
same flow rate for both types of engines.  Therefore, the plumes from the relatively sn^iie
sustainer engines contained relatively larger amounts of condensed water and appeared whitd
the plumes from the booster engines  appeared black.
                                         244

-------
TEST DESIGN
      Because of their short duration, high temperature, high gas flow rate, and non-ducted
emissions, rocket engine test plumes could not be sampled by standard source test methods. The
sampling methods selected were, in general, minor modifications of ambient sampling methods,
except for the methods for aldehydes and phenols, which used standard sorbent solutions and
analytical techniques with a newly-developed sampler geometry.
      As described in more detail below, samplers were mounted on the rock surface on the south
side of the canyon across from the test stand, approximately 120 to 140 meters from the test stand.
The  sampling locations were chosen to be within a well-defined plume and at  a survivable
temperature (about 35 °C  for  sustainers,  about  180 °C for boosters)  on the basis of visual
observations of tests, observations of natural light and infrared videotapes of tests, site topography,
and temperature measurements  near the sampling  location.

Target Analytes
      Target analytes were  selected from the AB 2588 list that are, in general, potentially emitted
from combustion of a petroleum-based hydrocarbon fuel. Samples were collected and analyzed for
the following volatile organic compounds (VOCs).  The range of quantification limits (QL) is also
listed for each VOC.

      VOC                                       PL fppbv)
      Benzene                                    0.1 - 0.2
      1,3-Butadiene                                    0.2
      Chloroform                                 0.1 - 0.2
      1,1-Dichloroethene (vinylidene chloride)       0.1 - 0.2
      Dichloromethane (methylene chloride)         1.0 - 2.0
      Toluene                                    0.2 - 0.5
      Trichloroethene  (trichloroethylene, TCE)      0.1 - 0.2
      Vinyl chloride                               0.2 - 0.5
      Xylenes                                    0.2 - 0.5

To assist in defining the lateral extent of the plume during each test, the canister samples for VOCs
were also analyzed for atmospheric gases (CO, CO2, N2, and O3) and methane. The  carbon dioxide
analysis results were used to aid in estimating the location of the edge of the plume.
      Samples were collected and analyzed for the following polycyclic aromatic hydrocarbons
(PAHs). The quantification limit for each PAH was 1.9 to 4.6 p,g/m? for four sustainer engine
tests.

      PAH                                       PAH
      Acenaphthene                               Acenaphthylene
      Anthracene                                 Benzo(a)anthracene
      Benzo(a)pyrene                              Benzo(b)fluoranthene
      Benzo(g,h,i)perylene                          Benzo(k)fluoranthene
      Chrysene                                   Dibenzo(a,h)anthracene
      Fluoranthene                                Fluorene
      Indeno(l,2,3,-cd)pyrene                      Naphthalene
      Phenanthrene                               Pyrene
      Methyl Naphthalenes

      Samples were also collected and analyzed for formaldehyde, acetaldehyde,  and phenol.
                                          245

-------
       Samples were collected and analyzed for the following 11 metals, which are
 analytes for source tests of combustion sources in the context of AB 2588. The quantification
 (QL) is also listed for each metal:
       Metal       OUfjL^/m3}                     Metal              OL(/ig/m3)
       Arsenic     0,7 - 2,5                        Beryllium          1.2-4.1
       Cadmium   0.1 - 0.2                        Chromium         0.1 - 0.2
       Copper     0.1 - 0.2                        Lead               0.7 - 2.5
       Manganese  0.7 - 2.5                        Mercury            0.02-0.08
       Nickel       0.1 - 0.2                        Selenium           0.7 - 2.5
       Zinc        0.7 - 2.5                        Chromium (VI)     1.2 - 4.1
Sampling and Analytical Methodology

       Volatile Organic Compounds.  SUMMA passivated stainless steel canisters were usedIt
collect the VOCs listed in the previous section.  Generally, the guidance provided in the USE*\
ambient method  TO-14 was  used  to  establish sampling  and  analysis procedures.   ^
subatmospheric pressure sampling mode was used; samples were collected in evacuated canister •
A Whitey stainless steel needle valve with a  0.02 inch orifice was installed on each canister
preset the flowrate based on the expected test duration and the canister volume. A constant 0°
rate can be  maintained through an orifice if  the pressure  drop  across the orifice is equal to
greater than 0.55 times the upstream pressure0'. A constant flow rate was achieved over most
each test period by limiting the final sample volume to approximately 50 percent of the canist
volume. To assist in documenting the flow conditions, a  vacuum gauge was  installed on &
canister to record the initial and final pressure. Previous to each sampling  event, all flow &
were established using an NIST traceable mass flowmeter.                                  ^
       Upon receipt of the canisters at the analytical laboratory, the canisters were pressurized W1
pure  nitrogen to  a  pressure  of  11  to   23  psig.   Analysis  was performed  using &
chromatography/mass  spectroscopy in the full scan mode (GC/MS/SCAN). Laboratory 
-------
flowmeter and Magnehelic gauge.  Prior to the booster engine tests, pressure transducers were
installed across the venturi flowmeters to monitor system flow during each of these sampling events.
Quality assurance/quality control elements implemented for these samples included field blanks,
method blanks, internal standards, multipoint calibrations, analytical blanks, analytical spikes and
sample duplicates.
      The USEPA ambient method TO-13 was used to prepare PUF sample media for sampling,
to prepare samples for analysis, and to perform the analysis.  Analysis was performed using gas
chromatography/mass spectroscopy in the full scan mode (GC/MS/SCAN).

      Aldehydes.  Samples for aldehyde  analysis were  collected using the sampling apparatus
shown in Figure 1.  The sampling apparatus consisted of a sampling nozzle, water cooled trap
(column) packed with 3.0 mm glass beads which contained an aqueous acidic solution of 2,4-
dinitrophenylhydrazine (DNPH), cyclone, and receiving flask. Presence of the 3.0-mm glass beads
in the trap increased the surface area on which the reaction took place between the aldehydes and
DNPH.  Aldehydes react with DNPH by  nucleophilic addition to the carbonyl followed by 1,2-
elimination  of  water and  the formation of 2,4-dinitrophenylhydrazone.  A solution of  2N
hydrochloric acid (HC1) was used to promote the protonation of the carbonyl due to the weak
nucleophilic characteristics0-^.                                         •
      After gaseous emissions from the  plume were captured,  the samples were immediately
transferred to a clean air-tight glass container to prevent contamination.  Samples were then
transported to the laboratory for analysis.  The samples were analytically extracted using a 70/30
(v/v) hexane/methylene chloride mixture. The complete test apparatus was rinsed with acetonitrile
and analyzed separately from the extracted organic solution. The organic extract was concentrated,
and the DNPH-aldehyde derivative was determined using reverse phase high performance liquid
chromatography (HPLC) with an ultraviolet (UV) adsorption detector operated at 360 nanometers
°'4).  Formaldehyde and acetaldehyde were quantified and compared against retention time and
area counts identified with the appropriate standards used during the analysis.
      The capture efficiency of the aldehyde sampling method was referenced against EPA method
TO-ll.  This  method uses DNPH saturated silica gel cartridges.   These Sep-Pak cartridges
saturated with DNPH have a known collection efficiency on the order of 100 percent at a maximum
sampling flow of 1.5 LPM(i).  This method served as the  control standard.  The capture efficiency
of the aldehyde sampling apparatus was calculated based on a capture efficiency of 100 percent for
the Sep-Pak cartridges.
      The laboratory apparatus that was  constructed to produce parts per billion volume (ppbv)
levels of a continuous steady state mixture of formaldehyde vapor consisted of a clean air generator
system, formaldehyde vapor generator, and gas dilution  system. The components of the test
atmosphere are shown in Figure 2.
      Dilution air for the test atmosphere used in validating the proposed method was generated
by a compressed air supply connected to dual silica gel cartridges to remove moisture. Molecular
sieve and activated carbon  removed organic  vapors from  the  primary dilution air.   The
dehumidified, organic-free dilution air from the clean air generator passes through a mass
flowmeter to measure the flow. The dilution air enters the mixing chamber and mixes with the
formaldehyde vapor, resulting in a dilute formaldehyde gas that enters the sampling manifold.
      The formaldehyde vapor generator system consisted of an ultra high purity (UHP) zero air
compressed gas cylinder, glass U-tube with a perforated  center divider, glass beads; diffusion vial,
and a temperature controlled water bath.  All gas delivery system lines were Teflon*. The glass U-
tube was placed into a  35.0 °C +, 0.5 °C controlled temperature water bath.  The temperature
remained  constant throughout the sampling process. Glass beads of 6-mm diameter were placed
in the inlet side of the U-tube to act as a heat transfer and warm the UHP air that flowed across
                                           247

-------
the diffusion vial.  A diffusion vial (bore diameter = 2.0 mm, diffusion path = 7.62 cm, overall
length =  15.2 cm) was filled with 2.5 - 3.0 mL of 37 percent formalin solution ( 37 percent
formaldehyde, 10-15 percent methanol and water) and placed on the exit side of the U-tube. The
entire apparatus equilibrated for 24 hours before collection of a sample. A constant flow across
the diffusion tube was set for the duration of the generation of the formaldehyde gas.  All flo*
measurements were made using a mass flowmeler calibrated to an NIST-traceable flow standard.
      The gas dilution system consisted of a 0.5-L mixing chamber and manifold.  Formaldehyde
was  generated at a rate of 1-2  jtg/min.   This system  was designed to provide  adequate
formaldehyde  sample so that sample could be extracted from the sampling manifold without
sampling ambient air.
      To establish formaldehyde concentration in the test atmosphere, samples were collected witn
Sep-Pak cartridges before and after each method validation sample.  Gaseous samples were drawn
through the sampling device using a high capacity vacuum pump. Flow was measured using a mass
fiowmeter between the sampling device and  the intake of the pump. Samples were collected at 5
to 9 LPM.  Samples were transferred and secured in  air tight glass containers.  Samples were
analyzed  for formaldehyde by HPLC. An average capture efficiency of 115 percent was obtained
using this method.
      Phenol.  Samples  for phenol analysis were collected using the same sampler
(Figure 1) as the aldehyde samples. Collection of phenol was accomplished by using 10 mL o
N NaOH as the collection medium. Samples were immediately transferred and transported to the
laboratory for analysis. Samples were acidified with sulfuric acid and extracted with methylene
chloride. Extraction was performed using a separator/ funnel technique in combination with a
drying and  concentration  step.   Analysis was performed using gas  chromatography/m35*
spectroscopy in the scan mode (GC/MS SCAN).
      The collection efficiency for phenol was validated using NIOSH method 3502 as a reference.
This method uses a midget impinger filled with 15 mL of 0.1 N NaOH and has a known collectio°
efficiency of 97 percent  at a  maximum sampling flow of 1.0 LPM.  Test atmospheres
generated using crystalline phenol in a system similar to that described above.
      To establish the phenol concentration in the test atmosphere, samples were collected
the midget impinger before and after each method  validation sample.  Gaseous samples
drawn through the sampling device using a high capacity vacuum pump. Flow was measured
a mass fiowmeter between the sampling device and the intake  of the pump.  After collect^11
samples were immediately extracted and analyzed using gas chromatography with photoionizatio
and flame ionization detectors (GC/PID/FID) in sequence.  An average capture efficiency of
percent was obtained using this method.
      Metals. Air samples for metal analysis were collected on quartz fiber filters using
Metal Works high volume PM10 samplers with volumetric flow controllers. Samples were  ..
for the 11 metals listed above by either atomic absorption spectrometry or inductively couple
plasma spectrometry. Fuel samples were also collected for each set of tests on a single engin6 a0
analyzed for the  same 11 metals.

Physical Parameters
      In order to estimate emission rates of the species  of interest, concentrations measured in
plumes were multiplied by the plume volumetric flow rate at the sampling location. The plumes
rocket engine tests were quite visible and had fairly well defined visible boundaries near the sam
locations.  Videotapes were made by Rocketdyne staff of the plumes resulting from most of the roc
engine tests during which sampling was done.  Specifically, videotapes were made from two
                                           248

-------
       1. All of the tests were videotaped from a position near the test control center; the line of view
       from this  location was approximately  perpendicular to the plume  flow direction and thus
       provided a good view of plume height (i.e., vertical cross-section) and velocity.

       2.  Most of the tests were also videotaped from a distant hilltop approximately in line with the
       test stand and the sampling location;  this position provided a good view of plume height and
       width.

       The dimensions of physical features visible in the videotapes were determined by  measuring
certain physical features directly, measuring the angles between various features (from the points of
view of the videotapes) with a theodolite, and using trigonometry to calculate the size of other physical
features.  Plume height, width, and velocity (and thus flow rate) at the sampling location were then
estimated by viewing the tests  and the videotapes of the tests, comparing the plume size to that of
physical features,  and timing the approach of the plume to the sampling location.
       Calculating emission rates in this manner was based on the approximation that the concentration
of each species is uniform within the visible plume volume. If the samplers were placed near the center
of the plume, this approximation would result in a conservative estimate (i. e., an over-estimate) of each
emission rate.  As discussed above, sampling locations were chosen  in part on the basis of visual
observation and temperature measurements in rocket engine test plumes.
       Samplers were located at five sites, as shown in Figure 3,  Sites 1 and 3 were primary sites with
a metal (PM^) sampler, VOC (canister) sampler, semi-volatile organic  (PUF) sampler, aldehyde, and
phenol sampler at each site. Sites 2, 4, and 5 were secondary sites with only a canister sampler at each
site. Site 1 was at a distance of 123 meters from the test stand and  was located approximately on the
plume center line. Sites 2, 3, 4, and  5 were located approximately along a line extending southwest
from Site 1. Inlets to all samplers were approximately 1.2 to 1,5 meters above the rock surface (except
for  the canister at site 5, which was mounted  on the roof of a small building at approximately the same
elevation as the other samplers). The sampling results indicate that sites 1, 2, 3, and 4 were within the
plume.  Also, visual observation of the rocket engine tests during which sampling was done confirmed
the  choice of locations as being well-placed within the plume.
       Temperatures at sampling sites 1 through 4 were recorded once per second  during each test.
Also, carbon dioxide concentration was measured in each canister  (VOC) sample as an indicator of
position within  the plume.

Sampling Strategy
       During each  test, power to the samplers was turned on at the test control center at the time of
engine start (10 seconds before actual  ignition).   Sampler start time was staggered slightly using time
delay relays to avoid overloading circuit breakers with the starting current of pump motors. The PM10,
PUF, aldehyde, and phenol samplers all started well within the 10 second period between engine start
and actual ignition.  Solenoids on canister samplers were opened at  approximately the time the plume
reached the samplers (15  to 20 seconds after engine start)  using  time delay relays.  Power to all
samplers was turned off from the control center at the time of engine cutoff.
       Sampler operation was verified by recording the following parameters once per  second during
each test with a digital data logger:

       1.  Julian date
       2,  Time (with a precision of 0,1 second)
       3,  Temperature at sampling sites 1 through 4
       4.  Power  on or off
       5.  The presence of flow (using pressure switches) in the PM]0 and PUF samplers
                                            249

-------
       6.  Power to aldehyde and phenol samplers
       7.  Power to canister solenoids

RESULTS AND DISCUSSION
       The plumes from sustainer tests appeared quite different than those from booster tests.  The
flame deflector on the test stand was cooled with water at the same flow rate for both types of tests.
Therefore, the plumes from the relatively smaller sustainer engines contained relatively larger amounts
of condensed  water and appeared white, while the plumes from the booster engines  appeared black.
The high moisture content of the sustainer plumes resulted in a large decrease in PUF sampler flow 0°
near zero) over the short duration of the test, generally 5 minutes or less.  Before the booster tests were
sampled, pressure transducers were  installed on the PUF  samplers to monitor flow once per second
during the test.  The PUF sampler  flow during the booster engine tests was significantly improved
because of the lower content of liquid moisture in the booster plumes.  None of the target PAHs were
detected.   Typically, benzene,  1,3-butadiene, dichloromethane, toluene,  trichloroethene, and xylene
were detected in the canister samples.
       To  calculate emission rates in grams per second, the mass detected for each contaminant  was
adjusted for sampler flow rate, total plume flow rate at the sampling location, and the test duration-
For each non-detection of a  contaminant, one-half of the  quantification limit was  used to provide a
conservative estimate of the  emission rate.  Metals were analyzed on filter  samples  collected in ^
plume and in fuel samples.  For the filter samples,  metals  typically detected were  cadmium, totaj
chromium, copper, manganese, and  nickel. Lead was detected infrequently.  However, for the fuel
samples, only copper, arsenic,  and chromium were detected at  very low concentrations.  Unlike the
PUF samplers, sampler flow for metals was maintained at a constant flow during sustainer tests because
water droplets in the plume were knocked out in the sampler inlets and did not reach  the filters.   ,
       The elevated temperatures measured  at sites 1 through 4 confirmed that the samplers were with'"
the plume.  Also, the temperature was  generally higher  at  sites  1, 2, and 3 and lower at site f,
confirming that the lower-numbered sites were nearer the plume center line.  Elevated carbon diox|de
concentrations  measured  in  canister samples  at sites  1  through 4   and higher  carbon
concentrations toward sites 1 and 2 confirmed that sites 1 and 2 were nearer  the plume center lit
CONCLUSIONS
       The estimated annual emission rates calculated from sampling and analytical results to date
sustainer engine tests) were all below the AB 2588 degree of accuracy requirements even thoug"
emission rates derived in the manner described in this paper are, in general, over-estimates        °
the implicit assumption of constant concentrations within the visible plume at the sampling 1°
The results did not show  a sufficiently consistent relationship between concentration and position to
allow a different assumption.  However, future test results may provide sufficient information to alw
defining, for example,  a Gaussian plume shape and thus a more realistic estimate of emission rates-
                                             250

-------
REFERENCES

1-  J- P. Lodge, Jr., J. B. Pate, B. E. Ammons, and G, A. Swanson, "The Use of Hypodermic Needles
as Critical Orifices in Air   Sampling," J. Air Poll. Cont. Assoc..  16: 4, 197-200 (1966).

2-  Compendium of Methods for the Determination of Toxic Organic Compounds in Ambient Air.
£PA/600/4-89/017, U.S.  Environmental Protection Agency,  Atmospheric  Research and  Exposure
Assessment Laboratory, Research Triangle Park, NC, 1988.

 -   "Method 3-430,  Determination of Formaldehyde  in Emissions From  Stationary  Sources," in
  Honarv Source Test Methods. Volume III. California Air Resources Board, Stationary Source
^vision, 1989.

4   v
:".  K- Fung and  D. Grosjean,  "Determination  of  Nanogram  Amounts  of Carbonyls as 2,4-
  mitrophenyLhydrazones by High-Performance Liquid Chromatography," Anal.  Chem. 53: 168-171

*
 1  K-  Kukwata, M.  Uebori, H.  Yamasaki, Y. Kuge and Y. Kiso,  "Determination of Aliphatic
Aldehydes in Air by Liquid Chromatography," Anal. Chem. 55: 2013-2016 (1983).

ACKNOWLEDGEMENTS
      Many people in addition to the authors contributed to this project.  Rocketdyne employees who
  &|sted with this project included: Richard Kistner of the Environmental Department, Steve Bommelje
  d other test engineers and members of the test crew, and members of the Photographic Services
  Partment.  Analysis of aldehyde samples and assistance with method development was provided by
g°°ky Fung of AtmAA, Inc.  Other chemical analyses were provided by Coast-to-Coast Analytical
 i/vices. ABB Environmental employees who contributed to the field measurements and/or method
 J^oproent included: Andre Casavant, John Cobb, Richard Countess, Joel Craig, Jim Cullen, Dave
        Randy Home, Jim Howes, James Huffman, C. C. Lin, Glen Salle, Stuart Webster, and Rick
                                          251

-------
               Table I. Canister Quality Control Results:
Canister Filled through Cleaned Sampling Train with Humidified Zero Air
Analyte
Benzene
1,3-Butadiene
Chloroform
1,1-Dichloroethene
Dichloromethane
Toluene
Trichloroethene
Vinyl chloride
Xylenes
PQL
(ppbv)
0.1
0.1
0.1
0.1
1.0
0.2
0.1
0.2
0.2
Analytical Results
(ppbv)
0.2
ND
ND
ND
2.0
ND
ND
ND
0.3
                                 252

-------
           Table II.  Canister Quality Control Results:
Accuracy and Precision for 2  Canisters filled with Calibration Gas
Analyte
Benzene
Chloroform
1 ,2-Dichloroethane
Dichloromethane
1,1, 1-Trichloroethane
Trichloroethylene
Vinyl Chloride
PQL
(ppbv)
0.1
0.1
0.1
1.0
0.2
0.1
0.2
Expected
Cone.
(ppbv)
4.03
1.01
6.02
7.88
0.81
0.85
8.34
Analytical
Results
(ppbv)
No. 1
4.3
0.9
6.3
20.0
1.1
1.0
15.0
No. 2
5.7
0.96
6.6
17.0
0.8
1.0
15.0
Recovery
(%)
No. 1
107
89
105
253
136
118
180
No. 2
141
95
110
215
99
118
180
Precision
(Difference as
% of average)
28.0
6.4
4.7
16.2
31.6
0
0

-------
                                                                       TO PUMP
GASEOUS
EMISSIONS
                       SAMPLING NOZZLE
                                                                                  CYCLONE
                                                                                  RECEIVING FLASK
                                                               GROUND GLASS BALL
                                                               AND SOCKET JOINTS
  FIGURE 1.  APPARATUS USED FOR DETERMINING ALDEHYDE CONCENTRATION FROM ROCKET ENGINE EMISSIONS
                                                254

-------
PUMP WITH
ACTIVATED
CARBON TRAP

REGULATOR Q_2
MASS FLOW
CONTROLLER
S /
00

                    CIRCULATING WATER
                    BATH WITH
                    TEMPERATURE
                    CONTROL
                                                                                     A
UHPZERO AIR
CYLINDER
                    GLASS U TUBE
                    WITH 80 mm GLASS
                    BEAD IN FIRST
                    SECTION AND
                    DIFFUSION VIAL W
                    SECOND SECTION
                                                                                            GLASS MIXING
                                                                                            CHAMBER
                                                                                            MANIFOLD
                     FIGURE 2. TEST ATMOSPHERE FOR GENERATION OF FORMALDEHYDE
                                                255

-------
                                     TEST STAND
                          APPROXIMATE
                             PLUME
                           ENVELOPE
                                  SITE1
                                                           SCALE:
                                                             10M
            /
SITES  •    /

           /
             • SITE 2

       • SITES
• SITE 4
NOTE:
DISTANCES AND
LOCATIONS ARE
APPROXIMATE
             FIGURE 3.  SAMPLING LOCATIONS
                                  256

-------
                Session 8
    Acid Aerosols and Related Pollutants
Petros Koutrakis and James Mulik, Chairmen

-------
                   OVERVIEW OF THE AREAL ACID
                   AEROSOL RESEARCH PROGRAM


                   Larry J. Purdue, Dale A. Pahl and William E. Wilson
                           U.S. Environmental Protection Agency
                  Atmospheric Research and Exposure Assessment Laboratory
                          Research Triangle Park, North Carolina


ABSTRACT
      The Atmospheric Research and Exposure Assessment Laboratory is implementing an acid aerosol
research program that supports the potential establishment of aerosol acidity as a new criteria pollutant.
This program was initiated in FY-88 in response to recommendations of the Clean Air Science Advisory
Committee.  Critical objectives include:  1) evaluation of current methodology and the establishment
of a standard measurement method; 2) the conduct of pilot studies to demonstrate that acid aerosols are
found in large urban areas as well as small towns; 3) extensive characterization studies in urban areas
to establish population exposure; 4) development of models to link ambient concentrations to human
exposure; and 5) fundamental research to understand formation, neutralization, and removal of acid
aerosols.  This paper reviews the status and  progress of the various development, evaluation and
monitoring activities of this program.

INTRODUCTION
      Section 109 of the Clean Air Act requires EPA to develop and review National Ambient Air
Quality Standards (NAAQS). A fundamental part of this process focuses on the scientific information
and data on which NAAQS are based. Section 109 specifies that a pollutant will be listed for NAAQS
development if the EPA Administrator concludes that the pollutant may reasonably be anticipated to
endanger public health or welfare.
      On December 15, 1988, the Clean Air Science Advisory Committee (CASAC) transmitted a
report to the Administrator which recommended that a fundamental research program be implemented
to address the potential need to list aerosol  acidity as a criteria pollutant. These recommendations
identified the  framework for a coordinated research  program  in  four areas: characterization and
exposure assessment, animal toxicity, human  exposure research,  and epidemiology.   The CASAC
indicated that the evaluation of acid aerosol measurement methods should be a fundamental first step
in this coordinated research program.  The CASAC specifically recommended that EPA's Office of
Research and Development (ORD) implement a research program to address six high priority research
objectives pertinent to acid aerosol characterization and exposure.  These six objectives are:  1) the
evaluation of those species  that should be emphasized in characterizing aerosol acidity, as well as
determining the best candidate measurement methods currently available (CASAC indicated that this
evaluation should include EPA sponsorship of a workshop of national experts to consider these issues);
2) the field testing, comparison, and data analysis of current acid aerosol and  ammonia measurement
methods; 3) the evaluation of the results of the methods testing and  comparison programs in a second
workshop to determine the causes and remedies for  differences among these methods; 4) the
establishment of standard methods so that research and monitoring conducted by different groups will
be comparable; 5) the spatial and temporal characterization of acid aerosols and gaseous ammonia; and
6) the estimation of population exposure to acid aerosols in all microenvironments.
      This discussion reviews the status and progress of the research program  implemented by EPA's
Atmospheric Research and Exposure Assessment Laboratory  (AREAL) to address these objectives.
                                          259

-------
ACID AEROSOL MEASUREMENT WORKSHOP
      In response to CASAC's recommendations, AREAL sponsored an acid aerosol measurement
workshop1  in  February  of 1989.  The workshop was attended by  national  experts in aerosol
measurements and by two CASAC members,  as well  as by health effects researchers and NAAQS
experts from EPA's Office of Air Quality Planning and Standards.
      The workshop was designed to solicit detailed information about several of the high priority
characterization  and  exposure  objectives  identified  in  CASAC's  research  recommendations.
Specifically, workshop participants were asked to consider and recommend the species that should be
measured to characterize  aerosol acidity; the suitability of current measurement methods; and designs
for field testing and comparison of measurement methods.
      In evaluating acid aerosol species that should be measured, workshop participants concluded that
the most appropriate indicator of aerosol acidity is fine particle strong acidity measure as hydrogen ion
by either pH or  titration.  Important initial research objectives included the evaluation of existing
methodology and the development  of an accurate and  reliable method that is free of possible
interference. The workshop participants also indicated that the evaluation must include (1) distribution
of audit standards to check the accuracy and  precision of laboratory analyses used in acid aerosol
methodology; (2) tests of sampling and analysis systems using laboratory-generated aerosols with known
composition and interferences;  and (3) one or more field tests of complete acid aerosol sampling and
analysis systems.

ACID AEROSOL METHOD INTERCOMPARISONS
      In response to the  recommendations of the workshop participants, AREAL has conducted three
method intercomparison studies; a laboratory intercomparison study,2 an outdoor smog chamber study(
and a follow-up  evaluation of extraction and  analytical  effects.4  Most of the research teams that
participated in these studies used variations of denuder technology to determine fine particle acidity-

Laboratory Intercomparison Study
      The laboratory intercomparison  study was conducted  at an AREAL test facility in two phase*
in December 1989 and February 1990. Three experienced investigators from the Harvard School to*
Public Health, Robert Wood Johnson (RWJ) Medical School, and Research Triangle Institute (B™
were invited to participate.  Phase I involved the operation of the three different annular denude*
systems (ADS), in duplicate, by each institution using a multi-port manifold. Single component pw^
aerosols were sampled simultaneously  by each investigator.  The aerosols used  for the  ind*1
experiments were sulfuric acid (H2SO4), ammonium bisulfate (NH^SO*), and ammonium
(NH.NO,).
      The Phase H evaluation addressed the effects of H2SO4 neutralization by NH^NOj on the
filters of the ADS . Additional Phase H experiments involved challenging the ADS with a photochemjc*!
smog/H2SO4 mixture generated in AREAL's smog generation chamber.  A summary of the
analysis of the results from these two experiments is shown below.
                               Phase I      Phase
                    H+           9           16
                    S04J          4           5
                                  7           9
        Average percent coefficient of variation for all experiments
                                           260

-------
Outdoor Smog Chamber Study
      Due to the physical limitations of the sampling manifold used in the laboratory intercomparisons,
the ADS's were evaluated without their particle separation inlets.  In order to evaluate the performance
of the entire sampling systems, and to better simulate field use conditions, an outdoor smog chamber
study was  undertaken.  This study was conducted during the summer of  1991 in an outdoor smog
chamber located in Chapel Hill, North Carolina.  Seven systems were evaluated: two from Harvard
and one each from RWJ, RTI, Brookhaven  National Laboratory (BNL),  the  University of Kansas
(KAN), and New York University (NYU) Medical Center.  Six of these systems used variations of
denuder technology in which fine particles are separated with an appropriate inlet, NH, is removed with
an annular or parallel type denuder, fine particles are collected on a Teflon filter and hydrogen ion is
determined with a pH electrode.  The seventh system, operated by BNL, did not use  a denuder, used
quartz filters for particle collection and used titration to determine hydrogen ion. Experiments were
conducted with a variety of test aerosols including H2SO4 only, photochemical smog with added HjSO^
photochemical smog with added H2SO4 and dust, and dust followed by photochemical smog with added
H2SO4. Two experiments with each of these mixtures were conducted. Estimates of the Ultra-laboratory
and inter-laboratory precision for all experiments are summarized as follows:

                                             % CV

             Species             Intra-Lab           Inter-Lab
              H+                 10                 26
              S042'                5                 11
              NH/                5                  9

Extraction and  Analytical Effects Study
      An additional study was undertaken to estimate the contribution of the extraction and analytical
components of the methods to the total variability as determined in the two previous experiments.  Three
experiments were conducted with five laboratories participating.  The laboratories were Harvard, RWJ,
RTI, KAN and NYU, The first experiment involved the analysis of spiked Teflon filters by each of
the laboratories. The second involved the collection of simultaneous atmospheric samples with identical
Harvard ADS samplers by one group (Harvard) for analysis by each of the laboratories.  The final
experiment involved the collection and extraction of simultaneous atmospheric  samples by one group
for analysis by each of the laboratories. Estimates of the intra-laboratory and inter-laboratory precision
is summarized below:

                                             %CV

             Species            Intra-Lab           fifter-Lab
             H+ Spiked            5                  12
             H+ Ambient          7                  10
             H+ Extract           2                  7

             NH/  Spiked         3                  16
             NIL/  Ambient       5                  16
             NH/ Extract         2                  11

             S042' Spiked          3                  10
             SO*1" Ambient        3                  8
             S04J- Extract          2                  6
                                            261

-------
 Conclusions
       The primary finding of these studies is that the acidity (hydrogen ion) was being measured to
 a precision of approximately ten percent within laboratories and a total precision between laboratories
 in a range from ten to twenty-six percent.  The extraction and analysis components of the methodology
 contributes about fifty percent of the total variability. These results should provide reasonable estimates
 of the contribution of measurement variability to the uncertainty of the results of existing and on-going
 epidemiology studies.  Considering the complexity of the methodology and the reactivity of the acid
 species, this level of precision was deemed acceptable and has encouraged AREAL to pursue tbs
 development of a standardized version of the annular denuder methodology in anticipation of improved
 precision in future applications of this technology.

 STANDARDIZED METHOD FOR MEASURING ACID AEROSOLS
       Based on the findings of the  method intercomparison studies,   AREAL  is developing 3
 standardized version of the annular denuder methodology based on the procedures used by most of tW
 participants in these studies.  The method description has been drafted, is currently under peer review
 and should be ready for distribution  by July or August of 1992. This  standardized methodology *^
 represent a composite of the most viable features of the research methods utilized in the intercomparisou
 studies.
       The method description will include two parts: Part 1 - Standard Method; and Part 2 - Enhanced
 Method.  The Standard Method utilizes a denuder for removing ammonia and filter assembly for deter'
 mination of atmospheric fine particle  strong acidity aerosol, but does not address potential interferences
 from  nitric  acid  (HN03)  and nitrate  aerosols such as NI^NOj which,  if present in  sufficient
 concentration, may bias the acidity measurement.  The Enhanced Method adds an additional denuder
 upstream of the filter assembly to selectively remove HNQ, from the gas stream prior to filtration. I"
 addition, backup nylon and citric acid impregnated glass fiber filters have been incorporated to correct
 for bias due to the dissociation of nitrate aerosol.
       The method description will be presented in document control format to facilitate
 changes as experience is gained with use of the method and advancements are made in  the
 of this technology.

URBAN ACID AEROSOL CHARACTERIZATION/EXPOSURE STUDIES
       Several projects have been initiated in response to CASAC's recommendations regarding spatfe1
and temporal characterization of acid  aerosols and estimates of population exposure.  In order t°
                                                                              .
facilitate planning  for  urban area  characterizations,  an analysis of existing data from two
epidemiological studies conducted by the Harvard University School of Public Health was undertaken. '
Conclusions from this analysis indicate that 1) acid aerosols are expected to occur most predominate^
in the east central U.S. ; 2) aerosol acidity peaks in July and August with substantial concentrations fro*
May through September; 3) the concentration of aerosol acidity shows an afternoon peak; and 4) t*J
distribution of aerosol acidity across a large urban area and the sources  of NH3 within urban areas ne«J
further investigation. Based on this and other information, AREAL has developed a program to sttw
seasonal and spatial variations of acidity and NHj, including winter and summer intensive studies v
address specific questions regarding  detailed chemistry, size distributions, neutralization processes, &
indoor/outdoor relationships. During the summer of 1990 and 1991, AREAL sponsored pilot st«***j
in Pennsylvania and Georgia to investigate concentrations of aerosol acidity in large urban area* **!:
address questions regarding NH3 neutralization.  Observations of significant aerosol acidity level*
Pittsburgh and Atlanta  supported the need for further characterization studies in other urban are**
Current plans call for conducting year long studies in five or six major metropolitan areas. Tne &*
of these studies will be  initiated this summer in Philadelphia, Pennsylvania.
                                            262

-------
OTHER RELATED RESEARCH
      AREAL has a continuing program  which addresses the development,  improvement and
simplification of acid aerosol measurement methodology.  A sampler capable of collecting day-time
and/or night-time samples for estimating weekly averages is under evaluation in the Philadelphia Study.
^e to the need and interest in real-time measurements, research is in progress to develop a real-time
continuous acid aerosol monitor.
      Research has been completed that suggests that for ambient NH3 concentrations less than 10 ppb,
acid aerosols are not completely neutralized.7  Research is also in progress which will address the
Possibility that  H2SO4  droplets  may be   coated with an organic film which prevents NH3 from
neutralizing the acid.  This possibility has important implications for sampling and for future health
studies.  Finally, a simple model to study H2SO4  formation, neutralization and  transport is under
development.

J^ERENCES
      Tropp,  Acid  Aerosol Measurement Workshop. EPA/600/9-89/056,  U.S. Environmental
      ion Agency,  Research Triangle Park, NC, 1989.
   I'M.  Barnes, A  Laboratory Intercomparison of Three Acid Aerosol Measurement Systems. Internal
      U.S. Environmental  Protection Agency,  Research Triangle Park, NC, 1990.
       Ellestad,  H.M.Barnes,  R.M. Kamens,  etal,  "Acid  Aerosol  Measurement  Method
               An Outdoor Smog Chamber Study,"  in Proceedings ,qf.theJL991 EPA/A&WMA
            ymposium on Measurement of Toxic and Related Air Pollutants. VIP-21, Air & Waste
           Association, Pittsburgh, Pennsylvania, 1991, pages 122-127.
**• T-G. Ellestad, L.L. Hodson,  S.J. Randtke, et al, "Acid Aerosol Measurement Methods: Studies
oL^toction and  Analytical Effects,"  in Proceedings of the 1992  EPA/A&WMA International
7"QESSJum  on Measurement of Toxic  and Related  Air Pollutants.  Air &  Waste  Management
*ss°ciation, Pittsburgh, Pennsylvania, 1992.
 .' ^-B'  Wilson, K.M. Thompson, M. Brauer, et al, Patterns in Ambient Concentrations of Aerosol
       Internal Report, U.S. Environmental Protection Agency, Research Triangle Park, NC, 1991.
      •  Thompson, W.E. Wilson, P. Koutrakis, et al, Measurements of Aerosol Acidity:  Sampling
  ^uaj. Seasnp^ Viability and Spatial Variations. A&WMA 84th Annual Meeting, Vancouver,
7njsh Columbia, 91-89.5, June 16-21, 1991.
     v""trakis, W.E. Wilson,  M.J. Wolfson, et al,  "Measurement of Partial Vapor Pressure of
         Over Acid Ammonium  Sulfate Solutions,"  in Proceedings of the 1992 EPA/A&WMA
            Symposium on  Measurement  of Toxic and Related Air  Pollutants. Pittsburgh,
            1992
                                          263

-------
 Measurement of Partial Vapor Pressure of Ammonia over Acid Ammonium Sulfate Solutions
                                 by an Integral Method

                    P. Koutrakis, M. J. Wolfson, and B. Aurian-BlaJeni
  Harvard School of Public Health, Dept. Exposure Assessment & Engn., Boston, MA 0211
                                       Abstract
We present a simple, integral, passive method for measuring partial vapor pressure. Integral
methods are useful tools when dealing with very low concentrations, because collection over
extended periods increases the analytical sensitivity. Passive methods have the advantage of not
introducing constraints external to the system.

The principle of the method used here is to react selectively the substance in the atmosphere
over a solution with an immobilized coating  on an appropriate support. The reaction product is
not volatile, but is soluble and can be extracted in an appropriate solvent and analyzed. The
method has been applied to measuring the vapor pressure of ammonia over aqueous solutions.
The results show that the vapor pressure over ammonium sulfate solutions depends on the acidity
of the solutions as well as on the salt concentration. The dependence can be explained with a
simple model. Furthermore, using the same model we calculated the ammonia vapor pressure
above different ammonium sulfate - sulfuric acid aqueous solutions as a function of sulfate
molarity and percentage of sulfuric  acid. The results from the calculations  suggest that f°r
ambient ammonia concentrations less than 10 ppb, acid sulfate aerosols are not  completely
neutralized.

I. INTRODUCTION

Although thermodynamic calculations of the equilibrium vapor pressure in  pure  and mixecl
systems abound, few experimental determinations are reported [Saxena et al., 1986]. In this work
we present a simple, integral, passive method for measuring partial vapor pressure. Integral
methods are  useful tools when dealing with very low concentrations, because collection over
extended periods increases the analytical sensitivity. Passive methods have the advantage of not
introducing constraints external to the system, e. g, forced flow over the solution, or through the
atmosphere for which sampling is performed. The principle of the method used  here is to colle0*
a gaseous substance over a solution,  on  an appropriately coated support, at a known distance
from the liquid surface. The reaction product was extracted in water for analysis. The technf"""
described was applied to measuring the vapor pressure of ammonia over ammonium  sulfate
ammonium sulfate/sulfuric acid solutions.

II. EXPERIMENTAL

The measurements were carried out in slender cells, that buffer small temperature changes.
cells have covers with a groove on one side, for sealing (Figure 1). The covers are flat on tn
other  side. Before each use, the cells were baked overnight to 150°C and cooled in a desiccato •
The coated surface for ammonia collection was a fiber glass filter. The filters were washe
                                         264

-------
sequentially with purified water, sulfuric acid
solutions, and methanol. After exposure, the
glass fiber  filters were extracted  with water
and analyzed.

Reagent  grade  chemicals  were  used.  The
filters were coated  with  a 0.75  N  H2SO4
solution in  3:1 (v/v) watentnethanol mixture.

Experiments consisted of exposing the coated
/H|
inters for various times and analyzing them
'or  ammonium   ions,   in   a   constant
temperature room, in a glove box flushed
with ammonia-free  air.  The  filters were
Placed  on the top of the covers  and coated
'"side the glove box (Figure la). When the
filters  were  almost dry,   the  covers were
flipped   to  expose   the   filters   to   the
atmosphere above the solution (Figure  Ib).
After the desired exposure period, the filters
Were  removed  and  stored  in  vials.  The
filtered  extracts  were  analyzed  by  ion
chromatography   or   with   ion   specific
                                             collecting layer
                                                                (31 art from aalo
                                                                disc  from toln
                                                                            Henry 'a constant
                                                                          c concentration
                                                     ®
©
                                           Figure 1   a)   cell    before   starting   the
                                           measurement;  b) cell in working position (the
        r-r~f                    -f        honeycomb  layer  represents  the  fiberglass
electrodes. The proton activity was measured   filter); c) ammonia concentration profile inside
    a pH electrode.                         the cell, at steady state.
        tests were  performed  for detecting
 ^erimental artifacts. One concern was the disturbance provoked by flipping the covers. The
 "ffusion time, for 1 cm distance between the collecting surface and the solution surface and for
 the diffusion coefficient of ammonium sulfate of 0.23 cm2 s \ is less than 4 s, however, while the
 "Mnirnum sampling time was 180 s. Therefore we do not  expect any  significant errors due to
 '"Pping the cell covers. The ammonium salts trapped on the filters were stable over several
 Weeks of storage at 4°C, and prolonged storage did not affect the analysis results of the water
 *tracts of the filters. Water kept in the laboratory atmosphere inside polyethylene wash bottles
 Was contaminated by ammonia, therefore fresh water was used for each experiment.  Analysis
 )f c°ated filters left exposed  and manipulated in the glovebox for 24 hours showed no signs of
 ammonia contamination.

    RESULTS AND DISCUSSION

                      and validation.The model used to interpret the variation of the amount
   ammonia collected on the fiberglass filters as a function of exposure time is expressed as:
 ^j6 WNHJ is the amount of ammonia collected (g), PNHj is the vapor pressure of ammonia (g
     » & is the diffusion coefficient of ammonia in air (cm2 s'T), t is the time (s), 0 is the area
                                           265

-------
of the solution air interface (cm2), and L is the distance between that interface and the
collecting surface (cm).

The physical assumptions underlying the measurement of vapor pressure based on this equation
are: - the concentration of ammonia  at the solution-atmosphere interface is equal  to the
equilibrium vapor pressure; - there is a linear gradient in the concentration of ammonia between
the surface of the  liquid and the collecting surface;  and: - the collection rate is controlled by
diffusion, not by chemical reaction.  In other words the collecting surface is a perfect sink and
the concentration  of ammonia at the surface of the filter is zero at all times. These three
assumptions are graphically illustrated Jn Figure Ic. In solution, there is a certain concentration
of ammonia, c. At the solution-atmosphere interface, the concentration of ammonia changes
according to Henry's law to He, where H is Henry's constant. Before the measurement starts,
the concentration of ammonia  is constant inside the eel!. When the measurement starts, the
concentration  drops to zero at the collecting surface.  A  steady state  linear concentration
gradient  forms between the solution surface and  the collecting surface.

For calibration purposes, the vapor pressure of ammonia solutions was measured and compared
with values estimated theoretically. The experiments showed that only the initial rates of uptake
should be considered for high values of the vapor pressure, because  of saturation effects.

The vapor pressure of ammonia solutions was estimated, using  Wilson's equation, as  folio*8
[Ohe, 1989]. The vapor pressure is
calculated from the equality:
           f-j = Pyt Xj
where f is   fugacity,  subscript   i
denotes the i-th component, L stands
for "liquid", Pj  is the vapor pressure
of the pure component i, Xj is the
mole  fraction of component i, and y{
is the activity coefficient. The activity
coefficients were calculated according
to Wilson's equation and the vapor
pressure  of the pure components was
calculated  according   to  Antoine's
equation [Ohe, 1989].
 100

 90

1 80

 70

. 60

. 50

 *0

 30

 20

 10
                 100     1!0      200
            maoi'd onvnonio uptok* rale (ng/i)
                                       250
                                    Figure 2  Correlation  between  the  calculated
Figure 2 illustrates the relationship  pressure  of  ammonia  over  ammonium  hydroxide
between  the  rates  of  ammonia  solutions and the initial uptake rate  of ammonia over
collection and  the predicted  vapor  ammonium hydroxide solutions.
pressure  of  ammonia   over  the
solution. The correlation is linear, and this makes us confident that the present method can b6
applied to measuring vapor pressures over salt  solutions. Good agreement is reported in * e
literature between predicted  and  measured values of ammonia vapor  pressure,  in l
concentrated and dilute solutions [Ohe, 1989; Wilson et aL, 1980]. The hypothesis of foi
of a linear concentration gradient in the gas phase between the surface of the solution and t»e
collecting surface was also tested and found valid. The test consisted in changing the distance
between solution and the collecting surface. The coated filters were exposed for differen
                                          266

-------
Periods. The time dependence of ammonium concentration in the aqueous extract is linear, as
e*pected, for each distance. The linear relation between the amount of ammonia collected and
toe inverse of distance between the surface of the solution and the collecting surface also agreed
with the model.

iLADplication  to ammonium sulfate solutions. The ammonia uptake above ammonium sulfate
folutions by coated filters was measured for different concentrations of both SO^  and NH/
ions. The vapor pressure was calculated using the calibration curve illustrated in Figure 2. The
lowest vapor pressure  measured in this study was about 5 ppb. The experimental data  are
summarized in Table I.

Table I. Vapor pressure (in ppb) and proton activity (pH) of ammonia over solutions containing
   / and
JliSO4 % -+
[S042']/M
^_ J
4.3
3.6
	 2.7
1.8
1.0
0
ppb
1310
1080
800
462
282
PH
4.5
4.55
4.85
5.14
5.30
.2
ppb
-
347
339
158
120
PH

3.06
3.11
3.53
3.70
.5
ppb
-
122
63
40
-
PH

3.06
2.70
3.20
3.33
1
ppb
-
55
32
13
-
PH

2.31
2.36
2.80
2.88
5
ppb
35
19
9.5
5.5
-
pH
1.53
1.55
1.59
1.77
2.14
    4.03 M sulfate concentration, which is very close to the saturation concentration at room
 niperature, was not investigated in more detail because of crystallization problems. The values
  **te ammonia vapor pressure over ammonium sulfate solutions containing 0.5% (mol/mol)
 'wric acid are about one order of magnitude lower than those without sulfuric acid, which is
 °nsistent with data in the literature for solid ammonium sulfate  [Scott and Caltell, 1979],

nj%&ico-chemical model was derived for the interpretation of the measured ammonia vapor
        over  ammonium sulfate solutions which is comprised of relationships for chemical
       *, mass balance, and charge neutrality:

       * NH3(aq)        Hc  Henry's constant - 60  mol kg'1 amV1 [Cleggand Whitfield, 1991]

        + H+ 52 NH4*   Ku - 1.7 109 kg mor1 [Clegg and Whitfield, 1991]

                        Ku = 1000  mol kg'1 [Robinson and Stokes, 1955]

                        Ku = 0.01 mol kg'1 [Robinson and Stokes, 1955].

                2[S04Z"] + [HS04-] (the [OH'] was neglected)

    total sulfate =  [SO^] + [HSO4'] + [H2SO4]
      * H*  + HSCV

   °»" 5S H+  +
 S*
                                         267

-------
 Based on the above equations:
 NH3(g) = A S (R-R2)/(R-2)

 where R= [NH/J/S, A= py,,yu/HeKiiKu.ytii ^MbwP'iu^W. andy13 = yHso4-/yH+y so4i-The
 factor p accounts for the change in the units of NHj(g) from atm to ppb and for conversion
 from molality to molarity units of concentration for S. Several  approximations were  applied
 when deriving this equation. First, in solutions for which the ammonium to sulfate ionic ratio
 is higher than 1, we can assume that all the sulfuric acid is dissociated and the [H2SO4] term can
 be neglected. Second, experiments showed that the highest activity of protons in the solutions
 investigated was less than 0,1  (Table I). We can therefore assume that in our system the H
 term can be omitted in  the neutrality equation. Third, from known molarity of ammonium
 sulfate, the  [NH4+] can be considered known as well, assuming that [NH4+]»NH3(g).

 The calculated values of A are listed in Table II. The experimental results show that A depends
 on S and R.

 Table II. Values of A as a function of solution acidity and molarity
R-*
S
3.6
2.7
1.8
1.996

0.194
0.253
0.177
1.990

0.172
0.118
0.113
1.980

0.157
0.122
0.074
1.900

0.31
0.205
0.179
In the range of ratios between 1.99 and 1.90, we can approximate the variation of A by a
straight line:

A = a+bR

The values of a and b are dependent on the value of S.  By extrapolating to lower values of *•
and assuming A to be linearly dependent on R in  the range 1.990 to 1.600, one can obtain1

NH3(g) = S(a+bR)(R-Rz)/(R-2)

Using the experimental data from Table I, the constants a and b can in turn be linearized »s *
function of S as:

a = c+dS  and  b = e+fS

The values of c, d, e, and f are 0.30, 0.82, -0.14, and -0.39, respectively, and were determin*
by linear regression. Using these values of the parameters we can calculate the vapor PreSSUfl£j
of ammonia as a function of R for different values of S. Figure 3 shows both the calculated»»»
the experimental values of the ammonia  vapor  pressure.  As it can be seen, the m
calculations were extended to predict ammonia vapor pressure in regions where
                                         268

-------
     1000
               1.7  1.7!  !,8   1.85  1.9
                ormonk.n/lu'foU loot rollj
                                 1.95
 FigureS  Vapor pressure of  ammonia  as  a
 function of the ammonium to  sulfate ratio for
 various total concentrations of sulfate. The lines
 are predicted  and the symbols are measured
 values for the sulfate concentrations indicated in
 the legend.
      have required prohibitively long times.
This has been done because pressures down
to 1 ppb are of great interest for atmospheric
chemistry studies.

G^-Atmospheric acid sulfate particles. Since
ammonia is the most important neutralizing
agent  of the atmospheric acid sulfates, it is
very  important  that  measurements   of
arnmonia vapor pressures above (NH4)y5O4 -
^zSO4 aqueous solutions be made. Because
typical ambient ammonia concentrations are
m the range of  few ppb,  in Eastern U. S.
"fra!  areas, (Koutrakis and Mueller, 1989],
^easurements  should be made down to this
 evel.  The method presented  here allows
termination   of   such    low  ammonia
^ncentrations. The lowest concentration we
Measured   was  5.5  ppb.   Using  model
filiations we  determined  lower  vapor
Pressures for more acidic solutions as shown
ln Figure  3, As  one would expect  ammonia vapor pressure  decreases as the acid content
lricreases and sulfate molarity decreases. Under typical  ambient relative  humidities aerosol
s°ttates have molarities higher than 1M [Koutrakis et aL, 1989], therefore for ambient ammonia
^ncentrations less than 10 ppb, acid sulfates can remain slightly acidic. For concentrations less
 han 2-3 ppb, a substantial part of sulfate particle acidity remains unneutralized.

  • Conclusions

  e 'Wegral method used in the present study is successful in measuring the ammonia vapor
Assure over ammonium sulfate/sulfuric acid solutions. This method is sensitive and allows
.^asurement °f low vapor pressure values, down to the parts per billion level in NHj. Because
  ls a passive method, it  is not subject to fluid flow approximations and errors. The main
          is that the method assumes a linear dependence between time and collected amount
         ce, which  is true only when the collection rate is low.

    n" i simple physico-chemical model we calculated the ammonia vapor pressure for different
      solutions as a function of sulfate molarity and percentage of sulfuric acid. The results of
      Calculations revealed  that for ambient ammonia concentrations less than about 10 ppb,
       sulfates remain partly unneutralized. Furthermore, for lower concentrations 2-3 ppb,
 «nn   /e tyPical of Eastern U. S. rural areas, IT/SO ^ could be higher than 0.4. This finding is
 acid^3"1 Since existin8 models assume that the ammonia vapor pressure above acidic or slightly
    10 s°lutions is zero [Saxena et aL, 1986].
 I
 ai*ttnlrtl-er studies we w*l' employ the same technique for measuring vapor  pressures above
 tj]e °nium chloride and nitrate aqueous solutions. Both salts are very important components of
               aerosol system.

269

-------
REFERENCES

Clegg S. L., and M. Whitfield, in Activity Coefficients in Electrolyte Solutions, K. S. Pitzer (Ed.).
2-nd Edition, CRC Press, Boca Raton (1991)

Koutrakis P., and P. K. Mueller, 82nd Annual Mtg. and Exhibition, Air and Waste Management,
Anaheim, Ca, June 25-30, 1989

Koutrakis, P., J. M. Wolfson, J. D. Spengler, B. Stern, and C. A. Franklin, /. Geophys. Res., 94,
6442 (1989)

Ohe S., vapor-liquid equilibrium data, Kodansha, Tokyo, 1989

Robinson R. A., and R. H. Stokes, Electrolyte Solutions, Butterworths, London, p. 373 (1955)

Saxena P., A. B. Hudischewskyj, C. Seigneur, J. H. Seinfeld, Atm. Env., 20,1471-1483 (1986) and
references therein

Scott W. D.,  and F. C. R. Caltell, Vapor  Pressure of Ammonium Sulfates,
Environment, 13, 307 (1979)

Wilson G. M., R. S. Owens, and M. W. Roe, in Thermodynamics of aqueous systems,
industrial applications,  S. A. Newman (ed.), ACS Symposium Series, v. 133, p. 187, 1980
  DISCLAIMER
  Although  the research  described  in this article  has been  funded
  wholly or in part by   the United  States  Environmental  Protection
  Agency though  EPA Cooperative Agreement  CR  816740,  to Harvara
  School of Public Health,  it has not been subjected  to Agency  review
  and therefore does not  necessarily  reflect  the views of the  Agency
  and no official endorsement should be inferred.
                                     270

-------
                  AN ASSESSMENT OF ACID FOG


                                Frederick W. Lipfert
                            Department of Applied Science
                           Brookhaven National Laboratory
                                  Upton, NY 11973


INTRODUCTION
     Airborne particles have long been associated with adverse effects on public health,
beginning with the notorious air pollution disasters of several decades ago.'  Although
was identified early on as a potential causal factors during these episodes (in part because of
f°8),2 concern for potential health effects of  particle acidity  per  se  has  intensified only
       .   Most of the recent aerometric research in the U.S. on acid fog has focused on the
ability of clouds and fog to deliver acidity to vegetation and ecosystems.
     Strong acids are characterized chemically by their pH or H+ concentration.  For  fog,
concentrations are referred to the droplet liquid content; for other (i.e., "clear air") aerosols,
to the volume of air sampled. A useful measure of the relationship between aerosol and fog is
obtained by comparing their mass concentrations on the basis of the same volume of air, by
multiplying fogwater  concentrations by liquid water content (LWC).  For fog,  LWC ranges
'Tom about 0.01 to 1 g HiO per cubic meter of air (about four orders of magnitude higher  than
dear air aerosols,  depending on the  relative humidity).   For this reason, the same mass
concentrations of acid fog particles and acid aerosol particles represent greatly different ionic
strengths and pH's. For example, a fog with LWC  = 1 g/m3 and pH = 3.7 corresponds to an
*** concentration of 10/ig/m3 as sulfuric acid.  That same concentration in a clear air aerosol
could correspond to pH values less than  1.  Inspired aerosols may be changed chemically and
Physically  during breathing because of humidincation and by neutralization from endogenous
^TOnionia.
     This paper reviews fog measurement capability, physical properties and chemistry, and
Presents a simple  urban  airshed model  which is used to simulate the evolution of fog and
p^osol concentrations under urban stagnation conditions. More detailed discussions of extant
Jfcld measurements of fog chemistry may be  found in the technical report4  from which this
Paper was  condensed.

^E PHYSICS AND CHEMISTRY OF FOGS

TJT>esofFog
0    The  source of the cooling identifies the type of fog. Adiabatic expansion due to flow
 /« a mountain creates lee clouds.  Advection of cooler air can create fog.  The situation of
     interest with respect to air pollution is  radiation fog, in which cooling is provided by
      of  radiative heat transfer from a more-or-less stagnant air mass.   Radiation fog can
      due to trapping in valleys or because  of thermal inversions.  The  major  urban air
     on fog episodes were caused by inversions,

  °8 Measurements
     k     Properties  of fogs are largely deduced from analyses of collected liquids;  number
            may be  estimated from particle counters. The methods used to accomplish this
 suhJIf crucial-  R is  important to collect fog droplets of all  sizes and  to prevent their
 surfa  Uent evaP°ration.  Droplets are usually obtained by impaction against nylon or teflon
 coll™*8'  In order to estimate LWC, the amount of air processed and the efficiency of liquid
   ^copn must be known with precision
         eld intercomparison of five different fog water collectors was performed  in June
      near  Los Angeles.5   The  LWC  "calibration'1  factors  of  each  sampler  ("true"
                                         271

-------
 value/sampler value)  varied  from  1.25 to 3.50;  it appears from these experiments that
 adjustments should be made to the LWC values obtained from specific types of fog collectors.
 Fogwater chemistry was found to be quite  repeatable in blind split replicate analyses for the
 major ions; coefficients of variation were in the range 3-5%.  The pooled standard deviation of
 pH was 0.6 pH units, with higher pH values in the laboratory than in the field.  pH values
 appeared to be unbiased, but variable.

 Physical Considerations
      Fog is often defined  as a cloud in contact with the ground and consists of a suspension of
 condensed water droplets  of the order of 5-50 /im  in diameter,  with number concentrations
 from ten to hundreds per cc of air.3  The distinction between a haze particle and a fog/cloud
 droplet is essentially one of size.  As relative humidity (RH) increases, hygroscopic particles
 increase in diameter.  Since the vapor pressure  of water over a droplet1 s surface depends on
 the surface curvature, there is a critical diameter above which the droplet will grow by means
 of additional condensation of vapor.   Particles  or  condensation  nuclei  which  exceed this
 diameter are said to be "activated." Because of the abundance of condensation nuclei, fog may
 be more common in polluted atmospheres, such as  British cities before smoke was controlled.

 Droplet Size Considerations
      Acid  aerosols are  conveniently  classified  according  to the  physical  nature of the
 particles, which in turn relates to the  way they are formed  in the atmosphere.   "Primary"
 sulfates  are emitted  from  combustion  of sulfur-bearing  fuels,   in  various size  ranges.
 "Secondary" aerosols are formed in the atmosphere from gas-phase precursors, involving some
 of the same  chemical reactions that can acidify precipitation.  These particles begin as very
 small condensation nuclei and grow over time, due to both agglomeration with other particles
 and by absorbing water vapor.  The characteristically submicron size of acid aerosols (at RH
 < -85%) reduces their rates of atmospheric deposition, thus increasing atmospheric residence
 times and transport distances.   Particles of this size can also penetrate deep  into the  lung.
 Thus, air concentrations rather than deposition rates are the preferred metric for acid aerosols
 (including fog) and the direct effects of inhalation are the main concern.
      Particles smaller than the critical  size (which depends on the amount of supersaturation
 present)  decay, while those that are larger will grow.  Hygroscopic particles such as sulfates
 lower the vapor pressure and the amount of supersaturation required and thus promote droplet
 growth.  Cloud droplets do not grow substantially by collisions and  coalescence; for diameters
 less than about 36 urn, collisions by falling droplets are infrequent.6  Droplet growth occurs by
 changes  in the entire population, by diffusion of water vapor onto droplet surfaces.  Larger
 drops  lead  to precipitation,  and  increases in droplet  size increases  settling  velocities.
 Gravitational settling is an important pollutant removal mechanism in fog
      After  fog droplets evaporate and  the fog clears, SO4~ particles may be left  behind.
 These  precipitated  particles tend to be  larger  (-0.7 jum)  than aerosol  particles formed by
 condensing gas phase precursors.7  Although data are sparse, there is evidence8-9 that solute
 concentrations tend to increase with droplet size in general but that the smaller particles may
 be more  acidic.

 Chemistry
     Fog water may reflect either the composition of the atmosphere before the fog formed or
 the composition may be modified by chemical reactions that would have otherwise been  much
 slower.  There are two paths  for acidification: absorption of previously-existing particles and
gases, and chemical reactions among these species in the aqueous phase.
     Among the latter, dissolution of SOi followed  by oxidation (Srv to Svi) is probably the
 most important.  Since photochemistry is less important during foggy conditions, models have
been proposed featuring transition metal catalysis as an important oxidation pathway.
     To the  extent that  additional  sulfate is  produced in  the aqueous phase, becoming
 submicron aerosol as the fog evaporates,  fog can add to the longer-term pollution of the
                                          272

-------
atmosphere.  In a sense, fog represents a temporary storage medium for water-soluble air
pollutants,10
                            Particles bv Foy.  Since the common sulfate  articles are quite
hygroscopic,  they are readily scavenged  by the relatively  large (ca. 5-50 urn) fog  water
droplets.  There is also evidence that soot is scavenged by fog. In addition, if gaseous SOi is
absorbed into the droplets,  it may be oxidized  to form HjSQ*  by any of several chemical
reactions involving either oxidants or catalysts within the dropkL These processes constitute
one of the natural "sinks" for SOj.
      The interactioa between aerosol and fog can be  very important-"   Aerosols  provide
condensation  nuclei for fog; after the  fog dissipates,  those  aerosol  particles which have not
been deposited on surfaces remain airborne.  Pandis et al." find that urban fogs may scavenge
around 80% of the aerosol,  with lower values for sulfate and higher values tor nitrate.  The
lower SO*- values result from the typically smaller sulfate aerosol particles
      Absorption of Cases and Hrt*rtiyM|fflW CbflffiitflT  Fo§ chemistry is also affected
by scavenging water-soluble gases.  Nitric acid is completely scavenged as is ammonia at pH
< 5.12   However. NO,  is nearly insoluble."  The solubility of  SOj is pH-depeodeat.
decreasing with pH.  This often limits the acidification process, depending on  the rate at which
the dissolved SOi (Srv) is  oxidized to SCV (Svi).  the oxidation of dissolved SOi  m  fog
droplets is potentially important, since the rates can be much faster than in gas phase.  Lamb et
al.14  considered limitations in  the availability of atmospheric  water, concluding that such
heterogeneous oxidation was not important in  haze, but could be important  in clouds.  Fogs
were intermediate, depending on the LWC.  Tliese observations are consistent with theory.11
      Since  fog droplets can readily scavenge soluble gases, they  can change the locus of
deposition of those species  within the respiratory tract.  These gases include HNOj, Hd,  and
SOj, among others.  As gases, these species may be efficiently scrubbed by the most upper
airways,  but as particles, some of them will penetrate to the lung."-1'  Fractional  penetration
was seen to vary substantially among individuals.  Also, droplet sizes tend to increase  with
time during a fog event, so  that the time of human exposure may be important
      In  the Eastern  United States, reactions involving  dissolved SOj are of  primary interest.
Current chemical models find  that the most important reaction  is that involving hydrogen
peroxide, which is very fast even at tow pH. The reaction is catalyzed by acid, with the  rate
increasing with decreasing  pH (for pH  > 2).   When coupled with the  decrease in  SOj
solubility with decreasing  pH,  the result  is  a rate expression for SOi  that  is essentially
independent of pH."  However, this reaction is effective only as long as HjOi is present,  and
cloud sampling has shown that  SOj and HjOi tend to be mutually exclusive.11  SOi levels in
clouds aloft over  nonurban areas tend to  be  of the order of a  few ppb. as does HjOj in
summer.  For high SOi concentrations and nonphotocheraical situations, this reaction  win be
of less importance, because of insufficient  HjOj.  These situations include most urban fog
events, and the major episodes of the 1960s and earlier should undoubtedly be characterized as
nonphotochemical.  The other aqueous phase reactions of interest for dissolved SOi involve
oxidation by Oj, catalyzed  by transition metals such as Fe* or Mn* or by carbon.  The  rate
for metal catalysis is positively dependent  on  pH, and thus cannot lead to  very  acidic  fogs
(especially when coupled with the rapid decrease in SOj solubility as pH decreases). Current
regional models do not consider carbon or scot catalysis, perhaps because elemental carbon is
not expected to be very abundant in clouds over nonurban areas.
      Hansen et al.1* compared the rates of SOi oxidation in a continuous flow doud chamber
with and without the presence of NHj.  Nad and soot particles served as ooooombon  nude*.
With an excess of »mmnni?_ conversion of SOj was rapid and 80% comniftf-  Without Nrb,
conversion was negligible.   Conversion was also negligible in  the  absence  of condensation.
Comparison of soot and Nad particle nuclei suggested a minor catalytic role (if any) fox soot
                                          273

-------
 Deposition Considerations
      It appears that water cycles between ground and air during a fog event. Fog droplets
 containing impurities (often  acids) deposit by gravity to surfaces, some of which may be
 warmer than the air. Evaporation prevents a continuous build-up on the surface. However, in
 many cases, the liquid water content of the fog decreases over time. If acids are present in the
 fog  droplets, they may attack the ground surfaces and  thus be effectively removed through
 neutralization,  leaving the salts behind as particles.  This  mechanism explains the observed
 general tendency for the aerosol equivalent loadings  (liquid concentration*LWC) to decrease
 over time during a fog  event.  Such  rates of change will also depend  on the presence of
 emissions sources within the area impacted by fog, as well as by transport in or out of the
 area.
      One of the favorable properties of fog from the standpoint of urban air quality is the
 resulting  increase in particle size and hence  rates of pollutant deposition.   Sulfate aerosol
 particles tend to remain airborne for many days since their deposition rates are only around 0.1
 cm/sec, due to  their predominantly submicrpn particle size.  However, when scavenged by 10-
 20 urn fog droplets,  the rates of deposition increase to  1-2  cm/s  (Waldman, 1986),  In
 addition,  large amounts of water are deposited from fogs, and the resultant wetted surfaces
 become much  more efficient sinks  for  gaseous SCh (Lipfert, 1989).20   Thus, a relevant
 question for a stagnating fog event may be whether the rates of pollutant removal exceed the
 rates of pollutant build-up.  This has been considered in some detail for a case study in the San
 Joaquin Valley of California,21 but  was not considered  in the early  analyses of the major
 pollution episodes which predicted high rates of conversion of SCh to H2SO4.2
      These depositional aspects of fog seem to have been  largely overlooked in considering
 fog  effects upon  health,  although  they are central to concerns about ecological impacts and
 were the main topic of Waldman's dissertation.22

 Typical Fog Concentration Data
      The time-course  of concentrations  in  fog  can  be quite variable, depending  on
 circumstances.  Figure 1  presents two contrasting examples. Figure l(a) shows a fog event in
 the San Joaquin Valley (CA);22 LWC, NOr, and NH4+ drop with time, as does dissolved SOi
 (Srv).  However, after about 7 hr SO4~ begins to increase, apparently due to aqueous phase
 oxidation.  This fog was not very acidic  (NH4+ was  the most  abundant ions as is commonly
 the case in this area).  However, Figure Ib shows a highly fog event at Del  Mar23 in SCAB,
 where NCV and H+ are the most abundant ions, and no SO4" oxidation is seen.  In both cases,
 we interpret the drop in equivalent aerosol concentrations over time as evidence of deposition.
     The relative contributions of the major ions are compared for Whiteface Mountain (NY)
 and a group of  California sites in Figure 2.  At the coastal California sites (north of the South
 Coast Air Basin [SCAB]), ammonium is less abundant than the other alkaline species, nitrate
 levels are  low,  and acidity is  moderate (pH=4.05). In the Bakersfield area,  where SOj (gas)
 levels are  the highest in California, SCu" is more important but, since NH4+ is quite abundant,
 average net acidity is also moderate (ph=3.9).  In  SCAB, nitrate is the major factor and
 	_	.	*	._ 1	* _	 !_•!_	 *•	._  ___ _ *«  m    *••••>   .••*      *-      -•*   -•   A. —
ammonium levels are higher than near Bakersfield but not high enough to neutralize the fog.
The average fog pH is 3.1.  Ionic strengths are lower at Whiteface Mountain (part of this
apparent difference may be due to differences in  the reported LWC values from different
fogwater collector designs).   S04~  is about the same  at Whiteface in the summer as in
California, but NQr  is much lower.  In general, fog SO4- levels are about the same as
typically found in aerosol, but NQr levels are much higher.
                                          274

-------
       '00  300 300  «00 SOO  600 700
                                              lOOOr

                                                      90     100
                                                                              .
Figure I.  Example time histories  of aerosol equivalent fog  concentrations,  (a)  Bakenfield
(CA)  Airport, Jan. 2-3,  1985.  Data from Waldman."  (b) Oel Mar, CA, Jan.  1983.  Data
from Jacob et al.23
                                        South COM*         WFC »umm«r
                                                   tAJC/** i^kJo^^^*
                                                   WrC WWMr
Figure 2.  Comparison of average fogwater anions and cations, as equivalent aerosol loadings,
for California sites and Whiteface Mtn., NY.
                                           275

-------
 SYNTHESIS

 Relevance to Urban Areas
      Fog  has been  shown  to have important air pollution consequences,  especially  for
 radiation fogs in urban areas.   These events are  more likely to occur under quiescent air
 conditions, and the higher air pollution loadings found in urban areas can increase the numbers
 of condensation nuclei.  However, the heat retention capacity of urban agglomerations can act
 to decrease the relative humidity24 and thus the frequency of fog formation.  Fogs may thus be
 more common downwind of major urban areas.
      Fogs often form at night  when fewer people are  likely to be exposed.   Although
 penetration of fog into indoor  environments  was reported during the major fog episodes in
 London during the  1950s,1 this is unlikely in the United States, in  part because of typically
 higher indoor air temperatures resulting from our near universal use of central heating

 A Simple Urban Stagnation  Model, Applied to London
      The tendency for fog to oxidize dissolved SOi to SO<~ (which may be acidic, depending
 on the NHs  level)  runs counter  to the trend of increased deposition; a simple model was
 devised to compare rates of formation and removal. A reasonable upper limit for oxidation (in
 winter, with  an abundance of SOa) may be about 3% per  hour.21  Neglecting  advection,  the
 rate of removal  depends on the deposition velocity (Vd) and  the volume  of the urban
 "reservoir" compared to the surface area available for deposition.  For a heavy fog event, it is
 reasonable  to assume that all of this surface area will be wetted  by deposition  of water,
 through gravitational settling, condensation, and impaction  of droplets.  In dense urban areas,
 the total structural surface  area (As) exceeds the ground plane area (A), by as much as a factor
 of three.25  The depositional flux is thus given by the product of As, the concentration (C), and
 Vd.  The mass stored in the atmospheric reservoir  is given by C*A*h where h is the mixing
 height.  Under the stagnant conditions typical of urban fog and ignoring  any mass transfer
 limitations  (the so-called  well-stirred reactor model), the SCh content of  the atmospheric
 reservoir at time t may be obtained from a mass balance:

      C(t) =  C(t-l) + (E/h)dt - C(A./A)(Vd/h)dt - rCdt                                 [1]

 where E is the emission rate per unit area, r is the fractional oxidation rate, and dt is the time
 increment.
      The parameters of the rate of SOa build-up in a stagnant situation are thus seen to be the
 emission rate, the mixing  height,  the effective deposition velocity VdA./A, and the oxidation
 rate.  When the last three  terms of Eq. 1  are balanced, an  equilibrium situation with constant
 air concentration  will be  attained.  However, as  a practical matter,  all  of the controlling
 parameters  are likely to vary diurnally, so that such an equilibrium state may never be reached
 in practice. With E set to zero, the half lives of 862 under specified conditions may readily be
 determined (by numerical integration). Under fog conditions, the half life could be as short as
 1 h; under the lower deposition conditions typical  of haze, it was  several hours.   A similar
approach was taken in tracking the build-up of SO-*" under stagnant conditions:

      C(t) =  C(t-l) + (E/h)dt - C(Vd/h)dt -I- rC(SCb)dt                                P]

In this case, the emission term refers to primary  emissions of SO*' and the conversion rate r
operates on the SOz remaining in the reservoir at time t.  For fog droplet deposition,  we
assume that only the horizontal surfaces are active (gravitational settling). The enhanced sinks
which characterize foggy conditions can act to limit the build-up of pollutants which would
have occurred under the same stagnation  conditions in the absence of fog.   However, SO*'
will continue  to form as long as SCh remains in the air, so that its concentration  does not reach
equilibrium.  Also, insoluble and chemically unreactive pollutants such as CO will continue to
accumulate in a stagnation  situation as long as  emissions continue.
                                          276

-------
      When sulfur-bearing fuels are used, the rate of emission of SOi in winter in a residential
area is controlled mainly by the demand for space heating.  In the U.S.,  for single-family
homes, the demand may be represented by about 160 Btu/mi* per degree day.26  For an average
heated floor space of, say ISO m2, in the mid-Atlantic region, this  figure  corresponds to a
maximum rate of about 50,000 Btu/h and a seasonal consumption of about 1000 gal of fuel oil.
If a fuel producing 4 Ib SQz/l^Btu (coal) were used (as was the case during the severe air
pollution episodes), the maximum SO2 emission  rate would be 0.09  g/hm2.  The average
emission rate in 1952 in London was  only about 0.015 g/hm2; the maximum  may have been
twice that.2 The London figures are lower because central heating was  not in  widespread use
and because single-family homes were less prevalent.

Estimates of SOj and HjSO4 Under Fog and Haze Conditions
      Assuming a stagnant  situation in which the stirred reactor model is appropriate, the
hourly rate of increase of SCh is given by the emissions relative to the content of the reactor
and the  rates of deposition and oxidation,  as shown  above.  The average  winter  SOj
concentration in London was about 200/ig/m3; we assume that under conditions  of good
ventilation, a typical value might have been 100 jig/m3.  Thus the content of the reservoir at
the beginning or an episode would be  given by 0.1  hA.  With a mixing height of 100 m., the
initial SCh content would be 0.01 g/m2, so that cessation of ventilation would act to increase
SOj concentrations quite rapidly.  Under non-foggy (haze)  conditions, with primarily gas-
phase reactions, both oxidation and deposition rates will be substantially lower.  By way of
comparison, an annual average emission rate of about 0.015 g/hm2 would yield an annual
average SCh concentration of about 80 ug/m3 under normal ventilation conditions.27
      These relationships are displayed parametrically in Figures 3 and  4 according to Eqs. 2
and 3, based  on  arbitrary conditions in the  "reactor* which are held fixed  over time and
neglecting mass transport limitations.  In reality, these conditions tend to change diurnally, so
that Figures 3  and 4 should  be used only to display the interactions among variables, not as a
prediction of actual environmental conditions.  Figure 3(a)  plots the evolution  of SCh. and
SO4"  emitted into a stagnant air mass with heavy  fog present.  The oxidation rate  is 3%/h
(independent of pH), the effective "dry" deposition velocity of SCh is  1 cm/s (including the
enhanced surface area); of fog, 2 cm/s  (high LWC and large droplets  are assumed).  Eq. 2
shows that under these somewhat artificial conditions, the equilibrium  concentration reached
(when losses  = emissions) depends  mainly  on the emission rate,  and the mixing  height
controls the time to reach equilibrium, as seen in Figure 3(a).  The evolution of SO4" (which
may or may not be acidic, depending on  the level of ammonia present, depends on (he fraction
of  SOX  emitted as SO4-, the  oxidation rate, and the deposition velocity,  as  well as the
volume/surface ratio  of the reactor.  With low mixing  heights and no primary emissions
(Figure 3b), only  small amounts of SO4- accumulate. However, as seen by comparing S04-
levels in Figures 3(a) and (b), even a small fractional primary emission can mate a substantial
difference in SO4- under stagnant conditions.  SOj concentrations scale roughly with emission
rate
      Under haze conditions, we assume an oxidation rate of 1%/h, a dry deposition velocity
of 0.25 crn/s for SCh and 0.1 cm/s for SO4".  As expected, with the reduced rates of loss, air
concentrations  reach much higher levels  and depend on both the emission rate  and the mixing
height (Figure 4).  Note that the assumed emission rate in Figure 4  is 1/3  of that in Figure
3(a).  Since the deposition of SO4~ is so much slower under haze conditions,  as compared to
fog, concentrations are much higher with low mixing heights (Figure 5). At  more moderate
mixing heights, the two  rates  are comparable and under large mixing  heights (which are
incompatible with the presence of fog), aerosol S04-  concentrations would be expected to be
lower than equivalent  fog  concentrations.   Note that  emissions from space  heating are
incompatible with high levels of photochemistry and thus  the oxidation rate assumed may be
unrealistically  high.  However, this might not be the case  in summer.  Also, Chang and
Novakov28  report  that SCh oxidation products act to "poison" the catalytic activity of soot in
                                         277

-------
 the absence of liquid water surrounding the particles, which would limit the extent of oxidation
 under haze conditions.
                                                too
Figure 3. Simulation of  the evolution  of  SOj  and SC>4'  under  foggy  stagnant urban
conditions.  Oxidation rate  = 3%/h, equivalent SQj dry deposition velocity —  1  cm/s, fog
deposition  velocity = 1 cm/s.   (a) SOi and SO-r with SCh. emissions  of 0.09g/hm2 and
primary S04" emission  = 1% of SO2 emission,   (b) SO4"  with SCh emissions of 0.03g/hm2
and no primary SO4= emissions.

CONCLUSIONS
      Scavenged  pre-fog  aerosols  and certain  gases  are  the main  contaminants  in  fog;
heterogeneous reactions  were found to  usually  play  a minor role.    Even though liquid
concentrations can be quite high  in  fogs,  the equivalent  aerosol  loadings (obtained by
multiplying by LWC) are comparable to aerosol levels.  The most acidic fogs were found in
the South Coast Air Basin of California, where scavenged nitric acid contributes  much of the
acidity.  Equivalent aerosol loadings may decrease over time because of droplet deposition to
the ground.  Although this mechanism appears to constitute a "cleansing" of the  atmosphere,
very few data are available comparing air quality before and after fog  events. Determination
of fogwater liquid  chemistry is a  straightforward  matter,  but there  are  large  uncertainties
associated  with most of the extant  liquid  water content measurements.   One  of the most
pressing  research needs is time-resolved experimental  data  on fog chemistry and LWC by
droplet size,  since deposition within the human  airways and to  surfaces is  size-dependent.
With respect to the major air pollution episodes of the past, SO*" production was  undoubtedly
accelerated during fog, but SOj and particles  were removed from  the atmosphere much more
rapidly by deposition on surfaces. In addition, few of the larger particles characteristic of fog
would have reached the deep lung.  In terms of today's urban air pollution, fogs are relatively
infrequent  in most locations and  tend to occur at night when fewer people are  likely to be
exposed.
                                         278

-------
Figure 4.   Simulation of the evolution of SCfc and SO4"  under hazy stagnant urban
conditions.  Oxidation rate = l%/h, equivalent SOz dry deposition velocity=0.25 on/s, fog
deposition velocity=0.1 cm/s, primary SO4" emission = 1% of SOj emission.
                  1000

                   Iflfr

                   •»

                   *
Figure 5. Comparison of SCV production under fog and haze conditions.  SO* emission
rate = 0.03 g/hm2, other conditions as in Figures 3b and 4.
                                      279

-------
 REFERENCES

 1. F.W. Lipfert, Air Pollution and Community Health. Springer-Verlag, New York (in press).

 2. A.R. Meetham, Atmospheric Pollution. 4th ed., Pergamon Press, London,  1981. p. 185.

 3. U.S. Environmental Protection  Agency, "An Acid Aerosols Issue Paper," EPA7600/8-
 88/005F (1989).

 4. F.W. Lipfert, "An Assessment of Acid Fog," Brookhaven  National Laboratory Report to
 the U.S. Environmental Protection Agency, October 1991.

 5. S.V. Hering, et al., "Field Intercomparison of Five Types of  Fogwater Collectors,"
 Environ.Sci.Tech 21:654-663 (1987).

 6. R.R. Rogers, and M.K.  Yau, A Short Course in Cloud Physics.  Pergamon Press, New
 York 1989. 3rd. ed.

 7. W. John, S.M. Wall, J.L. Ondo, and W. Winklmayr, "Acidic Aerosol Size Distributions
 During SCAQS," report to California Air Resources Board CA/DOH/AIHL/SP-51, California
 Air Resources Board, Sacramento, CA (1989).

 8. K.J.  Noone,  R.J. Charlson, D.S. Covert, J.A.  Ogren,  and  J.  Heintzenberg, "Cloud
 Droplets: Solute Concentration Is Size Dependent," J.Geophys.Res. 93D:9477-9482 (1988).

 9. J.A. Ogren, J. Heintzenberg, A.  Zuber, K.J. Noone, and R.J. Charlson, "Measurements of
 the size-dependence of solute concentrations in cloud droplets,"  Tellus 41B: 24-31 (1989).

 10. J.W. Munger, D.J.  Jacob, J.M. Waldman, and M.R. Hoffmann, "Fogwater Chemistry in
 an Urban Atmosphere," J.Geophys.Res. 88(C9):5109-5121 (1983).

 11. S.N. Pandis, J.H.  Seinfeld,  and C. Pilinis, "Chemical  Composition Differences in Fog
 and Cloud Droplets of Different Sizes" Atm.Environ. 24A: 1957-69 (1990).

 12. D.J. Jacob, J.M. Waldman, J.W. Munger, and M.R. Hoffmann, "A field investigation of
 physical and chemical mechanisms  affecting pollutant concentrations in fog droplets," Tellus
 368:272-285 (1984).

 13. S.E. Schwartz and W, H. White, "Solubility equilibria of the nitrogen oxides and oxyacids
 in dilute aqueous solution," Adv.Environ.Sci.Eng. 4:1-45 (1981).

 14. D.  Lamb, D.F. Miller,  N,F. Robinson, and A.W. Gertler, "The Importance of Liquid
Water Concentration in the Atmospheric Oxidation of SO2," Atm.Environ.  21:2333-2344
 (1987).

 15. B. Laube, S. Bowes, J. Links, K. Thomas, and R. Frank, "The Effect of Acidified 10 ftm
Fog  on Short-Term Mucociliary Clearance in  Normal Subjects," abstract for 1990 World
Conf. on Lung Health, Am.Rev. Resp. Dis. 141:A75 (part 1 of 2) (1990).

 16. S.M. Bowes, III, B.L. Laube, J.M. Links, and R. Frank, "Regional Deposition of Inhaled
Fog Droplets: Preliminary Observations," Environ. Health Perspectives 79:151-157 (1979).
                                        280

-------
17. S.E, Schwartz, "Aqueous Phase Reactions," in NAPAP State of Science and Technology
Report 2,  Atmospheric  Processes Research and Process Model Development, USGPO,
Washington, DC Oct. 1990.

18. P.H. Daum et al., "Measurement and interpretation of concentrations of H2O2 and related
species in the upper midwest." J.Geophys.Res. 95:9857-71 (1990).

19. A.D.A.  Hansen, W.H.  Benner, and T.  Novakov,  "Sulfur Oxidation  in  Laboratory
Clouds," Atm. Environ. 25A:2521-2530 (1991).

20. F.W. Lipfert,  "Dry Deposition Velocity  as an Indicator for SO2 Damage to  Materials,"
J.APCA 39: 446-452 (1989).

21. D.J. Jacob, F.H. Shair, J.M. Waldman,  J.W. Munger. and M.R. Hoffmann, "Transport
and Oxidation of SO2 in a Stagnant Foggy Valley," Atm. Environ. 21:1305-1314 (1987).

22. J.M.  Waldman, "Depositional Aspects of Pollutant Behavior in Fog,"  Ph.D.  Thesis,
California Institute of Technology, Pasadena,  1986 (UMI 8605420).

23. D.J. Jacob, J.M. Waldman, J.W. Munger, and M.R. Hoffmann,  "Chemical Composition
of Fogwater Collected Along the California Coast," Environ.Sci.Tech  19:730-736 (1985).

24. F.W. Lipfert, S. Cohen,  L.R.  Dupuis, and J.  Peters,  "Relative Humidity Predictor
Equations Based on Environmental Factors,"  Brookhaven National Laboratory Report 38957,
July 1986. Urban  Atmosphere (in press).

25. S.I. Sherwood, F.W. Lipfert,  M.L. Daum, E.A.  Smith, S.B. Chase, M.A. Panhorst, et
al. "The Distribution of Materials Potentially at Risk to Acidic Deposition."  NAPAP Report
21. Acidic Deposition:  State of Science  and Technology. National  Acid Precipitation
Assessment Program, 722 Jackson Place NW, Washington, DC 20503 (1990).

26. F.W. Lipfert,  P.O. Moskowitz, J.  Dungan, J. Tichler, and T. Carney, "The Interaction
between Air Pollution Dispersion and Residential Heating Demands," J.APCA 33:208-11
(1983).

27. F.W. Lipfert,  L.R. Dupuis, and J.S. Schaedler,  "Methods for Mesoscale Modeling for
Materials  Damage  Assessment,"  Brookhaven  National  Laboratory  Report  to  U.S.
Environmental Protection Agency, April 1985.  Also  see EPA/600/S8-85/028 (NTIS PB 86-
144862/AS).

28. S.-G. Chang, and T. Novakov, "Role of Carbon Particles in Atmospheric Chemistry," in
Trace Atmospheric Constituents: Properties. Transformations, and Fate. S.E.  Schwartz,  ed.,
Wiley, New York. pp. 191-217 (1983).
                                       281

-------
ACID AEROSOL MEASUREMENT METHODS:
STUDIES OF EXTRACTION AMD ANALYTICAL EFFECTS
T. G. Ellestad
U. S. Environmental Protection Agency
Research Triangle Park, NC  27711

L. L. Hudson
Research Triangle Institute
Research Triangle Park, NC  27709

S. J. Randtke and D. D. Lane
University of Kansas
Lawrence, KS  66045

G. D. Thurston
New York University Medical Center
Tuxedo, NY  10987

J. M. Waldman
R. w. Johnson Medical School
Piscataway, NJ  08854

P. Koutrakis
Harvard School of Public Health
Boston, MA  02115
ABSTRACT
Following a major intercomparison of acid aerosol measurement
methods, an additional study was held to investigate the sources
of variability among labs.  In addition, it was felt important to do
this comparison with atmospheric aerosol.  The first test was of
spiked filters in triplicate at six different levels; each lab had to
extract and analyze its filters.  The second test was of atmospheric
samples collected under carefully controlled sampling conditions; two
or more filters for three sampling periods were extracted and
analyzed by each lab.  The third test was of atmospheric samples that
were all extracted by one lab, with the resulting extract solutions
for each day combined, spiked, and divided among the labs for
analysis.  All labs reported hydrogen, ammonium, and sulfate ion for
each sample.  Results indicate that atmospheric aerosols gave a
precision comparable to spiked samples, that interlaboratory
precision was about 10 percent for H*,  and  that a minimum sample of
about 400 nanomoles of H*  is required  to obtain good interlaboratory
results.
                                 282

-------
INTRODUCTION
     In 1990 EPA sponsored an intercomparison of measurement methods
for acid aerosols1.   It was conducted in  an  outdoor  smog chamber in
which mixtures of nebulized sulfuric acid, photochemical aerosols,
and natural dust were generated.  The chamber was large enough to
contain seven samplers in duplicate including their inlets.  The
primary finding of the study was that acidity (hydrogen ion) was
being measured to a precision of 10 percent within lab, and a total
precision (within and among labs) of 26 percent, averaged over all
levels.  While that level of precision among labs was deemed
acceptable for epidemiological studies (the current main use of the
methods), it was recognized that improved precision might be attained
if we further investigated the sources of variability.  We therefore
undertook a study to examine the possible major contributors to
imprecision, including extraction, analytical performance, and real
versus synthetic sample.  By having one group collect the atmospheric
samples, factors such as flow rate and sampler differences were
eliminated as sources of bias in this study.

EXPERIMENTAL DESIGN
     Three types of samples were prepared for distribution to the
five participating labs:
     (1) Teflon filters were spiked with aliquots of ammonium
         bisulfate solution.  These were prepared at six different
         levels ranging from about 150 to 6,000 nanomoles of H* per
         filter.  Each lab received three spiked filters at each
         level, as well as three blank filters and three filters
         spiked only with the solvent (alcohol and water) used to
         prepare the spiking solution.  Each group extracted and
         analyzed its filters.
     (2) Atmospheric aerosol was collected using 18 identical
         samplers at State College, PA, during the summer of 1991.
         One group supplied and operated the samplers so that
         sampling would introduce no interlab bias due to flow rate,
         sampler design, inlet differences,  operating techniques,
         etc.  Samples were collected over three periods when acid
         aerosol was believed to be at concentrations above back-
         ground.  Our intention was that each group would receive
         triplicate filters from each sampling period, however, due
         to torn filters or flow problems, two periods had only
         duplicates for all groups.  The filters were relabeled
         before distribution to the labs to prevent comparison of
         results before reporting.  Each group extracted and analyzed
         its filters.  Before analyzing the results, we applied
         slight corrections for the measured flow rate of each
         sampler.  Although six sets of filters were collected, only
         five are reported herein because the sixth lab from the
         chamber study was unable to participate this year.
     (3) Atmospheric samples were collected using the same 18
         identical samplers at State College, PA, during the summer
         of 1991 for three additional sampling periods.  For each
         period's samples one lab extracted them, combined them,
         added ammonium bisulfate spiking solution,  and split the
                                  283

-------
         batch into triplicates for each lab.  Each lab then analyzed
         its three solutions for each of the three sampling periods.
         For these samples, interlab bias due to extraction
         differences would be eliminated.
              The spiking of these extracts had not been planned but
         was necessary because of the small amount of acidity on
         these filters.  The atmosphere was unusually clean during
         the eight weeks at State College and did not present the
         operators with the desired number or intensity of acidic
         episodes.  The amount of acidity due to spiking in these
         samples as distributed is estimated to have been 75 percent.
         This level of spiking made the extracts more like spiked
         samples than atmospheric samples; however, there were
         various atmospheric species in the samples that may have
         made the analysis more challenging.
     Harvard was the laboratory that did all spiked filter prepara-
tion, atmospheric sampling at State College, and extraction of the
third-type sample.  Harvard used Teflo™ Teflon filters throughout
the study.  The sampler used was the Harvard 4 L/min sampler, which
consists of a honeycomb denuder to remove ammonia, two series
impactors to remove coarse particles, and a Teflon filter to capture
the fine acidic particles2.   Samples were protected from  ambient
ammonia after collection using individual, sealed containers and by
handling them only in ammonia-free hoods.  Harvard distributed the
atmospheric samples to the participating labs by overnight air
express; the labs kept them refrigerated and performed the analyses
within one or two weeks.  The spiked samples were also distributed
simultaneously, but since it was known that these samples were
stable over at least one month, there was less concern about
coordinating their analysis among the labs.
     All labs were asked to follow the same procedures and use the
same apparatus as for the 1990 intercomparison, or else to document
any changes.  Only RTI reported a change: they had changed the
analytical method for ammonium ion from colorimetry to ion selective
electrode.  Each lab analyzed every sample for hydrogen,  ammonium,
and sulfate ion.  All labs used a pH electrode to determine hydrogen
ion concentrations.

RESULTS AND DISCUSSION
     There is substantial agreement among labs for all species on all
three types of samples.  Results for hydrogen ion are shown in Figure
1.  The lowest level of spiked filters shows a large variation among
labs, whereas the second and others do not.  This implies that with
the current level of performance, one should try to collect at least
400 nanomoles H* in order to  get  good comparability among labs.
Precision among labs did not improve consistently above the 400
nanomole level.
     The ambient filters all show good interlab precision, indeed
somewhat better than the spiked filters.  This implies that analysis
of real atmospheric samples is no less precise than that of spiked
samples.  Thus, spiked filters can be used in conducting quality
assurance on an acid aerosol measurement network.  The amount of
hydrogen ion in the ambient samples ranged from about 400 to about
                                 284

-------
1300 nanomoles, corresponding to an adequate level according to the
spiked filter results.
     The extract solutions have good interlab precision also,
marginally better than the spiked or ambient samples.  This indicates
that there is a small but not major effect of extraction by the
different labs.
     Table 1 presents coefficients of variation (CoV = standard
deviation/mean) for the various species and types of sample, both
intralab and total (intralab and interlab).  The lowest level of
spiked filters was not used in computing these statistics.  In every
case the extract solutions exhibit the lowest CoV, as expected, since
the only source of imprecision here is analytical performance (the
experimental design also factored out Harvard's extraction
variability since extracts from one day's filters were combined).
     The H* interlab precision observed this year  (10%)  is about half
that seen in last year's study (26%).  This improvement is probably
not due to the close control of flow rates this year by having one
group operate the samplers: while hydrogen interlab precision
improved, that of sulfate stayed about the same (8 percent this year
versus 11 percent last year) and that of ammonium worsened  (16
percent this year versus 9 percent last year).  Precision should have
changed by about the same amount for all species and certainly in the
same direction if flow rates were an explanation.  By the same logic,
the fact that last year several types of Teflon filter were used as
opposed to one type this year does not account for the improvement in
H* precision.   Presumably such an effect would be  due to variable
extraction efficiency from the different types of filters, but one
v/ould expect sulfate and ammonium to be affected similarly to
hydrogen since they coexist in the same particles on the filter
before extraction.  The other difference between this year's
procedures and last year's is that last year each group operated its
own samplers.  Again, it is difficult to see how hydrogen  (and not
ammonium and sulfate) would have been sampled more precisely by using
only one type of sampler this year.  Of course it is possible that
undocumented improvements in analytical performance for H* occurred
in some or all of the laboratories.  Whether this year's results
reflect a permanent or a temporary improvement will have to be judged
when more studies are done using similar data comparability tests.

CONCLUSIONS
\.  Ambient samples have a comparable precision to spiked  samples
for all species  (H*,  NH4*, and SO4Z").   This supports the use of
spiked filters for quality assurance of acid aerosol measurement
networks.

2.  The observed total precision for H* is about 10 percent expressed
as a coefficient of variation.  About half of that is due  to within
lab variability.  The remainder is not due to any one predominant
source such as extraction.

3.  Networks involving different groups should design their sampling
Strategy  (flow rate and sampling period) so that at  least  400
nanomoles of H* are collected at the desired minimum detection limit
for the network.
                                  285

-------
DISCLAIMER
     This paper has been reviewed in accordance with the U. S.
Environmental Protection Agency's peer and administrative review
policies and approved for presentation and publication.  Mention of
trade names or commercial products does not constitute endorsement or
recommendation for use.


REFERENCES
1. T.G. Ellestad, H.M. Barnes, et al., "Acid Aerosol Measurement
   Method Intercoroparisons:  An Outdoor Smog Chamber Study," in
   Proceedings of the 1991 EPA/A&WMA International Symposium on
   Measurement of Toxic and Related Air Pollutants. VIP-21, Air &
   Waste Management Association, Pittsburgh, 1991, pages 122-127.

2. P. Koutrakis, J.M. Wolfson, and J.D. Spengler, "An Improved Method
   for Measuring Aerosol Strong Acidity: Results from a Nine-Month
   Study in St. Louis, Missouri and Kingston, Tennessee," Atmospheric
   Environment, 22:157-162 (1988).
     Table 1.  Comparisons of Coefficients of Variation
                 (Level 1 of spiked filters not used)

                                     Mean
                  Species & Type   Intralab   Total

                      H*  Spiked       5%       12%
                      H* Ambient       7        10
                      H* Extract       2         7
    Spiked      3        16
   ;
V '
                     NH4* Ambient       5        16
                     NHA* Extract       2        11
                    SO42-  Spiked       3        10
                    SO42' Ambient       3         8
                    SO-2' Extract       2         6
                                 286

-------
00
-J
                    111
                    S   1.5 -\
                    cc
                    UJ

                    O
                          1 -•
UJ

00
_l
LJ_
O

2   0.5














+


X
*io% o-i- n + a n
x + + o x * i
J3 v* x — -A- 	 £ 	 ^ 	 ^ 	 	 - 	 O 	 *
X V ¥
O ^ g + 	 A
-10% A A ^
A D
B
Low ^ ^ High
n RTl
+ KAN
o NYU
A RWJ
X HAR

j X
A




                                            SPIKED
                                                  AMBIENT
                                                                                          EXTRACTS
                                  Figure 1. Lab means compared to overall means for hydrogen ion.

-------
    Development and Validation of a Model for Predicting Short
  Term Acid Aerosol Concentrations from  the HSPH Continuous
                  Sulfate/Thermal Speciation Monitor
                       George Allen and Petros Koutrakis
                   Harvard University School of Public Health
                             665 Huntington Ave.
                             Boston, MA 02115
ABSTRACT
A model that substantially improves the estimate of total strong aerosol acidity from a
semi-continuous flame photometric/thermal speciation monitor has been developed and
validated based on ambient data collected during the summer of 1990 in Uniontown, PA.
The model constants are calculated separately for day and nighttime samples since there
is substantial diurnal variation in the HVSO4= ratio.  Total H* data from co-located
integrated 12 h samples using the Harvard/EPA annular denuder sampler (HEADS) are
used to calculate the model constants.  As a preliminary check of the methods, 12 h
HEADS data were compared by linear regression with co-located continuous methods
for SO2 and SO4=, with good agreement (r*  =  0.97 for SO2, and 0.98 for SO/).  The
semi-continuous acidity model was validated by comparing 3 h HEADS H+ samples with
3 h averaged values from the corrected semi-continuous data.  Linear regression of
actual against predicted 3 h H+ concentrations showed good agreement, with daytime
(r2 = 0.92, N = 57) being somewhat better than nighttime (r2 = 0.89, N = 38).  Even
though the model's constants and performance are site and season specific, this method
allows shorter term estimates of aerosol acidity exposure than other techniques.
                                    288

-------
Introduction
   Real-time or short term (1 h or less) measurements of sulfate aerosol acidity are of interest both in
atmospheric chemistry modeling and for improved assessments of human exposures to ambient acid
aerosols. Limited data indicate that levels of sulfate aerosol acidity can have a distinct diurnal pattern,
similar to that of ground level ozone in urban areas (Wilson, et al, 1991). This paper describes the
development and field validation of a model to improve the estimate of total strong aerosol acidity using
data from the Harvard School of Public Health (HSPH) Continuous Sulfate/niermal Speciation Monitor
(CSTS) and the Harvard-EPA Annular Denuder System (HEADS) sampler.
   The HSPH CSTS monitor was run for 11 weeks during the summer of 1990 in Uniontown, PA(60 km
south of Pittsburgh) as part of an acid aerosol chemistry and acute human health effects.  The CSTS was co-
located with the HEADS sampler for aerosol strong acidity. The HEADS was used to collect 12 h and 3 h
samples of total paniculate acidity and sulfate. This method is similar to the simpler Harvard Impactor (HI)
/ Denuder acid aerosol sampler (Marple et al, 1987; Koutrakis et al., 1988b). The HEADS and HI methods
for H+ agree well (Keeler, et al, 1991). The Uniontown co-located data set provides the opportunity to
develop a model to determine a better estimate of short term (1 h or less) strong aerosol aadity
concentrations using CSTS data.

Methods
HEADS integrated sampler for aerosol oddity
   The HEADS system for total aerosol acidity  (Koutrakis et al, 1968a)is a 10 L min'1 sampler using a
glass PMjj impactor for large particles followed by two coated annular denuders, sodium carbonate and
citric acidC for acid and basic gases respectively. These are followed by a filter pack of three filters: a Teflon
filter for fine particles followed by two coated glass fiber filters coated with sodium carbonate and citric acid
respectively for ammonium nitrate artifact correction.  The HEADS sampler also measures SO2; 14212 h
HEADS SOj values were compared with a co-located ThermoEnvironmental (Franklin, MA) model 43
continuous SO2 monitor as an additional check of the HEADS method. Regression of HEADS against
continuous SO2 resulted in a slope of ljQ2 (±0.01) and an intercept of 0.4 (±15) ppb (i2  = 057, range = 1
to 38 ppb).  The agreement between HEADS SO2 and a continuous method suggests that HEADS SO2
may be a low cost alternative for integrated SO2 measurements. Limit of detection  (LOD) and precision
estimates for 12 and 3 h HEADS sulfate, SO* and H+ data are listed in table 2.
CSTS monitor
   The CSTS monitor measures sulfate using flame photometry, with thermal specUtion providing
additional information about the nature of the sulfate composition. This method uses concepts developed in
the late 1970's and early 1980's by other research groups (Huntricker, et al, 1978; Tanner, et ah, 1980).
Refinements to this method are described in further detail by Allen et al. (1984). The HSPH CSTS system
is the standard method for Semi-Continuous Acid Sulfur as described in a collection of sampling methods
(Appel, et al, 1989).  Although CSTS strong acidity measurements are accurate if none of the sulfate is
neutralized, only a partial measure of the total strong acidity of typical ambient sulfate aerosol is made.
   In this discussion, all particle S is considered SO4-, and all gas phase S is considered acidic (reasonable
assumptions at most  ambient sampling sites). A modified CSI/Meloy (Austin, TX)  model 285 total sulfur
analyzer is used as a total S detector and calibrated with SO2. Frequent auto-zeros, sulfur biasing, and

(litharge) acid gas denuder is used before the detector to remove all acid sulfur gases, resulting in a total
sulfate detector. NH, is added at the detector inlet (after thermal Speciation) to stabilize response to  JLSO4.
   A • 4* .   . _  * _ ^	J.^.J.1__*»_1   ____  _J»  . •       •*  .     •  if   •   '.   *     .___*•   ..   *^
   Sulfate species are selectively removed in the sample stream before detection by rapidly heating the
sample to two temperatures. The system has four sequential states, each of which lasts between 2 and 3
minutes (an entire cycle takes 10 minutes). The first state is with the sample unheated, to measure total
sulfate.  For the second state, the sample is heated to approximately 120" C; most of the sulfuric acid is
volatilized at this temperature and removed from the sample stream by the litharge acid gas denuder. Other
sulfate species (including ammonium sulfate and bi-sulfate) are stable at this temperature. For the third
state, the sample is heated to 300° C, which volatilizes and removes all sulfates except non-volatile sulfates
(such as sodium sulfate, calcium sulfate, magnesium sulfate, lead sulfate, etc, also referred to as "metal
cation" or "refractor/ sulfates). The final state of a cycle is sulfur free air to provide an accurate baseline for
the preceding measurements. These measurements give three directly measured parameters:  (1) total
sulfate, (2) total sulfate minus sulfate associated with sulfuric acid, and (3) non-volatile sulfates. From these,
concentrations of sulfate as sulfuric acid and partially neutralized sulfates (PN SO4" in HSPH CSTS
terminology, defined as the sum of sulfates as ammonium sulfate and ammonium bi-sulfate) can be derived.
                                              289

-------
The thermal volatilization curves of ammonium sulfate and bi-sulfate are almost identical, and can not be
distinguished by this method CSTS LOD and precision estimates are listed in Table 2.
   As a validation of both methods, sulfate from the CSTS was compared with sulfate from the 12 h
HEADS system for the Uniontown summer study over an 1 1 week period  Linear regression with the CSTS
as the dependent parameter gives a slope of 0.95 (± 0.01) and an intercept of 1.9 (± 13) vs/m3 (r2 = 0.98,
N = 122). A scatter plot of this regression is shown in Figure 1.
   Of the three directly measured CSTS parameters, the only theoretical uncertainty is for the second state,
where the sample is heated to 120° C. The above discussion on thermal spedation assumes an exiemaOy
mixed aerosol (where individual particles are a pure species, but the aerosol is a mixture of particles with
different compositions) with particles other than non-volatile sulfates that have H+/SO/ ratios of only 2:1
(H2SO4), 1:1 (NH,HSO4), or 0:1 ((NH^SO,). Under these conditions, any acidity associated with sulfuric
acid is detected, and any acidity associated with ammonium bi-sulfate is not detected        _
   Under ambient conditions, the error in the underestimate of aerosol strong acidity by the CSTS is not as
readily characterized Assuming a completely internally mixed aerosol this time (where each particle is a
mixture of H* and SO,' ions, and all particles in the aerosol have the same H+/SO4" ratio), aerosols with
H*/SO4" ratios of 1:1 or less are not detected as acidic (eg, ammonium bi-sulfate shows no acidic response).
With ratios between 1:1 and 2:1, only the acidity in excess of the 1:1 ratio is detected At 120° C (the
temperature used to detect acidity), any water in the particle is driven off, causing the ions in solution (SO4",
      and H*) to combine into salt crystals (NH4HSO4 and/or (NUJjSO^. For H+/SO4' ratios greater
than 1, there will be excess H+ and SO,' ions that will form HjSO* which is then volatilized and detected as
acidity. For ratios equal to or less than 1, there will be no excess H* and SO4" ions.
   With the acidity response defined this way, the relative CSTS monitor response for acidity is
characterized as follows, where 0% is no acid response and 100% is an accurate total strong aerosol acidity
reading;                                              2(JT-S0,")
                        % Relative response *
                                                          H'
                                                                 *100
   Table 1 lists H+ ratios and the relative CSTS monitor response to acidity of a completely internally mixed
aerosol, based on an acidic response only for sulfate associated with H* greater than a 1:1 ratio. For
example, take the 125:1 case (a 5:4 H* to SO4" ratio). This is the same as 10 H4 ions and 8 SO/ ions, and
can be represented in an internally mixed aerosol as 5 moles of H,SO4 (10 moles of H* and 5 moles of
SO4") and 3 moles of (NH4)2SO4 (another 3 moles of SO4'). To reduce the H*/SO4" ratio to 1:1, 2 of the 5
moles of H2SO4 would have to be volatilized yielding a relative CSTS monitor acid response of 2/5 or 40%.
   In ambient air, strong add aerosols are not completely internally or externally mixed; there would be a
range of H* to SO4' ratios among the particles. This would cause less error than that listed in Table 1  when
some of the aerosol is externally mixed
   Unless the H+/SO4" ratio is close to two or
the aerosol is mostly externally mixed (conditions
not common in ambient air), the CSTS
underestimates the amount of ambient sulfate
aerosol acidity. Despite this limitation, the
uncorrected CSTS method has been useful as an
indicator of paniculate acidity in acute health
effect studies in exposure chambers or in the field,
or in studies of short term atmospheric sulfate
chemistry, since other real time estimates of
sulfate or aridity have not been available.

Table 1 Method detection limits and estimates of precision
                                                    Table 1. Uncorrected CSTS Acid
                                                    Response with Internally Mixed Aerosol
                                                    H+/SO,- Ratio
Response
                                                       0.00:1
                                                       1.00:1
                                                       1.25:1
                                                       1.33:1
                                                       1.50:1
                                                       1.75:1
                                                       2.00:1
N/A (no acidity)
 0%
 40%
 50%
 67%
 86%
100%
Parameter
12 h HEADS SO4'
12 h HEADS H*
12 h HEADS SO2
3hHEADSSO4'
3 h HEADS H*
In CSTS Total SO4'
1 h CSTS Acid SO4'
1 h Continuous SO2
LOD
12nmole/m3(12ug/m3)
8 nmole/m3 (0.4 ug/m3 HiSO4 equiv.)
.4ppb
48 nmole/m3 (5.0 ug/m3)
32 nmole/mj (1.6 ug/mj HjSO4 equiv.)
10 nmole/m3 (IX) ug/m3)
20 nmole/m3 (2fl ug/m3)
2ppb
Precision
5%
7%
7%
7%
7%
5%
7%
5%
                                              290

-------
Model Development                                              	
   It is possible to estimate the total aerosol strong acidity from the HSPH CSTS monitor if there are
additional data available about the overall H+ to SO4' ratios at the measurement site. In its simplest form,
the model described below considers the CSTS monitor TN SO4" component (sulfates with H*/SO4~ ratios
of less than 1:1) to contribute some acidity as determined by a true measurement of total acidity from the
HEADS sampler, and adds that value to the acidity directly detected by the CSTS monitor. The ability of
this model to predict total aerosol acidity depends on the stability of the H*/SCy ratio during the HEADS
measurement interval and on the day to day or season to season variation.
   For the Uniontown data set, co-located 12 and 3 h HEADS SO4' and total H* data were available at the
same site as the CSTS monitor.  12 h HEADS samples were collected for the entire 11 week period 3 h
HEADS samples were run when sulfate levels were elevated (above 20 ug/m3 total sulfate). The entire 12 h
HEADS data set is used to develop the model constants, and the 3 h HEADS data are used to validate the
model's results. The 3 and 12 h HEADS samples have been compared for H* and SO4", and agree with
each other. The form of the model is:
                           H* = (Acid SO;  +  	-) * K *  Fc
where:
H*       CSTS monitor corrected estimate of total sulfate aerosol acidity as sulfuric acid equivalent, in
          nrnole/m1 (the units used to express aerosol total acidity).
AcidSCV CSTS monitor acidity component, in /*g/m3.
PN SO4"   CSTS monitor partially neutralized component (the sura of SO4' as both ammonium sulfate
          and ammonium bi-sulfate), in /ig/m3.
n         represents the relative amount of H* in the FN SO4 component (an n of 2 is 1/2 neutralized,
          4 is 1/4 neutralized, and a high number such as 20 is almost fully neutralized).
K        is equal to 1J02, the ratio of HjSC^ to SO4' molecular weights (96/96).
Fe        is equal to 20.4, the conversion factor for p% sulfuric acid to nmole H*

   The model factor n was chosen to maximize the correlation between 12 h HEADS H* and modeled 12
h averages of CSTS monitor total acidity data. No overall scaling factor was used, so the slope is not
necessarily dose to 1D. Since HEADS data show that the mean daytime (8A-8P local time) H* to SO4'
ratios are very different from the night-time ratios (day = 1DO, night = 039), model factors are determined
separately for these two time periods. Scatter plots of the day fFigure 2) and night (Figure 3) HEADS H*
vs. CSTS monitor modeled total H* are shown  below. It should be noted that any model factor n is specific
to the site and season, and would need to be determined using either the HEADS or Hl/denuder sampler.
   The daytime model factor for n was 1.88 (^=0.96). This suggests that the sulfate aerosol is typically not
more than half neutralized The high r2 indicates that the H*/SO4" ratio is reasonably constant for daytime
12 h intervals. The value of nin the daytime model is less than the theoretical minimum of 2D. This is due
to the model design maximizing correlation without respect to other parameters, as well as small (< 10%)
differences in overall response to total sulfate between the HEADS and continuous methods that was not
corrected for prior to generating the model parameter. The n of 538 (^=0.94) for nighttime data suggests
that about 2/3 of the sulfate aerosol is typically neutralized  Again, trie high i2 indicates that the H+/SO4'
ratio is reasonably constant for nighttime 12 h average intervals, but not as constant as daytime ratios.
   The good fit of predicted 12 h day or night total acidity to the actual measured HEADS acidity allows
missing 12 h values (from voided HEADS samples) to be estimated with a high degree of confidence.  This
has already proven to be of use for filling in missing 12 h HEADS acidity data to provide more complete
data sets for time-series analysis of health effects data.  However, useful short term H* concentrations can be
calculated only if there is usually little variation in the H*/SO4" ratio when it is less than 1:1 during the 12 h
HEADS sample interval (variations in this ratio are correctly accounted for by the model when the ratio is
more than 1:1).  For the daytime model, the acidity factor (1.88) is less than the most acidic value possible
(2D), so this is a reasonable assumption. For nighttime, much more neutralization (and variation in degree
of neutralization) is expected in a rural environment; the 5.88 factor and lower correlation of modeled vs.
measured aerosol acidity reflect this.
   Using the short term (3h) HEADS samples run during episodic periods in the Uniontown study,
validation of short term CSTS total H* model performance can been done. The day and night model
parameters derived from 12 h HEADS data are used to estimate total H* for the 3 h HEADS sample
times; these model results are compared to the  actual (HEADS) H* for the matching 3 h periods. A total
of 95 valid 3 h sample pairs of HEADS and CSTS monitor data were obtained between 28 June and
                                             291

-------
19 August 1990. Again, the day and nighttime data are kept separate, since combining them degrades the
model performance (for all 3 h samples, both day and night, N = 95 and r2 = 0.83). Scatter plots of actual
vs. predicted are shown in Figures 4 and 5. For daytime 3 h samples only (between SAM - 8PM local time):
        CSTS H* = 0.90 (±j04) * HEADS H+ +  80 (±58) nmole/n/  (N = 57, r2 = 0.92)
For nighttime 3 h samples only (between 8PM - 8AM local time):
        CSTS H+ = 0.73 (±j04) * HEADS H+ -  12 (±40) nmole/m3   (N = 38, r2 = 0.89)
   The average day/night difference in sulfete concentration and composition is shown in the plot of diurnal
variation in the CSTS acidity (Figure 6). Both the corrected and un-oorrected acid data are shown. The
"Un-corrected Arid Sulfate" is the CSTS "sulfate as HjSO4" output without any corrections. Note that the
times on this plot are starting hours in EST. Daytime HEADS samples run from hour 07 through hour 18
EST (this is the standard SAM to 8PM local time HEADS schedule).  The corrected acid sulfete has large
jumps at the transition between day and night periods; this is an artifact of limiting the model to only two
correction factors (day/night), as well as the choice of 8AM/8PM EOT run times. At this semi-rural site, a
10AM/10PM sample schedule would have been the highest 12 h period of acidity.  Additional smoothing
could be done in the model to minimize error at this transition point by using interim n factors for the hour
before, during, and after the day/night breakpoint; these could be determined by interpolation over time.

Conclusions
   The ability to measure  the total strong aerosol acidity concentration for short time intervals with the
CSTS monitor is improved by using 12 h HEADS H+ and SO4' data to estimate the acidity contributed by
sulfote with less than a 1:1 H*/SO4" ratio. The HVdenuder sampler can be used as a simpler alternative to
HEADS for this purpose.  About 90% of the variation of the estimated H+ for 3 h predicted values can be
accounted for by this model, similar to the variability due to precision of 3 h HEADS measurements alone.
Shorter time intervals (to 10 minutes) can be estimated for use with atmospheric chemistry measurements or
to improve exposure assessment. The model could be improved by correcting for overall differences in gain
or onsets between the co-located systems. Model error due to large discontinuities at the transition points
from day to nighttime periods (0700 and 1900 hours EST) could be smoothed to improve estimates during
that part of the day. Measurement periods less than three hours have not yet been validated
   The authors would like to express their appreciation to Andrew Damokosh for his statistical
programming efforts, and to JJVt Wolfson and W.E Wilson for their comments on this manuscript
Funding was provided by the Electric Power Research Institute under contract # RP1630-59, Mary Ann
Allan, Project Manager. Additional funding for data analysis and manuscript preparation was provided by
the United States Environmental Protection Agency under cooperative agreement # CR816740 to the
Harvard University School of Public Health, Robert Burton, Project Manager. Mention of trade names or
commercial products does not constitute endorsement or recommendation for use.

References
Alien, GA, WA Turner, JM Wolfson, JD Spender (1984). "Description of a Continuous Sutfuric Acid/SuKate Monitor*,
m Proceedings National Symposium on Recent Advances in Pollutant Monitoring cf Ambient Air and Statianay Sources,
US. EJ> A, #  EPA^OOAW-019, pp. 140-151.
Appd, BR, RL Tanner, DF Adams, PK Dasgupta, KT Knapp, GL Kok, WR Pierson, KD Reiszner (1989). Method
713: "Semi-Continuous Determination of Atmospheric Paruculate Sulfur, Sulfuric Acid, and Ammonium Suttates."
MahodsofAffSampting(mdAna^3rdedaicn,Wlj^^^te^x. Lewis Publisher, Inc, Chelsea Ml
Huntzicker, JJ, RS Hoffman, CS Ling (1978). "Continuous measurement and spedation of sulfur containing aerosols by
flame photometry." Atmos. Environ. 12:83-88.
KeekrGJ.JD Spender, RACastflb (1991) "Acid aerosol measurements at suburban Connecticut she." Atmos,
Environ. 25A, 681-690
Koutrakfe. P, JM Wolfson, JL Slater, M Brauer, JD Spengler, RK Stevens, CL Stone (1988a). "Evaluation of an annular
denuder/tilter pack system to collect acidic aerosols and gases," Envir. Sd TechnoL 22:1463-1468,
Koutrakis, P, JM WoHson, JD Spengjer (1988b). "An Improved Method for Measuring Aerosol Strong Acidity: Resute
from a Nine Month Study in St. Louis, Missouri and Kingston, Tennessee." Atmos. Environ. 22:157-161
Marple, V, KLRubow, W Turner, JD Spengler (1967). "LowFlow Rate Sharp Cut Impactorsfor Indoor Air Sampling:
Desfen and Calibration." J.AirPoOut. Control Assoc. 37:1303-1307.
Tanner, RL, T D'Ottavio, RW Garber, L Newman (1980). "Determination of ambient aerosol sulfur using a continuous
flame photometric detection system: L Sampling system for aerosol sulfate and suffuric aai" Atmos. Environ. 14:121-127.
Wilson, WE, PE Koutrakis, JD Spengler, GJ Keder (1991)  "Diurnal variations in atmospheric acidity, sulfate, and
ammonia." Presentation # 91*89.9 at the 84th Annual Meeting of the Air and Waste Management Association,
Vancouver, DC, June 1991.
                                              292

-------
      •
      *;
      40  •
      35  •
      51

      20  ^
       •
      10  ^

       D
N  =  I 22
m  = 0.95
b  = 1.9
         0  51015 20 25  30 35  40 45  50
            12 h  HEADS Sulfate  (/jg m~J )

Fipm 1. 12 h HEADS Total Sulfale vs. CSTS Total Sutfate
                                               o  *00 H
                                               •3
                                                •
                                                            1
                                                                     100  200   100  400  500  (DO  700  900
                                                       12 h Day HEADS H    (nmole/m  )

                                            Figure 1. Daytime 12 h  HEADS H' vs. corrected CSTS H*

-------
                                                               I 100

                                                               1000

                                                                000

                                                                BOO






                                                                SCO

                                                                -




                                                                :••

                                                                1 •

           12  h  Night HEADS H    (nmole/m )

Fijurr 3.  Nighttime 12 h HEADS H' vs. corrected CSTS H'
                                                             0   100 200 300 400 500 (CO 700 »00 100 10001100

                                                                3 h Day HEADS H*  (nmole/m3)

                                                    Figure 4.  DaytinK 3 h HEADS H'vs corrected CSTS KXaJH'
   -
   c
  •^   JOB

              N =  38
              m =  0.73
              b =  -12

              r2 =  0.89
  o    io o   1oo   JOG   *oo   aoo   aoo   TOO  aoo
     3 h Night  HEADS H*  (nmole/m3)

.  Nighttime 3 h HEADS H* vs corrected CSTS total H*
                                                                   0  2  4  6   8  10 12 14. 16 18 20 22
                                                                             Hour of day   (EST)

                                                                   Figure 6. CSTS diurnal sulfate and acidity.

-------
    MEASUREMENT  OF ATMOSPHERIC FORMIC AND
      ACETIC ACIDS:  METHODS EVALUATION AND
                  RESULTS FROM  FIELD STUDIES
                              J. E. Lawrence and P. Koutrakis
                              Harvard School of Public Health
                                 665 Huntington Avenue
                                   Boston, MA 02115

ABSTRACT

Formic and acetic acids are important contributors to atmospheric acidity, present in the low and sub ppb
range. This paper presents the results of lab and field studies to evaluate the performance of an annular
denuder system to collect gas phase formic and acetic acid.
      The collection efficiency for formic acid by KOH coated annular denuder has been determined to
be 99.12% with a precision of 1.89%. The collection efficiency for acetic acid by KOH coated annular
denuder has been determined to be 98.52% with a precision of 1.24%.  The capacities of the KOH coated
annular denuder  for formic and acetic acid are greater than 5.08  and 136 mg, respectively.  The extracts
of samples with chloroform added as a biocide have been shown  to be stable for storage periods of four
months at 4 «C in the dark. Interference by formaldehyde with measurement of formic acid and acetic acid
was determined  to be small, 2.5% and 0.68% respectively.  Interference by acetaldehyde with the
measurement of formic and acetic acid was also found to be small, 5.9% maximum for formic acid, and
0.8% maximum for acetic acid.
PA, ranged from not detectable at  1.4 and 84.0 ng/nr. Acetic acid concentrations measured ranged
between not detectable at 0.5 and 31.0 ^g/m1. Formic and acetic acid concentrations were correlated with
light absorbance measurement over the period  of the study, suggesting a common primary source of
incomplete combustion of organic material locally.  Daytime acetic acid levels were observed to be
correlated with sulfate levels over the period of the study, suggesting a common secondary source, probably
the aqueous phase oxidation  of CH,CHO and SO,, by OH radical, to form CH,COOH and. SO, ,
respectively. Night-time acetic acid  concentration was observed to be correlated wiDi ozone during the
period of the study, suggesting that ozonolysis of olefim may be a significant source of acetic acid locally.
                                          295

-------
INTRODUCTION

       Formic and acetic acids are important, ubiquitous gaseous components of the global troposphere.
The data are somewhat limited, but measurements indicate that concentrations of formic and acetic acid
are in the low and sub ppb range in rural areas, with elevated ppb concentrations in urban areas (1-6).
Formic and acetic acids have also been shown to be non-negligible contributors to precipitation acidity (7-
10), and to constitute the majority of free acidity in remote area precipitation (11-13).
       There is uncertainty about the sources for organic acids in the atmosphere; several mechanisms for
organic acids (17).  It has also been suggested that the aqueous phase oxidation ofaldehydes by OH
radicals may contribute to gas phase organic acid concentration by evaporation (23-26). The photochemical
decomposition of isoprene apparently does not yield significant amounts of acetic acid (20), but there is
evidence to suggest that acetic acid may be directly emitted by vegetation (5, 6, 21).
       Other sources of organic acids include direct emission in biomass burning (5), in automobile exhaust
(4, 25), and perhaps other anthropogenic sources as well  as secondary production from anthropogenic
organic precursors.
       This paper  presents the results of an evaluation of the performance of the annular denuder to
collect gas phase formic and  acetic acid, both in the laboratory under controlled test atmospheres, and in
the field under actual ambient conditions.

LABORATORY PERFORMANCE EVALUATION STUDY

       This work involved characterization of the annular denuder's performance parameters for fonnic
and acetic acid. Collection efficiency has been measured as a function of relative humidity, sampling rate,
sampling time, denuder coating, and organic acid concentration. The laboratory evaluation study has been
described in detail in a previous paper (27). The relative humidities tested were 10, 50, ana 80%; the
sampling rates tested were 4, 10, and 15 Lpm. The denuder coatings tested were KOH/glycerol and
NajCO,. The concentrations tested were all > 150 ng/nr. The annular denuders used for both laboratory
and field evaluatipn had the following physical dimensions: overall length, 24.2 cm; inner cylinder length,
21.5 cm; inner cylinder diameter, 2.20 cm; and annulus thickness, 0.1 cm.  Based on the work of Possanzini
et aL (28), the theoretical efficiencies were calculated using the following formulae:
                            E = 1 - C/C,                     (eq. 1)
                    C/C0  = 0.819 «p{-f2.53A.}               (eq. 2)
defining A. as
                    A,  = jjDL^FVd^djJ^dj-di)            (eq. 3)
where  E is the collection efficiency, C and C0  are the concentrations exiting and entering the denuder,
                                ,
respectively. D is the diffusion coefficient of the gas in air (in cmV1), L is the length of the denuder (in
cm), F is the flow rate (in cnrs*1), and dt and d2 are  the inner and  outer diameters of the annulus,
respectively (in cm).
       Samples were analyzed by ion exclusion chromatography; the analysis is descirbed in detail  in a
previous paper (27).

RESULTS OF THE LABORATORY PERFORMANCE EVALUATION

       The collection efficiencies for formic and acetic acid by KOH coated annular denuder have been
determined to be 99.12% (±0.92) and 98.52% (± 1.97), respectively, and are independent of sampling  rate
and relative humidity. The results of these experiments are presented in Table I. The precisions, based
on repeated duplicate (co-located) laboratory sampling, are 1.64% (±1.89)and 1.24% (±2.52) for formic
and acetic acid respectively, and are independent of sampling rate and relative humidity. The capacity or
theTCOH coated annular denuder for formic acid has been determined to be 5.08 mg at 10% RH, 6.55 fflg
at 50% RH, and  6.96  mg at 80% RH.  The capacity  of the KOH denuder for acetic acid has been
determined to be  3.69 mg at high humidity, 2.45 mg at  moderate humidity, and 1.36 mg at low relative
humidity. The observed trend ot increasing capacity with increasing RH occurred because at higher RH.
the glycerol in the denuder coating traps more water. The additional water dissolves more acid, and  also
increases the effective coating thickness, and therefore improves the capacity.             .      .
       The sodium carbonate coated annular denuder was also tested in the laboratory for its efficiency,
precision, and capacity  to collect fonnic and  acetic acid. Table I also includes  the  results of these
measurements.  The collection efficiencies were determined to be 98.83% (± 1.72) and 98.46% f± 1.71).
                                                       sampling rate. The precisions of the N^COj
                                              296

-------
RH. The capacity of the carbonate coated denuder for acetic acid has been determined to be 3,27 mg at
high relative mimidity, 1.97 me at moderate humidity, and 0.59 mg at low humidity.  Factorial ANOVA of
the collection efficiencies and precisions determined  for each coating  and for each acid showed no
significant differences for the nine sampling rate-relative humidity groups.
       Assuming that the denuder walls are a perfect sink for the  formic and acetic acid vapor, the
theoretical collection efficiencies can^be calculated using eq. 1-3 for^an annular denuder ^pfjhe physical

cm* , ___r	_,,	v__
efficiencies for formic and acetic acicT It can easily	
efficiencies are close to but slightly lower than their predicted values.
       Storage of (field) samples, with chloroform added as a biocide, at 4 -C in the dark, resulted in small
but not significant net changes in formate and acetate concentrations after four months. Table n shows
four month storage results.  Changes over a total of four months were not significant, based on a repeated
measures ANOVA, for either formate (p-value 0.265) or for acetate (p-value 0.113).  Due to  the potential
bacterial degradation of the organic acids in solution, there is concern over changes during the first 48
hours of storage as welL  Repeated analysis of laboratory samples at elapsed times of 0, 1, 2, 3, 4, 5, 24,
and 48 hours from the end of exposure showed no change at room temperature (all were within 1% of the
originally measured values, within the analytical uncertainty) in acid concentration over the 48 hour period
       Assessment of the  interference of  ppb concentrations of formaldehyde  and acetaldehyde in
collection of formic and acetic acids has been conducted, The aldehyde concentration was measured using
two DNPH-coated SEP-PAK cartridges in series, used, prepared and extracted as described by Tejada (30).
Aldehydes in the test atmosphere are trapped by reaction with  DNPH  to form hydrazone derivatives.
Analysis of the extracts was performed using a Dionex 4500i HPLC system equipped with a  UV detector
and an Ultrasphere ODS column (250 x 4.6 mm, 0.5 urn sphere).  The eluent used was 55% acetonitnle and
45% milli-Q water at a flowrate of 1.2 mL/min. Results of these tests have shown a small interference in
formate concentrations following exposure of denuders to elevated concentrations of acetaldehyde. The
 Vf^ft       -  •  I   ---'-  --  -- j ^— *._	_--	— -1      - — - -* — j. «A._ «.•«*•  <-wf tlb A Al^lALBf>J A ftnnffftn + rn ••sxr*
* ui me same experiments, tne oias in aceiaie concemrauun IUIIUWUIE wyuauio wa» u.iuyo ^iu.ii^ « w-m
relative humidity, 0.51% (±0.47) at 50% relative humidity, and 0.79% (±0.76) at 10% relative humidity.
The biases observed were independent of sampling rate and denuder coating.  A small bias in formate
concentration was also observed following exposure of denuders to formaldehyde. The average bias in
formate concentration measured following exposure to 120 *g/m3 of formaldehyde (sampling at least 0^
m3) was 2.48% (±4.23), independent of relative humidity, flow rate, and denuder coating (ANOVA yielded
a P-value of 0.078).  For the same experiments, the  bias in acetate concentration was 0.68% (±1.52),
independent of relative humidity, sampling rate, and denuder coating (ANOVA yielded a P-value of 0.403).
As expected, the interference for both formaldehyde and acetaldehyde was small, probably due to a low
collection efficiency for aldehydes.

FIELD STUDY

       There were  two segments of field study.  In the first segment, approximatelx 110 samples were
collected at a sampling rate of 4 liters per minute,  for a duration of 12 nours. Daytime and night-time
samples were collected between June 22,  and August  17, 1990.   The sampling  of organic  acids in
Uniontown, Pennsylvania was undertaken as part  of a  large acid aerosol study, sponsored by the Electric
rower Research Institute. Uniontown PA is a town of approximately 14,000 people, and is located in the
southwestern corner of the state, about 50 miles south-southeast of Pittsburgh.  Within the county, there
are no major industrial air pollution sources; however,  there are large regional sources that may affect the
If V&tfty to Uniontown, These regional sources  include the city of Pittsburgh, the Ohio nver valley, the
WatsfieUf  electric generating station  in Masontown, PA (15  miles west-southwest),  and a heavily
industrialized stretch of the Monongahela river (14-21 miles west to northwest). Open burning of trash,
both commercial and residential, is common in Uniontown and in the surrounding townships. Ambient
organic acid concentrations were measured  on  the  grounds of the Laurel  Highlands High School,
approximately 1.5 miles north of the center of Uniontown (39).                                  .
       In this field study, two KOH/glycerol coated annular denuders were used in series, and only single
samples were taken.  Immediately  following  exposure, the denuders were capped, stored at ambient
temperature, and returned to the field lab for extraction.  Chloroform (20 *L) was added immediately to
wte extracts as a biocide. The extracts were refrigerated and shipped cold to the home lab for analysis.
 rhe extracts were stored at   4 »C in the dark until they were analyzed. Field blanks were taken at the
rate of one denuder in ten. Lab blanks were extracted, chloroform added, and stored at 4 -C tn the dark
until the samples and field blanks were returned for analysis. ~ - ^L "--• -* *u	'" J	*	
                                                      .
was assessed, as previously described, by repeated analysis of samples at approximately two month intervals
for a period of sa months.         •  '  v~                       ™   ~              ,.    w  -
       The purpose of the second segment  of the field study was twofold: first, to assess the ambient
precision of the annular denuders to measure formic and acetic acid by using three co-located samplers:
and second, to investigate the levels of organic acids in urban areas. A total of 84 samples were collected
                                              297

-------
on 26 days between July 1 and September 1, 1991.  Two denuders were used in series, and three sample*
were co-located on the roof of the Harvard School of Public Health in Boston, Massachusetts.  Samples
were collected at a sampling rate of 10 liters per minute, for a duration of at least 6 hours. Samples were
extracted and chtoroform added immediately as a biociqe, as for the first segment of the field study. The
extracts were refrigerated at 4 'C in the dark until analysis (usually less than 48 hours). Again, lab and field
blanks were taken at the rate of one denuder in ten.

RESULTS OF FIELD STUDY

       In Boston, MA, KOH coated denuders were selected for use in the field on the basis of their
adequate performance and their greater capacity than carbonate denuders. Three co-located samples were
collected to assess ambient precision. The RMSE for collection of formic acid is 0.7 *g/m , resulting in a
detection limit for formic acid of 1.4 »g/m3, based on 84 samples collected i	"° J—     	'~"rt"
       in limit for formic acid of 1.4 »g/nr, based on 84 samples collected over 28 days. The concentration
measured (average of the three co-located samples) ranged between 3.4 and 27.9 jig/m , with an overall
        of 10.2 (tg/m3 (±6,1).  The estimated relative precision of the denuder to collect ambient formic
       	- • _ _ f j.i~* »•» m r**T^ .»_•_*__	__	t.	*. *	_ \ *_ fa *if  *TO_ _ r» % *or? £	II	t'	£	*!« n«**/l
average of 10.2 (tg/mj (±6,1). The estimated relative precision of the denuder to collect ambient formic
acid (a ratio of the RMSE to the average concentration^ 6.8 %.  Trje RMSE for collection of acetic acid
is 0.3 /ig/m3, resulting in a d<	'   "  '"	'
28 days.  The concentration
13.3 ttg/m, with an overall a   „       . „     ,    ,
to collect ambient acetic acid is 5.1%. The concentrations of formic and acetic acid measured in Boston
are shown in Figures 1 and 2, respectively, with the three co-located measurements and  their average
concentration. Figure 3 shows the simultaneous formic and acetic acid concentrations (average of the three
co-located samples) over the study period.  The concentrations were  found to be correlated (R = 0.474,
p-value 0.0001), indicating common or similar sources for both acids.
detection	   £                . „,            .                         „
concentration measured was 17.5 »Tg/rn3 ("± 15.&).  The anib'ient acetic acid concentration measured ranged
from not detectable  (ambient detection limits are approximately 0.5 *g/m ) to 31.0 >g/m3.  The overall
average for the acetic acid concentration measured was 9.4 #g/m3 (±6.4). The concentrations of formic and
acetic acid measured in Uniontown over the course of this study are presented in Figures 5 and o,
respectively.  The small, non-significant diurnal fluctuation in formic ana acetic acid concentrations are
consistent with observations in other studies (5, 6, 14, 15, 31. 32).
       Uniontown is a suburban township outside Pittsburgh which is located in a geographical corridor
with a history of elevated sulfate and acid aerosol concentration. Regional sources of ambient organic
material include, as previously discussed, industrial emissions from the heavily industrialized area alone, tne
Monongahela, power plant emissions, and local incineration of trash and other waste materials. These
potential sources may contribute to the concentration either by direct emission of organic  acids or by
emission of organic precursors which may be oxidized to form organic acids.
       Table III compares the simultaneous formic and acetic acid levels during the study period. T«e
formic and acetic acid concentrations were correlated (R = 0.44, p-value 0.0001), which indicates that bow
have similar or related sources.  There  are two types of sources to  consider, primary and secondary.
Regional primary sources expected to be significant include possible industrial emission from the industrwl
area along the Monongahela, automobile exhaust, and (most important)  the incineration of waste materials,
which is permitted for homeowners in the county.
       Elemental carbon (EC) levels were measured in Uniontown by aethalometer as part of the same
extensive air monitoring program (33). The aethalometer measures aerosol black carbon (BC), a surrogate
for the elemental carbon  component of  aerosol, by measuring the optical attenuation by TEC Partl!;*f*
collected on a quartz filter as air is drawn  through the filter (34). BC has known local and regional sources
that affect Uniontown. The effect of local open burning is clearly important (though not definitive due to
small sample size) as evidenced by the temporal relationship of open burning with BC peak concentrations
/-*-»\   A  *	•  _ _i	  _ r T7*™r	^^i^J  »^  I	•	.	.*_*.._* I.- *L.— IT— *£l^iJ _1 —•*_!• _«.. _._—*^«A ftottfltl*
(33).  A regional source of EC" expected  to  be important is the Hatfield electric generating station.
Comparison of formic acid and acetic acid (Table m) with light absorbance measurement shows that there
is significant correlation with light attenuation measurement, for both formic acid (R = 0.38, p-value 0.011
and acetic acid (R = 0.42, p-value 0.03). This suggests a common source of HCOOH, CH,COQH, ana
XI/"^ »  G I-H.MA In AA! A_*..4*d.  Ik* *#•*<«* fw  \e\ n «• m • (\f+n v+ * <>m i i*na f\f Alawwaw + nl nn f*W.n** f'I.'IX +nio • *v*nl td
                 .    .,  -       ..                                      --, _,j-
   .  Since local open burning is a significant source of elemental carbon (33), this implies that tne
incineration of trash may have an effect on the formic and acetic acid concentrations. Formic and acetic
acids may be  directly emitted from incomplete combustion of organic material (4, 5,  21, 30, 31).
       Sulfate levels were also measured continuously using a modified flame photometric detector, as pan
of the same air monitoring program (33). Table HI compares simultaneous daytime formic and acetic acw
(12 hour samples) and daytime sulfate (12 hour averages) levels over the study period.  There Urcprrelation
of both daytime formic and acetic acids and daytime sulfates.   For formic acid, the correlation is not
significant, though for acetic acid the correlation is very strong (R = 0.38, p-value 0.007). The major source
of sulfates is  expected to be the oxidation of SO2 emitted from combustion sources.  The correlation 01
sulfate concentration with acetic acid concentration is supportive of in situ production,  due to highly """*?
pathways for  formation of SO." from SO,, and of acetic acid from the corresponding aldehyd_e (5,14, a,
17, 23, 32). The oxidation of SO, to SO4  by OH radical is the mechanism expected to dominate during
the daytime (17, 23,  35):
                                               298

-------
       SO, + OH —* HOSO,
       HGSO, + H,0 —„ HOSO,-H,0
     .  HOSOj-Hp -*• O, -^ HOj + HjS04
And it is not unreasonable  to expect  this would be the major mechanism for oxidation of HCHO and
CH3CHO to HCOOH and CH,COOH, respectively (17,23-26):
       HCHO +  H,0 —» CHVOH),                                (4)
       CH,(OH)2 +  OH —> CH(OH), + H2O                      (5)
       •CH(OH), + 0, —* HO, + HCOOH                          (6)
rurther, this common pathway has also been described as the dominant mechanism for the oxidation of
SO^ HCHO, and CH3CHO in the gas phase at relative humidities greater than 50% (17).
       Ozone concentrations  were also measured continuously in Uniontown, using  an ultraviolet
Photometer, as part of the air monitoring program (33). Correlation with ozone concentration is apparent
for night-time formic  acid (R = 0.29, p-value 0.043), and night-time acetic acid is very strongly correlated
with night time ozone concentration over the period of the study fR = 0.56, p-value 0.0003). Table VU
compares simultaneous measurements of night-time formic acid (12 hour samples) and night-time ozone
lAtral rl^l	 \  _. i i .	 *!_.» *.'	*.?_ •kMJ «.«•*! m*A.«.A t&tt^te t\tt*f tnd> cturlu r*ori/\H
CONCLUSIONS
 .     The collection efficiencies for formic and acetic acid by KOH coated annular denuder have been
determined to be 99.12% and 98.52% with precisions of 1.89% and 1.24%, respectively, independent of
sampling rate and relative humidity. The capacity of the KOH coated annular denuder for formic and
acetic acid are greater than 5.08 and 1.36 mg, respectively. The extracts of samples with chloroform added
as a biocide have been  shown to be stable for storage periods  of four months at 4 ;C in the dark.
"uerference by formaldehyde with measurement of formic acid and acetic acid was determined to be small.
•i.5% and 0.68% respectively.  Interference by acetaldehyde with the measurement of formic and acetic acid
was also found to be small, ranging from 1.1% to 5,9% with decreasing RH for formic acid, and ranging
irom 0.1% to 0.8% with decreasing RH for acetic acid.                                      3
      Formic acid concentrations observed in Boston, MA, ranged between 3.4 and 27.9 ng/m. ine
              ......          •           1 was 10.2 (tg/m. The RMSEs for  the co-located
                                                     : acid respectively, resulting in detection limits
       	ic acid concentrations measured in Uniontown, PA, ranged between not detectable (at LOD
   1-4) and 84.0 *g/m3.  The overall average for the formic acid concentration measured was 17.3 »g/m .
Acetic acid concentrations measured ranged between not detectable (at LOD of 0.5) and 31.0 dg/m . The
overall average for  the acetic acid concentration measured was  9.4 *g/m3.  Formic  and acetic acid
CQn^rffcnfrvAfrl^^.^_ ____.	 _ _!_.. _ j 	f»L f* _	,.*_l _ I*^L.& _.L._._.UL^.^^B^  _««.^««A*«vn*v*d«*fr f\traf frn^k f
acetic acid locally.

ACKNOWLEDGEMENT

«* i j .P"8 Pn>i«ct *»« supported by the Electric Power Research Institute under contract RP1630-59. We
would hke to acknowledge the project manager Mrs. Mary Ann Allan for her contribution. Also special
"ttnks to Benjamin Rosenthal and Denise Belliveau for their assistance to laboratory analysis. Finally, the
authors would like to thank Robert A. Weker for his contribution to the project.
                                              299

-------
REFERENCES

1.   G. A. Dawson, et al.," Geophysical Research Letters 7: 725-728 (1980).
2.   J. C. Farmer and G. A. Dawson. Journal of Geophysical Res. 87: 8931-8942 (1982)
3.   P. L. Hanst, et al., Atmospheric Environment 16: 969-981 (1982).
4.   K. Kawamura, et al.. Environmental Science and Technology 19: 1082-1086 (1985).
5.   R. W. Talbot, et al., Journal of Geophysical Research 9371638-1652 (1988).
6.   M. O. Andreae, et al.. Journal of Geophysical Research 93:  1616-1624 (1988).
7.   J. N. Galloway, et al., Journal of Geophysical Research 87: 8771-8786 (l982).
8.   J. N. Galloway, et al., Science 194: 722-724 (1976).
9.   W. C. Keene and J. N. Galloway. Atmospheric Environment 11: 2491-2497 (1984).
10. R. B. Norton, et al., Geophysical Research Letters 10: 517-320 (1983).
11. W. C. Keene, et al., Journal of Geophysical Research 88:5122-5130 (1983).
12, W. C. Keene and J. N. Galloway, Tellus 36: 137-13lPJ	
13.  E. G. Chapman, et al., Atmospheric Environment 9: 1717-1725 (1986).
14.  D. Grosjean. Jpurnalj)j[ the_Air Waste Management Asspc. 40: 1522-1531 (1990).

16.
17.  J. G. Calvert and W. R. Stockwell, Environmental Sci. Tech. 17: 428A-443A (1983).
18.  F. Su, et al., Journal of Physical Chemistry 84: 239-246 (1980).
19.  R. A. Duce, et al.. Reviews of Geophysics and Space Physics 21: 921-952 (1983).
20.  D. J. Jacob and S. C. Wofsv. Journal 'of Geophysical Research 93:  1477-1486 (1988).
21.  W. C. Keene and J. N. Galloway. Journal of'Geophvs. Res. 91: 14,466-14,474 (1986).
             1., Journal of Physical Chemistry 83: 3185-3T9T71979V
23.  D. J. Jacob, Journal of Geophysical Research 91: 9807-9826 (1986).
22. F. Su, et al., Journal of:
24. W. L. Chameides. Jo
25. W. L. Chameides an
                       urnal of Geophysical Research 89: 4739-4755 (1984).
                       d D. D. Davis. Journal ofGeophvs. Res. 87: 4863-4877 (1982).
                       d D. D. Davis, Nature 304: 427-429 ii983.
26. W. L. Chameides and D. D. Davis, Nature 304: -,~, -,^ ^-v^,.
27. J. E. Lawrence and P. Koutrakis, Paper # 91-53.2 presented at the 84th annual meeting of the Air and
    Waste Management Assoc., Vancouver, BC, June 24, 1989.
28. M. Possanzini, et al., Atmospheric Environment 17: 2605-2610 (1983).
29. G. A. Lues. Analytical Chemistry 40: 1072-1077 (1968).
30. S. B. Teiada. International Journal of Environ. Analyt. Chem.. 26: 167-185 (1986).
31. H. Puxbaum. et  al.. Atmospheric Environment 22: 2841-2850 (1988).
32. D. Grosiean, Atmospheric'Environment 22: 1637-1648 (1988).
33. Harvard School of Public Health, Dept. Environ. Health, Preliminary paper prepared for Electric
    Power Research  Institute,  May 1991.
34. L. A. Gundel, et al., Science of the Total Environment 36: 197-202 (1984).
35. P. Koutrakis and P. K. Mueller, Paper # 89-71.4 presented at the 82nd annual meeting of the Air and
    Waste Management Assoc., Anaheim, CA, June 25-30, 1989.
36. D. Grosjean, Environmental Science and Technology. 23: 1506-1514 (1989).
                                              300

-------
 Table I Efficiency and Precision of KOH and Na2CO3 Coated Annular Denuder for Collecting
                                  Formic and Acetic Acids
 Denuder
 Coating

 KOH
 KOH
 Na2C03
 Organic
 Acid

 Formic
 Acetic
 Formic
 Acetic
   Predicted
   Efficiency

    99.85
    99.30
    99,85
    99.30
Experiment
Efficiency

 99.9
 98.5
 98.8
 98.5
Experiment
Precision

  1.6
  1.2
  4.8
  5.5
          Table U  The Stability of Field Samples After a Four Month Storage Period
 Sample
"Number
  1
  2
  3
  4
  5
  6
  7
  8
  9
 Original
 Formate
(dg/sample)

 187.8
  27.6
  42.8
  35.6
 106.3
  53.2
  85.1
  52.5
  86.6
 Formate
Four Months
(»g/ sample)

 166.4
  28.6
  43.6
  32.4
 112.7
  68.1
  89.7
  67.8
  91.1
   Original
    Acetate
   (dg/sample)

     46.5
     11.0
     24.0
     21.2
     36.0
     51.8
     38.9
     35.2
     54.6
  Acetate
 Four Months
 (dg/sample)

   42.1
    7.9
   22.4
   19.1
   28.3
   463
   41.1
   36.6
   54.5

-------
            Table ni  Correlations Between Formic Acid and Acetic Acid Concentrations
             and Elemental Carbon, Sulfate, Ozone, Temperature, and Relative Humidity

   Variable                                  Fgrrnic Acid                Acetic Acid

   Formic Acid                R.1               *                        0.44
                               p2                                        0.0001

   Acetic Acid                 R             0.44                         »
                               p              0.0001

   Elemental Carbon           R             0.38                       0.42
                               p              0.01                       0.03

   Sulfate (daytime3)          R             0.17                       0.38
                               p              0.10                       0.007

   Ozone  (nighttime4)         R             0.29                       0.56
                               p              0.043                      0.0003

   Temperature                R             -0.09                       0.09
                               p              0.44                       0.45

   Relative Humidity           R             0.01                       -0.19
                               p              0.93                       0.073


1 R is the Pearson correlation coefficient
2 probability of observing >  | R | under H0:  Rho = 0  (N = 80)
3 Daytime sulfate and daytime formic and acetic acid levels
 Nignttime ozone and nighttime formic and acetic acid levels

-------
40

35

30

25

20

15

10

 5

 0
     Figure 1 Formic Acid Concentration (pg/mS)
         Boston, MA  July - September, 1991
        Three Co-located Samples and Average
a  *
                10     15     20
                Sampling Period Number
                                      25
                                 O
 Site 1 Formic Acid
      *
 Site 2 Formic Acid
      O
 Site 3 Formic Acid
      D
Average Formic Acid
                                             30

-------
Figure 2 Acetic Acid Concentration (ug/m3)
    Boston, MA July - September, 1991
  Three Co-located Samples and Average
    16
    14
  .  10
  o
  c  o
  o  8
  u
  u
  4
         5   10  15  20  25
          Sampling Period Number
  Site 1 Acetic Acid
        *
  Site 2 Acetic Acid
        0
  Site 3 Acetic Acid
        D
 Average Acetic Acid
30
Figure 3 Simultaneous Formic and Acetic Acid
     Concentrations (|jg/m3) Boston, MA
   „ 30
   «
   I 25
   3 15
   •a
    10
   a
   o>
           Average of Three Co-located Samples
        Formic Acid

        Acetic Acid
          - •*-
                10    15    20
                 Sample Number
 25
30
                     304

-------
Figure 4 Formic Acid Concentration (ug/m3)
 Uniontown, PA  June 22 - August 17,  1990
     0|~~                   """Daytime Formic Acid
                               Night Formic Acid
            07-13-90  08-03-90
                Date
Figure 5  Acetic Acid Concentration (ug/m3)
 Uniontown, PA  June 22 - August 17, 1990
                              ODaytlme Acetic Acid
                              • Night Acetic Acid
     0
   06-22-90
07-13-90   08-03-90
    Date
                      305

-------
   METEOROLOGICAL AND SEASONAL VARIABILITY IN
  ACID AEROSOL LEVELS AND IN THE DEGREE OF ACID
                     AEROSOL NEUTRALIZATION
                                  J.R. Brook and K. Hayden
                               Atmospheric Environment Service
                                    Downsview, Ontario
                                        M. Raizenne
                                  Health and Welfare Canada
                                      Ottawa, Ontario
                                       J.D. Spengler
                               Harvard School of Public Health
                                        Boston, MA

ABSTRACT
    There is a need for more information on acid aerosol levels (H+) in North America. Starting in
1988, eight communities per year for a three-year period (24-Communities) were monitored by Harvard
School of Public Health and Health and Welfare Canada. These data are providing information on how
aerosol acidity varies spatially and temporally, but it  is  not  known how  representative  these
measurements are and many regions have not been monitored. Measurements of fine particle H+ and
SO4" from three of the communities have been examined in an attempt to develop a technique for
estimating H+ during periods when only SO/ data are available. The molar ratio of H+ to SO4 was
found  to  vary substantially from one measurement to the next and between sites.  In addition to
availability of NH3, these variations could be due to changes in season, meteorology and SO4 levels. A
relationship between the ratio of H+ to SO/ and SO4" was detected at one of the sites.  Differences in
the ratio  were best explained by season.  There appeared  to be some variation  in H*:S04  with
meteorological situation. However, there were few statistically significant differences. They were most
pronounced between conditions associated with high pressure systems or  stagnant conditions and low
pressure systems.
INTRODUCTION
    High ambient aerosol acidity levels have been observed in eastern North America1-2.  There is
concern that  human exposure  to such levels can produce  acute and  possibly  chronic respiratory
problems2-3.  The  "24-Community Study", which is being conducted by The Harvard School of Public
Health and Health and Welfare Canada, was initiated in  1988 to provide more information on the
relationship between aerosol H+ concentrations and the respiratory health of children.  Lung function
measurements, which were taken in the year in which air pollutant levels were monitored, were selected
as the primary indicator of respiratory health.  However, the children's lung function and the H+ data
collected during the study may not be related if the observed H+ levels were not representative of the
children's  long-term exposure. Consequently, we have been exploring techniques for estimating past IT
levels  from existing particle measurements.  Development of such a technique could  permit  more
widespread estimation of H* levels, which could be useful in explaining previously collected health date
and in planning future H+ monitoring programs.  In this paper, we examine the influence of  S0t
concentration, season and meteorological situation on H* concentration and on the ratio of H* to S04.
                                         306

-------
DESCRIPTION OF THE DATABASE AND METHODS
    Acid Aerosol Measurements.  The details of the 24-Community Study have  been described
elsewhere4. In this study, we have focused on H+ and SO4 measurements collected at three of the first
and second year sites.   The location  of these sites, the sample period  and the number of valid
measurements are  in Table 1.  Twenty-four  hour measurements were taken using the Harvard/EPA
Annual Denuder System (HEADS).  The experimental procedures involved with this  system were
described by Keeler et al.5.
    Meteorological Data. Running three-day periods from 1978 to 1991 were categorized according
to 850 mb wind flow over eastern North America6. Nineteen categories, representing a cross-section of
typical  wind  flow patterns  were identified.   These meteorological  categories  provide  a synoptic
climatology which can be used to help explain variations in atmospheric conditions.  They have been
found to explain variations in wet S04  and NOj deposition7 and ambient SO4" concentrations*.  Each
measurement of SO?" and H* taken during the 24-community study was matched with the associated
meteorological category.

Table 1   Location of, sample duration and number of measurements taken at the  24-Community sites
          selected for this study.  Mean annual  24-hour SO4~, H+ concentrations (n mole m'3) and the

Site
Dunnville, Ont.
Pembroke, Ont.
Uniontown. PA
Lat
42.9
45.8
39.8
Lon
79.5
77,1
79.8
Sample Period
Feb88 - Feb89
Mar88 - Feb89
May89-May90
N
133
135
171
so*
61.6
34.3
75.4
H+
28.9
20.6
47.7
H+:SOj"
0.31
0.63
0.58
               The simplest approach to estimating H+ given a measurement of SO4" would be to use
a mean H+ to SO4" ratio. However, the strength of the relationship between SO4" and H+ in any given
aerosol sample will  depend upon the degree of neutralization by NH3.  This is influenced by the
availability of NH3 between the sources of H2SO4 (i.e. SO2 emissions) and the measurement site, which
in turn, may be influenced by meteorology and time of year. This suggests that estimates of H+ based
upon SO4" could be refined with meteorological and seasonal information.  Therefore, the behavior of
the  molar ratio of H+:SO4~  between  categories and seasons (winter=Dec.-Feb.) was studied.  It was
hypothesized that if statistically  significant differences could be found then information on the
frequency of occurrence of the categories and season could be useful in estimating past H+ levels.

RESULTS
Mean Sulfate and Acid Levels
    The 24-community sites were selected to maximize differences in the air pollutant levels between
locations. Table 1 shows that there were differences in SoJ" and H+ between the 3 sites studied. The
roean 24 hour concentrations were  highest at Uniontown and lowest at Pembroke with the highest levels
closer to the main sources of SO2.
    The ratio of H+ to SO4~ also varied between sites.  On average, the greatest degree of aerosol
neutralization was measured at Dunnville. The least amount of neutralization occurred at Pembroke and
Unionville.  Thus, the aerosols collected at Dunnville were likely to have been more "aged" compared to
the  other sites.  With respect to the large  SO2 sources in the Midwest U.S. one would expect a greater
tendency for neutralization at Pembroke.  This suggests that  there were significant sources of SO2
Between Dunnville and Pembroke  and/or that other more local SO2 emissions had a measurable impact
at Pembroke.   The mean H*  to SO4~ ratios shown in Table 2 could be  used with past SO4
                                            307

-------
 measurements to estimate past H+ levels.  However, if this ratio varies from one time period to the next
 then there would be an unknown amount of uncertainty in the estimates.
     Influence of Meteorological  Category and Season,   The mean H+  concentrations for each
 category  and season are shown in Figure 1.  There was a considerable amount of variation between
 seasons.   At  all three sites, mean  24 hour  H+  concentrations were  greatest in  the  summer.
 Nonparametric statistical tests9 were used to test the differences between seasons. These tests indicated
 that at each site at least one season was significantly different (p<0.01) than the others.  However, the
 differences between individual seasons were not as significant. At Pembroke, only Spring and Summer
 were significantly different.  There was some  evidence that Spring and  Fall  were also different
 (p<0.03).  At Dunnville, all seasons were different at  the 98 percent level  of confidence (p<0.02).
 Differences between spring and summer, spring and fall and winter and summer were highly significant
 (p<0.001).  With the exception of fall and winter, all seasons were significantly different at Uniontown
     The variation between categories shown in Figure 1 suggests that meteorology had an effect on H*
 concentration.  Statistical comparisons indicated that at least one category was significantly (rxO.OOl)
 different than the others at Uniontown and Dunnville.   At Pembroke,  the differences were not as
 significant (p<0.04).  Tests of the differences between categories were hindered by variations in the
 frequency of occurrence of the categories. There were less than 10 observations associated with each of
 categories  1-5 and 12-19.  Categories  6-11  were more common.   Category  to category tests  of the
 differences in H* and H+:SO4~ were therefore limited to the more frequent meteorological situations.
     Figure 1 shows that category 9 was associated with high H+ concentration at all three sites.
 Category 9 is associated with a large stagnant high pressure area over eastern North America.  As would
 be expected, these conditions were conducive to high H+ levels. Categories 7 and 8 are also associated
 with high pressure systems. At Uniontown, they led to high H+ levels, but at Dunnville and Pembroke
 Figure 1 does not indicate that H+ levels were elevated during these situations. These results indicate
 that regional H+ episodes are most likely with category 9.
     Statistical comparisons indicated that at Uniontown. there were significant differences between
 categories 7, 8, 9 and categories 10 and  1 1. These two groups of categories tend to represent the high
 pressure and the low pressure situations, respectively. As might be inferred from Figure  1, there were
 generally no  statistically  significant differences  between  the frequently  occurring categories at
 Dunnville. The only exception was category 9, which was found to be significantly different (p<0.001)
 than categories 10 and 1 1. The same behavior was observed at Pembroke.
 Variation in the Ratio of Aerosol Acidity to Aerosol Sulfate Levels
     The mean H+ to SO/ ratios were listed in Table 1. The distribution of the ratios across all 24 hour
 measurements at Uniontown and Dunnville are shown in Figures 2(a) and 2(b), respectively. At both
 sites there was large amount of variation in the degree of neutralization between measurements.  The
 same behavior was observed at Pembroke.  At Dunnville. the H* to SO4~ ratio was below 0.2 a large
 percentage of  the time indicating  that there was usually a significant degree of neutralization of the
 H2SC>4 by the time  it reached the north Lake Erie shore.   At Uniontown, the ratio was generally
 between 0.2 and 0.6.  At Pembroke, there were neaks at 0.0-0.2 and 0.4-0.6 and  there was a greater
 frequency of measurements  with large H+ to  SO4" ratios.  This suggests that on some days there were
 some relatively nearby sources impacting upon Pembroke.
    The relationship between ln(SO4")and ln(H+) at Uniontown, is shown in Figure 3.  On the log scale
there appears to be a linear relationship.  While they were not as consistent, there were also weak linear
relationships at Dunnville and Pembroke. This behavior translates into an exponential relationship on a
linear scale. At Uniontown  and Dunnville, the exponents were found to be greater than one, suggesting
                                             308

-------
that H+ increases faster than SO4".  At Pembroke, the exponent was less than one, which suggests ^he
opposite relationship.
     The exponential relationships suggest that the H+ to SO4 ratio varied with SO?" concentration.
Plots of H+:SO4" versus SO4"  were examined  for evidence of a relationship.  At Pembroke  and
Dunnville, there was no consistent relationship.  At Uniontown, there did appear to be a relationship.
Figure 4 shows that when SO^" concentrations were large there tended to be a greater percentage of H+.
     Reasons. Table 2 lists the mean H+ to SO4~ ratio by site and season. While there were differences
between seasons, they were generally not consistent between sites.  At Uniontown, the largest ratio was
jn the summer and  ihe  smallest ratios were in the fall and  winter.  In contrast, the largest ratio at
Pembroke was in the fall and the mean ratio was also high in the winter.   However, there was more
uncertainty in these ratios because H* and SO4" were present in lower concentrations.
                                                                     2
             Table  2    The seasonal variation in the molar ratio of H+ to S04
Site
Uniontown
Dunnville
Pembroke
W
0.53
0.25
0.71
Sp
0.60
0.14
0.47
Su
0.78
0.42
0.60
F
0.48
0.42
0.77
     The statistical significance of the differences shown in Table 2 were tested using a nonparametric
method9.  At Dunnville, spring was found to be the most unique season.  However, there were also
statistically significant  differences  between winter  and summer and winter and fall (p<0.02).  At
Uniontown, all seasons except winter and fall were significantly different at,  at least the 95%  level.
Differences were detected between spring  and fall (p<0.01) and spring  and summer (p<0.03) at
Pembroke.
     Meteorological Categories. Seasonal differences were likely a result of variations in the natural
and anthropogenic sources of NH3.  They may have  also been  due to changes in meteorology.  Results
of the Kruskal-Wallis9 test comparing H+:SO4~  between meteorological categories indicated that there
were very few significant differences between categories. The most consistent difference was between
the stagnant category 9 and the low pressure system categories 10 and 11.  At both Uniontown and
Dunnville, these two groups were found to be different.  This behavior was not observed at Pembroke.
Instead, category 6, which is associated with moderate west to southwesterly wind flow, tended to be
the most unique. The mean ratio across all category six events was 0.32, which was the lowest value of
the categories studied. Categories 8 and 9 were also found to be different at Pembroke. Both of these
categories tend to occur in the summer, but category 8 winds tend to be light west to northwest and in
category 9 they are light southwesterly.  The mean H* to SO4" ratios are 0.94 and 0.55 in categories 8
and 9, respectively.  Thus, while Figure  1 shows that there is much less H* during category 8 events, it
is associated with the much smaller degree of ^SO^ neutralization.  While it is possible to interpret
gome of these results, the small number of statistically significant differences versus the number of
pairwise comparisons indicates that the meteorological categories were not very effective at resolving
differences in the H+ to SO4" ratio.

CONCLUSIONS
     The eventual  objective of this research is to  develop  an approach for estimating particle  H+
concentrations from available air  pollution data.   The ideal parameter is SO,  concentration, but
examination of the  data from 3 communities showed that the H+ to SO4" ratio  was variable. It is
important to  understand  the sources of this variation before using  the mean ratio to estimate  H+
concentrations.
                                             309

-------
     In this study, we investigated the influence of SO4" concentration, season and general synoptic
 pattern  on H+ and H+:SO4~.  There were statistically significant differences in H+ concentrations
 between seasons and meteorological categories. Likewise there were some significant differences in the
 ratio of H"*" to SO4  between seasons. However, most of the meteorological categories did not explain
 the variations in their ratio. The actual meteorological differences between the categories may have
 been too general to explain differences in H*:SO4". Additional, site-specific meteorological parameters,
 such as back-trajectories^will be employed in future investigations of the source of the variations in the
 ratio between H+ and SO "

                 100
                     Union lawn
                    .iiillllUI    iLill
                100
                 -,.
                 u
                    Pembroke
........... I
••••••
                                     .........   ...................... m
                             ••••••••••••••••I
                   123456789 1O 11 1213 14 15 16 17 18 19 W S S F
                        Meteorological Category / Season

Figure 1  The meteorological and seasonal variation in H* concentrations (n mole m'3) at Uniontown,
        PA, Dunnville, Ont. and Pembroke, Ont.
                                               3So§l----^

                                                   [H+MS04] Ranges
           [Ht]:(S04] Ranges

Figures 2a-b The distribution in the molar ratio of H*:SO4" at Uniontown, PA and Dunnville, Ont.
                                     310

-------
   '.

   !

   4

5. 3

   2

   i
         >
                      3      4
                       ln(S04>
                                                     " i
                                                      t
                                                     rn
                                                                    • • •
                                                        50   100
ISO  200
 (S04)
                                                                          250  300   MO
   Figure 3  The relationship between
             and InfH"1") at Uniontown, PA.
                                              Figure 4  The   relationship  between   the
                                                        molar ratio of H+  and SO4" and
                                                        SO/ concentration  (n mole m"3)at
                                                        Uniontown, PA.
 ACKNOWLEDGMENTS
     The 24-Community work was funded by the National Institute of Environmental Health Sciences,
 the Electric Power Research Institute and Health and Welfare Canada.

 REFERENCES
 1. Pierson W.R., Brachaczek W.W..  Gorse R.A.Jr., Japar S. M., Norbeck J.M. and G.J.  Keeler,
  "Atmospheric acidity measurements on Allegheny Mountain and the origins of ambient acidity in the
  northeastern United States." Atmos. Envir. 23: 431-459 (1989).
 2. Spengler J.D., Brauer M. and P. Koutrakis, "Acid air and health." Hnvir. Sc.  Tech. 24: 946-956
  (1990)
 3. Lippmann M., "Airborne acidity: estimates of exposure and human health effects." Envir. Health
  EsisissL 63: 63-70 (1985).
 4. Thompson K.M.,  Koutrakis  P.,  Brauer  M.,  Spengler  J.D.,  Wilson W.E.  and  R.M. Burton.
  "Measurements of aerosol acidity: sampling frequency, seasonal variability and spatial variation." in
  Air and Waste Management AssocjjjtiotlAnnual Meeting. 91-89.5. Vancouver. B.C.. 1991.
 5. Keeler G.J., Spengler J.D. and R.A. Castillo, "Acid aerosol measurements at a suburban Connecticut
  site." Atmos. Envir. 25A: 681-690(1991).
 6. Samson P.J., Brook J.R. and S. Sillman, "Aggregation of pollutant deposition episodes into seasonal
  and annual estimates." EPA Cooperative Agreement CR-814854-01.  Prepared for the United States
  Environmental Protection Agency, Meteorology and Assessment  Division, Research Triangle Park,
  NC, 1990.
7. Brook, J.R,, S. Sillman and P.J. Samson, "Categorization of sulfate  and nitrate wet deposition
  episodes based on three-day atmospheric circulation patterns."  in 83rd Air and Waste Management
  Association Annual Meeting. 90-100.2, Pittsburgh, PA, 1990.
8. Samson, P.J. and J.R. Brook, "Evajuation of the RADM aggregation scheme for estimation of annual
  sulfate probability density."  EPRI Cooperative Agreement RP-3189-02. Prepared for the Electric
  Power Research Institute, May 1990.
9. CRr standard probability and  statistics: tables and formulae., ed. W.H. Beyer W.H., CRC  Press,
  Boston, MA., 1990.
                                             311

-------
               ACIDIC GASES AND AEROSOLS IN THE
              EASTERN AND WESTERN UNITED STATES
                                  Eric S. Edgerton
                      Environmental Science & Engineering, Inc.
                                 1000 Park 40 Plaza
                                Durham, NC  27713

                                  Barry E. Martin
                        U. S. Environmental Protection Agency
                Atmospheric Research & Exposure Assessment Laboratory
                          Research Triangle Park, NC  27711
ABSTRACT
       The USEPA National Dry Deposition Network (NDDN) is designed to provide long-
term estimates of acidic gas and aerosol concentrations, and associated fluxes, across  the
continental  United States.  Inspection of data collected since  1988 shows species-dependent
variability in atmospheric concentrations from site to site, season to season and year to year. In
genera], gas and aerosol concentrations were much higher (factor  of 2-10) at eastern sites than
western sites.  Among eastern sites, annual average concentrations of SO42', SO2 and HN03
during 1991 ranged from 1.9 to 7.3 ug/m3, 1.7 to 19.4 ug/m3 and 0.5 to 3.5 ug/mj, respectively,
and all three species were invariably higher across the midwest and northeast than the upper
northeast and southeast. Data for 25 eastern sites operational from 1988 through 1991 suggest
that SO42' concentrations have been essentially constant.  In contrast, S02 and HNO3 appear to
have decreased, on average, by about 20 percent and 15 percent, respectively.  Examination of
sub-regional concentration patterns shows marked variability in areas of complex terrain.  Data
from a ridgetop site and a nearby base elevation site in southwestern North Carolina show that
reactive gas concentrations, but not aerosol concentrations, are 2-3 times higher at ridgetop than
at base elevation. Elevational gradients thus need to be accounted for in analysis of large-scale
concentration patterns.

INTRODUCTION

       Sulfur and nitrogen species have long been known to play an important role in the acid
deposition phenomenon.  Despite this knowledge, little historical information is available to
establish patterns and trends of acidic gases and particles across the U.S.  In 1986, the USEPA
contracted with Environmental  Science and Engineering, Inc. to establish and operate  the
National Dry Deposition Network (NDDN).   Among other things, the objective of NDDN is
to obtain a long-term record of acidic dry deposition and atmospheric concentrations at 50, or
more, regionally representative sites.
       This paper presents atmospheric concentration data for sulfate aerosol (SO*2'), sulfur
                                        312

-------
dioxide (SOj) and nitric acid (HN03) for calendar year 1991.  Also presented is an overview of
concentration data from 1988 through 1991 for a subset of 25 NDDN sites.  Seasonal and spatial
variability of measured species are discussed.  Also discussed are results of a preliminary
investigation of the influence of terrain on atmospheric concentrations.
METHODS

Network Description
       The NDDN was deployed over a two year period from 1987 through 1988.  The current
configuration includes fifty primarily rural monitoring sites, of which 41 are located in  the
east and 9 are located in the west (see Figure  1). In general, sites were selected to be out of the
direct influence of population centers, point  sources of SOj and NO, and other activities that
could influence regional representativeness. Several exceptions to this include site 116 (between
Washington,  DC  and  Baltimore,  MD) site  140  (near Evansville, IN)  and site 146 (near
ChicagoJL). These sites were established to assist model evaluation of pollutant gradients near
sources. In mid-1991, a temporary site was established in southwestern NC to assess elevational
differences in gas and particle concentrations.  This site was located on a
ridge about 1 kilometer northwest,  and 300 meters  above, site 137.

       For discussion purposes, sites in the eastern U.S. have been grouped somewhat  sub-
jectively into six  subregions: northeast (ME), upper northeast (UNE), midwest (MW), upper
midwest (UME), south central (SC) and southern periphery (SP). Site groupings were based on
land-use, and spatial concentration patterns, in addition to geographic location. The groupings
selected represent  a compromise between economy of presentation and observed variability in
concentration fields.  Considerable variability may exist within subregions, and differences
between subregions may vary from species to species. Sites in the midwest and upper midwest
were largely agricultural, while those in the northeast, upper northeast and southern periphery
were mostly forested. The south central subregion included both forested and agricultural sites.

Sampling Approach
       Atmospheric concentrations  of SO42', S02 and HNQ, were determined weekly using three
stage filter packs (Savillex, Inc.) mounted atop a 10-meter tower.  Filter packs contained
teflon, nylon and  base-impregnated cellulose filters in sequence for collection of particles,
HNO3 and SOj, respectively. Air flow through the filter pack was maintained continuously
at 1.5 liters/minute  (for standard  conditions  of 298K  and 760 mm Hg) using mass  flow
controllers and recorded, as hourly averages, on a data  acquisition system.  Mass flow
controllers were calibrated quarterly and generally found to be stable, with respect to an NIST-
traceable standard, within -f/-  5 percent.  Field blanks were collected at each site once a
month.
       Following receipt from  the field, exposed filters and blanks were placed in color-coded
extraction bottles and extracted (with sonication and shaking) in 25 mL of deionizcd water
(teflon), 25 mL of 0.003 N NaOH (nylon) and 50 mL of 0.05 % H2Q, (cellulose). Extracts were
analyzed within 72 hours for SO* and N03",  via ion chromatography. Ambient concentrations
                                          313

-------
 were then calculated based on the volume of air sampled (typically 15 m3) and the mass of SO42
 or NCV recovered from each filter stage. Details of field and laboratory operations have been
 documented elsewhere (1,2).
       The accuracy of filter pack measurements is not known, but a variety of reactions may
 cause positive or negative interferences (3,4).  Several recent comparisons between filter packs
 and other sampling approaches (principally annular denuders) suggest that biases for SO«2' and
 HNO3 are less than 10% and those for SO2 are less than 15% (4,5,6). The overall precision of
 NDDN measurements is roughly 5% for SO4J- and SO2 and 10% for HNO3, based on collocated
 sampling at various sites (7).

 RESULTS AND DISCUSSION

       Annual arithmetic mean concentrations of S(V", SO2 and HNOj for 1991 are listed by
 subregion in Table 1.  Average SO42" values range from less tham 1 .0 ug/m3 for the west to 6.0
 ug/mj for the midwest (MW) and northeast (NE).  Marked  differences are evident between
 adjoining subregions, especially the NE and UNE,  where concentrations differ by more than a
 factor of two. Not unexpectedly, the highest SOf levels are observed in the centrally
 located subregions, while the lowest concentrations are observed around the periphery of the
 network.  Without exception, the lowest concentrations occur at the nine western  sites.
       Results for SQz show a similar pattern, but with a larger range of values, both in the east
and  the west.  Mean concentrations  are less than 4.0 ug/m3 in the UNE, UMW and SP
subregions and above 12.0 ug/m3 in the NE and MW subregions.  Concentrations in the
SC subregion exhibit large (factor of 8) variability that is difficult to explain strictly on the basis
of SO2 emission patterns.  In this case, the lowest concentrations  (i.e., less than 2.0
ug/m3) occur in complex terrain sites in eastern  Kentucky (site 121) and southwestern North
Carolina (site 137), while the highest concentrations occur at neighboring sites in rolling terrain.
In general, SO2 concentrations at western sites are less than 1.0 ug/rrij.  The only exception to
this is site 167 (2. 1 ug/m3), which appears to be influenced by emissions near the U.S. -Mexican
border.

       Mean HNO, concentrations range from less than  1.0 ug/m3 in the west and the UNE to
more than 2.0 ug/m3 in the NE and MW and exhibit significant variability within all
subregions.  As for SO2, pronounced concentration gradients occur in the SC subregion and the
lowest concentrations are observed in complex terrain.  With  only one exception (site 174)
average HNO} concentrations at western sites are 0.5 ug/m3 or less.

       As described earlier, a ridgetop location within 1.0 km of site 137 was equipped with a
filter pack sampler to evaluate elevational differences in gas and aerosol concentrations. Results
of this sampling effort suggest marked differences between the ridgetop and base site for SQj
and HNOj, but only minor differences for S
-------
substantially higher (i.e., 50- 300%), while SO4J- is only slightly higher (i.e., 5-30%).
The absence of a strong elevational gradient  for SQf indicates  that the two locations are
sampling essentially the same air mass.  Strong gradients for the reactive gases suggest that
depletion is occurring at the base elevation site. This could be the result of dry deposition or
various gas-particle reactions.

       The quarter to quarter variation of S042", HNO3 and SOj concentrations is shown in
Figure 3 for sites in the UNE (site 105), SC (site 120) and MW (site 122) subregions.
All three sites exhibit maximum SO42' concentrations during the third quarter (i.e., July-
September) and minimum concentrations during the fourth quarter (i.e.,  October-December).
Temporal variability is greater, both on a relative and absolute basis, for sites 120 and  122 than
for site  105. The convergence of mean concentrations during fourth quarter and the divergence
of concentrations during third quarter indicate that the latter plays a dominant role in the
inter-regional variability of annual concentrations.

       HNO,  concentrations  exhibit no consistent quarter to quarter pattern  between sites.
Quarterly variability at site 122 is similar to that described for SO42', while that at site  105 shows
the exact opposite.   Site  120, on the  other hand, shows no clear pattern of maximum or
minimum concentrations.  Data for SO2 exhibit a fairly reproducible pattern (from site to site
and year to year) of maximum  concentrations in the  first or fourth quarter and minimum
concentrations in the second or third quarter.

       Data for 25 sites operational since the beginning of  1988 provide information on year to
year variability of gas and aerosol species (Table 2).  Results for SO42' show  relatively little
variability in annualized concentrations over the past four years and an overall range in annual
average concentrations of only about 6%.  Concentrations for the most recent year are  virtually
indistinguishable from the first year (1988). Data for SO2, in contrast, show substantially lower
concentrations in 1990 and 1991 than in 1988 and 1989. Annualized concentrations for the 25
sites were  roughly  20% lower in 1991 than  in  1988.   Although the  magnitude of annual
differences varies somewhat, a similar pattern is observed in each of the six eastern subregions.
HNO3 concentrations  show a nearly monotonic decrease  from 1988 through  1991,  with an
overall reduction of about 13%. Western sites, in contrast, showed essentially no difference in
annual concentrations over the period 1989 (the first full year of operation) through 1991.
Although it may be  tempting to infer a permanent reduction in SO2 and HNO, concentrations,
based on data  presented in Table 2, such a conclusion is premature given the brief period of
record.

CONCLUSIONS

      Filter pack samples for SO42', S02 and HNO, were  collected at up to 50 sites for all or
part of the period 1988 through 1991. A preliminary overview of the database shows that peak
concentrations of all  three  species are observed  in  the  mid-section of the eastern U.S.,
intermediate concentrations are observed around the periphery of the eastern U.S. and that the
lowest concentrations are observed in the intermontane west.  Areas of the U.S. that are not
                                          315

-------
currently represented include the Pacific coast and the Great Plains.  Inspection of seasonal
variability shows that SOf and SO2 vary inversely with respect to each other at all sites;
that is, SO42" concentrations peak in the summer and SQ concentrations peak in the fall or
winter.  This seasonal behaviour appears to play a central role in spatial variability across the
eastern U.S.   Comparison of annualized data from  1988 through  1991 at a  subset of sites
indicates that S02 and HNO3 have decreased in a non-randon fashion since 1988.  Additional
analyses are needed to determine whether this is the result of manmade activities (e.g. emission
reductions) or simply a manifestation of non-random  natural variability.  Comparison of data
from two sites within 1 km (horizontal) but separated by 300m in the vertical shows that strong
(i.e., factor of 2-3) elevational gradients occur for reactive gases.  The exact mechanism of
depletion is not known, but it it clear that terrain-induced variability can distort regional
concentration patterns.

REFERENCES
1.  Environmental Science and Engineering,  Inc. (1990).  National Dry  Deposition  Network
(NDDN) Field Operations Manual.   Prepared for U.S.  Environmental Protection Agency.
Contract No.  68-02-4451. Gainesville, FL.
2.  Environmental Science and Engineering,  Inc. (1990).  National Dry  Deposition  Network
(NDDN) Laboratory Operations Manual.  Prepared for U.S. Environmental Protection Agency.
Contract No.  68-02-4451. Gainesville, FL.
3.  Appel, B. R.( Tokiwa, Y. and  Haik, M. (1981).  Sampling of nitrates in ambient  air.
Atmos. Environ.,  15, 283-289.
4. Sickles, J. E.  II, Hodson, L. L., McClenny,  W. A., Paur, R. J., Ellestad, T. G., Mulik,
J. D., Anlauf, K.  G., Wiebe, H. A., Mackay, G. I.,  Schiff, H. I. and Bubacz, D. K. (1990).
Field comparison  of methods for the measurement of gaseous and paniculate  contributors to
acidic dry deposition.  Atmos. Environ., 24(A)(1), 155-164.
5. Dasch, J. M., Cadle, S. H., Kennedy, K. G.  and Mulawa, P. A. (1989).   Comparison of
annular denuders and filter packs for atmospheric sampling.  Atmos. Environ., 23(12),2775-
2782.
6. Anlauf, K. G., Fellin, P., Wiebe, H. A., Schiff, H. I., Mackay, G. I., Braman, R. S.  and
Gilbert,  R.  (1985). A comparison of three methods for measurement of atmospheric nitric acid
and aerosol nitrate and ammonium.  Atmos. Environ., 19(2), 325-333.
7. Edgerton,  E. S. and Lavery, T. F, (1991). National Dry Deposition Network Fourth Annual
Progress Report (1990). Prepared for U.S. Environmental Protection Agency.  Contract No.
68-02-4451.  Environmental Science  and Engineering, Inc., Gainesville,  FL.

ACKNOWLEDGEMENTS

The information in this document has  been wholly  funded by the U.S. Environmental Protection
Agency  under  contract No. 68-02-4451 to  Environmental  Science and Engineering, Inc.
Although it has been subjected to agency review and approved for publication, it  does  not
necessarily  represent agency policy.
                                         316

-------
-
                                                                                                             UPPER
                                                                                                           NORTHEAST
                                                                                                              NORTHEAST
                                                                                       SOUTHERN
                                                                                       PERIPHERY
                                                                                                           SOUTH
                                                                                                          CENTRAL
                                                     Figure 1.  NDDN monitoring sites

-------
                  12

                  10

                   -
               •-=  4
                    •
 Sulfur Dioxide
* **(i 1 I
* (M«I* N0>' t'l
                                     1991
                     Roiio (Rldgelop SHe/Rouline SHe)
                                    1991
Figure  2.   Ridge  versus  base elevation concentrations in south-
            western North Carolina  (site 137).
                                 318

-------
               !-
              12

            f:
            .1  E
               .
Sulfcl*
                         1567-1950
                     / / / / / / / /
                         19E7-1950
                                  /-I    p
                         I987-19SO
                                                      COO Sill 105
                                                          Sii«120
                                                          SHt 122
Figure 3.  Seasonal variability of SO43', SO2 and HNO, concentrations,
                                     319

-------
Table  1.  Annual average  concentrations  (ug/m3)  for 1991.
so,2-
Subreaion
upper NE
NE
upper MW
MW
SP
SC
west
Mean
2.6
6.2
3.5
6.0
4.0
5.7
0.7
Range
1.9-3.1
4.8-7.3
2.7-4.1
4.7-7.0
3.8-4.4
4.3-6.6
0.6-1.4
SO,
Mean
2.4
13.2
3.9
12.3
2.4
6.1
0.6
Ranae
1.7-3.6
9.9-19.4
2.0-5.9
7.1-18.8
1.8-3.3
1.5-11.0
0.3-2.1
HNO,
Mean
0.9
2.5
1.2
2.4
1.2
1.8
0.5
Ranae
0.5-1,4
1.5-3.5
0.8-1.5
1.9-3.0
0.9-1.4
0.8-2.7
0.3-0.9
NE = northeast;MW = midwest;SP
SC = south-central
southern periphery;
Table 2.  Annual average concentrations across the eastern
          U.S.  (25 sites), 1988-1991.
so,2-
Year
1988
1989
1990
1991
Mean
6.1
6.3
6.0
5.9
S.D.
0.7
1.1
0.9
1.0
so.,
Mean
12.7
12.6
11.1
10.2
HNO,
S.D.
5.3
6.9
5.8
5.0
Mean
2.5
2.3
2.2
2.1
S.DL
0.8
0.8
0.7
0.7
S.D. = standard deviation
                                320

-------
 SULFATE AIR POLLUTION AS AN INDEX OF ATMOSPHERIC ACIDITY
Frederick W. Lipfert                        Ronald E, Wyzga
Environmental Consultant                   Electric Power Research Institute
Northport, NY 11768                        Palo Alto, CA 94303
INTRODUCTION AND BACKGROUND
      A variety of air pollutants can be classified as acidic, including gases, aerosols and
fog droplets.  "Acid  aerosols" have been  proposed for consideration as a  criteria air
pollutant.1   Since research is  still under way to define the detailed nature of the health
risks associated  with  acidic air pollutants, a precise definition of the pollutant is still
emerging.2-3 Designation as a criteria pollutant would require specification of a reference
measurement  method (which  is defacto definition of the pollutant).  EPA must theft
determine whether the ambient air complies with the corresponding national ambient air
quality standards (NAAQSs), which are to be promulgated to protect public health against
the risks encountered  by breathing the pollutant.  It is axiomatic that this suite of processes
must be consistent, i.e., that the ambient measurements should accurately reflect exposure
to the health risks that the standard is intended to forestall.1
      Monitoring all  the acidic air pollutants likely to be present in a given situation would
require  a wide variety of measurements, in terms of both species and phases.  The most
convenient species for regulatory monitoring may  not be the most appropriate from the
standpoint  of health risks and  vice versa.  Use of an "index" pollutant or surrogate species
thus entails a  different type of risk, the risk that the monitoring-health effect connection
may be  broken  because the  index pollutant  does not adequately match  the   target
pollutant.   If the index pollutant is inappropriate, excessive public health risks may go
unrecognized or alternatively, emissions controls could  be applied unnecessarily.  c"te[ia
for the acceptability of an index pollutant, in terms of its representation of the actual health
risks associated with  the target pollutant, include accuracy and precision. In this sense,
"accuracy" refers to the degree to which the effects of the index pollutant mimic the effects
of acid aerosols.  "Precision"  refers  to  the  degree to which the spatial and temporal
variability of acid aerosols are represented by the index pollutant.

Previous Uses of Index Pollutants
      Ozone was originally an index pollutant for all oxidants, but since most of the health
risks have  been  defined on the basis of experimental ozone exposures,  its  use is self-
consistent.   Suspended  paniculate matter  offers  a different  example.   Much of the
underlying health risk information was obtained on the basis of fine  particles or smoke
measurements, whereas the initial  ambient  standards were based on  total particulate
matter  (TSP).  In dusty locations, violations of the ambient TSP  standard may _ not
correspond to elevated public health  risks.  The present use of a particle size-classified
standard has attempted to rectify this situation.
      The 1969 EPA Criteria Document for sulfur oxides4 implied that SOa was originally
selected to serve as an index of all sulfur oxide species.  The hydrogen peroxide monitoring
method for SOi, which was widely used before the development of modern real-time
instruments, is also sensitive to other acid or basic gases and thus represented a kind of an
index of net (gaseous) acidity. The lead peroxide monitoring method ("sulfation rate") used
deposition as  a surrogate for  air concentration but was shown to provide inadequate
precision.  Although  it was not specifically so stated in the 1969 document, the implication
                                         321

-------
 at that time seems to have been that controlling SO2 to meet the appropriate ambient
 standards would also control acidic sulfates and thus would address the potential risks from
 all  SOX  species.  Recent  experience  reveals the  fallacy in this assumption, since  the
 relationship between ambient H+ and SO2 varies by season and location, as discussed
 below.

 Definition of Acid Aerosols
       Acid aerosols are usually defined as acidic particles suspended in a gaseous medium
 which may or may not contain acid gases; fog droplet acidity can derive from both acid par-
 ticles and acid gases. At present, attention has focused on the (strong) acid particles rather
 than on the acid gases. An EPA workshop on measurements derived a working definition
 of acid aerosols based on the  determination  of strong acids  collected by filtration;5 that
 definition is now in common use by the  research community.
       The most commonly found acidic particles in ambient air are acid sulfates,  which
 usually occur as submicron particle mixtures of  HiSC^ and ammonium  salts (NHjHSO^
 [NH4]3H[SO4]2, [NH4]2SO4). If the concentrations of H2SO4, H+, and SO4- are determined
 separately, the sulfate mixture is defined;  there is  no measurement method specific to
 NtttHSO-).  Parameters of these mixtures include the ratios H2SO4/H + , H2SO4/SO4", and
 H+/SO4*. If H  is determined by titration, the end point must  be specified to define the
 degree to which weak acids may be included. Candidate index pollutants for acid aerosol
 particles might include H2SO4, H+, or SO4= or the pH  of  the filter extract; this  paper
 emphasizes SO*", since it tends to have the most extensive measurement data base.

 Content of the Paper
       We begin with a capsule summary of some of the important biological responses
 that have been associated with acidic aerosols, in 'order to  consider  monitoring data
 requirements that might  ensue from a future health-related  ambient standard. We then
 present data on the spatial and temporal variability of acid aerosols and of sulfate aerosols,
 which are examined in the context of using sulfate to infer acidity levels. An earlier version
 of  this paper6  was  presented at the 1990 Annual Meeting of  AWMA;  this paper
 supplements and updates that information.

 SUSPECTED HEALTH EFFECTS OF ACID AEROSOLS
       Before a meaningful index  pollutant may be considered, the "target" pollutant must
 be shown to be consistent with the health effects data base. Next,  it must be shown that  the
 candidate index pollutant is also consistent  with the health effects  that the air quality
 standard is intended to forestall.  The  primary health effect issues in this context are  the
 differential effects of various acidic pollutants and the effects of particle size, which can
 influence the design of aerosol samplers.

 Experimental Studies
       The evidence for health concerns about acid aerosols has been derived largely from
 animal toxicology and human clinical exposures. This data base  has been described7-8 and
 summarized elsewhere.2-3-9  Most  of the experimental studies have used relatively short-
 term exposures to H2SO4, at concentrations which are generally higher than the equivalent
 H+  levels that have been measured in the  ambient environment,  to examine  health and
 biological responses such as changes in lung  function or  clearance.  These  experimental
 protocols were intended to identity the nature of health hazards/risks of concern; hence
 high concentrations of the strongest agent were employed.  For  example,  29 of the 43
 human exposure studies listed in Reference 3 used H2SO4 as the only sulfate species; only
 four included NH4HSO4.  Some of these studies have artificially reduced the natural human
breath ammonia defenses in order to heighten responses;10-12 this finding provides evidence
 that the active agent is the hydrogen ion.  In vitro cell response has also been associated
with the level of H+ exposure.13  There is some support for the  hypothesis that biological
                                        322

-------
 response is also tied to the quantity of acid (moles of H+)  to which the laboratory subjects
 were exposed.  However, recent studies11-15 have shown that quantitative responses in vivo
 cannot be predicted solely on the basis of the estimated hydrogen ion dose.
       The quantitative relationships between ambient dose and health responses remain
 unclear, at least in part because laboratory exposure times have  generally been much
 shorter than  the duration of typical ambient excursions in acidity.16  Until such time that
 the appropriate averaging time and dose measures have been established for the specific
 healtn end points of concern, an index pollutant must reflect the detailed time-history of
 the target pollutant (H+) for times ranging from hours to annual averages.
       The size of acid  aerosol  particles is  also  an important determinant  of health
 response. The deposition pattern of an aerosol in the respiratory tree is clearly dependent
 upon  particle  size; this,  in  turn,  influences the  nature  of any  biological  response.
 Experimental results demonstrate quite different responses for different-sized particles. At
 extremely high  concentrations (20-100 mg/m3),  the lethality  of H2SO4  to  guinea pigs
 increases  with particle size, in the range 0.4-2.7  urn.7   Conversely, the lung function
 response of  guinea pigs  increases as  particle size  decreases, in the range  0.05-1 um.7
 Amdur found that 2.5 um particles elicited slightly higher (and different) responses than
 did 0.8 um particles, but that 7 um particles had essentially no effect.17 More recent work
 has shown greater symptomatic responses to larger particles for some subjects.18 This poses
 a dilemma for  aerosol  monitoring, since the routine methods use aerodynamic inlets
 designed to capture a specific particle size range and inadvertent neutralization can occur
 when larger  particles (which are  often alkaline)  contact  the smaller acid particles on a
 filter.
       There is very little information on biological responses to acid gases at ambient con-
 centration  levels,  either  with  or without coincident acid  particle exposures.   Recent
 experiments with HNCb at 200 ug/m3 on healthy adults19 showed no  changes in respiratory
 mechanics but increases were seen in phagocytic activity of alveolar macrophages.

 Epidemiologica! Studies
       Epidemiplogical studies are necessary  to characterize health risks under  realistic
 ambient conditions.  Most of them have not  been successful in identifying  the  harmful
 agents with certainty. During the  periods of severe air pollution of decades ago, ambient
 monitoring was insufficient, especially in terms of the numbers of species measured.  In
 today's cleaner environment, the biological responses tend to be more subtle but the mix of
 pollutants that can be measured is  more complex, although  measurements are often limited
 to only a few sites; these factors combine to make the task of identifying the responsible
 agents more difficult.
       Although the presence of sulfuric  acid was suspected in  three of the worst historic
 air pollution episodes (the Meuse,  Donora, London [1952]), no acidity measurements were
 made then and most of it would likely have been in the form of fog droplets.20 In addition,
 many other species were likely present at high concentrations during these and other severe
 episodes, including CO and fine smoke particles, which makes the assignment of health
 effects to only one species problematic/1  The most recent epidemiological finding on
 London mortality22 indicated that the association  between mortality and acidity was no
stronger than it was for SC>2 or smoke.
       Many  previous epidemiological studies were limited by the lack  of concurrent
acidity  measurements.2*24    Among   those  studies  which  have  had  appropriate
measurements, aerosol  acidity  has not been unequivocally identified  as the  agent
responsible for observed health  effects, although  fine particles, sulfates,  and ozone have
been  implicated, in some cases, along with acidity.7-25-29   For example, Schwartz et al.28
found significant associations over time among the Harvard Six Cities between childhood
lower respiratory disease and PMio, ozone, fine particle mass, fine particle SCV, visibility
(nephelometrv), and SO? (listed in approximate decreasing order of the magnitude of the
effect), but with neither H+ nor HfoSCX In a preliminary report,29 Schwartz also noted that
                                        323

-------
aerosol acidity was not a significant predictor of daily mortality in St. Louis, where PMio
was shown to have a relationship with daily mortality similar to that found in several other
cities.

Summary of Health Considerations
       In  summary, experimental research on health  effects  has identified some of the
biological  responses  associated  with  breathing  specified  acidic  pollutants.   Major
uncertainties remain as to the effects of dose, species, delivery phase (gas, liquid, solid),
exposure time, and particle size.  In general, epidemiological studies have not been able to
separate the  various constituents or "summer haze."  As a result, even  though working
definitions of acid aerosols have been derived, the variability in biological responses is sucn
that even the target pollutant requires further specification.  Nevertheless, since sulfates
are usually identified with acidic aerosols, the potential use of the sulfate ion as an index of
acidity is considered next.

SPATIAL AND TEMPORAL VARIABILITY OF ACID AEROSOLS
       A national ambient air quality standard specifies concentration levels averaged over
specified periods and the number of allowable exceedances per year at a given location.
The  need for precise temporal  tracking  by  an index  pollutant thus  depends on the
averaging time of the standard, which has  not been  specified for acid aerosols.  However,
for all averaging times, the index pollutant must bear the same relationship to the target
pollutant (and the health risk) for all locations, since national standards are to be applied
uniformly throughout the country. The data sets examined below include locations with
high acidity (SW  Pennsylvania)  and  high population  density (New York City), among
others including some more recent measurements.

Temporal Variability
       Peak levels of aerosol acidity tend to be higher in the summer;7'50 results from three
summer sampling campaigns are given in Figures 1-3.  Even though temporal correlations
between the two are often quite high (R > 0.9), SCV is not a reliable predictor of H+ for
individual events (which might correspond  to violations of some future NAAQS), especially
at peak SCV levels. For example, in New York City31 (Figure 1), titrated H+ values from
           o
           
            IN
           X
           M
           O
           K)
            c
            o
            o
            o
            
-------
                 15      20
            sample start dote (Aug. 1983)
    15       20
sompte start dote (Aug. 1983)
 Figure 2.  Aerosol data from Southeastern Pennsylvania, August 198332 (a) time histories
 of SO41  and H + . (b) time histories of SO? and ozone. Data points are plotted midway
 between sample start and stop times.


 about 2-7 ug/m3 {as H2SO4) were seen at SOr values above 30 ug/m3, but higher H*
 values occurred at lower SQr values. There were also some apparent outlier values where
 H+ exceeded  SO4 = (this could be the result of weak acids). At Allegheny  Mountain and
 Laurel Hill, PA33 (Figure 2a), the molar ratio  of H + /SCV varied from  about 0.5 to 1.5 in
 the SC>4 = range from 18-29 ug/m3.  Part of the reason for this variability relates to  the
 tendency for neutralization to proceed as an air mass ages.  The events of Aug 17-19, 1983
 at Allegheny Mountain,  PA (Figure 2) are  instructive in this regard.  The entire period is
 characterized  by elevated  SCV levels (about 800 neq/m3  or 40 ug/rn3), but the  H+
 concentrations drop  steadily  during  this  interval, apparently  because  of  progressive
 neutralization. It can also be seen from Figure 2a that the HVSO-r  ratio differs between
 the events of  Aug. 17-19 and Aug. 27-29.  Figure 2b presents the  coincident  behavior of
 Sp2 and ozone at Allegheny Mountain;  although the highest sulfate and H+  values tend to
 coincide with simultaneous peaks in SO? and ozone,  these signals are not as well correlated
 as H+ vs. SC>4=. We have no data at these locations for other seasons.
       Data from Uniontown, PA,33 which is in the  same high-acidity region as Allegheny
 Mountain, showed larger day-night differences for H+ than for SC>4=, which could be an
 important  consideration for  personal exposures,  especially considering the emphasis of
 much of the health effects research on exposures of a few hours.
       Temporal comparisons including hourly measurements of H2&O4 were presented by
 Spengler et al.34 and  by Morandi et al.35 The 12-hr average H+ values in these two data
 sets were in the range 0-27 ug/m3 as H2SO4. These data allow the split between H2SO4 and
 NH4HSO4 to be inferred by difference, as mentioned above. The hourly HiSC^ data were
 highly variable; in Spengler et al.'s  data from Southern Ontario,  zeroes were recorded
 during each of the  12-hr H+ averages. The trend of average H2SO4 as  a function of H+  was
 similar in both of these brief data sets, but  the ratio H2SCyH+ ranged from 0.18 to 0.72,
       .  •f  ^ ug/m3.  Thus, it  does  not appear possible to predict  the  detailed sulfate
 composition with confidence on the basis of H+ alone. In addition,  if peak concentrations
 of HzSO^ are important, averaging times  of less than a few hours will be required.
       Long-term temporal  variability plays an  important  role in determining the averaging
 time for  an air quality standard.  The data from the Six-Cities Study34 show that a typical
monitoring record  consists of long periods of near-zero acidity, punctuated  by occasional
spikes of varying intensity and duration. In this case, an annual  average may have  less
relevance to health effects than the statistics of the spikes, perse. For example, acidity data
from four of the cities34 show the following statistics (ug/m3 as H2SO4):
                                        325

-------
       City	Mean	Median     #davs> 5   #davs>  10
Steubenville
Kingston/Harriman
St. Louis
Portage
1.3
1.8
0.5
0.4
0.7
1.1
0.3
0.2
8
15
1
0
4
3
0
0
 These figures show that the ranking of cities depends on the concentration level of concern.
       Year  to year variations are a further consideration in the selection of an index
 pollutant.  Waldman and Koutrakis40 show that seasonal median SO4" periods and most
 of the peak acidity periods were seen nearly simultaneously in all three locations; similarity
 was also noted between Buffalo and Toronto for a 2-month period.  In  contrast, Waldman
 and Koutrakis40 found  substantial variability  in the H+/SO4= ratios measured at five New
Jersey cities, which they attributed to the presence of local ammonia.
       On the scale of the Eastern United States, considerably more variability would be
expected.   Figure 4  plots long-term average H+  vs. SO4' for the sites having sufficiently
long ( > 5 mo!) sampling periods. The three New York  sites of Thurston et al.39 are tightly
 frouped, but  the New Jersey sites40 are spread much  more widely.  Data from the Harvard
 chool of Public Health  24-City Study,40 which are mainly small towns (including  four in
the Western  U.S.), form a reasonably tight group, but data from their Six City Study-*9,
which also used common monitoring and analysis methods, are more widely scattered. The
variation in H + /SO4= is seen to be about a  factor of twelve, apparently because of spatial
differences in atmospheric neutralizing capacities.  The highest degree of neutralization
was seen in Newark,  NJ,40 which is also the most densely populated city sampled.  It should
also be noted that comparisons of measurements between investigators implicitly assumes
equivalency of  measurements and  analytical methods; it is  possible that  some  of  the
differences shown in Figures 3 and 4 are due to differences in experimental protocols.
       A comparable plot for peak levels at these and additional locations24^8-3!.32.34-37'39'41;44
is given in Figure 5; there are many more locations shown because many acidity sampling
programs were  conducted only in summer, when  peak levels are expected. Pairs of peat
values are defined in  two ways for each site; the Hf measured during the time of maximum
SO4=,  and  the  SO4= measured daring the time of maximum H*.  Coincident peaks
occurred in more than half the cases.  In some instances, both day and night sampling data
                                        326

-------
                .
                        O Toronto Site 1
                          Toronto Site 2
                        A Toronto site 3
                          Allegheny Mtn.
                        D Laurel Hi
  Figure 3.  Aerosol acidity as a function of SO4=  concentration for six sites32'37-38, based on
  summer sampling of a few weeks' duration.  Aerosol data from metropolitan Toronto,37
  summer 198637 Sites 1 and 2 are suburban; site 3 is urban.  Sample durations are 16 hr for
  days;, 8 hr for nights.
                           50   100  150   ZOO   250  300   350   400
                                     •uffota (n©q/mS)
 Figure 4.  Long-term average acidity vs. long-term average sulfate for various
                    1200
                            H+@ max S04 A SO4@m«xH
                      0   200   400  800   600  1000 1200  1400 1600
Figure 5. Peak aerosol acidity vs. peak sulfate for various sites.24.28.31.32,35.37.39,41,42.43,44
                                           327

-------
are shown on Figure 5. Again, the relationship between H+ and SCV is seen to be highly
variable, with a spread of about a factor of six. The locations bounding this assembly of
sites were Laurel Hill, PA (high) and Toronto (low), which are separated by about 400 km.
The correlation coefficients were  0.40 and 0.53 for the two sets of data corresponding to
the different definitions of "maximum".
       The relative variability of several  pollutants on combined time and space scales can
be seen from the frequency distribution data given by Schwartz et al.28 for the Harvard Six
Cities, which are located in the Eastern  half of the country. The ratios between 90th and
10th percentiles for the pooled data were 2.1 for ozone, 3.4 for PMio, 3.9 for PM2.5, 6.5 for
SO4°, 7 for visibility as determined by nephelometry,  14.4 for H+, 22 for Sp2, and 360 for
H2SO4 (as  determined by volatilization and flame photometry).  This comparison illustrates
the greater variability in the acidic species.

Summary of Aerometric Data
       The composition of  sulfate  aerosol  is highly variable  in both time and  space,
presumably because of variability in both oxidation rates and neutralization capacity.   In
addition, at  a given level of acidity, the split between H^SO-t and  NH4HSC>4  can vary.
Superimposed on these varying levels of aerosol acidity are variable  levels of gaseous and
fog-borne  acidity.  The  relationship  between  H+ and  SO-t"  tends to be  much  more
consistent  at a given site  or region than it  is among sites, especially when large cities are
included, even when the comparison is limited to the eastern half of the country.

CONCLUSIONS
       As a result of our review of the literature, we find the following:  In spite of the fre-
quent use of the term, "acid  aerosols" lack precise definition.   Strong and weak acids are
found  in the  atmosphere as gases,  liquids, and solids;  the health effects and biological
responses  of many  of these substances and their  combinations  have  not been fully
characterized. The composition of sulfate aerosol is highly variable in both  time and space,
presumably because of variability in both oxidation  rates and neutralization capacity. The
degree of SCV  neutralization was shown to  vary by an order  of magnitude for long-term
averages and by a factor of six for peak values.  In addition, at a given level of acidity, the
split between H2SO4 and  NH4HSO4 can vary.  Superimposed on these varying levels  of
aerosol acidity are variable levels of gaseous and fog-borne acidity. The few available data
suggest that HzSCXi concentrations are more variable than the  total aerosol acidity.  Thus,
sulfate concentration per  se can be a variable (and thus unreliable) measure or aerosol
acidity. Ratios of H*  to ozone or to SO2 also exhibit too much variability to be useful  as
indices of acidity.
       An  important  additional  implication  of this  finding  is that,  in  our judgment,
epidemiological  studies associating health effects with  sulfates should not be interpreted as
also necessarily implicating  aerosol acidity.  For  time-series studies, peaks in sulfates
frequently  occur that are  not accompanied  by peaks  in  acidity.  Similarly, locations with
high long-term average SCXr levels do not  all have correspondingly  high levels of acidity.
Thus, studies finding associations  with SCV  provide  no direct evidence about a possible
role of acidity, as opposed  to fine particle mass, for example.
       Since  additional research is needed  to address uncertainties as to which indicators
of aerosol acidity relate to specific biological responses (health effects), including species,
averaging time, particle size,  and physical phase, we recommend that ambient monitoring
continue to have a research rather than a regulatory focus and  that efforts to describe the
atmosphere in as much detail as  possible  be emphasized, as opposed to  a search for
shortcuts.
                                        328

-------
ACKNOWLEDGMENTS

      This research was supported by the Electric Power Research Institute, under RP
3253; however, the opinions expressed are those of the authors alone.

REFERENCES

1.  Clean Air Scientific Advisory Committee, Subcommittee on Acid Aerosols, Report on
Acid Aerosol Research Needs, EPA-SAB/CASAC-89-002, U.S. Environmental Protection
Agency, Washington, DC. Oct. 19,1988.

2.  F.W. Lipfert, S.C. Morris, and R.E. Wyzga, "Acid aerosols - the next criteria pollutant?",
Envir. Sci. Tech. 23: 1316-1322 (1989).

3.  J,A. Graham, et al, Direct Health Effects of Air Pollutants  Associated with Acidic
Precursor Emissions, SOS/T Report 22, Volume 1, National Acid Precipitation Assessment
Program, Washington, DC. 1990.

4.  U.S. Department of Health, Education, and Welfare, "Air Quality Criteria for Sulfur
Oxides,"  National  Air   Pollution Control  Administration   Publication   No.  AP-50,
Washington, DC. 1969.

5.  R.J.  Tropp,  Acid Aerosol  Measurement  Workshop,   EPA/600/9-89/056,  U.S.
Environmental Protection Agency, Research Triangle Park, NC. 1989.

6.  F.W. Lipfert and R.E. Wyzga, Indices  of Atmospheric Acidity: Spatial and Temporal
Relationships, Paper  90-146.5, presented at the 83rd Annual Meeting of the Air & Waste
Management Association, Pittsburgh, PA. (1990).

7.  U.S. Environmental Protection Agency, An Acid Aerosols  Issue Paper,  EPA/600/8-
88/005F, Washington, DC, 1989.

8.  Acid Aerosols, Envir. Health Persp. 79:3-205 (1989).

9.  J.D. Spengler, M. Brauer, and P. Koutrakis, "Acid air and health," Envir. Sci. Tech 24:
946-956 (1990).

10. T.V. Larson, R. Frank,  D.S.  Covert, D. Holub,  and M.S. Morgan,  "Measurement of
respiratory ammonia and the chemical neutralization of inhaled sulfuric acid aerosol in
anesthesized dogs," Am.Rev.Resp.Dis. 125:502 (1982),

11, J. Q. Koenig, "An assessment of pulmonary function changes and oral ammonia levels
after exposure of adolescent asthmatic subjects to sulfuric or nitric acid," Paper 89-92.4,
presented at the  82nd Annual Meeting of the  Air & Waste  Management Association,
Anaheim, CA (1989),

12. MJ. Utell, J.A. Mariglio, P.E. Morrow, F.R. Gibb, and D.M. Speer, "Effects of inhaled
acid aerosols on respiratory  function: the role of endogenous ammonia," LAerosol  Med.
2:141-147(1989).

13. R. B. Schlesinger, L.C. Chen, I. Finkelstein, and J.Z. Zelikoff, "Comparative potency of
inhaled acidic sulfates:  speciation and the role of  hydrogen ion," Envir.Res. 52:210-224
(1990).
                                        329

-------
 14.  R.B. Schlesinger, "Factors affecting the response of lung clearance systems  to acid
 aerosols: role of exposure concentration, exposure time, and relative acidity," Envir. Health
 Persp. 79:121-126 (1979).

 15. H.A.N. El-Fawal and R.B. Schlesinger, Effect of acute in vivo acid aerosol inhalation
 on in vitro airway reactivity: dose-response relationships. Amer. Rev. Resp. Dis. 145:A430
 (1992).

 16. R.E. Wyzga and F.W. Lipfert,  The need  to  reconcile experimental and ambient
 exposures to acid aerosols," presented at  the NAPAP 1990 International Conference  on
 "Acidic Deposition: State of Science and Technology," Hilton Head, SC, Feb. 1990.

 17. M.O. Amdur, "The  physiological response of guinea pigs to atmospheric pollutants,"
 Int.J.AirPoll. 1:170-183  (1959).

 18.  W.S. Linn,  E.L. Avol, K.R. Anderson, E.A. Shamoo,  R-C. Peng,  and J.D. Hackney,
 "Effect of droplet  size  on  respiratory  responses to inhaled sulfuric acid in normal and
 asthmatic volunteers,"Am. Rev. Respir. Dis. 140:161-166 (1989).

 19. S. Becker, L.J.  Roger, R.B. Devlin, and H.S. Koren, Increased phagocytosis and
 antiviral activity of alveolar macrophages from humans exposed to nitric acid, Amer. Rev.
 Resp. Dis 145:A429 (1992).

 20. A.R. Meetham, Atmospheric Pollution. Its History. Origins, and Prevention, 4th ed.,
 Pergamon Press, Oxford. 1981.
21. B.T. Commins and R.E. Waller, "Observations from a ten-year study of pollution in
City of London," Atm.Envir. 1:49-68 (1967).
the
22. K. Ito, G.D. Thurston, and M. Lippmann, "Association of daily mortality with ambient
exposure  to  an air pollutant  mixture:  paniculate  matter,  sulfur dioxide,  and  acidic
aerosols." Paper 91-137.1, presented at the 84th Annual  Meeting of the Air & Waste
Management Association, Vancouver, BC. (1991).

23. D.V. Bates, "The Ontario Air Pollution Study: identification of the causative  agent."
Envir.Health Persp. 79:69-72 (1989).

24. F.E. Speizer, "Studies of acid aerosols in six cities and in a new multi-city investigation:
design issues." Envir.Health Persp. 79:61-68 (1989).

25. G. Thurston, N. D'Souza,  M. Lippmann, M. Bartoszek,  and J.  Fine, Associations
between summer haze air pollution and asthma exacerbations: a pilot camp study, Amer.
Rev. Resp. Dis. 145:A429 (1992).

26. G. Thurston, P. Kinney, K. Ito, and M. Lippmann, Daily respiratory hospital admissions
and summer haze air pollution in several New York metropolitan areas, Amer. Rev. Resp.
Dis. 145:A429 (1992).

27. L.M.  Neas, D.W.  Dockery, J.D.  Spengler, F.E. Speizer, and D.J. Tollerud, The
Association   of  Ambient  Air  Pollution  with   Twice  Daily  Peak  Expiratory  Flow
Measurements in Children, Amer. Rev. Resp. Dis. 145:A429 (1992).
                                        330

-------
 28. J. Schwartz et al., "Acute effects of acid aerosols on respiratory symptom reporting in
 children," Paper 89-92.1, presented at the 82nd Annual Meeting of the Air &  Waste
 Management Assoc., Anaheim, CA. (1989)

 29. J. Schwartz, "Paniculate air pollution and daily mortality," presented at the annual con-
 ference of the Society for Occupational and Environmental Health, Crystal Citv VA
 March 25-27,1991.                                                          *'   ^

 30.  F.W. Lipfert, Exposure to Acidic Sulfates in the Atmosphere, EPRI EA-6150, Electric
 Power Research Institute, Palo Alto, CA. 1988.

 31. R.L. Tanner, et al., "Chemical composition of sulfate as a function of particle size in
 New York summer aerosol," Ann. NY Acad. Sci. 322:99-113 (1979).

 32.  W.R. Pierson et al., "Atmospheric acidity measurements on Allegheny Mountain and
 the origins of ambient acidity in the Northeastern United States," Atm. Envir. 23:431-459
 (1989).

 33. K.M.  Thompson and P. Koutrakis, Results from  the Uniontown  Summer Study,
 presented at at the  EPA/AWMA Symposium: Measurement of Toxic and Related Air
 Pollutants, May 7,1991.

 34.  J.D.  Spengler,  et al., "Exposures to acidic aerosols," Envir. Health Persp.  79:43-52
 (1989).

 35. M.T. Morandi, et al., "The measurement of H2SO4 and other sulfate species at Tuxedo,
 New York with a thermal analysis flame photometric detector and simultaneously collected
 quartz filter samples," Atm.Envir. 17:843-848 (1983).

 36. H.H Suh, J.D. Spengler, and  P. Koutrakis, Personal exposures to acid aerosols and
 ammonia,  1991 Int. Symp.  on Measurement of Toxic and Related Air Pollutants, Air &
 Waste Management Assoc.,  Pittsburgh, pp. 279-284.

 37. J.M. Waldman, P.J. Liov, G. D. Thurston, and  M. Lippmann, "Spatial and temporal
 patterns in summertime sulfate aerosol acidity and  neutralization within  a metropolitan
 area," Atm.Envir. 248:115 (1990).

 38. T.J. Kelly, Trace Gas and  Aerosol Measurements  at Whiteface  Mountain,  NY.
 Brookhaven National Laboratory Reports BNL 37110 (Sept. 1985) and BNL 39464 (1987).

 39. G.D. Thurston,  J. Gorczynski, P. Jaques, J. Currie, and Deke He, "Daily acid aerosol
 monitoring in three New York State metropolitan areas: sampling techniques and results,"
 presented  at the 84th Annual Meeting of the Air & Waste management Assoc., Vancouver,
 BC, Paper 91-89.6 (1991).

40. J.M. Waldman and P. Koutrakis,  Acidic Aerosol and  Local Ammonia:  Is There  a
Relationship?  Proc. 1991 Int. Symp. on Measurement of Toxic and Related Air Pollutants,
Air & Waste Management Assoc., Pittsburgh, pp. 153-157.

41. P. Koutrakis, personal communication, Dec. 6, 1991.

42. A, Van der Meulen, B.G.  Van Elzakker,  J.M. Waldman, and G. Hoek, "Results of a
year long  study of atmospheric acidity in the Netherlands," Proc. 8th World Clean Air
Congress, L.J. Brasser and W.C. Mulder, eds. pp. 569-574 (1989).
                                       331

-------
43. J.M. Waldman et al., "Summertime  patterns of  atmospheric acidity in metropolitan
Atlanta," presented at the 84th Annual Meeting of the Air & Waste management Assoc.,
Vancouver, BC, Paper 91-89.8 (1991).

44. M.  Brauer,  P.  Koutrakis,  G.J.  Keeler, and J.D.  Spengler,  "Indoor  and outdoor
concentrations of acidic aerosols and gases," presented at the 84th Annual Meeting of the
Air & Waste Management Assoc,, Pittsburgh, 1990. Paper 90-75.3.

45. W.E. Wilson, P. Koutrakis,  and J.D. Spengler, "Diurnal variations of aerosol acidity,
sulfate, and ammonia in the atmosphere," presented at the 84th Annual Meeting of the Air
& Waste management Assoc., Vancouver, BC, 1991. Paper 91-89.9.

46. P. Koutrakis, J.M.  Wolfson, and J.D. Spengler, "An improved  method  of measuring
aerosol strong acidity: results from a nine-month study in St. Louis, Missouri, and Kingston,
Tennessee," Atm.Envir. 22:157-162 (1988).
                                       332

-------
GAS  AND PARTICULATE  PHASE  ACIDS  AND
OXIDANTS IN TWO UNIVERSITY LIBRARIES
Departments of Chemistry and Zoology, Brigham Young
University, Prove, UT 94602

Delbert J.  Eatough*, Nathan Williams*, Laura Lewis*,
Edwin A. Lewis*, Constance K. Lundberg* and Randy H.
Silverman'

Department of Chemistry*, School of Law", and Lee
Library*, Brigham Young University, Prove, UT 84602
INTRODUCTION

      The stability of manuscripts and other paper artifacts during long term storage in a
library is impaired by the presence of acids and redox agents in the library environment1. For
example, exposure of artifacts to ozone at a concentration of 1 ppb over a time period of
100 years results in significant damage13.  Air quality standards have been set to establish
guidelines for the protection of such artifacts  by both the Library of Congress and the
American National Institute of Standards (ANSI)**, for ozone, nitrogen oxides, and sulfur
dioxide, Table I.  The standards set by the two organizations are in general agreement with
the exception of the standard for ozone. The order of magnitude higher standard set by the
Library of Congress probably reflects the quantitation limits of the measurements on which
the standard was based and the lower standard set by ANSI should be considered the better
limit of safety for the preservation of artifacts2.

      The various species for which standards have been set may be  introduced from
outside air or produced by processes in the library such as emissions from electrical motors,
copy machines and furnishings in the facility.  Brigham Young University, as part of an
evaluation of needed improvements in environmental control in the Lee (main University)
and  Law School libraries, has investigated the concentrations and sources of gas and
paniculate phase acids and oxidants in the two  facilities.
                                        333

-------
 DESCRIPTION OF THE LIBRARIES

       The Harold B.  Lee Library is a research library containing more than 3,000,000
 volumes.  The building is constructed in two adjoining wings; the north, constructed in 1960
 has five floors, and the south, constructed in 1976 has six floors. The first two floors of both
 wings  are underground.   The total  indoor area of this library is 430,000 square feet
 Geographically situated in a desert-steppe climate,  the Lee Library is subject  to extreme
 fluctuations in daily and seasonal temperature and relative humidity. The heating, ventilating
 and cooling (HVAC) system is comprised of 1960-  and  1976-vintage equipment that was
 designed primarily to achieve human comfort rather than archival storage conditions for the
 collection. As such, temperature in the library is maintained between 20-24" C year round.
 Control of the library's indoor relative humidity is less precise, however, fluctuating between
 10%-25% in the winter and 35%-65% in the summer. Paniculate filtration of incoming air
 is only accomplished at a 65% efficiency level,  and  gas  phase pollution  removal  is
 nonexistent.

       The BYU Law Library is a research library housed on four floors of the law school
 building. It occupies approximately 40,000 net square feet of the 100,000 square foot total
 area building.  Each of the four floors houses book storage and computers.  The third floor
 houses a copy center. The collection is comprised of 325,000 volumes with most printed on
 acid paper.  Unlike the main library, the law library is part of the central campus HVAC
 system. There are no air quality controls in place, even a simple dust filter. There are no
 separate ventilation systems for the library. The library has experienced severe temperature
 fluctuations, from 13-35° C.  Recent modifications in the electronic controls have reduced
 the temperature fluctuations to 15-28° C

 EXPERIMENTAL

 Species Monitored in Each Library. All species collected in the two libraries were obtained
 using a Briefcase Automated Sampling System, BASS7. The inlet to the BASS was a Teflon
 line  leading  to   an   impactor  (University   Research  Glass  Model   2000-30K/30P
 elutriator/impactor) to  remove particles larger than 2.5  jim.  The sampled  air stream
 containing pollutant gases and fine particles was sampled into various sampling systems from
 a Teflon lined manifold after the impactor7. Total inlet air flow for the sampling system was
 12 sLpm.

      The concentrations of fine paniculate sulfate, nitrate, ammonium ion and acidity were
 determined using diffusion denuder sampling techniques. The corresponding concentrations
of gas phase SO* HMO* HNO2 and NH3 were also determined using the diffusion denuder
sampling system. The micro-diffusion denuder7 consisted of a 7.5 cm long annular diffusion
denuder (URG  Model 2000-15B) coated with a 5 wt% NaHCOj/5 wt% glycerine solution
to collect acid gases. This was followed by a second  denuder section coated with a 5 wt%
citric acid/5 wt% glycerine solution to collect ammonia.  The two denuder sections were
followed by a Teflon filter pack (URG  Model  2000-15A-ABT) which contained a Teflon
filter (Gelman Science, Zefluor P5PJ047) to collect particles followed by a Nylon  filter
(Gelman Science,  Nylasorb 66509) to collect any nitric acid lost from the particles during
                                        334

-------
sampling.  The  annular denuder sampling system operated at a  flow rate of 3 sLpm
controlled by a critical orifice.  The species  collected  in the carbonate coated denuder
section were determined by washing off the coating and the collected gases with distilled
water and determining the collected acid gases by anion  chromatography using a DIONEX
Model 2000S instrument with 2.4 mM NaHCC>3/4.0 mM Na2CO3 eluent Anions in collected
panicles on the Teflon filter or nitrate collected on the  Nylon filter after the Teflon filter
were determined by ultrasonic extraction of the sample with water or 1C eluent, respectively,
and determination of anions by 1C Ammonia collected on the acid coated annular diffusion
denuder section or ammonium ion in the collected particles were determined in aqueous
extracts of each sample by a spectrophotometric analytical procedure*. The acidity of some
samples  was determined by  pH measurements on the  aqueous extracts of the collected
particles.

      Concentrations of NO,, NO2 and O3 were determined using appropriate  Drager
absorption tubes7.   The  concentrations  of each of these species were  determined in
integrated samples by pulling the sampled air stream through the denuder tube at a constant
flow rate of 200 mL/min. Flow was controlled for each tube using a critical orifice. The
color change of each  tube  was noted immediately  after sampling and converted to a
concentration based on the sampling time and sample  flow rate for each Drager tube. The
collection efficiency of the tubes used in this manner has been previously reported*.

Sample Collection. The concentrations of each of the species studied were determined at
three locations in each library.  Samples were collected in the Lee library  in the Archives
on the fifth floor in the older section of the library, on  the  main (third) floor in the copy
center in the newer section of the library, and on the first floor in the new section of the
library at a circulation  desk.  Samples  were collected the Law School library in the copy
center on the main (third floor), in the student computer section on the main floor and in
the book stack area on the first floor.

      Samples were collected at the various locations  in the  main library on three different
days.  Samples were collected from 08:00 to 12:00, from 13:00 to 17:00 and from 18:00 to
22:00 each sampling day.  Two sample days were selected for the Lee library when the
concentrations of acidic species and oxidants were high in the outdoor environment because
of the presence of winter inversions in the local area10 and on one day when the outdoor
environment was clean  because of heavy rain.  Samples  were also collected in the outdoor
environment as a function of the time of day on the two days.  Samples were collected at
the three locations in the Law School on two different days when the concentrations of
oxidants were moderately high in the outdoor environment  Samples were also collected in
the outdoor environment as a function of time of day on one of the two sample days.

RESULTS AND DISCUSSION

      The daily average  concentrations of ozone, nitrogen oxides, nitrogen dioxide and
sulfur dioxide  at each  sampling  location  in each library are compared to the ambient
concentrations, where available, and to the recommended ANSI pollutant standards in
Figures 1-4,
                                       335

-------
       The concentrations of ozone did not show a marked pattern with time of day but
 tended to peak during the mid-day sample.  The concentrations determined in both libraries
 were always higher than the ANSI standard, Figure 1. The concentrations of ozone in the
 Lee Library, Figure 1, tended to be highest in the copy center and lowest in the Archives.
 Similar patterns were seen  in the  Law Library where the concentrations of ozone were
 highest on any given day in the copy center. The results indicate that the air inlet systems
 are not effective in removing ambient ozone.  In the absence of carbon filters to remove
 ozone in building intake air, the ratio of the indoor to outdoor ozone concentration is
 expected to  vary from  about 0.4  to 0.6".  This was generally observed  in the library
 environments studied except for the copy centers where the observed indoor/outdoor ratio
 varied from 0.7 to 1.3.  The  results suggest that ozone is formed in the copy  centers of the
 libraries.  On the average, about  1/3 of the ozone measured in the copy centers appears to
 have  been formed in the indoor environment

       The concentrations of NO, (NO  plus NO2) were generally higher in the library than
 in the ambient air, Figure 2, suggesting sources of NO, exist in the buildings. These sources
 might include the HVAC or other electrical equipment. There are no combustion sources
 within the buildings.  Heated air is provided  to both buildings from a central coal-fired
 heating plant  The NO, concentrations in both libraries showed a definite pattern with
 highest concentrations of NOX during the morning or evening sampling periods and lowest
 concentrations (usually by a factor of about 2) during the mid-day sampling period. The
 concentrations of NOX are comparable in all parts of each library on any given sampling day,
 Figure 2.  This was true whether the data were compared on the basis of daily averages as
 are given in Figure 2 or on the basis of individual sampling periods.  The concentrations of
 NO2 were from 10  to 20 percent of the NOX concentrations in all rooms in each library,
 Figures 2 and 3. The highest NO2 concentrations were always found in the copy centers,
 Figure 3.  This may be attributed to the increased- conversion of NO to NO2 in the copy
 centers as a result of the higher concentrations of ozone in the copy centers12. In all cases,
 the concentrations of NOX in the  indoor library environments exceeded the recommended
 standard.  In fact, the concentrations of NO2 in the library environment was above the ANSI
 recommended standard for NOM even when the concentraion of NO2 in the ambient air was
 below the standard.

       Concentrations of SO2 in each of the libraries generally did not show a pattern with
 either time of sample collection or location in the library.  The concentrations of SO2 were
 always lower than the ambient SO2 concentrations where data were available.  The results
 are consistent with  the  source  of SO2 being the ambient environment  as expected.
 Consistent with the observation for ozone, the  HVAC systems of the two libraries are not
 effective in the removal of SO2 from inlet fresh air. Even though the concentrations of SOj
 in the libraries are much lower than the  concentrations of NOe the SO2 concentrations are
 generally close to or above the recommended limits, Table I and Figure 4.

      The concentrations of HNO3(g)  and paniculate sulfate and nitrate  in the  library
environments were comparable, Figures 5-7. The equilibria between gas phase HN03 and
paniculate nitrate is consistent with that expected for the equilibrium reaction,
                                        336

-------
      NH4N03(s) = HN03(g) + NH3(g)                                         (1).

The equilibrium constant for reaction (1) at 22'C is 11 ppb2 13.  The  product  of the
ammonia, Figure 8,  and nitric acid, Figure 5, gas phase concentrations are generally close
to this value. The particulate nitrate was collected by the annular diffusion denuder after
removal of both the gas phase nitric acid  and ammonia.   This  particulate nitrate was
dominantly present on the  Nylon filter, consistent  with  the  expected  dissociation of
ammonium nitrate during sampling according to reaction (1) in the absence of the gas phase
species. There was  a trend for the concentrations of total nitrate to be higher in the copy
center of the Lee, but not the Law Library.  Total nitrate in the library environments was
frequently higher than the ambient concentrations, suggesting that reactions to form gas and
particulate nitrate exist in the library environments.  It has been previously suggested that
both homogeneous and heterogeneous reactions with indoor surfaces can lead to elevated
nitrate and nitrite concentrations1*14-". Detectable concentrations  of HNO2 were seen on
only a few of the total samples collected in  the indoor library environments in this study.
consistent with the expectation that the building occupants might be a source of ammonia,
where data are available, Figure 8, the observed ammonia concentrations in the library were
higher than the observed ambient concentrations. The ammonia concentration was not
related to the time of sample collection in either the ambient or indoor samples.

      The high acidity of the indoor library environments as  reflected in the concentrations
of SO2 and HNO3 was not reflected in the acidity of the particulate matter.  The ratio of
strong acid to total equivalents of nitrate and sulfate, Figure 9, was very low.

CONCLUSIONS

      The HVAC systems of the two libraries  studied were not effective in the removal of
ozone, NO,, SO2 or particulate species.  The concentrations of these species which are
expected to be dominated by outdoor sources generally followed the outdoor concentrations.
The data indicate that significant sources of NO, exist in the libraries. Ozone and NO2 were
highest in concentration in the copy centers of each library, presumable due to the formation
of ozone from the operation  of the copy equipment and the subsequent conversion  of NO
to NO2 by the ozone so formed.  There is also evidence for the formation of nitrate species
in the indoor library environments. The concentrations of all Oj, NO* NO2 and SO2 in the
two library environments exceeded the recommended limits for preservation of manuscripts
and artifacts. The current HVAC systems in these facilities are not adequate to meet ANSI
or Library of Congress standards and an improvement in the HVAC systems is advised,
including the addition of systems to remove ozone and nitrogen oxides in both inlet and
recirculation air systems. In view of the apparent production of ozone and NO2 in the copy
centers, it would seem desirable to have separate ventilation and exhaust systems for these
areas,

REFERENCES

1.    NRC (1986) "Preservation of historical records," National Research Council, National
      Academy Press, Washington D.C.
                                        337

-------
 2.     Cass G.R., Dnizik J.R., Grosjean D., Nazaroff W.W., Whitmore P.M. and Wittman
       C.L (1988) "Protection of works of art from photochemical smog," Report tot he
       Getty Conservation Institute, Marina del Rey,  CA.

 3.     Druzik J.R.  (1990)  "The measurement and  model prediction of indoor ozone
       concentrations in museums," Atmos. Environ..  24A, 1813-1823.

 4.     Baer N.S. and Banks P.N. (1985) "Indoor air pollution:  Effects  on cultural  and
       historic materials," Int. J.  Museum Manage. Curatorship. 4, 9-20.

 5.     ANSI (1985) "American National Standard practice for storage of paper-based library
       and archival documents," ANSI 39.xx, American National Standards Institute, New
       York.

 6.     NBS (1983) "Air quality criteria for storage of paper-based archival records," NBSIR
       83-2795, National Bureau of Standards, Washington, D.C

 7.     Eatough D.J., Caka P.M., Wall K., Crawford J., Hansen L.D. and Lewis E.A. (1989)
       "An Automated Sampling System for the Collection of Environmental Tobacco
       Smoke Constituents in Commercial Aircraft," Proceedings. AWMA/EPA Symposium
       on Measurement of Toxic and Related Air Pollutants. 565-576.

 8.     EPA (1979) "Methods for the chemical analysis of water and wastewater," EPA-600/4-
       79-020, Method 350.1, Ammonium, Colorimetric, U.S. Environmental Protection
       Agency.

 9.     Eatough D.J. (1990) "Environmental Tobacco Smoke in Commercial Aircraft," final
       report submitted to CIAR.

 10.    Caka P.M., Lewis E.A and Eatough D.J. (1992) "Sulfate and nitrate formation in
       Utah Valley during winter inversions." Proceedings of the 85th Annual
       Air and Waste Management Association. Paper 92-62.05.

 11.    Weschler C.J., Shields H.C and Nalk D.V. (1989) "Indoor ozone  exposure,"
       39, 1562-1568.

12.    Weschler C.J., Brauer M. and Koutrakis P. (1992)  "Indoor ozone and nitrogen
       dioxide:   A potential pathway to the generation of nitrate radicals, dinitrogen
       pentoxide, and nitric acid  indoors," Environ. Sci. Tech.r 26,  179-184.

13.    Finlayson-Pitts B.J. and Pitts J.N. Jr. (1986) Atmospheric Chemistry: Fundamentals
       and Experimental Techniques. John Wiley and  Sons, New York.
14.    Eatough  D.J.,  Lewis  L, Lamb J.D., Crawford J., Lewis E.A., Hansen LD. and
       Eatough  N.L. (1988) "Nitric and  nitrous acids in environmental tobacco smoke,"
       Proceedings. EPA/APCA  Symposium on  Measurement  of Toxic a^ Related Ail
      Pollutants, pp.  104-112.
                                      338

-------
 15.    Nazaroff W.W. and Cass G.R. (1986) "Mathematical modeling of chemically reactive
        pollutants in indoor air," Environ. Sci. Tech.. 20, 924-934.
 Table I. Recommended Standards (ppb) Required for the Preservation of Artifacts and
 Documents in Libraries**.
        Pollutant

        S02(g)
        NCUg)
        0,(g)
           ANSI

           0.4
           ^5
           i
                      Library of
                      Congress

                       0.4
                       2.5
                      13
cc
cc
	  rr
1 " . H  FF
                                                     Archly*
                                                     Computer
Ambl.nl
ANSI
     -a
      a
      n
     o
                   Clear    Inv. 1     Inv. 2
                        Lee Library
                        Inv. 1    Inv. 2     ANSI
                       Law Library    standard
Figure 1.      Average concentrations of ozone in the first floor, copy center and Archives sampling locations
in the BYU Lee Library and in the first floor, copy center and computer study sampling locations in the BYU
Law School Library on the indicated sampling days as  compared to ambient concentrations and ANSI
recommended limits.
                                           339

-------
                  wimtP  <
                  t   23  cc
mmm® Archive    K»XXKI  Amblint
EZ 3 Compultr  EEI ZD  ANSI
            90
            60
       Q.
       Q.
      >—'
       M
      o
                    Clear    Inv. 1     Inv. 2
                          Lee  Library
 Inv. 1     Inv. 2
Law Library
ANSI
Standard
  Figure 2.      Average concentrations of nitrogen oxides in the first floor, copy center and Archives sampling
  locations in the BYU Lee Library and in the first Qoor, copy center and computer study sampling locations ii
  the BYU Law School Library on the indicated sampling days as compared to ambient concentrations and AN*
  recommended limits.
                                                        Archive   K&r&Xl Ambient
                                                        Computer
                                                                        ANSI
       Q.
       a
       -^'
       N
       O
                     Clear     Inv. 1     Inv. 2    Inv. 1     Inv. 2    ANSI
                          Lee  Library       Law Library    standard
Figure 3.       Average concentrations of nitrogen dioxide in  the first floor, copy center and Archives
sampling locations in the BYU Lee Library and in the first floor, copy center and computer study sampling
locations in the BYU Law  School Library on the indicated  sampling days as  compared  to ambient
concentrations and ANSI recommended limits.
                                            340

-------
                                                   •;-'-l-l  Computer  LilL'^l'il-'J
                                                                  Ambient
                                                                  ANSI
      1.20
      0.00
                                                                 ANSI
                                                                 Standard
                     Clear    Inv. 1     Inv. 2     Inv. 1    Inv. 2
                          Lee Library       Law Library
Figure 4.      Average concentrations of sulfur dioxide in the first floor, copy center and Archives sampling
locations in the BYU Lee Library and in the first floor, copy center and computer study sampling locations in
the BYU Law School Library on the indicated sampling days as compared to ambient concentrations and ANSI
recommended limits.
                                                                   Ambl«nt
a
a
       1.50
       1.00
       0.50
       0.00
                                                     Inv. 1      Inv. 2
                                                     Law Library
                      Clear       Inv. 1      Inv. 2
                             Lee Library

Figure 5.      Average concentrations of gas phase nitric acid in the first floor, copy center and Archives
sampling locations in the BYU Lee Library and in the first floor, copy center and computer study sampling
locations in the BYU Law School Library and in ambient on the indicated sampling days.
                                     341

-------
                                                                    Ambl.nl
         0
         £
         c

         o"
         *••
         (B
                      Clear
  Inv. 1
Inv.
                                                    Inv. 1      Inv. 2
                          Lee Library            Law Library
Figure 6.      Average concentrations of paniculate nitrate in the first floor, ropy center and Archives
sampling locations in the BYU Lee Library and in the first floor, copy center and computer study sampling
locations in the BYU Law School Library and in ambient on the indicated sampling days.

                                   Sulfate

                Average of the  sampling periods
                         ^*                BwjswjAyWi         WJAAXV1
                                                                 Ambient
      o
      E
      c

      o"
      +*
      a

      "5
      (0
                    Clear
Inv. 1
                          Lee  Library
                      Law Library
Figure 7.      Average concentrations of paniculate sulfatc in the first floor, copy center and Archives
sampling locations in the BYU Lee Library and in the first floor, copy center and computer study sampling
locations in the BYU Law School Library and in ambient on the indicated sampling days.
                                         342

-------
                                                                       Ambl.nl
       Q.
       a
                     Clear       Inv. 1       Inv. 2      Inv. 1       Inv. 2
                            Lee Library             Law  Library
  Figure 8.      Average concentrations of gas phase ammonia in the first  floor, copy center and Archives
  sampling locations in the BYU Lee Library and in the first floor, copy center and computer study sampling
  locations in the BYU Law School Library and in ambient on the indicated sampling days.
                                                                          AmbUnl
      3
      (0
      CM
      t

      *-
Figure 9.
0.50 1


0.40


0.30


0.20
                         Clear
                                               Inv. 1      Inv.2
                                               Law Library
                                    Inv. 1       Inv. 2
                                Lee  Library
             Average mole ratio of paniculate acidity to the sum of paniculate nitrate and twice the
paniculate sulfate in the first floor, copy center and Archives sampling locations in the BYU Lee Library and
in the first floor, copy center and computer study sampling locations in the BYU Law School Library and in
ambient on the indicated sampling days.
                                            343

-------
MEASUREMENTS  OF  NITROUS  ACID:  VARIABLES
AFFECTING INDOOR CONCENTRATIONS
M. Brauer
The University  of British  Columbia:  Respiratory  Division,
Exposure   Assessment   Laboratory,  2775   Heather  Street,
Vancouver, BC  CANADA V5Z 3J5
Prior measurements have indicated that concentrations of nitrous acid (HONO) in indoor air
exceed concurrently measured ambient levels, particularly when an indoor NO2 source is
present. Peak levels of 100 ppb have been measured during the operation of an unvented
gas-fired space heater, while homes using gas stoves for cooking present 24-hour averages
concentrations of up to  15 ppb.  Indoors,  HONO appears to be produced by at least two
distinct processes, a fast process which incorporating flame chemistry, and a slower pathway
which is likely to involve a  heterogeneous reaction  mechanism.  Factors affecting  the
heterogeneous production of HONO were investigated by measuring HONO concentrations
as a function of NOj concentrations, residence time (ventilation rates), relative humidity and
surface composition in a series of climate chamber studies.  Increasing relative humidity led
to greater HONO concentrations at a given  NO2 level.  At 80% relative humidity, HONO
concentrations were 11 % of the NOj concentration.  Increased residence time in the chamber
increased HONO levels only slightly. The presence of wool carpets in the chamber was not
found to affect  significantly the  HONO production  or NOj decay rates.  Additionally,
controlled  atmospheres  containing predominantly  HONO, but also NO and NO2 were
produced, and concentrations of HONO measured  with Na^COj-coated annular denuders,
Na2CO3-coated filters and by a modified chemiluminescence technique.  Comparisons of
these measurements were made and denuder and filter efficiency and capacity  tests were
performed for a range of relative humidities.
                                      344

-------
Introduction
Research efforts concerning the human respiratory effects of NQj exposure have indicated
that concentrations of NO2 which may be encountered in ambient and indoor environments
(100 ppb) may provoke acute effects on the airways of asthmatics. However,  problems in
study design and statistical analysis have weakened the conclusions of many of these studies1.
Additionally, there is a great deal of uncertainty regarding the lower threshold  limit for the
provocation of airway effects following NOj exposure.
Since most common measurements of nitrogen oxides are not specific to NQz, one possible
confounding factor in NO2 exposure studies is the presence of other nitrogen oxides in the
exposure environment.  For example, nitrous acid (HONO) and nitric acid (HNO3) may be
formed indoors from the reaction of NO, with water on indoor surfaces. It is likely that this
process  may be  influenced by the type of surface  material (i.e. the chamber  walls and
furnishings)  present in the  chamber and  the  surface-to-volume  ratio.  Research  has
demonstrated that the rate of NOj removal from an indoor atmosphere is influenced by the
composition of surface materials present2, the exposed surface area3 and the relative humidity
above the surface2-4.  In many instances, NOj removal may be  accompanied by HONO
production such that increasing NO2 decay rates result in greater HONO production. Recent
evidence also suggests that HONO may be produced directly in the combustion  process in
addition to its production in heterogeneous reactions4ii6.  Studies of HONO formation have
demonstrated that approximately 50 ppb of HONO are produced in an atmosphere containing
1000- 1200 ppb NO23'".  Although the possible respiratory toxicity of HONO has*Xxot been
investigated in detail, the acidic nature of this compound, its reactivity and aqueous solubility
suggest that respiratory damage is  plausible,

In clinical human exposure studies, reactive chemistry within the  exposure chamber has
seldom been considered. Some of the previous NO2 exposure studies were conducted in small
volume, low airflow chambers with low surface/volume ratios. Such conditions may promote
the formation of HONO from reactions of NOj.  Since the possible confounding effect of acid
gases on the provocation of exposure effects have not been controlled for, it may provide a
partial explanation for the observed inconsistencies  in the threshold concentration for the
provocation of airway effects.

Acid gases could also be important co-factors or competitive causes of the effects associated
with NO2 exposure in  epidemiological studies.  In these studies all of the products of
unvented combustion, and not just NO?, are the exposure variables. In this context, the direct
production of HONO during gas combustion,  in addition to HONO production from NO2
surface reactivity, is important. As most of the measurement techniques commonly used in
epidemiologic  investigations measure total  (excluding nitric oxide  (NO)) nitrogen oxides
(NO2, HONO, HNO3, etc.), exposure assessment has not been specific for the compound of
interest,  presumable  NO2.  Accordingly,  any  epidemiological  study demonstrating  a
relationship between health endpoints and NO2 exposure should be  viewed with caution until
the presence  of other  potentially toxic nitrogen oxides in the exposure environment  is
evaluated.  Elucidating the relative contribution of NOj reactivity and of direct production
to indoor HONO levels will help to clarify the confounding factors in chamber studies as
well as the appropriate exposure parameters to measure in epidemiologic studies.

In this investigation we sought to measure  the production of HONO in a stainless steel
exposure  chamber into  which known concentrations  of NOfe were introduced from gas
cylinders.  Furthermore,  we conducted  preliminary measurements of exposure chamber
parameters which may influence HONO production.  The hypothesis which serves as the
                                       345

-------
 basis for these experiments is that in  prior studies addressing NO2 exposure, HONO is
 produced heterogeneously on surfaces.  The presence of HONO then interferes with the
 assessment of NO2 exposure - health effect relationships.  Indoor conditions and the source
 of NQj will influence the production of HONO.

 Methods
 All  measurements were conducted in  a clean  and empty 79 M3 stainless  steel  climate
 chamber located  at the Institute of Environmental and Occupational Medicine,  Aarhus
 University, Denmark. The chamber is  computer-controlled to achieve constant ventilation,
 temperature, relative humidity and pressure conditions.  For all experiments NO2 was added
 into the ventilation air directly from a cylinder containing 1 %  NO2.  Initial measurements
 were made at six vertical and horizontal positions within the chamber to ensure adequate
 mixing. Measurements from all positions agreed within ±5%.

 Climate chamber measurements of nitrous acid were made by  annular denuders, and a
 modified chemiluminescent analyzer.  The  annular denuder method has been described
 previously5-7, 3 Na2C03-coated denuders were connected in series and sampled at a flow rate
 of 10 L min~'.  The limit of detection for the denuder measurements of HONO, based on the
 sensitivity of the ion chromatographic analysis,  was 0.85 ppb*m3.  Therefore, a two hour
 sample at the 10 L min"1 flow rate, has a detection limit of 0,71 ppb.

 A series of denuder collection tests were conducted  with a  test atmosphere  containing
 approximately 600 ppb HONO, 60 ppb  NO and 30 ppb NOj, in purified air at 45% RH, 22
 °C.  Results indicate 99% collection efficiency and a collection capacity of 190 pg of HONO
 based on chemiluminescent monitoring of HONO downstream of a single denuder coated
 with  1% Na2CO3 / 1%  Glycerol.  Denuder sampling efficiency and capacity were also
 calculated from the 2-hour chamber sampling experiments. Up to HONO concentrations of
 90 ppb, collection efficiency is above 99% on the first denuder, based on measurements of
 HONO on  the second and third denuders in the sampling train.  At 90 ppb HONO, the
 highest concentration at which  >99%  collection efficiency was measured, the denuder
 collected 207 /ig HONO, in good agreement with the breakthrough tests.  Additionally, the
 capacity and efficiency appear to be unaffected by relative humidity over the 30%-80%
 range.  For all experiments the HONO concentration was determined from the sum of the
 NO2" collected on the first two denuders minus the NO2" collected on the third denuder.  This
 procedure provides  the most accurate determination of HONO,  assuming high efficiency
 collection of HONO and a very low efficiency collection of NC^ (196) on the denuder which
 interferes with the HONO determination. The denuder capacity for HONO of approximately
 200 /xg is substantially lower than capacities obtained for HNO3  and SO2 in earlier tests10
 where capacities of  > 1  mg were observed.  This suggests that HONO collection capacity
 is controlled by a more complex mechanism than simple breakthrough.  Displacement of
previously adsorbed or absorbed HONO by other acidic gases or even by clean air is a likely
possibility.   Previous investigations also support this mechanism3-5, suggesting  that the
presence of NO2~ on the second denuder appeared to be relatively independent of the HONO
concentration, but dependent on the sampling volume.

HONO was also sampled continuously with a modified  chemiluminescent NOx  analyzer
(Thermo Electron 14B/E). The NOx analyzer was calibrated biweekly with a gas dilution
 system (Thermo Electron 101) using a certified gas cylinder of 20 ppm NO (Union Carbide).
The limit of detection of the modified chemiluminescent analyzer, based upon 3 * standard
deviation of HONO measurements in the chamber under conditions of clean air, was found
to be 6 ppb. During all  experiments the inlet for the chemiluminescent analyzer and the
                                       346

-------
denuder  samplers  were  collocated  in  the  middle of  the  79 m3  exposure chamber,
approximately 1.5 meters above floor level. A Teflon sampling line approximately 6 meters
in length led to the  chemiluminescent analyzer itself, which was placed outside of the
chamber.

Tests of HONO generation were performed by following a  standard protocol which consisted
of 3 replicate measurements of two hours each. The flow  rate of gas from the cylinder was
increased initially in order to obtain  the desired concentration within the chamber as soon
as possible. When the NOj concentration reached the desired level, the denuder sampler was
connected to the sampling pump.    Following the first two hour sample, a new  denuder
system was placed within the chamber, new Na2CO3-coated filters were placed in the filter
pack upstream of the chemiluminescent analyzer, and the  second two-hour experiment was
initiated.  Chamber conditions were always  equilibrated  at least three hours prior  to the
beginning of sample collection, and the chamber was flushed with clean air for at least 12
hours between different exposure conditions.

ggsults and discussion
A recent study  on the effects of NOj exposures  was  conducted the same stainless steel
chamber, with a high airflow and no  recirculation of the air, expected to reduce the content
of acids in the air to a minimum and to thereby eliminate the possible confounding  effect of
HONO.  This study  showed no signs  of acute  effect  of 2-hour exposure to  NOz in
concentrations up to 800 ppb among 20 asthmatic and 20 healthy subjects8. The first series
of tests were designed to simulate the conditions of this previous NQ human exposure study.
Results indicate that a low level of HONO (1-3 ppb) was present in the chamber under these
conditions. HONO/NO2 concentrations  increase slightly  with increasing NO2 levels. The
rate of conversion is quite low, and can be expressed as HONO  =  0.002*NO2 + 1.47
(1^=0.9).  Under these conditions of ventilation, temperature and humidity, substantial
HONO production from the introduced NOj  is not apparent.  The most likely explanation
for these results is that trace levels of HONO were present in the ventilation air and/or the
NO2 cylinder and that significant HONO production and release into the gas phase did
not occur during the residence time of air in  the chamber.  At the ventilation rate used for
these tests, residence time was 4.9 minutes. These results indicate that significant gas phase
release of HONO was unlikely to have occurred in the previous NOj human exposure study
performed in this chamber.  Comparisons with HONO  measurements in other chambers
previously used for NO2 exposure studies  will help to  determine the magnitude  of the
confounding factor due to HONO production within exposure chambers.

The remaining  sets of experiments were designed to identify the chamber parameters for
which  substantial HONO production would be observed.  To replicate more closely the
chamber environment during an actual exposure study, we examined the effect on HONO
production due  to human subjects being present in the chamber when NOj was introduced
(Figure la).  At the high ventilation rate (12.3 ACH) no differences (p < 0.01) were observed
between HONO concentrations with  subjects  in the chamber  relative to identical  chamber
environments in which  people were not inside the chamber.  However, at the lower
ventilation rate  (0.5  ACH), HONO/N02 ratios were one-half to one-third  lower when
subjects were present in the chamber. Mean HONO/NOj ratios were significantly lower at
0.5 ACH when  subjects were present in the chamber (p<0.05). These results suggest that
HONO removal mechanisms, such as adsorption, were important when residence times in
the chamber were increased above 4.9 minutes.

Although separate tests indicated essentially complete  removal of inspired HONO in the
                                       347

-------
 airways, a  simple  calculation reveals  that the observed  decreases in chamber MONO
 concentrations could not be attributed solely to respiratory tract removal by the subjects.
 Under the conditions of the exposure study (3.0 ACH target, but possibly as  low as 2.2
 ACH), and with 8 subjects ventilating at 10 L min'1,  the maximal removal of HONO due
 to the ventilation of the subjects was 2.7%, far below our observations  of up to 30%
 decreases in HONO concentrations.  These results indicated that in addition to removal of
 HONO by ventilation, reactions with body surfaces, clothing or bioeffluents were acting to
 remove HONO from the air.

 The third series of experiments  investigated the effect of chamber  relative humidity on
 HONO levels (Figure Ib). Our observations indicate that increasing the relative humidity
 increased the HONO concentration (p<0.01).  This  result clearly implicates chamber
 reactions, in particular the heterogeneous reaction of NOj with H2O, rather than HONO
 contamination in the NO2 cylinder, in  HONO production. For these tests, a low ventilation
 rate (0.5 ACH) was used in order to increase  chamber residence times to maximize the
 potential effect of heterogeneous chemical reactions. At the highest relative humidity tested,
 80%, HONO concentrations were approximately 8% of the observed NO2  level. The
 measurements at 30% and 45% relative humidity resulted in HONO/NO2 ratios of 0.9% and
 2.7%, respectively which are in good agreement with ratios observed in the studies of Pitts,
 et al. for injections of NOj into a mobile laboratory6-'.  Examination of the NO2 decay data
 also implies HONO production  that is associated with NO2 decay (Table 1). NO2 decay rates
 increase  with respect to increasing  relative humidity, while HONO decay rates decrease,
 suggesting HONO production.

 Our next series of experiments investigated  the  effect of ventilation rate on HONO
 concentrations (Figure Ic). Air exchange rates of 0.5, 3.0 and 12.3 hr1 were used, with an
 NO2  concentration  of  800  ppb.  These  tests also  indicated  an  increase  in HONO
 concentrations with decreasing ventilation  rates, again implicating reactions inside the
 chamber in our  observations of HONO in the chamber air. Note that there  is no difference
 between  HONO/NO2 ratios at  12.3 and 3.0 ACH (p=0.54), while the ratio is increased
 approximately 5-fold at  0.5 ACH.  The HONO/NO2 ratio is significantly increased at 0.5
 ACH relative to 3.0 ACH (p<0.005). These results indicate that residence times between
 20 and 120 minutes are required for measurable HONO release to occur within the chamber
 at 45%  R.H., 22°C.  NO2 decay rates, normalized to the ventilation rate, increase with
 increasing residence time in the chamber, implicating reactive removal of NOj.  Similarly,
 HONO decay/air exchange decreases with increasing residence time, suggesting production
 within the chamber (Table 1).

 The final set of tests investigated the effect of increased surface area, due to the placement
 of wool carpets into the chamber, on HONO concentrations (Figure Id).  Approximately 30
 m2  of new  100% pure  wool carpet  (Polypropylene primary  backing,  Polypropylene
 secondary backing with  butadiene-styrene + CaCO3 adhesive; Weston Tsppefabrik) were
 placed inside  the chamber  and  equilibrated  at the  different  relative  humidities for
 approximately 12 hours  prior to  the  introduction of NO^   Results of these experiments
 indicated that, particularly at the higher relative humidity levels, the presence of wool carpets
 lowered the HONO concentration.   Mean HONO/NO2 ratios  were significantly lower
 (p<0.05) when carpets  were present  in the chamber at 45% and 80% relative humidity.
These results agree  well with the tests of subject presence in the chamber and appear to
 further implicate HONO adsorption/absorption on textiles present inside the chamber.
Examination of the decay rates indicates that  NO2 reactivity  was increased due to the
presence  of carpets in the chamber. When carpets were in the chamber, NC^ decay rates
                                       348

-------
were approximately double the decay rates measured under the same conditions  without
carpets.  However, with carpets in the chamber, there was no increase in NOj decay rate
with increasing relative humidity, as was observed in the comparison tests.  This observation
suggests that the increased surface of the carpets leads to NOj reactivity via an alternative
pathway than that occurring on stainless steel surfaces at elevated relative humidities.  In this
situation, NO2 decay does not result in concomitant HONO production.  NO2 may react on
the wool carpets to produce non-volatile species or other gases besides HONO may be
released.  More likely, HONO is produced but is adsorbed quickly on the carpet surfaces.
This explanation is consistent with our observations of HONO removal when subjects were
present in the chamber, and the likely removal of HONO on clothing.

Conclusions
Results indicate that in the previous NOj exposure study performed in the climate chamber
at Aarhus University8 HONO concentrations were not elevated above background levels.
Although traces of HONO were present in the chamber environment, it is extremely unlikely
that these HONO concentrations were high enough to have any effect on the NOj exposure
response relationship.  Our results  indicate that the high ventilation rate  and moderate
relative humidity used for this previous study precluded any substantial HONO formation in
the chamber atmosphere.   Further tests indicate the strong association  between  HONO
production and relative humidity.  This  is consistent with  previous chamber investigations
which have found HONO production to be first order with respect to both NOj and H2O.
However, our finding that the presence of a wool carpet  in the chamber did not increase
HONO production indicates that the nature of the surfaces present for reactions to occur is
important.  This finding, in combination with our observation that HONO concentrations
decreased  when  people were present in the chamber, suggests  substantial absorption of
HONO on fabrics.   Further, we found HONO  concentrations to be a function  of  the
residence time in the chamber, and our  results indicate that residence times of at least 20
minutes are  required  for measurable  increases in the HONO concentration.  Accordingly,
future chamber investigations should have adequately high ventilation rates and should avoid
high humidities to ensure that HONO production is minimized.

Acknowledgements
Support for  this  research comes from the Gas  Research  Institute (U.S.A.) and from  the
Nordic Gas Technology Center (Denmark).

References
 1.    Samet, J.M. and  Utell, M.J.  (1990) The risk of nitrogen dioxide: What have we
       learned from epidemiological and clinical  studies. Toxicol. Ind. Health 6(2):247-262.

 2.    Spicer, CW, RW Coutant,  DW Joseph, GF Ward, IH Billick: Control of Indoor NOj
       Pollution  by Adsorptive Surfaces.  1989 International Gas Research Conference,
       Japan.

 3.    Febo, A. and Perrino, C.  Prediction  and  experimental  evidence for  high  air
       concentration of nitrous acid in indoor environments.  Atmos. Environ. 25A(5/6):
       100-1061  (1991).

 4.    Yamanaka, Shin'Ichi: Decay Rates of Nitrogen Oxides in a Typical Japanese Living
       Room. Environ Sci Technol. Vol.l8(7):566-570.

 5.    Brauer, M,  PB Ryan, HH  Suh, P Koutrakis,  JD Spengler, NP Leslie,  IH Billick:
                                        349

-------
       Measurements of nitrous acid inside two research houses. Environ Sci Technol 1990,
       24:1521-1527.

 6.     Pitts, J.N. Jr., Biermann, H.W., Tuazon, E.G., Green, M., LOng, W.D., Winer,
       A.M.  1989 Time-resolved identification and measurement of indoor air pollutants by
       spectroscopic techniques: Gaseous nitrous acid, methanol,  formaldehyde and formic
       acid. JAPCA 1989,39(10): 1344-1347.

 7.     Perm, M. and Sjodin, A.  A sodium carbonate denuder for detrmination of nitrous
       acid in the atmosphere.  Atmos. Environ.  23:1517-1530(1985).

 8.     Rasmussen, TR, SK Kjaergaard, OF, Pedersen: Effects among Asthmatic and Healthy
       Subjects of Short Term Exposure to Nitrogen Dioxide in Concentrations Comparable
       to  Indoor Peak-Concentrations. Precedings of the 5th International Conference on
       Indoor Air Quality and Climate, Toronto, July 1990.

 9.     Pitts, J.N. Jr., Wallington,  T.J., Biermann, H.W. and Winer, A.M.  Identification
       and measurement  of nitrous  acid in  an indoor  environment.    Atmospheric
       Environment 19(5): 763-767 (1985)

10.    Brauer, M., Koutrakis,  P., Wolfson, J.M. and Spengler, J.D.  Evaluation of an
       annular denuder system under simulated atmospheric conditions.  Atmos Environ. 23:
       1981-1986 (1989).
EXPT
A 10-12
E 37-39
C 19-21
C 22-24
C 25-27
E 28-30
E 31-33
E 34-36
RH
45
45
30
45
80
30*
45*
80*
ACH
(hr1)
12,3
3.0
0.5
0.5
0.5
0.5
0.5
0.5
NO2
DECAY
(hr1)
7.86
2.44
0.51
0.55
0.64
1.18
1.13
1.18
HONO
DECAY
(hr1)
3.51
NA
0.20
0.17
0.15
NA(-O)
NA(»0)
0.13
NO,
DECAY
/ACH
0.64
0.81
1.02
1.10
1.28
2.36
2.26
2.36
HONO
DECAY
/ACH
0.44
NA
0.40
0.34
0.30
NA
NA
0.26
HONO
PRODUCTION
(cm3 molec'1 s"1)
5.1 x iaB
7.5 x 10'23
3.9 x iaa
6.0 x Iff23
9.7 x IQr*
5.7 x 10*
3.5 x 10"33
4.2 x 10-°
 *Wool carpet present in chamber.
Table 1.  Decay and production rates.  Decay rates were determined by measuring the concentrations in the
chamber for at least one hour following the cessation of NO2 injection. HONO production rates were estimated
from experimental data assuming first-order dependence on both NCI, and HjO, and a deposition velocity of
3.6 X 10^ m g'1.
                                         350

-------
                  Effect of subjects
      HONO (ppb)
HONO/NO2
     12 ACH • Subject!                0.9 ACM • 8ut)J*ot«
                    Experimental Condition
  22 C, 40% RH

Figure la.
               Effect  of relative  humidity
     70
        MONO (ppb)
  HONO/N02
           30 %
    80%
                        Relative humidity
   2J C, 0.6 ACH

 Figure Ib.
                            351

-------
              Effect of  residence  time
   25
      MONO (ppb)
                                           % HONO/N02
   20
   16-
        M MONO (ppb)
        EZ3 % HONO/N02
   10-
  22 C. 46 % RH

Figure Ic.
                   Residence time (minutes)
                                               120
                 Effect of  wool carpet
       MONO (ppb)
                        % HONO/NO2
     30% RH • C«rp«t -

   22 C. 0.6 ACH

 Figure Id.
  46% RH • C»rp«t -       60% RH • C«rp»t -
Experimental Condition
                           352

-------
              Session 9
 Lake Michigan Urban Air Toxics Study
Gary Evans and Gerald Keeler, Chairmen

-------
         LAKE MICHIGAN URBAN AIR TOXICS STUDY
                              Design and Overview


                    Gary F. Evans, Alan J. Hoffman, and Dale A. Pahl
               Atmospheric Research & Exposure Assessment Laboratory
                     Research Triangle Park, North Carolina  27711

ABSTRACT
      During the summer of 1991, an air toxics monitoring program was conducted in the lower Lake
Michigan area. This study was designed to take advantage of the extensive meteorplpgical and oxidant
database being generated concurrently by the Lake Michigan Ozone Study (LMOS).  Integrated 12-hour
atmospheric samples were collected daily from July 8 through August 9,1991 at three ground sites (two
collocated with LMOS stations). Over 1,200 samples were analyzed to determine atmospheric levels
of PCBs, pesticides, PAHs, VOCs, particle mass, and trace elements (including mercury).  In addition,
a research vessel and a small aircraft were employed on selected days to measure micro-meteorological
parameters, pollutant concentrations and some fluxes at offshore locations near Chicago.  The major
goals of this pilot study were to evaluate methods of sample collection and analysis,  quantify the
atmospheric concentrations of toxic substances in the lower Lake Michigan area, compare measurements
made  over land and over water,  attempt  to  differentiate the Chicago urban plume from regional
background, identify categories of sources for the target pollutants, and estimate deposition to the lake.

DISCLAIMER
      This paper has been reviewed in accordance with the U.S. Environmental Protection Agency's
peer and administrative review policies and approved for presentation and publication. Mention of trade
names or commercial products does not constitute  endorsement or recommendation for use.

BACKGROUND
      The presence of persistent toxic substances within the Great Lakes Basin has been a matter of
interest in both the United States and Canada for many years.   Of particular  concern are those
contaminants which tend to bioaccumulate in the food chain. These include several of the pesticides,
polychlorinated biphenyls (PCBs),  and some trace elements (especially mercury).  Advisories have
frequently been issued by local health authorities, warning  against overconsumption of fish taken from
the  lakes.  In  recent  years,  much effort  has been directed  toward reducing or eliminating direct
discharges of contaminants to the lakes and  tributaries.  In addition to these obvious sources, however,
some studies have suggested  that atmospheric transport and deposition processes  may account for a
significant portion of the overall loadings of toxic substances to the lakes. Section 112(m) of the 1990
Clean  Air Act (CAA) amendments  specifically requires a program to identify and assess the extent of
atmospheric deposition of hazardous air pollutants to the Great Lakes,  as well as to other large lakes
and coastal waters.
      In response to the 1990 CAA amendments and the 1987 International Water Quality Agreement
between the United States and Canada, a long-term monitoring program is being jointly implemented
by the two countries to assess the relative contribution from atmospheric processes to water quality
degradation in  the Great  Lakes.   This program,  known  as the Integrated Atmospheric Deposition
Network (IADN), currently is measuring concentrations of selected toxic substances in ambient air and
                                          355

-------
precipitation at one shoreline location for each of the five lakes.  Four or five monitoring sites per late
are planned for the network.  The IADN siting criteria requires all monitoring sites to be located in
remote areas along the shorelines, well removed from local air pollutant emission sources.  A k»y
objective of the IADN program is to detect trends in atmospheric loadings to the lakes; thus, the
program focuses on the contributions from regional air masses entering the Great Lakes Basin.

INTRODUCTION
       In addition to IADN, the U.S. Environmental Protection Agency (EPA) is planning to conduct
a shorter, intensive study of Lake Michigan during the next few years.   The Lake Michigan Mass
Balance Study will employ both monitoring and modeling techniques to provide greater understanding
of the sources, transport, and fate of toxic substances entering the lake.   For a period of one year,
measurements will be made of target contaminant concentrations in (and exchange between) lake water,
tributaries, sediments, and the atmosphere.  The resulting data will be used to develop whole-lake
mathematical models for  predicting the response of Lake Michigan and its  fish to proposed regulatory
actions.  This project will require information on the impact of local air emission sources, as well as
the contribution from regional air masses.  The maximum local source density near Lake Michigan
occurs along its southwestern shoreline which is dominated by the greater Chicago, Illinois and Gary,
Indiana urban areas.  With a population of over eight million, this is the third largest metropolitan area
in the country. In addition to the usual urban air pollution sources, emissions occur from point sources
such as iron and  steel manufacturing in  Gary, petroleum refining in southwest Chicago, and other
industrial and  municipal activities within the metropolitan area.
       A persistent, regional air quality problem has long been expeienced in the lower Lake Michigan
area with high summertime ozone levels.  Multi-day ozone episodes frequently develop in the region
when the predominant wind direction is from the south to southwest, temperatures are relatively high,
and relative humidity is low.  During such episodic periods, the National Ambient Air Quality Standard
(NAAQS) for ozone is often exceeded at routine monitoring sites near the lake shore in all four states
bordering Lake  Michigan (i.e.,  Illinois, Indiana, Michigan,  and Wisconsin).   Typically, ozone
concentration decreases rapidly with increasing distance from the lakeshore.  Following several yean
of unsuccessful attempts to address the summer ozone problem around the lake through individual State
Implementation Plans, the four states involved decided to join forces to develop a regional response.
A program was undertaken, with assistance from EPA, to take intensive air quality and meteorological
measurements during the summer of 1991.   The resulting database will  provide the basis for a
photochemical reactive grid model of the lower Lake Michigan area.  Once it has been fully validated
and calibrated, the model will be used to assess alternative regional ozone  control strategies.
    The field measurement portion of the program, known as the Lake Michigan Ozone Study (LMOS),
was conducted over the period from June 17 through  August 9, 1991. In addition to ground-based
continuous measurements, on ten selected days measurements were made of ozone, ozone precursors,
and meteorological parameters aboard several vessels operating on the lake and aircraft flying transects
through the study domain.  Upper air soundings were also collected with balloon  systems on the
intensive days. In April 1991, at the request of EPA's Region 5, a decision  was made by EPA's
Atmospheric Research and Environmental Assessment Laboratory at Research Triangle Park, North
Carolina (AREAL/RTP) to take advantage of the extensive LMOS database by conducting a concurrent
air toxics monitoring study in the lower Lake Michigan area.   This project was designated the Lake
Michigan Urban Air Toxics Study (LMUATS) and was designed to serve as a pilot for the atmospheric
measurements portion of the Lake Michigan Mass Balance Study, scheduled to begin in the spring of
1993. LMUATS participants included AREAL/RTP, NOAA's Atmospheric Turbulence and Diffusion
Division (ATDD), the University of Michigan, Illinois Institute of Technology, Massachusetts Institute
of Technology,   ManTech  Environmental,  Battelle,  Southwest  Research Institute,  and  Sunset
Laboratories.
                                             356

-------
OBJECTIVES
      The major goals established for the LMUATS were to quantify the concentrations of selected
air toxic species in the lower Lake Michigan area, identify the source categories responsible for these
contaminants, attempt to differentiate the contribution of the  Chicago/Gary urban plume  from  the
regional air masses, compare measurements made over land with those made over water, estimate  the
rates of dry deposition to the lower lake area during the study period, and evaluate methods for  the
sampling and analysis of toxic substances in ambient air.  This latter goal was of particular importance
for measuring mercury in the vapor phase, as the AREAL/RTP has very limited experience in making
such measurements.

STUDY DESIGN
      Three land-based sites were selected for monitoring air toxic concentrations in the lower Lake
Michigan Basin.  The LMUATS sampling site locations are shown in Figure 1. Southwesterly winds
are normally predominant during the summer months in the upper Midwest. The sites were located to
characterize air toxic concentrations upwind, within, and downwind of the Chicago/Gary urban area.
Two sites (Kankakee, IL and South Haven, MI) were collocated with the LMOS program to maximize
the usefulness of the information collected.  Most  of the sampling equipment, set-up, and operator
training for the LMUATS was provided by AREAL/RTP. Through a cooperative agreement with EPA,
the University of Michigan managed the field sampling program, provided a research vessel (the R/V
Lauremian) for making measurements over the lake on selected days, and performed the sampling and
analytical work for vapor-phase mercury determination.
      The Kanlcakee site was on the property of a small, private airport located just south of Kankakee
and about 60 miles south-southwest of downtown Chicago.  The surrounding area is agricultural, with
com being the predominant crop. The site near South Haven, MI was located in an open pasture on
a farm about three miles inland from the lakeshore and 90 miles northeast of downtown Chicago. The
surrounding area is rural,  with fruit orchards being the major agricultural activity.  The site was
operated by graduate students from the University of Michigan and was used as a central staging area
for the field study. Duplicates of all sampling equipment were operated at this site to provide overall
method precision data.  The downtown Chicago site was located on the campus of the Illinois Institute
of Technology (TIT) and was operated by HT graduate students, who also performed collocated size
distribution and dry deposition measurements.
      Daily samples were collected at each ground site from July 8 through August 9,1991.  The R/V
Laurentian was in operation on July 11 and 12 along the eastern shore near Grand Haven, and from July
23-27 and August 5-8, 1991 at a position approximately six miles  offshore from the Chicago/Gary
waterfront. Samples were integrated over a 12-hour period, beginning at 8:00 a.m. CDT. Table 1
summarizes the classes of pollutants measured, the  sampling and analytical techniques employed, the
laboratories involved, the number of individual species and samples that were quantified.  Because of
the  relatively high  costs  for mass spectrbmetrical  analysis of semi-volatile  organic compounds
(pesticides, PCBs and PAHs),  it was decided in advance to analyze only a subset of samples collected
for  these compounds.  The PS-1 samples collected each day were  shipped in cold packs  to  the
appropriate laboratory. Filters and traps were combined,  desorbed, and placed in cold storage. A
decision regarding which samples to analyze was made after an examination of the particulate, trace
element, and meteorological data.
      Trace element data were obtained for both fine C£ 2.5 n) and coarse (2.5-10 p) particles using
a non-destructive X-ray fluorescence (XRF) technique.  A  subset of filters was then sent to  the
Massachusetts Institute of Technology Nuclear Reactor Lab for neutron activation analysis (NAA) to
obtain information on mercury and other elements at very low particulate concentrations. Additionally,
some filters will be examined  by  scanning electron  microscopy to obtain element-specific size
distributions for estimating dry deposition rates.  Fine particle samples were analyzed by Sunset Labs
                                            357

-------
 using combustion flame ionization detection (FID) to measure total elemental and volatilizable carbon
 content, useful for source apportionment.  Samples for gaseous  mercury were collected at all sites
 except Kankakee via amalgamation on gold-coated sand, following a pre-fired glass fiber filter. These
 samples, along  with some filter  extracts, were  analyzed for mercury content at  the University of
 Michigan using cold-vapor atomic  fluorescence  (CVAF).  Annular denuder  samplers (ADS) were
 operated for acid and basic aerosol  measurements at the South Haven site and aboard the R/V
 Laurentian.
       Micro-meteorological  measurements were made aboard the research vessel to determine the
 vertical structure of the atmosphere in the layer  just above the lake surface.  Flux information was
 considered useful for making inferences about likely deposition rates of toxic  substances to the lake.
 Rapid-response instruments were mounted off the  vessel's bow to measure wind direction, wind speed,
 temperature, water  vapor,   carbon  dioxide,  and  ozone.    These measurements  were  taken  at
 logarithmically spaced elevations between two and seven meters above the lake surface.  In addition,
 on five days (July 21-25,1991) identical and coordinated measurements were made aloft aboard a small
 aircraft flown at low elevations by NOAA's Atmospheric Turbulence and Diffusion Division.  This
 information will be used, in conjunction with the LMOS database, to estimate dry deposition rates.

 PRELIMINARY RESULTS
       The papers that follow present preliminary results for various classes of pollutants measured in
 the study. As an introduction to the database, PM10 concentrations  for three LMUATS ground sites are
 plotted by site and sample date in  Figure 2. Paniculate levels are  highly correlated  for all three sites,
 indicating that most of the ambient paniculate loadings are  regional in nature.  The concentrations
 observed at the rural South Haven, MI site tended to be the lowest of the three locations.  Also shown
 in the figure are the predominant daytime wind directions (WD).  During the first week of the study,
 winds were from northerly and easterly directions and PM10 levels were relatively low at all sites.
 Beginning on July 15, wind direction switched first to the south and then to the southwest and remained
 from there for the  rest  of the week.  Paniculate concentrations  rose well above  the PM ]0 annual
 NAAQS level of 50 ngfm\ exceeding 80 /zg/m* at the ITT and Kankakee sites.  Concurrently, a major
 ozone episode developed in the area on July 16 and lasted through July 20.  The NAAQS for ozone was
 exceeded along both shorelines of Lake Michigan, with the highest concentrations occurring on July 18
 and 19 along the eastern shore. The LMOS program operated in its intensive mode during this period,
 collecting additional measurements from boats, aircraft and balloons.  On July 23, the prevailing wind
 direction became northwesterly and PM10 concentrations decreased dramatically. With winds from the
 north, the Kankakee site became the downwind site and the maximum concentrations were observed
 there.   On  August  1, winds once more became southwesterly for a two-day period, and PMu
 concentrations for August 2 again approached 80  jtg/m* at the HT and Kankakee monitoring sites.
       As previously noted, duplicate sampling instruments were operated at the  South Haven base site.
 Results for PM,0 concentrations (fine + coarse mass) from the pair of dichotomous samplers operated
 at the site are shown in Figure 3 as a linear regression of one sampler's results on the other.  The slope
 of the regression is near  1.00, the intercept is close to zero, and the r-square value is 88 percent. This
 indicates very good agreement between  the two instruments.   In addition to collecting duplicate
 measurements, a field audit was conducted at each ground site during the second week of the study.
 Most instruments were found to be operating properly, and recalibrations were performed as necessary.
 For  each of the pollutant classes  included in  the study, field blanks and  audit  materials wen
 incorporated into the analysis  scheme,  as appropriate.
      In the papers that follow, results obtained by the various analytical laboratories participating in
the LMUATS are presented and discussed. Once validated and made available, the LMOS database will
be combined with the LMUATS results.  A final project report, including detailed  analyses of the
combined meteorological and pollutant databases, should be completed and published by December 1992.
                                            358

-------
                                                 Muskegon
                  Milwaukee
                   II
                                                            IN
                                            LEGEND
                                            SOUTH HAVEN (FARM)
                                            If! (FARR DORM)
                                            R/V LAURENTIAN
                                            KANKAKEE (AIRPORT!
           Figure  1.   Ixication  of  IJ1UATS  sampling  sites.
           POLLUTANT CLAM    «»>»SJ«I    AMM.VM  IA»OUTO*V  HO. l»lt» MO t*MPtn
         OC/HRMS    lwf«

         OC/MMI    >wf«

W1/XAO    OC/M9    ton***

 C«nwl«'    OC/MSD    ••»•••
10

to

It

44
Tout pcai

PAH*

VOCl

Tr«c« Etomwit*     Otetal    XRF/NAA  MTl/MT     i«/u

Carbon »/w        FPS        RD   tun*.! Lib*    t

Oat*ou* Hg     OFF/A* Mnd   CVAf      UN        1

PvHcutot* Hg      OFF       CVAF      UM        1

Ottw htorgtnfct     ADt        1C       UM        •
                                                                TO

                                                                TO

                                                                75

                                                                1tO

                                                              3OO/1M

                                                                1M

                                                                170

                                                                10

                                                                Tt
Table I.   Pollutant  measurements  made during  the  LMUATS
                                    359

-------
     Date  7/B  10  12  i4  16  i»  20  22 24 aa ai jo «/i  j   5  7  •

      WO   N  E6EN  SSWSWSWNWNSESSWNNESEN


 Figure  2.   PM-10  concentrations  observed during the  LMUATS.
          70
          H
          H


          H

          10
            X^
                 10
                       to     10     «o     to
                         OICHOT SAMPLER # 57
                                              •o
Figure  3.   Duplicate PM-10  results  from South  Haven, MI.
                               360

-------
                  SUMMER 1991  FIELD  MEASUREMENTS

                  THE LAKE MICHIGAN OZONE STUDY
                         Norman E. Bowne
                      Senior Program Manager

                 ENSR Consulting and Engineering
                     95  Glastonbury Boulevard
                      Glastonbury, CT   06033
                             ABSTRACT

Measurements of air quality and meteorology were made in the Lake
Michigan area during the summer of 1991.  These data will be used
to for evaluation  of  models that calculate ozone concentrations.
The  ultimate use  of  the  models will  be  to evaluate  control
strategies  to  achieve  compliance with  the  ambient  air  quality
standard for ozone. Routine air quality observations were obtained
hourly from the existing state  networks in WI, IL,  IN and MI and
from an additional 20 monitors installed for the project.  Special
measurements were made from boats and aircraft.  In addition the U.
S.  Environmental  Protection  Agency  conducted  special  toxics
measurements at two  sites  in Illinois, one in Michigan and on a
boat in Lake Michigan  during the period to take advantage of the
LMOS routine measurements.   The observation  network is described
and  preliminary  results  for an  ozone  episode  when the  toxics
observations were obtained is discussed.
                               361

-------
                  SUMMER 1991  FIELD MEASUREMENTS

                  THE LAKE MICHIGAN OZONE STUDY



                           INTRODUCTION

The Lake Michigan area experiences numerous events when the ozone
concentration exceeds the National Ambient  Air Quality Standard.
Control strategies used  to date have been unsuccessful in achieving
the  desired  reductions  in  ozone  levels  in  this  region  and
nationally.  The  number of  exceedances observed  in 1988  was the
highest in ten years.  A number of reasons have been cited for the
continued  non-attainment problem,  including  ineffective  rules,
insufficient enforcement programs, overly optimistic forecasts of
emission  reductions,  inadequate  data bases  and  inaccurate  air
quality models.  A study was developed to address the questions of
whether the modeled source/receptor relationships fail because of
the inadequacy or unrepresentativeness of model formulations, yet
unknown    limitations    in    chemical   mechanisms,    emissions
uncertainties, or adverse meteorological conditions.

The states of Illinois,  Indiana, Michigan and Wisconsin joined the
U. S.  Environmental Protection  Agency to  develop a  program of
measurement, air quality model development  and evaluation of the
model to  calculate ozone concentrations.    A major step in that
program was the 1991 Summer  Field Measurements  Program.   The 1991
measurement period was  from June 10 to August 9, 1991.

The U.  S.  Environmental  Protection Agency Human Exposure and Field
Research Division planned a  similar toxics measurement program for
the area at the same time and it was decided to take advantage of
the intensive measurements being carried out by the Lake Michigan
Ozone Study  (LMOS)  group to  enhance  the toxics program.   Other
papers in this  session will address those measurements.  This paper
describes the setting for the ozone study and the observations of
routine meteorology and air quality that are available.


GOALS AND OBJECTIVES.    The broad goals and  objectives  of the Lake
Michigan  Ozone  Study  (LMOS)  were to  develop  the  best available
understanding of elevated ozone concentrations in the Lake Michigan
area through the use of measured  data and  photochemical modeling
techniques.    The  end  product  of  the  study  is to  provide  a
technically credible photochemical reactive  grid model that can be
used to assess strategies and support revised implementation plans.
The objective of the 1991 Summer Field Measurements Program was to
provide measurements for model development  and evaluation.
                               362

-------
                  OVERVIEW OF THE FIELD PROGRAM

The 1991 Field Program consisted of  1)  a region-wide air quality
and meteorological  monitoring effort  with two-dimensional  data
plane monitoring corridors, 2) ozone and precursor flux planes near
the Chicago metropolitan,  industrial  complex and  across  Lake
Michigan, 3) documentation of  the boundary conditions of the study
area,   4)   operation  of  enhanced  States'  existing  air  quality
monitoring networks,  and  5)  operation of enhanced meteorological
measurements at the surface and at  levels aloft.  The measurements
and how they fit these tasks are described below.

The sampling period  was June 17 to  August 9,  1991.   The toxics
program was operated during  July.    Routine measurements  from
continuous meteorological and air  quality  monitors were recorded
as hourly averages for the period  from the end of  May  to the end
of August.   Intensive measurements were planned for twelve  days
when weather conditions were expected to be  conducive to high ozone
concentrations.  The  intensive measurements consisted  of placing
three  boats on  the  lake with  air quality  and  meteorological
instruments, flying five  airplanes for  air quality measurements,
operating  upper  air  sounding  balloon  systems   and  acquiring
hydrocarbon samples.   We had intensive measurements on seven days,
three during July.

The study domain and surface measurement sites are illustrated in
Figure  l.   These air   quality  and  meteorological  monitoring
locations  were designed  to  document the  region  wide  ozone and
precursor distribution.   The  primary wind  directions  of interest
are southerly  to westerly.   This map shows the ozone  monitoring
sites.  Most, but not  all, had surface meteorological measurements
associated with them.  Note that three boats were used on the lake
to supplement the land based stations to give us a better idea of
what was happening over this rather large area  in the middle of our
domain of interest.

We measured oxides of nitrogen at the sites illustrated in Figure
2.   The  "X"  markers  indicate  sites  that  had  special  toxics
measurements associated with LMOS instruments.

Figure 3 shows  the locations of the measurements for hydrocarbons.
We measured both  volatile organic compounds  and  carbonyl.  Two-hour
integrated samples were collected  in canisters and on  cartridges
four times during the day at these sites on designated days.  Sites
located in major source areas, Chicago,  Gary  and  Milwaukee,  were
only sampled twice daily.  The arrangement of samplers was designed
to provide us with background information, speciation in the source
areas  and speciation in our expected receptor areas.
                               363

-------
The existing upper air measurement network operated by the National
Weather Service was augmented  with  seven added sounding systems,
three  on  the boats and  four on shore  near the  lake.   Vertical
profiles  of winds  and temperature  were obtained in  much more
spatial and temporal detail than before.  Seven radar profilers and
one doppler acoustic  wind profiler  were deployed near the flux
planes.  The profilers  operated continuously, the sounding systems
on intensive measurement days.

Aircraft  measured air  quality  aloft  along several  flight paths in
an attempt  to define the upwind  boundary condition and the areal
and temporal  distributions of aerometric  data within  the study
domain.  An experimental DIAL  airborne laser system was employed
to nap the  regional distribution and along-path vertical profile
of ozone on a few days.
                             RESULTS

A major ozone  episode occurred from Tuesday July  16 to Saturday
July  20.    Winds  were from  the south  on  Tuesday, but  became
southwesterly on Wednesday  and remained  from the southwest until
Saturday.    Speeds  were 10  to  15  miles per hour.   Highest ozone
concentrations  on  Tuesday  were  near 120 ppb  at the  Illinois -
Wisconsin state  line,  near  Manistee, MI and in  Door County, WI.
High concentrations on Wednesday were near 130 ppb at  Benton Harbor
and south Haven, MI.  Concentrations exceeded 150 ppb in Michigan
on Thursday, but were generally below 100 ppb on the west side of
the lake,  see Figure 4.  The measurements by the boats and aircraft
ended on Thursday.  High  concentrations  of ozone continued to be
observed in  Michigan  on  Friday with peaks  over 150 ppb between
Hears and  Frankfort.  Saturday was the last day of the episode with
peak concentrations just over 130 ppb in Wisconsin and near 100 ppb
in Michigan.

Aircraft  sampling  showed  that  ozone  was  well  mixed  aloft.
Concentrations of  N)~ were  too small to  judge  distribution with
height.   Concentration distributions  frequently  showed  little
difference in the vertical from the  ground to the top of the mixed
layer during the program because  conditions conducive  to ozone
formation are  convective.   Toxic measurements on  days  with high
ozone concentrations should be well mixed in the atmosphere also.

The data  acquired  by the  states  from their routine  monitoring
networks in  the LMOS  program  are  in  the AIRS  data base.   The
special measurements  are  being reviewed for consistency at this
time.   These data will be released to the LMOS modelers in June and
all data will  be made available to  the  scientific community not
later than next March.  Requests for data should be directed to the
Lake Michigan Air Directors Consortium in Des Plaines, IL.
                               364

-------
LAKE MICHIGAN OZONE STUDY
LAKE MICHIGAN OZONE STUDY

-------
f
                                                     IM MICHIGAN OZONE SHJOY
                                                           ttodnun fame CoKtflMom
G
                                                                                                            fl
       U\KE MICHIGAN OZONE STUDY
             Uonmun ttsmc Conctntroiim
                                                                                                                                I
                                                                                                                I	I

-------
    ATMOSPHERIC  MERCURY MEASUREMENTS:
                   RECENT OBSERVATIONS
                IN THE GREAT LAKES BASIN
                Marion Hoyer, Carl Lamborg, Gerald Keeler
                           Air Quality Laboratory
                         The University of Michigan
                      Ann Arbor, Michigan 48109-2029

                              Alan Hoffman
                             USEPA-AREAL
                 Research Triangle Park, North Carolina 27711
ABSTRACT

      In order to characterize ambient levels of vapor phase and particle mercury at
source and receptor locations in the Great Lakes Basin, and to diagnose source regions of
atmospheric mercury, samples were collected at  three locations: Illinois Institute of
Technology  (IIT) in Chicago, IL and South Haven, MI (SHA) and aboard  the R/V
Laurentian (LAU).  Vapor phase  mercury samples were collected onto gold coated sand
traps and analyzed by cold vapor atomic fluorescence (CVAFS).  Paniculate phase
mercury samples were collected onto both Teflon filters and pre-fired glass fiber filters.
Teflon filters were analyzed by neutron activation analysis (NAA) and glass fiber filters
were analyzed by CVAFS after acid digestion/extraction.  Results of particle phase
analysis from glass fiber filter samples and results of vapor phase  mercury samples are
presented here.

      Mean vapor phase mercury concentrations were 8.7 ng/m3 at IIT, 2.3 ng/m3 on
the LAU and 2.0 ng/m3 in SHA.  Mean particle phase mercury concentrations by site
were 97.5 pg/m3 at IIT, 28.4 pg/m3 on the LAU and 18.6 pg/m3  in SHA.  Particulate
phase mercury comprised 1.7% (IIT), 1.3% (LAU) and 1.2% (SHA) of total mercury
measured on the average.
INTRODUCTION

      Currently atmospheric mercury deposition to surface waters is a topic of intense
interest due to the high incidence of mercury contamination of fish in the Great Lakes
Basin.  To the extent that these fish are found in remote lakes where direct discharges
can be ruled out, the atmosphere must necessarily present a significant pathway for this
                                  367

-------
toxic metal (Nriagu,  1990; Johansson et al., 1988; Glass et al.,  1990; Barrie et al,
1987).  While the concentration of mercury in the atmosphere in  remote locations is
typically quite low (ppt), mercury can bioaccumulate in animal tissue, such that, even in
the  presence  of extremely  low concentrations of mercury  in  the  water  column,
concentrations of mercury in  fish tissue can reach levels that pose a significant human
and wildlife health risk.  In Michigan alone 40 of the 107 lakes studied by the Michigan
Department of Natural Resources from 1987-1990 were found to contain at least one fish
with levels of mercury greater than the public health fish consumption advisory level of
0.5 mg Hg/Kg (MDNR,  1991).

       To investigate the sources and transport of mercury in  the  Great Lakes Basin,
vapor and paniculate phase samples were collected during the Lake Michigan Urban Air
Toxics Study (LMUATS), a cooperative project between the USEPA and The University
of Michigan Air Quality Laboratory.  Sampling sites utilized for the one month study
included  a site at the Illinois Institute of Technology (IFF) in Chicago,  IL, aboard  the
Research Vessel Laurentian (LAU), and a farm near South Haven,  MI (SHA).  Vapor
and paniculate mercury measurements were taken as part of the LMUATS in order to: 1)
provide accurate mercury measurements for the Great Lakes Region using state-of-the art
clean sampling and analysis techniques; 2) to investigate spatial  and  temporal variations
in vapor and  paniculate mercury;  3)  to investigate the deposition  and transport  of
mercury; and 4) to begin to investigate the potential sources and source regions for  the
observed mercury.
Sample Analysis

       Ultra-clean techniques were used in all phases of the mercury  sampling and
analysis.  Filter packs and sample storage containers were prepared using a two-week
acid-cleaning procedure, the  last step of which  must be completed in an ultra-clean
room.  Sample analysis was also carried out in the class 100 clean room.

       Vapor phase mercury was collected onto gold-coated sand traps at a flow rate of
0.3 1pm.   Elemental mercury  levels were  determined  using  the  dual  amalgamation
technique described by  Bloom and Fitzgerald  (1988) followed by cold  vapor atomic
fluorescence spectroscopy.

       Vapor phase samples at SHA were collected for  a duration of  12 hours (8am-
8pm, CDT).  At HT 12 hour daytime vapor phase samples were collected when the R/V
Laurentian was in port and two six hour daytime (8am-2pm, 2pm-8pm) and one 12-hour
night time sample was collected when the R/V Laurentian was at station.   Vapor phase
samples on the R/V Laurentian  (LAU)  were also collected  for two six-hour periods
during the day (8am-2pm and 2pm-8pm) and for 12-hours during the night. Two traps
in series were run at various times throughout the study with no discernible breakthrough
observed.
                                      368

-------
       Paniculate phase mercury was collected onto 47 mm glass fiber filters (Gelman,
Type A/E) which were fired  at 500°C for one hour  to drive off mercury before
sampling. Twenty-four hour paniculate samples were collected using acid-cleaned open-
faced Teflon filter packs at a nominal flow rate of 301pm.  Exposed Miters were placed
in 25 ml acid-cleaned Teflon vials which were capped tightly, sealed with Teflon  tape,
triple-bagged  in polyethylene and frozen until analysis.   Field blanks were routinely
taken at each site during the study to ensure that contamination was not occurring. Field
blanks were prepared, placed in the samplers, stored, and analyzed exactly the same way
as the actual samples.

       Paniculate mercury  was extracted from  the glass fiber filter samples using a
nitric/sulfuric acid solution followed by 30 minutes of sonication, one hour oxidation in
bromine monochloride and  finally, reduction with stannous chloride and liberation of
mercury from solution by  bubbling with a mercury-free stream  of nitrogen.  The
liberated mercury was  captured on a gold-coated sand  trap which was analyzed  by
CVAFS. The detection limit for total mercury concentrations as presently performed in
the UMAQL is about 9 pg/m3.  All paniculate samples were analyzed in duplicate with a
precision of better than  15%. It should be noted that the data given in this paper are not
corrected to STP.
RESULTS

       Vapor-phase mercury measurements

       Vapor phase mercury concentrations measured at ITT during the period July 10-
August 9, 1991 ranged from 1.8 - 62.7, with an average of 8.7 ng/m3 (Table 1).  On the
R/V Laurentian,  25 vapor phase mercury samples were collected during three separate
cruises. The average vapor phase mercury concentration measured on the LAU was 2.3
ng/m3.  Of  the 38 samples collected in South Haven resulted in a mean vapor phase
mercury concentration was 2.0 ng/m3.  Duplicate samples taken at South Haven agreed
quite well with a better than  15% variability with concentrations near 1 ng/m3.

       Table I. Vapor phase mercury measurements in Chicago (IIT), on the
            R/V Laurentian (LAU) and in South Haven (SHA) in ng/m3.

          SITE     N   MEDIAN   MEAN   STDDEV  MEV   MAX
IIT
LAU*
SHA
58
25
38
4.5
2.2
1.8
8.7
2.3
2.0
12.0
0.7
0.6
1.8
1.3
1.8
62.7
4.9
4.3
        'Sampling Dales:  7/11-7/12,  7/25-7/27, 8/5-8/8
                                   369

-------
       Diurnal Variations in Vapor Phase Mercury

       At IIT 18 samples were collected between 8am-2pm (designated as AM), 17
samples were collected between 2pm-8pm (PM),  11  daytime  12 hour samples were
collected between 8am-8pm (DAY) and  12 night time samples  from  Spin-Sam were
collected (NIGHT) in order to investigate potential diurnal behavior of vapor phase
mercury.  The average concentration (ng/m3) for AM samples was 3.3 times larger than
the NIGHT samples and the average concentration for PM samples was 2.1  times larger
than NIGHT samples.  The average vapor phase mercury concentration for AM and PM
samples was  10.1 while the average vapor phase concentration for DAY samples was
9.9.

       Particulate mercury measurements

       Total paniculate mercury was measured at the  three sites  for periods when the
R/V Laurentian was at station.  At IIT 16 samples were collected and the concentrations
varied  from 22.0-518.0 pg/m3 (Table 2).  The average concentration of particle phase
mercury at IIT was 97.5 pg/m3. On the R/V Laurentian 9 samples  were collected giving
an average paniculate phase mercury concentration of 28.4 pg/m3, with  a range of 9.0-
54.0 pg/m3.  In  SHA 18  glass fiber filters were collected and the average particulate
phase mercury concentration was 18.6 pg/m3 with a range of 9.0-29.0 pg/m3.

       Particle phase  mercury represented 1.7% of the total atmospheric Hg measured
(elemental vapor  phase +  particulate mercury) at DT,  1.2% at SHA and 1.3% on the
LAU.  The range in  vapor phase mercury was largest at IIT where the percentage of
mercury found in the particle phase varied from 0.07% to 7.3%.  Particle phase mercury
at SHA and  LAU varied from  0.6-1.9%  and 0.6-2.3%  of  vapor phase mercury,
respectively.
      Table D.  Particle phase mercury measurements in Chicago (IIT), on the
                R/V Laurentian (LAU) and in South Haven (SHA) in pg/m3.
SITE N MEDIAN MEAN
IIT 16 60.0 97.5
LAU* 9 24.0 28.4
SHA 18 18.5 18.6
STD DEV RON MAX
118.1 22.0 518.0
16.7 9.0 54.0
5.7 9.0 29.0
      •Sampling Dates:  7/23-7/27, 8/5-8/7
                                    370

-------
CONCLUSIONS

       The vapor and paniculate mercury concentrations measured during the one month
study decreased from Chicago to downwind sites on the R/V Laurentian and in South
Haven MI.  Diurnal variation in vapor phase mercury observed at ITT  indicated that
samples collected between 8am-2pm may be influenced by local sources  impacting the
sampling site during typical daytime flow patterns,  while predominant nighttime  wind
patterns (from Lake Michigan) may not result in local point source impacts at ITT.

       Vapor phase concentrations measured in SHA were similar to those measured in
other rural and remote locations in the Great Lakes Basin (Fitzgerald, 1990).  Vapor
phase mercury levels measured in South Haven did not demonstrate episodic behavior
with flow from  the southwest urban source region as did other pollutants measured.
However, fine fraction  (< 2.S urn) paniculate Hg concentrations as determined by NAA
did reveal a peak during the main episode with SW  transport.  While ambient mercury
levels at SHA were uniformly low,  these low  concentrations are present in  remote
environments where the atmosphere is implicated as a dominant source of mercury to
waterbodies.

       Paniculate mercury  concentrations varied widely at ITT, possibly due to  local
source influence.  However the processes that control formation of paniculate mercury
are not well understood.   Volatilization  of mercury from  the particle  phase during
sampling probably  represents a small loss of paniculate mercury during the 12-24 hour
duration samples at the flow rates used in this study.

       Fine fraction and total  suspended paniculate samples collected onto Teflon filters
will be analyzed and results will be compared to those for glass  fiber filter digestion
collected simultaneously.

      This data will be merged with measurements  taken for organic and elemental
carbon, volatile  organic carbon, polyaromatic  hydrocarbons, fine and  coarse  trace
elements and acidic aerosol  and gaseous species.  Receptor modeling techniques will be
applied  to  the combined data sets  to determine sources and  source strengths of the
observed atmospheric mercury.

REFERENCES

Barrie, L.A., Lindberg, S.E.,  Chan, W.H., Ross, H.B., Arimoto, R. and Church, T.M.
      (1987).  On the concentration of trace metals in precipitation.   Atmos.  Env.
      21:1133-1135.
Bloom, K, and Fitzgerald,  W.F. (1988)  Determination of volatile mercury species at
      the picogram level  by low-temperature gas  chromatography with cold-vapor
      atomic fluorescence detection. Analvtica Chimica Acta.  208:151*161.
                                     371

-------
Fitzgerald, W.F., Vandal, G.M. and Mason, R.P. (1990)  Mercury in temperate lakes,
       EPRJ - Wisconsin mercury research annual progress report: Air-water exchange
       studies of mercury.
Glass, G.E., Sorensen, J.A., Schmidt, K.W, and  Rapp, G.R.  (1990)  New source
       identification  of mercury contamination  in  the  Great  Lakes.  Environ.  Sci.
       I&hnfil. 24:1059-1069.
Johansson, K., Lindqvist,  O. and Birgitta, T. (1988) Occurrence  and turnover or
       mercury in the environment.  National Swedish Environmental Protection Board
       Report No.4E.
Michigan  Department of Natural  Resources Surface Water Quality Division (1991)
       Michigan fish contaminant monitoring program  1991 Annual Report, Report #
       MI/DNR/SWQ-91/273.
Nriagu, J.O. (1990) Global metal pollution:  poisoning the biosphere? Environment 2:6-
       11,28-33.
                                      372

-------
   THE U.S.  EPA LAKE MICHIGAN URBAN AIR TOXICS
          STUDY: AMBIENT AIR MONITORING AND
           ANALYSIS FOR POLYCYCLIC AROMATIC
                            HYDROCARBONS


                                 Jane C. Chuang
                                  Dave B. Davis
                                Michael Kuhlman
                                     BatteUe
                                 Columbus, Ohio

                                 Gerald J. Keeler
                               University of Michigan
                               Ann Arbor, Michigan

                                 Nancy K. Wilson
                                  Gary F. Evans
                         U.S. EPA, Atmospheric Research and
                           Exposure Assessment Laboratory
                        Research Triangle Park, North Carolina

ABSTRACT
      The U.S. EPA Lake Michigan Urban Air Toxics Study (LMUATS) was conducted at four samp-
ling sites in and around Lake Michigan in July and August 1991. This paper addresses the portion of
the study that dealt  with ambient air monitoring and analysis for polycyclic aromatic hydrocarbons
(PAH). The PS-1 medium volume sampler was equipped with a quartz fiber filter in series with a
XAD-2 cartridge to collect total PAH. Ambient air was sampled over a 12-h period at a nominal flow
rate of 4 cfm.  Parallel sampling was conducted at one site to determine the overall precision of the
sampling and analytical methods used in this study. The corresponding filter and XAD-2 samples were
combined and extracted with dichloromethane (DCM).  The DCM sample extracts were analyzed  by
gas chromatography/mass spectrometry (GC/MS) to determine target PAH. The validation of the samp-
ling and analytical methods for ambient monitoring of PAH, quality control/quality assurance proce-
dures, and ambient PAH concentration profiles from the LMUATS are discussed.

INTRODUCTION
      Section 112(m) of the 1990 Clean Air Act Amendment (CAAA) requires a program  to identify
and assess the extent of atmospheric deposition of hazardous air pollutants to the Great Lakes, as well
as to other large lakes and coastal waters.  It is suggested that a significant portion of the toxic con-
taminants found in the Great Lakes are deposited from the atmosphere. However,  there are insufficient
data, at present, to  estimate reliably the magnitude  and importance of the input to the lakes from
atmospheric deposition of most air toxics.'  In addition, the selection of monitoring sites (e.g., inland
versus shoreline versus open lake siting) is critical to this assessment.  It is also  unknown how much
of the air toxics in the air over the iai»f originates from sources near (within 20 km) the lake shoreline
versus sources farther upwind.  Therefore, studies are needed to determine the dynamics of air toxics
transport over and deposition into the Great Lakes.
                                       373

-------
       As part of the initial phase of the studies, the U.S. EPA Lake Michigan Urban Air Toxics Study
(LMUATS) was conducted in the summer of 1990 to monitor various chemical classes of air toxics in
and around the Lake Michigan area. The four LMUATS sampling sites included three sites on land:
(1) downtown Chicago, at the Illinois Institute of Technology (ITT), representing input from an urban
complex, (2) Kankakee airport, a site upwind of ITT, and (3) South Haven, a site along the eastern side
of Lake Michigan.  The fourth sampling  site was on the research vessel RV Laurentian, representinf
over-the-water input; the Laurentian was used for monitoring air toxics along the western shore of Late
Michigan at least 10 mi  offshore from  Chicago.  The main objective of the LMUATS  was to collect
representative air samples and provide accurate measurements of air toxics at these four sampling sites.
       In the LMUATS, polycyclic aromatic hydrocarbons (PAH) are one of the compound classes of
air toxics monitored at the four sampling sites. Many PAH found in ambient air are potent carcinogen^
mutagens, or both.2"4  We have  conducted several studies  to develop and evaluate  sampling and
analytical methods for both indoor and outdoor monitoring of PAH.5"8 This methodology has been
successfully employed in several small-scale field studies9'11 and was also utilized in the LMUATS.
       In this paper, we summarize the validation of sampling and analytical methods for ambient air
monitoring of PAH, the utilization of quality control/quality assurance  procedures for the LMUATS,
and the ambient PAH concentration profiles from the four sampling sites of the LMUATS.

EXPERIMENTAL SECTION

Sampling Procedures
       The PS-1 samplers (General Metal Works, Cleves, Ohio) were located at each designated
sampling site.  The sampling  module consisted  of a  quartz fiber filter (104 mm QAST, PallfleXi
Putnam, CT) and XAD-2 (Supelco, Bellefonte, PA) trap to collect both particle-bound and vapor-phase
PAH.  The cleaning and preparation procedures for quartz fiber filters and XAD-2 traps are detailed
elsewhere.6  In the breakthrough study, the PS-1' sampler was equipped with  a quartz fiber filter and
two XAD-2 traps in series. The first XAD-2 trap was spiked with 2 /*g of each naphthalene-dj, phen-
anthrene-d,0, pyrene-d10, benz[a]anthracene-d,2, chrysene-di2, benzo[e]pyrene-dI2, and benzo[a]pyrenC'
d,2 prior to sampling.  Then air was sampled for 24 hours at a nominal flow rate of 5 cfm at ColumtoiSi
Ohio.  Two tests were conducted and the average sampling temperatures were 72°F and 94CF.
       In the LMUATS, the clean filters  and XAD-2 traps were prepared at Battelle and sent to each
sampling site.  A standard operation procedure for loading, operating, and unloading of PS-1 sample*1
was prepared for the  field sampling team.   At the beginning of the field sampling, an experienced
Battelle technician went to the South Haven Site and demonstrated the proper sample handling procedure
to minimize any possible field contamination and ensure the integrity of the collected samples.  The
PS-1 sampler equipped with quartz fiber  filter in  series with an XAD-2 cartridge was used to collect
total PAH.  Ambient air was sampled over a  12-hr period at a nominal flow rate of 4 cfm.  The
collected samples were stored in the dark at 0°C  before they  were sent back  to Battelle for analysis-
Sampling data sheets containing necessary sampling information (e.g.,  sample I.D. code) were filled
out by the field operators for each set of filter and XAD-2 samples and were sent back with samples-

Analytical Procedures
       The filter and XAD-2 samples from the breakthrough study were extracted separately. The cor-
responding filter and XAD-2 samples from LMUATS were combined and extracted with dichloro-
methane (DCM). The DCM extract was concentrated by Kuderna-Danish (K-D) evaporation. The con-
centrated DCM extract was analyzed by GC/MS in electron impact (El) mode to determine target PAH.
A Finnigan TSQ-45 GC/MS/MS operated in GC/MS  mode was employed.  Data acquisition and pro-
cessing were controlled by an INCOS 2300 data  system. The MS was operated in the selected ion
monitoring (SIM) mode.  Peaks monitored were the molecular ions and  characteristic fragment ions of
                                            374

-------
the target analytes.  The GC column was a DBS fused silica capillary column (30 m x 0.25 mm;
0.25 urn  film thickness,  Supelco).  The GC temperature was held at 70°C for 2 min,  and then pro-
grammed to 290°C at 8°C/min.  Identification of target analytes was based on correct molecular ions,
correct fragmentation ions, and their GC retention times relative to that of the corresponding internal
standards (phenanthrene-dlo and/or 9-phenylanthracene).  Quantification of target analytes was based
on the comparison of the respective integrated ion current responses of target ions to that of the cor-
responding internal standard,  with average response factors generated from analyses of  standard solu-
tions.'-10

RESULTS AND DISCUSSION
      In the breakthrough study, the recoveries of the seven spiked perdeuterated PAH on the first
XAD-2 trap after 24 hours ambient sampling ranged from 80% for pyrene-d10 to 100% for phen-
anthrene-d|0 from both tests.  We did not find any spiked perdeuterated PAH on the second XAD-2
traps from both tests. Therefore, there is no evidence of breakthrough of the spiked PAH compounds
to the second trap.  This  finding is in agreement with our previous studies5 when only one XAD-2 trap
was used and quantitative recoveries were obtained.  We also measured the native, non-spiked, PAH
in the XAD-2 traps.  The ratios  of the concentrations of native PAH on trap 2 to trap  1 ranged from
<0.01 (pyrene) to 0.05 (phcnanthrenc).  In most cases, the levels of native PAH found in the second
traps were either similar to or even lower than those  found in the field blank.  These results demon-
strated that the detection of  the native PAH in the  second trap is at background levels and is not
associated with sampling or breakthrough.  Based on these results, we do not anticipate any serious
breakthrough problems would occur when the PS-1 sampler with a quartz fiber filter in series with one
XAD-2 trap is used to collect ambient PAH.
      In the LMUATS at the South Haven Site, duplicate PS-1 sampling was carried out for 3 days.
The results of duplicate samples were used to determine the overall precision of sampling and analysis
methods. The measured  total PAH concentrations were in good agreement between the  duplicate sam-
ples.  The mean relative standard deviations ranged from 1.3% for dibenzo[a,h] anthracene to 14% for
fluoranthene.  Field blanks from each sampling site were also prepared and analyzed the same way as
the samples.  The results showed that some 2- to 4-ring PAH and benzofluoranthene were present in
the field blanks. The amounts of PAH found in the field blanks are about two to five times higher than
those in  the laboratory  blanks.  The field  blanks were handled  identically to the actual samples,
including loading and unloading of the PS-1 sampler, except that no air was drawn through the field
blank modules. Therefore, somewhat higher PAH on the field blanks compared to the laboratory blanks
is not surprising.  The amounts of individual PAH found in the field blanks represent  0.3-4% of the
average total amounts of these PAH in the samples from the ITT site.  Because the loadings of PAH in
the samples from the other three sites were lower than that from the HT site, these background levels
were about 2-30% of the average PAH loadings in the samples from these three sites.   Note that the
actual air volumes sampled ranged from 50 m3 to 120 m3.   The total PAH loadings in the samples
varied depending upon the sample volumes.  As a  result, the levels of phenanthrene, anthracene,
fluoranthene, and pyrene found in the field blanks accounted for approximately 30% of these PAH load-
ings in samples with low  sample volumes. The field blank levels for all other PAH accounted for lower
percentages in all samples.
      Table I summarizes the minimum, maximum, and average background-corrected  concentrations
observed at the four sampling sites for each target PAH. The most abundant PAH found in ambient
air was naphthalene and the least abundant target PAH was either anthracene or cyclopenta[c,d]pyrene.
Highest average ambient concentrations of all target PAH were found at the ITT site. At this site, the
average concentrations ranged from 0.22 ng/m3 of cyclopenta[c,d]pyrene to 530 ng/m3 of naphthalene.
tfote  that the average concentrations of some known carcinogens,  such as benzo[a]pyrene and
indeno[l,2,3-c,d]pyrene, at this urban site were approximately ten times higher than at the other three
                                           375

-------
sites. In general, ambient concentrations for other target PAH at the ITT site were also significantly
higher than those at the other three sites except that naphthalene, acenaphthyene, and retene showed
some regional concentration patterns. The higher PAH concentrations at ETT may arise from mobile
source emissions and  stationary sources nearby.  Among the other three sites, the average ambient
concentrations from the same sampling days were generally higher at R/V Laurentian than those at the
Kankakee and South Haven sites, and average levels at South Haven were generally the lowest among
these three sites.  We  are still in the process of data analysis incorporating the meteorological data, in
an attempt to understand the atmospheric transport and deposition of PAH to Lake Michigan.

CONCLUSIONS
      The following  conclusions can be drawn  from this study:

       1.   The overall precision of the sampling and analysis methods for PAH monitoring ranged
           from 1.3% (dibenzo[a,h]anthracene) to 14% (fluoranthene) for duplicate PS-1 samples from
           parallel sampling.

      2.   The PAH  concentration profiles revealed that the highest average ambient concentrations
           were observed at the ITT site for all  the sampling dates.

      3.   There are  temporal variations  observed at each sampling site.  Further data analysis to
           incorporate meteorological data is necessary in an attempt to understand the atmospheric
           transport and deposition of PAH  to Lake Michigan.

REFERENCES
1.    W.M.  Strachan and  S.J. Eisenreich,  International  Joint  Commission Workshop  report,
      Scarborough, Ontario,  1986, published May 1989.

2.    IARC Monographs on the Evaluation of the Carcinogenic Risk of Chemicals to Humans;
      International Agency for Research on Cancer: Lyon, France, 1983, 32(1), pp 95-447.

3.    G. Motykiewicz, J. Michalska, J. Szcliga, arid B. Cimander, "Mutagenic and clastogenic activity
      of direct-acting components from  air pollutants of Silesian industrial  region," Mvta'-  ^&-
      204:208-296 (1988).

4.    S.  Salomaa, J.  Tuominen, E, Skytta, 'Genotoxicity and PAC analysis of particulate and vapor
      phases of environmental tobacco smoke," Mutat. Res.  204:173-183 (1988).

5.    J.C. Chuang, S.W. Hannan, and N.K. Wilson, "Field comparison of polyurethane foam and
      XAD-2 resin for air sampling for polynuclear aromatic hydrocarbons," Envir.  ScL fcdmcL
      21:798-804 (1987).

6.    J.C. Chuang, M.W. Holdren, M.R. Kuhlman, and N.K, Wilson, "Methodology of indoor air
      monitoring for  polynuclear aromatic hydrocarbons and related compounds," Prre, flf the  ^
      Int. Symp. on Measurement of Toxic and Related Air Pollutants Pub. VIP-13, Pittsburgh, PA,
      1989,  pp 495-501.

7.    J.C. Chuang, M.R. Kuhlman, and N.K. Wilson, "Evaluation of  methods for simultaneous
      collection and determination of nicotine and polynuclear aromatic  hydrocarbons in indoor air/
      Envir. Sci. Technol. 25:661-665 (1990).
                                            376

-------
8.    N.K. Wilson, J.C. Chuang, and M. R. Kuhlman, "Sampling Polycyclic Aromatic Hydrocarbons
      and Related Semivolatile Organic Compounds in Indoor air/ Indoor Air. 4, in press (1991).

9.    J.C. Chuang, G.A. Mack, J.R. Koetz and B.A. Petersen, Pilot study of sampling and analysis
      for polynuclear aromatic compounds in indoor air.  N.K. Wilson, Project Officer, Report,
      EPA/600/4-86/036. U.S. Environmental Protection Agency, Research Triangle Park, NC, 1985.

10.   J.C. Chuang, G.A. Mack, J.W. Stockrahm, S.W. Hannan, C. Bridges, and M.R. Kuhlman,
      Field evaluation of sampling and analysis for organic pollutants in indoor air.  N.K. Wilson,
      Project Officer, Report, EPA/600/4-88/028. U.S. Environmental Protection Agency, Research
      Triangle Park, NC, 1988.

11.   J.C. Chuang, G.A. Mack, M.R. Kuhlman, N.K. Wilson, "Polycyclic aromatic  hydrocarbons
      and  their  derivatives in indoor and outdoor air  in an eight-home study," Atmos. Environ.
      25B(3):369-380 (1991).
                                             377

-------
                                     Table I.  Ambient concentration (ng/m3) for target compounds.
IIT^ Kankakee('>
Compound
Naphthalene
Acenaphthylene
Acenaphthene
Fluorene
Phenanthrene
Anthracene
Fluorenone
Retene
Fluoranthene
Pyrene
Benz[a]anthracene
Chrysene
Cyclopenta[c,d]pyrene
Benzofluoranthenes
Benzo[e]pyrene
Benzo[a]pyrene
Indeno[ 1 ,2,3-c,d]pyrene
Dibenzo[a,h]anthracene
Benzo[gth,i]perylene
Coronene
min
160
1.7
4.0
7.0
17
0.44
1.5
0.21
3.9
2.4
0.29
0.53
0.08
0.80
0.25
0.29
0.37
0.20
0.43
0.26
max
840
14
130
130
430
18
23
0.92
110
55
8.9
13
0.63
33
9.1
15
10
3.2
8.0
3.9
ave
530
4.8
56
54
170
7.6
12
0.58
47
24
3.0
5.2
0.22
10
2.8
3.0
3.9
1.4
3.3
1.4
min
7.8
0.02
0.07
0.16
1.8
<0.01
0.27
0.03
0.49
0.20
0.01
0.03
<0.01
0.06
0.03
0.02
0.06
0.08
0.04
0.02
max
960
6.7
3.4
6.5
14
1.4
2.0
0.53
7.1
5.2
2.7
2.8
0.11
5.1
1.4
2.5
2.3
0.76
1.7
0.34
ave
330
2.6
1.8
3.7
8.0
0.30
1.0
0.27
2.1
1.1
0.25
0.33
0.03
0.58
0.17
0.26
0.30
0.19
0.23
0.13
South Haven*>
min
11
0.16
0.50
1.3
1.9
0.06
0.27
0.16
0.65
0.27
<0.01
0.03
<0.0l
0.04
0.03
0.02
0.04
0.02
0.03
0.02
max
230
1.0
1.8
7.8
8.9
0.23
2.0
0.76
3.7
1.8
0.57
1.3
0.18
2.6
0.74
0.69
1.3
0.60
1.0
0.31
avp
64
0.51
1.0
3.3
4.6
0.13
0.84
0.42
1.5
0.75
0.12
0.28
0.04
0.50
0.15
0.13
0.24
0.15
0.19
0.08
R/V Laurentian(c)
jnin
15
0.42
0.40
2.4
1.3
<0.01
0.30
0.21
0.53
0.23
0.01
0.03
<0.01
0.06
0.03
0.02
0.04
0.03
0.03
0.03
max
420
3.8
8.1
16
31
0.78
2.4
1.3
8.8
5.2
1.2
2.5
0.52
3.7
1.0
0.80
1.6
0.58
1.4
0.43
avE
120
1.4
2.3
7.2
11
0.27
1.1
0.57
3.2
1.6
0.26
0.62
0.09
0.92
0.25
0.25
0.41
0.21
0.33
0.16
(a)  Data are from 16 tests (daytime sampling) performed at 7/16/91-7/24/91, 7/29/91, 7/31/91, 8/2/91-8/8/91.
(b)  Data are from 21 tests (daytime sampling) performed at 7/12/91, 7/16/91-7/24/91.7/29/91, 7/31/91, 8/2/91-8/9/91; duplicate tests performed
    at 8/7/91-8/9/91.
(c)  Data are from two samplings (daytime versus nighttime) of each of the following sampling dates: 7/11/91,7/23/91,7/24/91,8/6/91, and 8/7/91;
    one daytime sampling at 7/12/91; and one nighttime sampling at 8/5/91.

-------
           Atmospheric Acidity Measurements During the
                Lake Michigan Urban Air Toxics Study
                        Carl Lamborg and Gerald J. Keeler

                              Air Quality Laboratory
                             The University of Michigan
                         Ann Arbor, Michigan 48109-2029

                                   Gary Evans
                                 USEPA-AREAL
                        Research Triangle Park, N.C. 27711
ABSTRACT

       During the summer of 1991, as part of the Lake Michigan Urban Air Toxics Study
(LMUATS), measurements of atmospheric reactive gases, fine fraction, and size fractionated
acidic aerosol samples were taken at two sites (South Haven, MI and on the research vessel,
Laurentian).  The fine aerosol samples were collected using  an annular  denuder system
(ADS) which allowed quantification of acidic and basic gases, as well as inorganic tons in the
fine particle fraction  (<2.5 jun). The size fractionated data was obtained using a six stage
micro-orifice impactor (MOI) equipped with ammonia-scrubbing denuders.
       The ADS aerosol results showed extreme  episodic behavior which correlated well
with air mass transport  from the southwest.  The maximum concentrations observed in South
Haven after over lake  transport from the southwest were 241  nmol/m3  for aerosol strong
acidity (IT),  and 3.8  ppb for nitric acid (HNO3).   These elevated acid levels were
accompanied by  hourly maximum O} concentrations of 128  and  153  ppb, respectively.
Levels at South Haven  and aboard the Laurentian were very similar for most of the species
measured. Size fractionated paniculate mass results also compared well for most species,
and showed a typical  size  dependent behavior.   Measurents  of aerosol acidity are also
compared to those taken in Ann Arbor, MI during the one month study.

INTRODUCTION

       The Lake Michigan Urban Air Toxics Study (LMUATS) was jointly carried out by
the University of Michigan and the U.S.  Environmental Protection Agency during  the
summer of 1991. A  primary  goal of the study  was to quantify the levels of toxic air
pollutants in the  southern Lake Michigan basin in order to determine  how much of the
airborne pollutants are being deposited to aquatic and terrestrial ecosystems.  Measurements
of atmospheric acidity, both gaseous and aerosol strong acidity, H,+ were  performed to
                                      379

-------
chracterize the chemical composition of the atmosphere and to investigate the behavior of the
regional and urban plumes advecting across Lake Michigan.

EXPERIMENTAL
       Annular denuder/filter pack measurements were performed at two of the four sites
operated during the  LMUATS.  The  first was South Haven, MI,  located in a rural area
approximately 5 miles from the lake.  The inlet  to the samplers was approximately  7  feet
above the ground in  an open field.  Continuous monitoring equipment was also operated at
this site as part of the Lake Michigan  Ozone Study (LMOS) providing hourly ozone (O3),
NOx, and meteorological data.
       The second site was the University of Michigan's research  vessel, the R/V Laurentian.
The  ship  was positioned in two areas during  the  study.   The  first station or on-lake
monitoring position was about 20 miles west of Muskegon. The second station was about 4-
10 miles E-NE of the Chicago-Gary urban/industrial area.  The sampling inlets were roughly
5 feet above the deck but off the side of the bow  area of the ship (which stood an additional
20' above the surface of the water).  Sample collection took place only when the vessel was
anchored which keeps the bow pointing into the prevailing  wind at all times.
       Acidic aerosol and gas measurements were  taken at South Haven throughout the
duration of the study while the size fractionated samples were collected occasionally.  While
the Laurentian was docked, two 12-hour samples were collected in South Haven from 8am-
8pm and 8pm-8am CDT.  While the ship was on station, 3  samples were taken daily at South
Haven and on  the  R/V Laurentian:  8am-2pm,  2pm-8pm, 8pm-8am CDT.   All  size
fractionated samples  were 24-hours in  duration starting at Sam CDT,  and were operated at
both South Haven and on the  R/V Laurentian.  ADS samples were also collected in Ann
Arbor as part of an ongoing study of atmospheric acidity in Michigan.
       The annular denuder sampling system was used for collection of acidic aerosols  and
gases and has been described previously (Koutrakis,  et al. 1988, Keeler et al., 1990). The
ADS was utilized to quantify gaseous SO2, HNO3, HONO, NH3,  and fine fraction (<2.5 um)
paniculate species S042% NO3", NH4+, and aerosol strong  acidity (H+).  Additionally, the
system removes the  gaseous ammonia and protects  the  collected paniculate matter from
possible neutralization.
       Size fractionated  samples were collected at South Haven  and aboard the R/V
Laurentian using a six-stage micro-orifice type impactor (Koutrakis et al.,  1989, Keeler et
al, 1990).  The six stages have been characterized to separate atmospheric aerosols into the
following  size ranges when operated at 30 LPM: #1: > 5 ^m #2: 5-2.5 |im #3: 2.5-lum
#4: 1-.6 um  #5:  .6-.18 urn  #6:  <18 \un (Marple and  Rubow, 1984).  The system is
designed  to operate with a  minimal  pressure  drop  so  that vaporization of water  and
subsequent alteration of the aerodynamic diameter of the particles being collected is avoided
(Biswas et. al, 1987).  The impactors were placed in a stand which forced incoming air to
pass through 8-citric acid-coated honeycomb-style aluminum denuders to remove ambient
ammonia (Koutrakis  et al, 1988).   The aerosol  material  was collected onto Teflon filters
(Teflo) and analyzed identically to the Teflon filters from the ADS.
                                        380

-------
       Sulfate collected on ADS, MOI and on dichotomous filters (analyzed by XRF) were
compared to assess the precision of the three techniques.  Regression analysis of XRF S
against ADS SO42" shows quite good results with a slope of 0.33 ng/m3 S / ng/m3 SO42" and a
correlation coefficient of 0.994.  Likewise, the regression of ADS SO42' versus MOI SO42'
(fine fraction, stages 3, 4, 5 and 6) displays a slope of 0.93 and a correlation coefficient of
0.986.  These results indicate that the collection and  analytical techniques utilized were
comparable and precise.

RESULTS
       In all, 74 ADS samples were collected in South Haven, and 22 on the Laurentian and
a total of 17 MOI samples at the two sites. The measured H*and SO42" concentrations at the
two sites can be seen in Figures 1 and 2. A  statistical  summary of these values as well as
concentrations measured in Ann Arbor during the same period are shown in Table 1.  The
values measured are typical of summertime values previously measured in the midwest  U.S.
(Pierson et ai, 1989). Concentrations of most species were slightly higher on the Laurentian
(relatively close to Chicago) than in South Haven but in general levels were very similar.
       Although most species measured showed their peak concentrations during an episode
(see below) two species, HN03 and  SO2 showed significant  deviations  from this pattern.
Peak values for HNO3 were observed during the evening of July 11 and were measured to be
41.8 and 10.4 ppb on the Laurentian and at South Haven, respectively. SO2 also showed its
peak value during this overnight sample.  Unfortunately, no sample was  collected in South
Haven due to power failure, but the Laurentian S02 level was  31.9 ppb.   The concentration
spike  was not displayed in any of the other species measured.  As the mixed layer trajectory
switched from the NW on the 11th to the SW  on the 12th, it appears that emissions from the
Muskegon/Grand  Haven area were transported to the  ship (off Muskegon) and to South
Haven.  A similar brief event occurred during the evening of 6 August. The second highest
value  for SO2 was observed during this period on the Laurentian, but without a similar peak
in South Haven.  This can be easily explained by examining the air mass trajectory during the
period which carried emissions from the Gary/Michigan City  area north  to the Laurentian
anchored off Chicago.  The contact of this plume was  confirmed by operators on the ship
from the pronounced odor, visibility degradation,  and ozone depletion with winds from the
direction of the Fe-Steel plant.
       A sustained episode of elevated pollutant levels  was observed in  South Haven from
July 16-22. This episode resulted in  peak concentrations of HN03, paniculate S042', and
aerosol strong acidity (H+) and SO2 of 3.8 ppb, 241 nmole/m3 and 9 ppb, respectively. Most
of these  species showed typical day/night variation  (daytime values being higher).  This
episode was associated with sustained air mass transport from the  SW bringing pollutants
from the St. Louis/industrial areas in  central  Illinois through the Chicago/Gary area.  High
ozone concentrations were measured during  this period in South  Haven with maximum
hourly values of 128 and 153 ppb being reported.
       Results  of the analysis  of filters from the MOI were used to observe  the size
distribution of chemical species at the two sampling sites.  SO42', NH4* and  H* consistently
appeared on stages 4, 5 and 6 (primarily 4 and S).  The observation of these species in <1 u,m
                                        381

-------
diameter particles is typical of other similar measurements (Pierson et al., 1989). Mass mean
diameters ofhT, SO42" and NO3" were calculated from data from all 6 stages by determining
the approximate diameter size at which 50% of the mass resided .  The graph suggests that
IT and SO42' were on very small particles of mass mean diameter approximately 0.35 nm
while NO3" appeared to reside on slightly larger sizes (1.5 ujn).
       Changes can be observed in the chemical profile of fine fraction aerosols measured
during the LMUATS. The H* to SO42 ratios at different sites were 0.78, 0.44,  and 0.16,
on the R/V Laurentian, South Haven, and Ann Arbor, respectively.  This indicates that
the acidic SO/ aerosol  measured over  the  lake is to a large extent unneutraUzed.
However, as the aerosol is transported inland, even a short distance as at South Haven, an
additional 25% of the acidity is neutralized. This is most likely due to rapid fumigation of
the air  mass after reaching  the shoreline where  relatively high levels of ammonia react
rapidly with the acidic SO42. However, compared to the average inland values measured
in Ann Arbor during the study, both the over-lake and  South  Haven areas  appear to be
exposed to relatively unneutralized sulfate.

CONCLUSION
       The  acidic aerosol measurements during the LMUATS  indicate  that western
Michigan is impacted by sulfate-containing air masses as is much of the  region, and that
the atmosphere can be quite acidic during certain episodic conditions.  It appears that air
masses  transported long distances over large bodies of water, eg., Lake Michigan, can
maintain the acidity  of the aerosols until reaching the downwind shoreline, where rapid
neutralization  may occur.   This over-water  transport may provide  relatively  large
exposures of atmospheric acidity to areas located near the shore.

BIBLIOGRAPHY

P. Biswas, C.L. Jones and R.C. Flagan, Distortion of Size Distributions by Condensation
and Evaporation in Aerosol Sampling  Instruments.   J.  Aerosol Sci.  Tech.  7: 231-247,
1987.
V.A.  Marple and K.L. Rubow, Development of a Micro-orifice Uniform Deposit Cascade
Impactor,  Final Report, DOE Contract DE-FG22-83PC61255, Pittsburgh Energy Tech.
Cent., Pittsburgh, PA, 1984.
G.J. Keeler et al., Transported Acid Aerosols Measured in Southern Ontario,  Amos.
Environ. 24A, 12: 2935-2950, 1990.
P. Koutrakis et al.. Evaluation of an annular denuder/filter pack  system  to collect acidic
aerosols and gases. Environ. Sci. Technol.  22, 1463-1468, 1988.
W.R. Pierson et al., Atmospheric Acidity Measurements on Allegheny Mountain and the
Origins of Ambient Acidity in the Northeastern United  States. Amos. Environ. 23, 2:431-
459, 1989.
                                        382

-------
Table 1. Levels of atmospheric trace species measured during the LMUATS
           from 8 July - 9 August, 1992.
Species
NH,


HNO,


SO,


Acidity


NH/


NO,'


SO/


Site
South Haven
Laurentian
Ann Arbor
South Haven
Laurentian
Ann Arbor
South Haven
Laurentian
Ann Arbor
South Haven
Laurentian
Ann Arbor
South Haven
Laurentian
Ann Arbor
South Haven
Laurentian
Ann Arbor
South Haven
Laurentian
Ann Arbor
N
69
18
22
70
19
22
70
19
22
70
19
22
70
10
22
70
19
22
70
19
22
Mean
1.3ppb
1.8
3.1
.7ppb
1.3
.8
1.7ppb
2.6
2.8
22. 1 nmole/m3
15.6
24.2
72.1 nmolc/m3
35.0
131.3
6.3 nmole/m3
1.2
10.7
46.3 nmole/m3
30.7
79.0
Median
1.2
1.5
3.0
.4
1.2
.5
.9
1.4
2.2
9.2
15.2
6.7
36.5
33.8
37.5
5.0
0
7.0
22.1
18.6
23.1
SD
1.2
1.4
.8
.8
1.0
.7
1.9
3.6
2.0
41.3
11.9
41.4
91.9
26.8
171.4
6.0
3.1
12.3
61.0
26.1
102.3
Min
0
0
1.8
0
0
0
.2
0
.7
0
0
0
0
0
13.2
0
0
0
0
8.7
5.2
Max
9.7
5.1
4.4
3.2
3.7
2.6
8.9
15.8
8.7
240.5
35.1
129.7
397.6
98.4
544.1
29.2
13.0
59.4
281.3
96.9
329.3
                                383

-------
                               Aerosol  Strong  Acidity
                                     Laurention





^

E
i


100 -
90 -
80 -
TO -
80 -

50 -

«O -
30 -
10 -
0 -




m
E
\
S>
o
1
! I
li Pill ,1
                1112
                                       2J24232627
                                                                5 « 7 8
                                    South  Haven
,
100
 i
 '•
 •
 M
 •
 H
 M
 10
 10
 a
                              2403
                        1221        2I2.S
            JjJ

Mil. l.|[|.l,l.!l..ll
                                 i
         78* 1011 t2tAI4ISt«IT1lt«2021UU2413U272B2tMJI i3J<567
                    July                                       August
                                         Data
                                        Fig. 1
                                   384

-------
                           Porticulot* Sulfole
                               Laurention
300 -
270 -
240 -
210 -
180 -
ISO -
120 -
 •0 -
 60 -
 30 -
  0 -
                                  2324292627
                               South  Haven
300
270-
240-
210
180

150
120 H
 10

 80 -
 30 -
 0
                   • <617I«I9202I2223242S26272B2»3031 I  2  J  4  S 6  7 • » 10
                                                          Auguflt
                                    Dote
                                   Fig. 2
                                  385

-------
        DRY DEPOSITION AND  COARSE PARTICLES  SIZE
          DISTRIBUTIONS  MEASURED DURING LMUATS
      Kenneth E. Noll, Thomas M. Holsen, G. C. Fang, J. M. Lin, W. J. Lee
                    Pritzker Department of Environmental Engineering
                            Illinois Institute of Techchnology
                                3201 South State Street
                                    Chicago, Illinois
ABSTRACT
    The dry deposition flux of mass and metals in Chicago, South Haven (Michigan) and over
Lake Michigan were measured during the summer of 1991. Chicago had the highest and Lake
Michigan has the lowest dry deposition flux for both mass and metals.  A 4 or 12-step method
was used to calculate the dry deposition flux from measured atmospheric size depositions. The
average ratio of calculated to measured flux for all samples was 0.92. The results of the modeling
work show  that coarse particles dominate the dry deposition flux.

INTRODUCTION
    Deposition is an important pathway for the transfer of pollutants  like heavy metals from
air to land and water.  Recent  estimates suggest the greater than 50% of  both lead and PCB
inputs into Lake  Superior, Michigan and Huron come from the atmosphere. However, attempts
to quantify this pathway have found  that there are insufficient data to reliably estimate the at-
mospheric deposition of these contaminants and that information about the rates of deposition of
contaminants associated with dry particulates is insufficient to construct a reliable mass balance
model.1 Even though an accurate determination of the dry deposition of contaminants is criti-
cal in understanding their movement in the environment, there is still no generally acceptable
technology  for sampling and analyzing dry deposition flux.2 The quantification of dry deposition
flux is difficult because of large spatial and temporal variations and because most  measurement
methods do not simulate natural surfaces. The use of a surrogate surface to collect dry deposition
is a technique that allows a comparison to be made  of measured and modeled data because it
can be used to directly assess deposited material.

MATERIALS AND METHODS

Dry Deposition Plate
    The dry deposition plate used in  this study3 is similar to those used in wind tunnel studies.
It was  made of polyvinyl chloride (PVC) and is 21.5 cm long, 7.6 cm wide and 0.65 cm thick
with a sharp leading edge (<10 degree angle) that is pointed into the wind by a wind vane. Each
of 3 plates were covered with 4 Mylar strips (7.6 cm x 2.5 cm) coated with approximately 8 nag
of Apezion  L  grease (thickness  w 8 /im) to collect impacted particles (123 cm2 total exposed
surface). The film was  placed on the plate and held down on the edges with a 5 mil thick  Teflon
template, which was secured at each end by acrylic slats screwed into the plate. The plate was
cut to slide onto  a 3 cm diameter rod.  Two screws fastened through the plate to a wind vane
allowed the plate  to swing freely into the wind. Each plate was separated  by 46 cm (horizontally)
which has been shown experimentally to be sufficient to prevent sample interactions.3 The strips
were weighed before and after exposure to determine the total mass of particles collected.
                                         386

-------
Particle Size Distribution

    Atmospheric particles in Chicago were measured with both an Anderson 1 ACFM non- viable
ambient particle sizing sampler (with preseparator)(AAPSS) and a Noll rotary impactor (NRI).
Particle size distribution in South Haven was measured with the NRI only. The AAPSS is a
multi-stage, multi-orifice cascade impactor. It was calibrated with unit density spherical particles
so that all particles collected are sized aerodynamically equivalent to the reference particles. The
AAPSS separates particles into the following size ranges: > 10 ^m (preseparator), 9.0-10.0 ^m,
5.8-9.0 /im, 4.7-5.8 ^m, 3.3-4.7 ^m, 2.1-3.3 pm,  1.1-2.1 /im, 0.65-1.1 pm, 0,43-0.65 /im, and <
0.43 fxm. The media used was greased Mylar to minimize particle bounce.
    Atmospheric coarse particles were measured  with the NRI which is ideally suited  to collect
the large particles conventional samplers exclude.  It is a  multi-stage rotary inertia!  impactor
that collects coarse particles  by simultaneously rotating four rectangular collectors (stages) of
different dimensions through  the air.  The stages were covered with Mylar strips coated  with
Apezion L grease.  The cut size for NRI are 6.5 fim, 11.5 f/m, 24.7 ^m and 36.5 /xm for  stages A,
B, C, and D respectively.  The strips were weighed before  and after sampling to determine the
total mass collected. Metal analysis of collected  particles  was performed with furnace AAS as
described previously.5

MODELING
    A 4 or 12-step method was used to calculate the dry deposition flux from Noll Rotary and
cascade impactor .6~7 The flux can be calculated  with the following equation:
                                        t=i
where d is the concentration of each impactor stage; efp,- is the midpoint cut-off diameter of each
impactor stage, V*(dpi) is the  deposition velocity of the mid-point particle size calculated with
the model of Slinn and Slinn,9 and n = 12 for Chicago samples and 4 for South Haven samples.

Sampling program
    During July 1991, samples were collected in Chicago 1.6 1cm west of Lake Michigan, at South
Haven, Michigan which located approximately 2 km east of the Lake Michigan and 130 km east
of Chicago. Samples were also  collected from a boat in southern Lake Michigan between Chicago
and South Haven.

RESULTS
    The measured mass and metal flux in Chicago was higher than in South Haven or over the
Lake (Figure 1 and Table 1).   The metals of crustal origin had a higher flux than metals of
anthropogenic origin at all 3 sites. In general the flux measured over the Lake was lower than
that measured at either land sites.
    The lead flux into the southern 1/3 of Lake Michigan was estimated by multiply the average
Pb flux measured on the boat  (0.235 ng/cm2day) by one-third the surface area (57,800 km2) of
Lake Michigan to be 45.28 kg/day which is 30 times greater than the average lead flux (1.50
kg/day) estimated for all of Lake Michigan by previous researchers.1 This finding indicates the
importance of atmospheric inputs into the Great Lakes.
    The particle size distribution measured in Chicago was bimodal with roughly half of the mass
in each of the coarse and fine particle modes. The coarse particles concentration in Chicago were
higher than in South Haven (Figure 2). Anthropogenic and crustal element distributions were
also bi-modal. However, the anthropogenic elements existed primarily in the fine particle mode
and the crustal elements existed primarily in the coarse particle mode (Table 1).
                                           387

-------
    The mass flux distributions for Chicago and South Haven (C2 and SH2) were obtained by
multiplying dc/dlog(dp)  by Va obtained with the model of Slinn and Slinn9 for each particle
size. The area under the flux distribution curve is the dry deposition flux. The cumulative flux
obtained from these samples indicates that the majority of the flux is due to particles > 6.5 ^m
in size (Figure 3). A similar analysis of the Pb and Ca data at the Chicago site yielded similar
results, the modeled flux due to particles < 6.5 pm were 0.31,  1.2, and 0.46% for mass, Pb and
Ca, respectively.
    The ratios of the calculated/measured  flux for  mass, Pb, and Ca for both Chicago and
South Haven are shown in Figure 4. The average ratio of calculated/measured flux for mass, Pb
and Ca in Chicago were 1.39,  0.55, 0.66  and in South Haven were 1.13, 0.73, 1.01, respectively.
It is important to note that the modeled  flux for South Haven used only coarse partixle size
distribution yet gave similar results to models using  complete size distributions. These results
show that: 1) flux can be accurately modeled using atmospheric size distributions and  modeled
deposition velocities, 2) coarse particles dominate dry deposition even for species like Pb  which
exist primarily in the fine particle mode.
[ ggg South nav«n. wi (EH:;
L nrmi Chicago. 11 (C:)
600 j- == Lak« Michigan (LKO
f
t
— 500 -
1 F
- r
"- 400 r
1, t
3d k
^ JCG [
1 t
- :cc -
f




I






^









3





.


o
X
H
a
2

i







.









i
•
!


;
i
^
:
= 3
I J 1













                                                £ ^ u
   Figure 1.
                            Element
Comparison of mass and elemental flux measured with a smooth sur-
rogate surface in Chicago, South Haven and  over Lake Michigan.
                        '   10
                       •o
                            i
                            a
                                  Urban (N.R.I.)  (C2)
                                  Urban (Caicadi Impocror)  IC21
                                  Nonurbon (N.R.I.)  (Sn2)

                                              ICO
                                        Panicle jizs. um
     Figure 2. Mass - size distribution measured in Chicago and South Haven.
                                            388

-------
Table I. Sampling Information.
aita
Chicago
South
Bavm
LaKi
Michigan
Soapla
Ho.
7/8/91-7/16/91
Cl
7/23/91-7/29/91
C2
7/30/91-8/6/91
C3
7/7/91-7/11/91
SHI
7/11/91-7/21/91
SB2
7/19/91-7/27/91
SH3
7/23/91-7/29/91
LH1

8/3/91-8/7/91
LM2

Epeci»a
Na«»
fa
Ca
Kaac
?b
Ca
tteam
Pb
Ca
Ma»
Pb
Ca
HABB
Pb
Ca
Mail
Eb
Ca
Man
Fb
Ca
Hau
Pb
Ca
CDncantracion (^g/n }
Cf
13.685
0.032
0.339
21.765
0.040
0.232
18.475
0.037
0.377
DA
!U
HA
DA
SA
HA
SA
HA
HA
NA
HA
HA
HA
SIi
HA
C
11.390
0.015
0.734
16.485
0.015
0,629
37.895
0.017
0.806
19.53
0.00208
0.393
13.48
0.00238
0.304
13. S7
0.00296
0.423
m
HA
NX
HA
1U
HA
FlUX
ng/cmVday
9820
11.326
751.48
10290
10.427
£01.16
19540
14.492
597.85
3620
1.04
342.97
3830
1.48
254.83
4410
1.58
no. 25
2720
0.26
122.78
2490
0.21
158.94
               389

-------
                   100
                    10
                               Mass

                           • :  C2

                           O :  SH2
                                                  o
                3
                £
                   0.1
                  0.01
                     0,1
                                                              100
                                1            10

                                    dp (um)

Figure 3. Cumulative flux calculated for mass in Chicago and South Haven.
                   100
                                           1     I
               x
               3
               •O

               L.

               in
               ffl
               0)
               •c
               a
                10
                           O  : Chicago sample (C1-C3)
                           •  : South Haven sample (SH1-SH3)
                     1
                       O
                       -*-
•    •
                                               o
                                                               $>
                   0.1
                  0.01
                                                t     1
                     if I   #2    #3    #1    #2   #3   #1   #2   #3

                         Mass             Pb             Ca
Figure 4. A comparison of Calculated/measured flux in Chicago and South Haven.
                                       390

-------
CONCLUSION
     (1) Chicago had a higher flux than South Haven, and Lake Michigan for mass, crustal and
        anthropogenic elements.  In general fluxes measured over Lake  Michigan were lower
        than at either land site.
     (2) The calculation of dry deposition flux using Slinn and Slinn9 modeled deposition veloc-
        ities and a 4 or 12-step method is comparable to measured dry deposition flux.
     (3) Fine particles are responsible for only a small fraction of the dry deposition flux, > 90%
        of the flux is due to coarse particles.

REFERENCE
  1.  W. M. Strachan, S. J. Eisenreich, "Mass balancing of toxic chemicals in the Great Lakes:
    the role of atmospheric deposition;"  International  Joint Commissiion Workshop Report,
    Scarborough, Ontario 1986 - published May 1989.
  2.  C.I. Davidson, S. E. Lindberg, J. A.  Schmidt, L. G. Cartwright and L. R. Landis, "Dry
    deposition of sulfate onto surrogate surface," J. Geophvs. RefL 90: 2123-2130 (1985a).
  3.  K. E. Noll, K. Y. P. Fang and L. A. Watkins, "Characterization of the deposition of particles
    from the atmosphere to a flat plate," Atmospheric Environment.  22: 1461-1468 (1988).
  4.  D. I. McCready, "Wind tunnel modeling of small particle deposition," Aerosol Sci. Technol.
    5: 301-312 (1986).
  5.  K. E. Noll, P. F. Yuen and Y. P. K. Fang, "Atmospheric coarse particlate concentrations and
    dry deposition fluxes for ten metals in two urban environments," Atmospheric Environment.
    24A, (4): 903-908 (1990).
  6.  F. Dulac, "Dry deposition of mineral aerosol paticles in the marine atmospheric:  A critical
    evaluation of current field and modeling approach," presented at 5th Int. conf, on precipi-
    tation scavenging and atmosphere - surface exchange processes, Richland, WA. U.S.A., July
     15-19, 1991.
  7.   K. E. Noll, T. M.  Holsen,  G. C. Fang and  J. M. Lin, "Mass-size distribution and dry
     deposition flux of particles and Metals in Chicago," For Presentation at the 85th Annual
     Meeting of the Air Pollution Control Association Minneapolis, Minnesota, June, 22-27, 1992.
  8-   W.G.N. Slinn, "  Review paper, some aspects of the transfer of atmospheric trace con-
     stituents pass the air-sea interface", Atmospheric Environment. 12: 2055-2087 (1978).
  9-   S. A. Slinn and W. G. N. Slinn,  "Predictions for particle deposition on natural waters,"
     Atmospheric Environment. 14: 1013-1016, (1980).
                                           391

-------
        Session 10
 VOC Methods Development
William McClenny, Chairman

-------
               EVALUATION OF A SORBENT-BASED
   PRECONCENTRATOR FOR ANALYSIS OF VOCS IN AIR
                USING GAS CHROMATOGRAPHY -
                  ATOMIC EMISSION DETECTION
                     Karen D. Oliver and E. Hunter Daughtrey, Jr.
                       ManTech Environmental Technology, Inc.
                                 P. O. Box 12313
                         Research Triangle Park, NC  27709

                               William A. McClenny
                        U.S. Environmental Protection Agency
                         Research Triangle Park, NC  27711


ABSTRACT
      A Hewlett-Packard 5890 gas chromatograph and 5921A atomic emission detector (AED)
were used to determine volatile organic compounds (VOCs) at part-per-billion-by-volume levels
in ambient air samples which were preconcentrated by using the Dynatherm ACEM 900 sorbent-
based preconcentrator.  Several combinations of multisorbent sampling tubes and focusing tubes
were tested.  Mixtures of 51 VOCs including 10 polar compounds were prepared in humidified
scientific-grade air and were used to evaluate the system with regard to compound recoveries,
linearity of compound concentration with varying sample volume, and the optimum volume of
purge gas needed to remove water from the sorbent before  thermal desorption. The automated,
unattended operation of the system was also evaluated by allowing the instrument to sample indoor
air at intervals of approximately 1 h over a 24-h period.
      Because individual elements are detected by the AED, the hydrogen response due to water
may be monitored concurrently with the response of other elements. This allowed a  thorough
investigation of the effect of water vapor on the carbon, chlorine, and bromine response for those
compounds in the standard mixtures which coelute with water. Also, the relative amount of water
vapor still  present in the  sample after  various drying techniques were employed was easily
monitored. These results and the results of the experiments mentioned above are discussed in this
paper.
      This paper has been reviewed in accordance  with the U.S. Environmental Protection
Agency's peer and administrative review policies and approved for presentation and publication.
Mention of  trade  names or commercial  products does  not constitute  endorsement  or
recommendation for use.

INTRODUCTION
      Currently,  the  U.S. Environmental  Protection  Agency is evaluating automated gas
chromatographic systems (autoGCs) for use in network monitoring stations.1  Desirable features
of these systems include (1) the need for  little or no liquid nitrogen, (2) the capability for
unattended, continuous operation, (3) the capability for drying the sample stream without removing
polar volatile organic compounds (VOCs) and (4) easy  deployment  in the field.  The autoGC
system being  evaluated in our laboratory utilizes a Dynatherm  Automated Continuous
Environmental Monitor (ACEM) Model 900 sorbent-based sample preconcentrator and a Hewlett-
Packard 5890 GC and 5921A Atomic Emission Detector (AED). The AED has been a useful and
interesting detector for the laboratory evaluation of the system but has never been considered
                                       395

-------
 suitable for field deployment because of the fragility of the GC-AED interface and support gas
 requirements.

 EXPERIMENTAL
       A  Dynatherm  Analytical  Instruments,  Inc. (Kelton, PA)  ACEM 900  for sample
 preconcentration and thermal desorption is interfaced to a Hewlett-Packard (HP, Avondale, PA)
 5890 GC which is equipped with an HP 5921A AED. The ACEM 900 is a sorbent-based system
 which employs two tubes; one sorbent tube collects sample and a  second, narrower sorbent tube
 focuses the sample prior to thermal desorption onto the capillary column. A Dynatherm External
 Sampling Module is used to load sample onto the collection tube from a canister or to pull ambient
 air through the tube by using a vacuum pump.  Helium may be  used to purge water from the
 collection tube  prior to desorption of the sample onto the focusing tube.  The 1-m x 0.20-tnm
 deactivated fused-silica transfer line which connects the ACEM 900 to the GC column was heated
 to 200 *C.  A 60-m x 0.32-mm x  S-pm DB-1 capillary column (J & W Scientific, Inc., Rancho
 Cordova, CA) was used for the experiments discussed here, and the GC oven temperature was
 programmed as follows: 6  min at 30 °C, an 8 °C/min ramp to 240  *Q and a 10 min hold at
 240 * C. For the analyses, the AED transfer line and cavity block were heated to 250 * C, and the
 AED was programmed to monitor responses of emission lines of carbon at 496 nm, hydrogen at
 486 nm, chlorine at 479 nm, and bromine at 478 nm.
       Challenge gas mixtures for the experiments included 6-L canister samples of a mixture of
 10 ppbv of the 41 VOCs on the EPA Compendium  Method TO-14 target list2 in humidified air
 at  -50% RH.   The  canisters were prepared3 from a  cylinder  containing 1-2 ppm of each
 compound in nitrogen  (Alphagaz,  Walnut Creek, CA).  Also used were canister samples of a
 mixture of 10—20 ppbv of 10 polar compounds (methanol, ethanol, isopropanol, butanol, acetone,
 methyl ethyl ketone, acetonitrile, acrylonitrile, methyl methacrylate, and ethyl acrylate in humidified
 air  at ~50% RH) which were prepared from cylinders containing 10 ppm of the compounds in
 nitrogen  (Scott  Specialty  Gases,  Plumsteadville, PA).   Mixtures of C2-C6  compounds at
 concentrations of 15-100 ppm in nitrogen (Scott Specialty Gases) were also used to spike the tubes.
 This was accomplished by moving the collection tube from the ACEM 900 to a Dynatherm Model
 10 tube conditioner and injecting the sample from a gastight syringe  into a  stream of nitrogen
 flowing at 50 cm3/min through the tube.  The collection  and focusing  tube combinations
 (Dynatherm Analytical Instruments, Inc.) tested are presented in Table I.
      Initially,  the effect of different  helium purge volumes (used to remove water from the
 collection tube) on the response of VOCs was investigated. In these experiments, a 480-cm3 sample
 of the 41-compound mixture was collected on the sorbent tube from a 6-L canister by using 8
 0-500-sccm mass flow controller (MFC, Tylan General, Torrance, CA) set at 80 cm3/min. The
 tube was then purged with 26 cm3/min of helium; the helium purge volumes used were 0,50,100.
 250, 500, and 1000 cm3.  The collection tube was normally held at 40  "C for these experiments,
 although some experiments were repeated with the tube at 55 and 65 * C. Sample was desorbed
 from the collection tube onto the focusing tube for 3 min at 200 or 300 • C, followed by 2 min in
 cool mode (in which helium continues to flow through the tube in the desorb position while the
 tube is cools down from the desorb temperature). Then, the focusing tube was heated to 350 "C
 as indicated by a thermocouple located outside the tube, for 3 min  to desorb sample onto the GC
 column.
      The linearity of response of the 41 VOCs and the polar compound mixture was investigated
 by collecting sample volumes of 250,500,1000, and 2000 cm3. Again, an MFC set at 80 cnr/min
was used to load the samples from 6-L canisters onto  the collection tube, and the tube was purged
with 500 cm3 of helium to remove residual water.  Tube heating and cooling parameters were the
 same as those listed above.
                                          396

-------
Table I.  Tube combinations
                                                             Experiments
                                               Vary              Retention
Tubes (Sorbent" and Focusing)                  He Purge            of Q        24-h
                                               Volume  Linearity  Compounds Monitoring

Tenax-TA/Ambersorb XE-340/Charcoal            X          X        X         X
  + Tenax-TA/Silica gel/Ambersorb XE-340/
  Charcoal
Carbotrap C/Carbotrap B/Carboxen 1000           X          X        X         X
  + Tenax-TA/Silica gel/Ambersorb XE-340/
  Charcoal
Tenax-TA/Carboxen 1000                         X                   X
  + Carbotrap B/Carboxen 1000
Tenax-TA/Ambersorb XE-340/Charcoal            X                   X
  + Carbotrap B/Carboxen 1000
*6-tnm-o.d. sorbent tubes.
      The retention of ethane, ethylene, and acetylene on different collection and focusing tube
combinations was investigated by spiking 6-mm-o.d. and  10-mm-o.d. tubes with 1—10 cm3 of the
Q—C6 gas mixtures as discussed above. In addition to the tube combinations in Table I, nine tube
combinations were evaluated by using one of each of the following 10-mm-o.d. collection tubes:
Tenax-GR/Carboxen  1000,  Tenax-GR/Carboxen  1000/Spherocarb, or Tenax-GR/Carboxen
1000/Carbosieve Sill; the collection tube was used with one of each of the following focusing tubes:
Carbotrap B/Carboxen 1000, Tenax-GR/Spherocarb,  or Tenax-GR/Carbosieve SHI.  In these
experiments, the collection tube was held at 40 • C and desorbed at 300,325, or 350 *C. The heat
and cool mode times were varied from 1 to 3 min and 0  to 2 min, respectively, to determine the
optimum operating conditions  for retention of Q compounds.   The focusing tube was then
desorbed for 3 min at 300 or 350 °C.
      To  test the unattended, repetitive operation of the ACEM 900, the unit was set to collect
-20 samples of ambient indoor air during a 24-h period.  A sampling  pump was  used to pull
sample across the sorbent tube by using the external sampling module.  Sample volumes of 250 cm3
of air were collected, and the tube was flushed with 500 cm3 of helium. The collection tube was
heated to 200 or 300 • C for 3 min and then cooled for 2 min prior to desorbing the focusing tube
for  3 min at 350 'C

RESULTS AND DISCUSSION
      Because  the GC-AED is capable of monitoring the responses  of individual elements, the
effect of water vapor on the responses of Q,  Br, and C for the  41  VOCs could be easily
investigated.  Of the four tube combinations evaluated for recovery of the 41 VOCs as a function
of varying the  helium purge  volume,  two combinations  worked  satisfactorily.   When the
Tenax/silica gel/Ambersorb/charcoal focusing tube was used in combination with either the
Tenax/Ambersorb/charcoal or' the Carbotrap C/Carbotrap B/Carboxen 1000  sorbent tubes, the
large amount of water left on the sorbent tube at low-helium purge volumes resulted  in decreased
responses for lighter compounds eluting simultaneously with the broad water peak.  The responses
of compounds which eluted after the water had eluted were not affected.  Examples of this are
presented in Figures la and Ib.  When the Carbotrap B/Carboxen  1000 focusing tube was used in
combination with either the Tenax/Carboxen 1000 or Tenax/Ambersorb/charcoal sorbent tube,
                                         397

-------
substantially less water was retained, and the response of the lighter compounds was not suppressed
at lower helium purge volumes.  This is illustrated in Figure Ic.
      The results of the linearity tests  for both the 41-compound mixture and the polar mixture
showed good linearity for most compounds for up to 1  L of sample  collected. Some compounds,
such  as  benzyl  chloride,  m-, p-,  and  o-dichlorobenzene, chlorobenzene,  and  1,1,2,2-
tetrachloroethane collected  on the  Tenax/Ambersorb/charcoal tube and the polar compounds
collected on the Carbotrap C/Carbotrap B/Carboxen 1000 tube, were observed to be linear for up
to 2 L of sample collected. Bromomethane became nonlinear when more than 500 cm3 of sample
was collected on the Tenax/Ambersorb/charcoal tube, possibly because at higher sample volumes
the bromomethane travels into a sorbent layer from which it is not easily desorbed.  The linearity
results for two representative compounds are presented in Figure 2,
      For retaining the Q compounds,  the optimum operating parameters were determined to be
heating the collection tube 2 min and cooling 0 min.  When the tube was heated and cooled for
3 min and 2 min, respectively, as for the 41-compound mixture, the ethene and acetylene were not
retained. To obtain better separation of the light compounds for the determination of recoveries,
the GC oven was programmed as follows:  -50 'C for 2 min,  8  •C/min to 150 *C, 150 *C for
3 min. The best tube combinations for recovering the €2 compounds were Tenax-GR/Carboxen
1000/Carbosieve S-III or Tenax-GR/Carboxen 1000/Spherocarb sorbent tubes coupled with a
Tenax-GR/Carbosieve  S-III focusing tube.  With these tube combinations,  recoveries  were
estimated to be -100% for ethane, -70% for ethene, and -30% for acetylene when a 500-cro
helium  purge volume was used.  Other  tube combinations tested retained less, if any, of the
ethylene and acetylene when purged with 500 cm3 of helium. A sorbent tube combination that will
retain 100% of acetylene and ethene has  not yet been identified.
      The ACEM 900 was easily programmed for unattended, continuous operation, and the
system ran without fail for the two 24-h experiments.  Figure 3 is a plot  of the concentration of
dichloromethane observed in  the laboratory air  vs. time of day for the experiment using foe
Tenax/Ambersorb/charcoal sorbent tube and the Tenax/silica gel/Ambersorb/charcoal focusing
tube combination.

CONCLUSIONS
      The Dynatherm ACEM 900 preconcentrator offers several attractive features. It is reliable
and easy  to  operate.  The instrument  requires  no  cryogenic  liquids  and may be operated
unattended, and the helium purge option allows water to be removed from the sample  without
removing polar VOCs. These features contribute to the ACEM 900's promise as a preconcentrator
for use in an autoGC network for monitoring polar and nonpolar VOCs. However, the instrument
must be further evaluated to compare the results of these experiments with those of a cryogenic
preconcentrator and to challenge the system with the  very low (low-part-per-billion-by-volume)
levels of VOCs found in ambient air.

REFERENCES
1.  WA. McClenny, G.F. Evans, K.D. Oliver et al., "Status of VOC methods development to meet
monitoring requirements for the Clean Air Act Amendments of 1990," in Proceedings flf tt*e *991
U.S. IjPA/A&WMA  International Symposium on Measurement of Toxic anfl  P?lfltgrf All
Pollutants." VIP-21, Air & Waste Management Association, Pittsburgh, 1991, pp 367-374.
2.   W.T.  Winbeny,  Jr.,  N.T. Murphy and R.M. Riggin, Compendium ^f Mfttimfr  fnr ***
Determination  of Toxic  Organic  Compounds  in  Ambient  Air.  EPA-600-4-84-041,  U.S.
Environmental Protection Agency, Research Triangle Park, 1988.
3.  K.D. Oliver and J.D. Pleil, Automated Cryogenic Sampling and Gas ChromaKfeTflphfc Analysis
of Ambient Vapor-Phase Organic Compounds: Procedures and Comparison Tests. TN4120-85-02,
EPA contract 68-02-4035,  Northrop  Services, Inc., Research Triangle Park, NC, 1985.
                                          398

-------
                  2000
                  1600


               43
               §  1200
               o
               U

               3   800
                   400
             B
   o

2000



1600
               g  1200
 400



   0

2000



1600



1200
              U         • •    •

               8   800"
                      II ••
               o
               U
               3   800
                   400



                     0
                                                        Vinyl Chloride
                                                        Benzyl Chloride
                                      Vinyl Chloride
                              200      400      600     800

                                    Purge Volume (cm3)
                                              1000
Figure 1. Effect of purge volume on Cl response with different sorbent tube - focusing tube
         combinations: Tenax/Ambersorb/charcoal-Tenax/silicagel/Ambersorb/charcoal (A)
         and (B), and Tenax/Carboxen 1000 - Carbotrap B/Carboxen 1000 (C).
                                         399

-------
                                                B
   50x103
   40x103
   30x103
|

§.  20x103
   10x103
                               1,2-Dibroiruwthane
                               500-tm1 Purge
                                                40x103
                                                30x101
                                                20xHP
                                                10x10)
               400     800     1200     1600    2000

                  Sample Volume (cm3)
                                                                           Methyl Melhacrylate
                                                                           500-cin1 Purge
                                                           400     800     1200    1600

                                                               Sample Volume (cm-1)
Figure 2. Linearity test  with (A) Tenax/Ambersorb/charcoal  - Tenax/silica gel/Ambersori)/
          charcoal  tubes and  (B)  Carbotrap C/Carbotrap  B/Carboxen  1000 -  Tenax/sili«a
          gel/Ambersorb/charcoal tubes.
            5.0
            4.0
         a
         a
         a  3-°
         o
         o
        U
            2.0
            1.0
            0.0
                  Dichloromethane
                                                           Release of
                                                         Dichloromethanef
                                                           in Nearby
                                                             Hood
               2:00 pm
                            July 2
                                         12:00 am

                                             Time
July 3
               2:00 pm
Figure 3.  Diurnal variation in concentration with the ACEM 900 and the Tenax/Ambersorb/
          charcoal  sorbent  tube  -  Tenax/silica  gel/Ambersorb/charcoal  focusing  tube
          combination.
                                             400

-------
 DESIGN CONSIDERATIONS FOR AN AUTOMATED ON-LINE AIR SAMPLING
                                    SYSTEM

G. Broadway and E. Woolfenden, Perkin-Elmer Ltd, Beaconsfield, Bucks., UK and
J. Ryan and I. Seeley, The Perkin Elmer Corporation, Wilton, CT.
Introduction
       The 1990 Clean Air Act Amendments requires that ambient air be monitored for
concentrations of ozone and its precursors. Certain volatile organic compounds, including
light hydrocarbons and aromatics, are generally regarded as precursors to ozone formation
over urban and industrial areas and may be present in the atmosphere at low ppb
concentrations. Sampling ambient air may be performed in a number of ways. Whatever
method is chosen, it is usually necessary to perform some preconcentration step on the
sample before analysis by gas chromatography is feasible.  The most common methods are
collection in evacuated, passivated canisters or by drawing air through a tube containing
an adsorbent. Both techniques have drawbacks; passivated canisters suffer in that they are
suited only to short term "spot" samples whereas the tubes are more suited to time
weighted averaged sampling over longer periods. Neither technique is suitable for the
detection of diurnal variations in ambient concentration of volatile organic compounds.

       The system described in this paper enables automatic sampling of ambient air at
regular intervals throughout the day. Such sampling is likely to be required at relatively
remote non-laboratory locations. Therefore, one major requirement of the system was
that sampling and subsequent chromatographic  separation should not require liquid
cryogens.  The system uses a commercially available apparatus which can also be used for
analysis of both passivated canisters and sampling tubes.

Methodology
       A schematic of the system is shown in Figure 1. Air is sampled using a Perkin-
Elmer ATD-400 thermal desorption instrument equipped with a standard injection
accessory (valve 2). The  standard ATD-400 glass-lined stainless steel tubing was
modified to allow a sample of ambient air to be  pulled through the electrically cooled
trap (which is incorporated in the ATD-400) for a fixed time period using a small pump.
A Tylan mass flow controller was incorporated in the system to ensure that the air
volume sampled remained constant.  A separate valve (valve 1) has also been incorporated
into the system enabling a standard gas mixture  to be sampled at regular intervals for
calibration. Although the packed trap can tolerate  relatively large amounts of water [1], a
Nation dryer has been included between the first and second valves to reduce the amount
of moisture reaching the Peltier cold-trap. The performance of such a dryer has been
described previously [2].  After the sampling period, valve 2 is switched so that carrier gas
is directed through the trap.  Simultaneously, the trap is rapidly heated to transfer the
adsorbed compounds  to the gas chromatographic column. The performance
characteristics of the trap have been described previously [3] and it has been shown that by
                                       401

-------
using an adsorbent filled trap, a temperature of -30 °C may be used to retain compounds
with boiling points in the order of -90 °C [4,5] and eliminates the need for liquid cryogen
for this application.
Figure 1. Principle components of the air sampling system.

To enable the gas chromatographic separation to take place at super ambient
temperatures, a two-column system has been developed based on the Deans' principle of
remote pressure switching [6]. The hardware used is identical to that described by
Johnson [7,8], but employs a 50m x 0.22mm id l.Oum BP5 precolumn and an analytical
column, 50m x 0.32 mm AljOj column deactivated with
The second column was chosen in preference to the more common AljOj/KCl deactivated
column because the column manufacturer states that the former is more tolerant of
moisture that the latter. The separation of a 60 component USEPA evaluation sample
mixture using this column configuration is shown in figure 2 with the component
identification listed in Table 1.
                                      402

-------
                                     11 u J
Figure 2. A 60 component ozone precursor standard mixture at lOppb and 75% R.H.
Sample collected for 15 minutes at 20mL/min, trapped at -30°C. Trap heated at 40°C/sec
to 400°C and held for 10 minutes.  GC conditions: precolumn - 50m x 0.22mm l.Oum BP%,
analytical column - 50m x 0.32 mm A12O3 column deactivated with Na^O^ oven 40°C
for 5 minutes programmed at 15°C/min to 200°C for 15 minutes.
                                      403

-------
       Peak No.             Component.
        1                    ethane
        2                    ethylene
        3                    propane
        4                    propylene
        5                    iso-butane
        6                    acetylene
        7                    n-butane
        8                    trans-2-butene
        9                    1-butene
       10                    iso-butene
       11                    cis-2-butene
       12                    iso-pentane
       13                    n-pentane
       14                    3-methyl-l-butene
       15                    2-methyl-2-butene
       16                     trans-2-pentene
       17                     2,2-dimethylbutane
       18                     1-pentene
       19                     cis-2-pentene
       20                     methylcyclopentane
       21                     2-methylpentane
       22                     3-methylpentane
       23                     2-methylhexane  and 3-methylhexane
       24                     n-heptane
       25                     benzene
       26                    methylcyclohexane
       27                     2,3,4-trimethylpentane
       28                    toluene
      29                    2-methylheptane
      30                    3-methylheptane
      31                    n-octane
      32                    perchloroethylene
      33                    ethyl benzene
      34                    p-xylene  and  m-xylene
      35                    styrene
      36                    o-xylene
      37                    n-nonane
      38                    iso-propylbenzene
      39                    n-propylbenzene
      40                    1,3,5-trimethylbenzene
      41                    1/2,4-trimethylbenzene

Table I. Component identification for figure 2.
Results and Discussion
      System evaluation was performed using a 60 component mixture of hydrocarbons
and halocarbons listed for the USEPA Atlanta field studies as ozone precursors. The
components were present at a concentration of lOppb and were humidified to 75% R.H.
To trap all sample components, the trap was packed with a mixed bed of two carbon-based
adsorbents. A weaker adsorbent was used to retain the less volatile components and was
followed by a stronger adsorbent for the lower boiling compounds. During trap heating,
the gas flow through the trap was reversed to backflush the VOCs from the adsorbent bed
into the precolumn. In the evaluation, two factors were of greatest concern.
                                  404

-------
First, it was important that the trap retain all components of interest through the who
sampling period. Second, it was important that all of the sample be released to the gas
chromatograph when the trap was heated. Trap breakthrough was determined by
measuring the peak area counts for increasing volumes of sample introduced to the trap.
The C2 to C4 hydrocarbons, being most volatile and therefore most likely not to be strongly
retained, were studied for breakthrough. This was determined to be where area counts
cease to increase with increasing volumes of sample. Figure 3 shows the effect of
increasing the sample volume for C2 and C3 hydrocarbon. For the volumes studied, there
was no evidence of breakthrough for C3 and C4 hydrocarbons. However, it is evident that
breakthrough of ethylene occurs around lOOOmL.  Ethane continued to increase in a linear
manner to at least 2000mL, the largest volume measured. If the safe sampling volume is
considered to be one-half of the breakthrough volume, samples of up to 400mL may be
taken if it is important to determine either acetylene or ethylene. If neither of these
components is of interest, then volumes of lOOOmL or more may be taken.
             6OOOOO -i
             sooooo -
            '4OOOOO-
                          60  COMPONENT MIXTURE AT 7S» RH
           o
           o
             3OOOOO -
             200000 H
             1OOOOO-
                             500      1000      1500     2000
                                    SAMPLE  VOLUME (mL)
2500
Figure 3. Sample volume vs. chromatographic area counts

      To establish if all components were released from the Peltier device, the trap was
heated a second time and the chromatographic run examined for residual traces of each
compound. When the trap was held at its upper temperature of 400 °C for 10 minutes, no
carryover could be detected.
      If a 400mL sample is taken, it is estimated from the peak areas of the lOppb sample
that the detection limit is in the order of low ppb or even sub-ppb levels. However, this
will also be dependent on other interfering components in the sample at a particular site.
If the C2 hydrocarbons are not of interest, then the sample volume may be increased with a
corresponding reduction in the detection limit.
                                       405

-------
      The repeatability of the system has been found to be in the order of +10%. Table
II shows data for a number of representative compounds in the 60 component sample
mixture.
                                                           perchloro
         ethane      benzene      toluene      oc"taoe       ethylene     o— xylen

           333          684         233          263          125           319
           336          6OO         226          303          1O9           308
           298          551         21^'          233           95           283
           284          638         2O3          222           88           272
           284          535         197          218           92           296
           273          528         196          217           94           283

 ««n      301          589         212          243          1OO           293
 sd     24.70        57.0*       14.22        31.22        12.65         16.28
 rad       8,2*         9.71         6.7»         12.91        12.61           5.6X
Conclusions.
      This work shows that the system described is a convenient means of sampling air
and has been evaluated using a 60 component mixture of hydrocarbons known to be
precursors to ozone formation in the urban environment. By using a packed cold-trap
containing a mixed bed of carbon based adsorbent, a safe sampling volume of 400 mL can
be used for C2 determinations at -30 °C. The sampling volume determines the detection
limit which, for the standard 60 component mixture, is on the order of low ppb to sub-ppb
levels.  The system described uses commercially available instrumentation and is suitable
for tube type samplers and canisters as well as direct ambient air sampling.  By using a
Peltier-cooled trap and a two-column gas chromatographic system, the need for liquid
cryogenic cooling is eliminated, and a wide boiling range of compounds is separated in less
than 30 minutes.  The ability to work without liquid cryogen is an advantage when field
sampling is required.

References

   1. Perkin-Elmer Thermal Desorption Application Note 29.
   2. Piell, J.D., Oliver, K.D., McClenny, W.A. JAPCA,37:(1987),pp 244-248.
   3. Broadway, G.M., Trewern, T., Proc. 13th Intl. Symp. on Capillary Chrom., Vol 1, pp
      310-320.
   4. Kristensson, J., Schrier, (Ed), Proc. Analysis of Volatiles, International Workshop,
      Worzburg, F.R.G., 28-30th Sept. 1983, pp 375-378.
   5. Broadway, G.M., Proc 9th Australian Symp. on  Analytical Chemistry, Sydney 1987,
      Vol 1., pp 375-378.
   6. Deans, D.R., Chromatographia 1 (1968), pp 18.
   7. Johnson, G.L., Tipler, A., Proc. 8th Intl. Symp. on Capillary Chrom., Vol 1, pp 540-
      549.
   8. Johnson, G.L., Tipler, A, Crowshaw, D., Proc. 10th Intl. Symp.  on Capillary
      Chrom., Vol 2, pp 971-985.
                                        406

-------
  ADVANCES IN HIGH SPEED GAS CHROMATOGRAPHY FOR MONITORING
   GAS AND VAPOR CONTAMINANTS IN WORKPLACE AND AMBIENT AIR

          Huiqiong Ke (A), Steven P. Levine (A,*) and Richard Berkley (B)
 (A) The University of Michigan, School of Public Health, Department of Environmental
                and Industrial Health, Ann Arbor, MI 48109-2029
   (B) U.S. Environmental Protection Agency, Atmospheric Research and Exposure
     Assessment Laboratory, AREAL, MD-44, Research Triangle Park, NC  27709
                   (*) To whom inquiries should be addressed.

ABSTRACT

      The use of Fast-GC was investigated for the separation and analysis of mixtures
of organic vapors in ambient air. Mixtures of up to 34 components were separated. Total
analysis times ranged from 8 to 100 seconds. Analyses were performed  using both flame
ionization and electron capture detectors.

INTRODUCTION

      Gas chromatography (GC) is one of the most widely used analytical techniques
for  monitoring contaminants in  ambient  air,  especially for  analysis  of  low  and
intermediate molecular weight organic vapors such as those included on the U.S. EPA
list of 41 target compounds.  Starting in  1965, reports have appeared  about the theory
                                     2-8
and practice of "high speed" or "fast" GC. * Recently, we have reported on the design
                                                Q J2
and application of a  Fast-GC system to air monitoring.    In this study, we report on
the bases for choosing optimal conditions for use of Fast-GC in monitoring of complex
mixtures of organic vapors in air.

METHODS

      The Fast-GC is based on the use of optimized components for each GC module:
injector, column, detector, electronics. The injector is based on  a capacitive  discharge
which is used for rapid heating.13 The system design has been presented previously.9'12
      A model  301 gas  chromatograph (HNU Systems, Inc., Newton  Mass.)  was
modified to use both a standard HNU flame ionization  detector (FID) and an HNU
                                       407

-------
Systems-Nordien electron capture detector (ECD) which had  a cell volume of 90
microliters.
                                                                          p
       The cold trap was a  15 cm long, 0.25 ram i.d.  x  0.625  mm o.d. Monel  400
capillary tube which was cooled to -120°C by a continuous flow of cold nitrogen gas that
had passed through a copper tube immersed in liquid nitrogen.
       The frozen sample was rapidly vaporized to form a narrow injection band by
running a pulse of current through the trap tubing. Details of the inlet system design and
performance characteristics have been presented elsewhere.9-12
       Five, ten and thirty meter 0.25  mm i.d. capillary columns were used with a O.I
urn bonded methyl silicons stationary phase (Quadrcx). Hydrogen  was used as the carrier
gas for FID and operated at average linear  velocities ranging from 60 to  175 cm/sec.
Hydrogen, or argon with 5% methane was used as the carrier gas  for ECD. The velocity
of argon was from 34 to 50 cm/sec and make-up gas of argon/methane was used at a flow
rate of 120 ml/min.
       The mixtures of gas  standards  used  in this study were obtained from the U.S.
EPA (AREAL, Research Triangle Park, NC), and were delivered in  Summa-polished
cannisters. Those mixtures contained 41 compounds routinely analyzed in ambient air
samples by the AREAL.

RESULTS AND DISCUSSION

       The significant advantage of Fast-GC is a 50 to 100-fold reduction in  analysis
time while maintaining resolution. Because Fast-GC must be operated isothermally, it is
important to  consider those factors  necessary for optimal operation,  especially when
separating components of complex mixtures. These factors include: column conditions:
(carrier gas velocity, column length, oven  temperature),  and detector operation. The
question of the relationship between carrier gas velocity and column efficiency has been
well-developed.      In  this study, the computer model written in our laboratory by
                  1718
Mouradian and Puig      was used.
       The instrument dead-time values were chosen  to  be representative  of those
estimated for  this system, as well as values reported in the literature for similar systems
(about  I ms).  '   A diffusion  coefficient in the gas phase of 0.6 cm /sec was used for
hydrogen.  A liquid phase diffusion coefficient of 9 X 10   cm/sec was used.      The
gas viscosity  was estimated at  105 uP, which is characteristic of hydrogen gas at 100
   22
°C.   A capacity factor of two  (K=2) was used to represent a "typical" analyte cluting in
the middle of the chromatogram. Predicted optimum linear carrier gas velocities of 110,
                                       408

-------
 85, and 60 cm/sec (3.2, 2.5 and 1.8 cm^/min) were obtained from the computer model
 for columns of 5, 10 and 30 meter lengths .
       In order to baseline-resolve the most volatile components of complex mixtures, a
 2*3 minute chromatographic analysis must be performed using a 30 meter column. On
 the other hand,  if there are only  seven principal components of interest (carbon
 tetrachloride through  chlorobenzene), then the separation can be accomplished in 20
 seconds using a 5 meter column.     According to chromatographic theory, resolution is
 proportional  to the square root of the column length at the  optimal carrier gas flow
 condition. The increase in resolution when going from a 5 meter to a 10 meter column
 was predicted to be (2)1/2, or 1.414. The predicted increase in resolution when going
 from a 5 meter to a 30 meter column would be (6)'^ or a factor of 2.45. These results
 represent  very  good  agreement  between  theory and  practice,  and should guide the
 chromatographer in setting up the method to minimize analysis time  and ensure the
 separation of critical pairs of analytes.
       In addition to comparing the results obtained  for critical pair  resolution with
 column length to that predicted by theory, the efficiency of the system can be calculated
 for individual analytes. The parameters most indicative  of system performance are "NE"
 (number  of  effective  plates) and  "NE/second",  or the  number  of effective  plates
 "produced" per second. NE is equal to:

       NE - 5.54 (rtVwj/2)2'    whcrc

 if = "adjusted" retention time (retention time minus the retention time of a completely
 unretained peak), and  wj/2 = the peak width at half-height.
       In Fast-GC, a parameter of significance is how many effective plates are available
 in the  short time of the analysis. Thus, if a 20  second analysis is performed, only a
 certain number of plates will be needed to provide the  critical pair resolution described
 above. A useful objective, given the experience with the instrumentation described in this
 paper, is the production of close to 1000 effective plates per second  of analysis time. In
 this effort NE/second of 778 to 953 was achieved. Had  fewer been achieved under these
conditions, that would have been an indication of a problem with the system.
       Theoretical calculations indicate that, for example, the  case of TCE,  NE/second
should have been 981, 1301, and 805, for the 5, 10 and 30 meter column lengths. This
represents a loss of 8.6 to 32% in rate of plate production between what was obtained in
practice, and what was predicted by theory. If baseline separation of all components in a
                                       409

-------
 20-30 component mixture is required, then a 30 meter column and a 100 second analysis
 time will be necessary.
       For air monitoring applications, there are a significant number of analytes for
 which the FID will not be the detector of choice. The BCD is an alternative detector that
 may be useful  for compounds such as Freons.  The difficulty with using the  ECD
 primarily centers around the fact that it is a closed cell" type detector with internal "dead
 volume", as opposed to the FID, which is a zero volume detector.
       This internal dead volume leads to peak broadening. The detector used in this
 study had an internal  volume of 90 ul. Make-up gas is commonly used to reduce peak
 broadening when using closed cell detectors. Clearly, the more make-up gas that is used,
 the narrower that  the peak will get (up to a certain limit), but also the more  diluted
 samples will be in the detector cell. Thus, the detector response will be reduced when
 more make-up gas is used. For this instrument configuration, a make-up gas volume of
 120 cnrVmin was optimal. This was also effective in eliminating peak tailing.
       Even with the makeup gas, the performance of the system with the ECD did not
 match that with the FID.  One of the reasons  is  that the response time of the FID
 electrometer  was  5 msec, whereas the  response  time of the  ECD amplifier was
 approximately 100 msec. This effectively limits the minimum peak width signal that can
 be output from the Fast-GC, and must be corrected with higher speed amplifiers. These
 amplifiers are being developed.
       For an ECD, hydrogen  carrier gas can be  used as long as  the argon-methane
 make-up gas is also used.  For  an equivalent separation, the retention times when using
 hydrogen carrier gas  are  reduced by a factor of  two. The rate of plate production,
 NE/second, is doubled when using hydrogen  carrier gas. Even then, NE/second when
 using the ECD is significantly lower than that obtained when using the FID.

 CONCLUSIONS

       In this  study, the  applicability of Fast-GC was tested  for the analysis  of
components of complex mixtures of organic vapors in ambient  air.  The separation
achieved for components of these mixtures correlated well with the separation predicted
by theory.  In all  cases tested, appropriate compromise conditions  for separation  of
components could be established. This was important to the success of the method
because of the limitations imposed by the requirement that isothermal conditions be used
for these separations. Both FID  and ECD systems were applied successfully.
                                       410

-------
REFERENCES

1. J.D. Pleil, K.D. Oliver, W.A. McClcnney, " Ambient air analyses using nonspecific
flame ionization and electron capture detection compared to specific detection by mass
spectroscopy," JAPCA 38:1006 (1988).
2. D.H. Desty," Capillary columns: Trials tribulations and triumphs," in  Advances in
Chromatography, Vol 1, J.C. Giddings, R.A.  Keller, Eds., Marcel Dekker, New York,
1965,  pp. 199-228.
3. D.H. Desty, A. Goldup, W.T. Swanton," Performance of coated capillary columns," in
Gas Chromatography, N. Brenner, I.E. Callen, M.D. Weiss, Eds., Academic Press, New
York, 1962, pp. 105-135.
4. J.C. Sternberg,"  Extra  column contributions to chromatographic band  broadening,"
Advances in Chromatography, Vol 2, J.C. Giddings, R.A. Keller, Eds., Marcel Dekker,
New York, 1966,  pp. 203-270.
5. G. Caspar, R. Annino, C. Vidal-Madjar, G. Guiochon," Influence of instrumental
contributions on the apparent column efficiency in  high speed  gas Chromatography",
Anal.Chem. 50:  1512(1978).
6. G. Caspar, P. Arpino, G. Guiochon," Study in  high speed  gas Chromatography,"
J.Chromatogr.Sci. 15: 256 (1977).
7. A. van  Es, J. Janssen, R. Bally, C. Cramers, J. Rijks," Sample introduction  in high
speed capillary gas Chromatography: Input band width and detection limits," J. HRC&CC
10: 273 (1987).
8. C.P.M. Schutjes, E.A. Vermeer, J.A. Rijks, C.A. Cramers,"Increased speed of analysis
in isothermal and temperature programmed capillary gas Chromatography by reduction
of the  column inner diameter," J.Chromatogr. 253:1 (1982).
9.  R.F. Mouradian,  S.P. Lcvine, R.D. Sacks,"  Evaluation  of a  nitrogen-cooled,
electrically heated cold trap inlet for high  speed gas Chromatography," J.Chromatogr.Sci.
28: 643 (1990).
10. R.F. Mouradian, S.P.  Levine, R.D. Sacks, M.W. Spence,"Measurement of organic
vapors at  sub-TLV concentrations using  fast gas  Chromatography," Am.  Ind. Hyg.
Assoc. J. 51 (2): 90  (1990).
11. R.F. Mouradian, S.P. Levine, HQ. Ke," Measurement of volatile organics at  part per
billion concentrations using  a  cold  trap inlet and high speed  gas  Chromatography,"
JAPCA 41:1067-1072 (1991).
12. HQ. Ke, S.P. Levine,  R.F, Mouradian, R.  Berkley," Fast GC for environmental and
industrial health air monitoring," Am.Ind.Hyg.Assoc.J. 53: 130-137 (1992).
                                      411

-------
 12. HQ. Ke, S.P. Levine, R.F. Mouradian, R. Berkley," Fast GC for environmental and
 industrial health air monitoring," Am.Ind.Hyg.Assoc.J. 53: 130-137 (1992).
 13. L.A. Lanning, R.D. Sacks, R.F. Mouradian, S.P.  Levine, J.A. Foulke," Electrically
 heated cold trap inlet system for computer-controlled high-speed gas chromatography,"
 Anal. Chem. 60: 1994(1988).
 14. D.F, Ingraham, C.F.  Shoemaker, W. Jennings," Computer comparisons of variables
 in capillary gas chromatography," J. HRC&CC 5: 227 (1982)
 15. E.N. Fuller, P.D. Schettler, J.C. Giddings," A new method for prediction of binary
 gas-phase diffusion coefficients," Indus. Eng. Chem. 58: 19 (1966).
 16. R. Tijssen, N. van den Hoed,  M.E. van Kreveld/Theoretical aspects and practical
potentials of rapid gas analysis in capillary GC", Anal.  Chem. 59: 1007 (1987).
 17. R.F. Mouradian," Fast gas chromatography  for industrial  hygiene  analysis  and
monitoring," Ph.D. Thesis, University of Michigan, (1989).
 18. L. Puig," High speed vacuum outlet capillary gas chromatography with selective
detection," Ph.D. Thesis,  University of Michigan, (1990).
 19. L, Butler, S.J. Hawkes," Diffusion in long-chain solvents," J. Chromatogr. Sci. 10:
518(1972).
20. J.M. Kong, S.J. Hawkes," Diffusion in silicone stationary phase" J. Chromatogr. Sci.
 14:279(1976).
21. W. Milieu, S.J. Hawkes,"  Diffusion and-partition of  n-alkanes in dimethylsilicone
stationary phases," J. Chromatogr.  Sci. 15:  148(1977).
22. R.L. Grob, Modern Practice of Gas Chromatography, 2nd Edition, John Wiley &
Sons, Inc. New York, 1985, pp 296.

       Work was supported by U.S. EPA (AREAL/MRB) cooperative agreement CR-
817123-01-0. Earlier work leading to  this stage had been supported by the Centers For
Disease Control, National Institute for Occupational  Safety  and  Health  Grant  R-01-
OH02303, the U.S. EPA (OER) R814389-01, and The Dow Chemical Company Health
and Environmental Studies Laboratory.
                                      412

-------
EVALUATION OF COMMERCIALLY-AVAILABLE
PORTABLE GAS CHROMATOGRAPHS
R. E. Berkley, Environmental Protection Agency, Atmospheric
Research and Exposure Assessment Laboratory, Research Triangle
Park, NC 27711,

M. Miller and J. C. Chang, IIT Research Institute, Chicago, IL
60616

K. Oliver and C. Fortune, ManTech Environmental Services, Research
Triangle Park, NC 27709.


     Six commercially-available portable gas chromatographs (PGC)
were evaluated at a Superfund site during startup of bioremedia-
tion.  Concentrations of volatile organic compounds (VOC) were
slightly above ambient background levels.  Concurrent colocated
grab samples were collected periodically in Summa-polished canis-
ters.  They were analyzed by Method TO-14 using a mass-sensitive
detector.  The grab samples served as standards to assess the ac-
curacy of data reported by the PGCs.

Introduction
     Portable gas chromatographs (PGC) offer the advantage of pro-
viding immediate data.  They can often produce more information at
less cost than laboratory-based methods of analysis.  A variety of
PGCs are currently available.  During January 1992, we evaluated
five PGCs at the French Limited Superfund Site in Crosby, TX.  They
were selected on the basis that they were field-deployable, and the
manufacturers were each willing to provide technical support and a
unit for evaluation.

     The French Limited Superfund site is an abandoned sand pit
into which refinery waste has been dumped.  Before remediation, ten
feet of sludge underlay twenty-five feet of water, covering an area
                                413

-------
of seven acres.  The water was clear, but volatile solvents were
leaching from the sludge into ground water.  The  French  Limited
Task Group  (FLTG) , formed by the potentially responsible parties,
proposed bioremediation.  Their plan was approved by EPA after
successful pilot-testing.  They installed a containment  barrier
around the site projecting 65 feet downward into  a clay  layer
below and extending 15 feet above ground to keep  out flood water.
A similar barrier divides the pond in half; the two sides are being
treated consecutively.  Dredges loosen sludge  from the bottom of
the pond and high-speed stirrers mix it with the  water,  streams or
pond slurry are being pumped out of the pond,  injected with oxyge11
gas and nutrients, then pumped back into the pond below  the sur-
face.  This selectively enhances growth of those  strains of indi-
genous bacteria which feed on the sludge,

Experimental
     The PGCs (with their detectors) included  Photovac 10SPLUS -
10.6 eV photoionization (PID) , Microsensor Systems 301 - surface
acoustic wave, Sentex Scentograph - 11.7 eV Argon ionization, HNO
Model 311 - 10.2 ev PID, and SRI 8610 - 10.2 eV PID and  electro-
lytic conductivity (ELCD) .  A previously-evaluated Photovac 10S70
which is owned by EPA was also included (1,2).  All units were op-
erated inside a power-control shed located 20  feet away  from, an
15 feet above, the edge of the pond.  The interior of the shed was
maintained at about 70°F,  All units were connected to 110 volt oJJ
Hz commercial power.  Each unit used its own sample pump to i»por^
outside air through 1/8 inch OD stainless steel tubing.  Calibra-
tions were performed periodically using mixtures  prepared by dyn-
amic dilution of commercial standards (Alfagaz, Scott) and
in 6 liter Summa-polished canisters.  Grab samples were  taken
iodically by opening the valve of an evacuated canister  while
ing it as close as possible (within three feet) of the assemb     .
of intake tubes while they were collecting samples.  Grab canis*-eto
were returned to the laboratory and analyzed by GC/MSD according
Method TO-14.  Canister grab sample data were  taken to be true c
centrations of the compounds analyzed by the PGCs.

Results and Discussion
     Detection limits for the PGCs were calculated using data «c
quired during field calibrations.  They are shown in TABLE !•  r
the MSI 301, which doesn't have an identifiable baseline, and.r.
Scentograph, which doesn't output a baseline signal, it  was di* r-
ficult to estimate a meaningful detection limit.  Baseline dij! -^d»
bances can render calculated detection limits  meaningless, an t-
problems are common in field operations.  Any  of  the instrumenthaV«
operating uncontaminated in a more sheltered environment »i9nt
shown apparently-lower detection limits.
     TABLE 2 contrasts data from three grab samples with
ponding PGC data.  Analyte levels were near the detection l*  to
shown in TABLE 1.  The PGCs generally produced results
                                414

-------
the grab sample.  There were a few flyers, for example the HNU 311
at 10:30 and the Photovac 10S70 at 11:28.  These could have been
caused by poor mixing of air, contamination of equipment, or simi-
lar accidents.  Agreement between the methods, though not exact,
was close enough to show that all of the PGCs provided reasonable
estimates of the concentrations of compounds which they could
detect and for which they were calibrated.

     In TABLE 3 the degree of agreement between PGC and canister
data is analyzed in terms of the absolute values of the differences
between them.  Averages of absolute differences for each unit for
each compound are shown with their standard deviations (in paren-
theses) .  A low average difference indicates good agreement between
canister and PGC data.  The standard deviation, considered together
with the range, which is defined by the maximum and the minimum
values which are shown, indicates how consistent the agreement was
between PGC and canister data.  A small average difference with a
smaller standard deviation and a narrow range would indicate close
agreement between the two methods.  A large average difference with
a small standard deviation and a narrow range could be due to sys-
tematic error, perhaps an inaccurate calibration standard.  A small
average difference with a standard deviation of comparable magni-
tude and a narrow range would indicate that the PGC was producing
data of reasonable accuracy but mediocre precision.  That would be
expected when analyzing concentrations which are near detection
limits.  Most data in TABLE 3 are of that type.  A larger average
difference with a still larger standard deviation and a very broad
range would suggest a data set which contains a flyer.  Examples in
TABLE 3 are Photovac 10S70 (benzene), MSI 301 #10 (toluene), and
HNU 311 (benzene and toluene).  A large average difference with a
broad range and a standard deviation comparable in magnitude to the
range would indicate little or no agreement between methods.  That
pattern is not seen in TABLE 3.  Zero minimum values result from at
least one case of exact agreement between the two methods, but the
multitude of zero minima in TABLE 3 actually resulted from runs in
which neither method detected anything.

     All units performed as expected reasonably well.  Examination
of TABLES 2 and 3 shows agreement to better than an order of magni-
tude among all methods, except for the four bad points.  This is
encouraging, since these instruments were built according to dif-
ferent design criteria and intended for different applications.  In
view of this general agreement it would be futile attempt to rank
the instruments arbitrarily on the basis of the results obtained,
which in this casa reflects only their performance in one environ-
ment.  Concentrations of VOCs encountered during this study were
much lower than expected, and the range of concentrations was quite
narrow.  A study .carried out in a different environment might have
produced a similar body of data differing only in detail and pos-
sibly yielding no additional knowledge about relative capabilities.
                                415

-------
Conclusions
     The  instruments  evaluated  in this  study  all  performed satis-
factorily according to  claims for their capabilities.   All of  them
were able to detect the levels  of compounds encountered at the
French Limited  superfund Site,  usually  with a reasonable degree  of
accuracy,  choosing one of  them for  a particular  application should
be based  upon consideration of  its particular features  and capabil-
ities.

References
1. R. E.  Berkley, K.  Kronrailler, and K.  Oliver, Proceedings of the
   1990 EPA/AWMA  International  Symposium: Measurement of Toxic and
   Related Air  Pollutants,  849,  1990.

2. R. E.  Berkley, J.  L.  Varns,  and J. Pleil,  Environ. Sci.
   Technol., £5,  1439 (1991).
Disclaimer
     The information in this document has been  funded by  the United
States Environmental Protection Agency.  It has been subjected to
agency review and approved  for publication.


     TABLE 1. DETECTION LIMITS FOR PORTABLE GAS CHROMATOGRAPHS
                 CALCULATED FROM FIELD CALIBRATIONS


(parts per
billion by
volume)
Tetrachloro-
Benzene Toluene ethylene
Photovac 10SPLUS
MSI 301
Sentex Scentograph
HNU 311
SRI 8610 PID
SRI 8610 ELCD
0.5
6.7
3.8
2.7
0.4
NR
1.2
20.5
4.3
3.6
0.3
NR
0.5
INT
3.4
4.9
0.2
2.4

chloro-
benzene
1.5
INT
7.6
4.2
0.2
5.2
-
INT  Interference.  Another peak or an elevated baseline made  it
     impossible to calculate detection limit.
NR   No response to electrolytic conductivity detector.
                                416

-------
          TABLE 2. COMPARISON OF CANISTER GRAB SAMPLE WITH
                    PORTABLE CHROMATOGRAPH DATA
Several simultaneous colocated samples collected and analyzed on
January 18, 1992 at the French Limited Superfund Site.
                   (parts per billion by volume)

Time
10:30








10:59








11:28










Canister Grab Sample
Photovac 10S70
Photovac 10SPLUS
MSI 301 #06
MSI 301 #10
Sentex Scentograph
HNU 311
SRI 8610 PID
SRI 8610 ELCD
Canister Grab Sample
Photovac 10S70
Photovac 10SPLUS
MSI 301 #06
MSI 301 #10
Sentex Scentograph
HNU 311
SRI 8610 PID
SRI 8610 ELCD
Canister Grab Sample
Photovac 10S70
Photovac 10SPLUS
MSI 301 #06
MSI 301 #10
Sentex Scentograph
HNU 311
SRI 8610 PID
SRI 8610 ELCD

Benzene
3.3
3.9
4.2
5.0
2.0
11.0
163.0
3.8
NR
1.6
NA
ND
3.0
1.0
ND
ND
2.0
NR
2.7
22.9
3.2
4.0
1.0
ND
ND
3.6
NR

Toluene
3.1
7.1
3.9
2.0
1.0
ND
88.0
4.6
NR
1.3
NA
2.0
1.0
1.0
ND
ND
2.0
NR
2.5
5.1
2.7
1.0
1.0
ND
1.2
4.1
NR
Trichloro-
ethylene
0.2
ND
0.5
ND
ND
ND
ND
0.0
ND
ND
NA
ND
ND
ND
ND
0.2
ND
0.5
0.1
ND
ND
ND
ND
ND
0.3
ND
0.4
Chloro-
benzene
0.3
0.3
0.9
ND
ND
ND
ND
0.8
ND
0.1
NA
ND
ND
ND
ND
0.4
0.8
ND
0.2
4.0
0.5
ND
ND
ND
0.1
0.7
ND

ND   Not detected.
NA   Not analyzed.  Photovac 10S70 calibrated automatically.
NR   No response to electrolytic conductivity detector.
                                417

-------
          TABLE 3. ABSOLUTE VALUES OF DIFFERENCES BETWEEN
                CANISTER TO-14 REFERENCE METHOD AND
                  PORTABLE GAS CHROMATOGRAPH DATA
Absolute differences between concentrations found by the portable
gas chromatograph and concentrations found in a simultaneous
colocated canister grab sample.  Samples collected at French
Limited Superfund Site during startup of bioremediation.
January 11 - 19, 1992                 (parts per billion by volume)

Benzene
Photovac 10S70 (14 samples)
Maximum 20.3
Mean (STD) 2.5 (5.0)
Minimum 0.3
Photovac 10SPLUS (14 samples)
Maximum 2 . 5
Mean (STD) 1.0 (0.6)
Minimum 0.1
MSI 301 #06 (13 samples)
Maximum 12 . 0
Mean (STD) 2.3 (2.9)
Minimum 0.5
MSI 301 |10 (13 samples)
Maximum 4 . 4
Mean (STD) 1.7 (1.1)
Minimum 0.2

Toluene

4.1
1.3 (1.1)
0.0

2.0
0.8 (0.6)
0.0

3.2
1.2 (0.7)
0.3

41.0
6.8 (13.3)
0.0
Trichloro-
ethene

0.3
0.1 (0.1)
0.0

2.7
0.3 (0.7)
0.0

0.2
0.1 (0.1)
0.0

0.2
0.1 (0.1)
0.0
Chloro-
benzene

7.8
1.2 (2.1)
0.0

1.7
0.4 (0.5)
0.0

0.3
0.1 (0.1)
0.0

0.3
0.1 (0.1)
0.0
Sentex Scentograph (13 samples)
Maximum 7 . 7
Mean (STD) 2.2 (1.9)
Minimum 0 . 4
HNU 311 (15 samples)
Maximum 159 . 7
Mean (STD) 11.9 (39.5)
Minimum 0.1
SRI 8600 PID (13 samples)
Maximum 6.2
Mean (STD) 1.6 (1.5)
Minimum 0.1
SRI 8610 ELCD (13 samples)
Maximum
Mean (STD) NA
Minimum
3.5
1.9 (0.8)
1.0

84.9
7.1 (20.8)
0.4

7.6
1.8 (1.8)
0.2


NA

0.2
0.1 (0.1)
0.0

0.2
0.1 (0.1)
0.0

1.4
0.3 (0.4)
0.0

3.4
0.5 (0.9)
0.0
0.3
0.1 (0.1)
0.0

0.3
0.1 (0.1)
0.0

1.6
1.0 (0.3)
0.6

7.2
2.1 (2.9)
0.0

NR   No response to electrolytic conductivity detector.
                                418

-------
System for Real Time, Hourly Analysis of C2 - C,0
Compounds  in Air Using 55  Minute Sample Integration
                 Peter J. Milne, Rod G. Zika and Charles T. Fanner
                          RSMAS-MAC, University of Miami
                      4600 Rickenbacker Cswy, Miami,  FL 33149

                                 Daniel B. Cardin
                           ENTECH Laboratory Automation
                    950 Enchanted Way #101, Simi Valley, CA 93065
ABSTRACT
An integrated system that quantitatively measures speciated C2- CH, hydrocarbons and other
volatile organic chemicals (VOC's) down to the sub ppb range is described, Sampled air
was collected for up to 55 minutes of each hour into an integrating canister, without the use
of sorbents or cryogens. Subsequent analysis, by cryotrapping and cryofocussing gas
chromatography (GC), with either flame ionization (GC-FID) or mass selective (GC-MSD)
detection, allowed for quantitation and  identification of sampled VOC's .  Under the
chromatographic conditions used, the total analysis time of one hour enabled concurrent
sampling and analysis of the previously collected sample in a continuous,  automated  mode.
The  use of this system over a two week exploratory campaign at a remote field site in
Tampa, Florida (Sep '91) is discussed.

INTRODUCTION

      Control strategies for the regulation of ozone levels in urban atmospheres are
presently under active revision (National Research Council'). Despite some twenty years of
federally mandated regulation, EPA estimates that some 67 million people in the USA are
now routinely exposed to ozone levels exceeding those set under the Clean Air Act. VOC's
are important precursor compounds that, in conjunction with nitric oxide and nitrogen
dioxide, photochemicatly catalyze the formation of tropospheric ozone. It is likely that
existing inventories of many reactive VOC's in urban atmospheres are inadequately known.
This situation negates the efforts of atmospheric modelers trying to understand  urban  air
quality. It further places constraints on containment and control strategies for  ozone
attainment.
        Several existing analytical difficulties  must be overcome before the knowledge base
of VOC inventories can be expanded. The first of these is that there are so many individual
compounds, literally hundreds in complex urban atmospheres. Further, this diverse range of
compounds arises from widely different sources. A second consideration is that many of the
most important ozone precursor VOC's are reactive, so that their presence in air maybe
                                        419

-------
ephemeral, or otherwise restricted in space and time. For instance, the contribution natural
vegetation makes to urban VOC loads has recently been subject to renewed interest2. Other
considerations include the low concentrations (ppb to ppt) of these compounds and also the
large amount of data that continuous speciated monitoring  of even modest target lists of
VOC's entails.

Analytical approach

       Necessary steps  in the VOC  analyses of ambient air by capillary GC, which is the
most widely used method,  usually include variants of the following:
       a) sample introduction or collection
       b) an enrichment or concentration step
       c) cryofocussing step
       d) quantitation of detector response (FID, MSD etc) against known standards.
Several strategies have been used to achieve the first two of these steps. In the first, and the
most 'state-of-the-art' of these,  ambient air is sampled into stainless-steel containers that have
been carefully pretreated and cleaned3'4-5. Electropolishing of all internal surfaces and
electron-beam vacuum welding  of the canister connections ensure the optimum performance
(i.e. inertness) of these  vessels.  Providing that the collection of air sample by means  of an
metal bellows or other inert pump into the canister is achieved, canister sampling allows the
collection and stable storage  of a large number of atmospheric trace components at ppb
levels and less. The collected air samples are transported to a laboratory for analysis.  The
disadvantage to this scheme is the relative expense of the canisters themselves. This is the
main reason that other containers such as glass vessels, or Teflon and Tedlar sample bags are
still employed although  it is well-known that they may cause  contamination effects
substantially higher than the ppb range. These vessels also must be shielded from ambient
light in the analysis of photochemically sensitive  components.
       The use of a number of solid  sorbent materials for sampling and enrichment of air
samples has also been used6'7-8.  An ideal solid sorbent would  selectively adsorb only the
target trace organic compounds and not interact  with any other atmospheric constituents.
Thermal  desorption and subsequent chromatographic analysis would allow separation and
quantitation of the VOC's.  In practice, sub-optimum usage can  involve one or more of the
following:
       i) sorbent bleed-off of interferant or target VOC's  (this may be alleviated by
thorough cleaning prior  to the concentration step9)
       ii) low break-through volumes  for some volatile VOC's10
       iii) incomplete desorption of individual VOC's
       iv)  chemical interaction of target VOC's  with sorbent
       v) chemical interaction of other trace atmospheric components (e.g. Oj, NO, NO2,
halogens  etc)  with adsorbed VOC's) leading to artifacts and losses11'12-13.
       A third approach combines the sampling and enrichment of VOC's into one step.  The
compounds are frozen out (liquid nitrogen) in a cold trap, and then analyzed directly in a
field laboratory. If correctly implemented, this "on-line" approach  should be subject to
minimal sampling artifacts14'15.
                                          420

-------
       The automated concentrator used in this study (ELA 2000, Entech Laboratory
Automation, Simi Valley, Ca) has previously been described for semi-automated use in the
analysis of canister samples16. Modifications to the hardware and procedural details that we
have made here have demonstrated the utility of this device for continuous 'on-line'
monitoring from an all glass sampling manifold and  subsequent capillary GC analysis in a
mobile field laboratory. With the provision of an independent mass flow controller (ELA
4510 Realtime Interface, Entech, Simi  Valley, CA),  a time integrated sample was
accumulated into an electropolished SUMMA canister, every 55 minutes. At the end of this
period, a subsample was automatically  introduced into the ELA 2000 concentrator. The
integrating canister was then evacuated, and  the integration-fill cycle recommenced. During
the ensuing 55 minutes, the GC analysis was completed, and the whole cycle repeated.

EXPERIMENTAL

       Materials and Chemicals. Gases for the GC included; He, 99.999% purity (Liquid
Carbonic, Chicago, II), zero air generator (Type 75-85, Balston, Lexington, MA), hydrogen
generator (Model 8400, Packard, Downers Grove, II). Calibration gases were commercially
obtained (Scott Specialty Gases, Plumsteadville, Pa), but the mass calibrant gas mixture was
a NIST traceable butane - benzene mix supplied to us by Dr. Eric Apel (NCAR). Chemicals
used for identification purposes were analytical grade from Aldrich (Milwaukee, Wi).
       Chromatography column was a  30m, 0.25mm, l.Ojim film thickness, DB-1 capillary
(J&W Scientific, Folsom, CA).
       Stainless steel (Supelco, Bellefonte, Pa) tubing was used for gas supply lines. All gas
supply regulators were high purity regulators (various suppliers). Stainless steel canisters
were of the two valve (Nupro) type supplied by BRC Rasmussen (Hillsboro, Or).  Vacuum
pumps were all teflon wetted surfaces (KF Neuberger, Princeton NJ).
       Gas Chromatography. A HP 5890  Series II (Hewlett Packard,  Avondale, PA) with a
Cool On-Column Cryo option and FID detector was used.  A HP 5971A mass selective
detector could also be interfaced to the GC system. Data reduction was carried out using HP
3365 Chemstation II software on PC-Dos based personal computers.  The temperature
program used was: 3 min at -50 C, ramp at  8 C/min to  10 C,  then 5 C/min to 150 C, 40
C/min to 250 then held for 6.5 min.
       Measurement Conditions Fig. la gives an overview of the analytical systems as
configured for this study. Most of the sixteen possible inlet ports to the concentrator were not
used in this work, although three were dedicated to routine canister sampling from other
sites.  Fig Ib. shows a schematic of the sample integration device. Important components of
the ELA 2000 included: i) the cryotrapping module which was  a nickel tube (0.3  cm o.d., 25
cm long) filled with glass wool, deactivated  silica and glass beads ii) a Nafion drying
module for water removal (which could be replaced  with a short length of stainless steel
tubing under conditions of moderate ambient humidity or low sample volume (i.e. <400 ml)
and iii) a small volume (Megabore tubing) cryofocussing trap interfaced to the analytical
column.  All concentrator functions including operation of a multiport sample introduction
valve, external device (GC) signal recognition, cryogen delivery valves,  heated zone
temperature control, internal gas (purge nd sweep) flow settings, and system bakeout
                                          421

-------
 functions were under software control (Entech) implemented from a personal computer.
 Table 1 gives an overview of the steps of an analysis cycle.
       field Laboratory and sampling site The above equipment together with a deployable
 10 m aluminium met tower and Pyrex (4 cm i.d.) sample manifold were transported to the
 field site at Simmons Park, Tampa, Florida in a 33  ft recreational vehicle that had been
 previously outfitted as a mobile laboratory17. Power, and regular deliveries of cryogen {Liq.
 N2), were available at the site, which is a recreational park operated by Hillsboro County and
 situated at a coastal semi-rural area to the east of Tampa Bay at Ruskin.
          Table 1. Analytical cycle of VOC analysis with ELA 2000
   concentrator
         Step   Event                                          Condition

         1.     Wail forGC ready
         2.     Flush manifold and concentrator lines                    1 inin
         3.     Set temperatures internally                            Cryoirap -16$ C
         4.     Draw sample volume through e ryot rap                   450 ml
         5.     Record initial, final sample pressure
         6.     Sweep lines to ensure quantitative transfer                5 min
         7.     Cool cryofocussing trap                              -185 C
         8.     Heat sample trap, backflushing onto cryofocusser           Cryotrap ISO C
         9.     Inject VOC's onto capillary column; send Start CC signal
         10.    Bake out traps; wait for set time befo're recycling
RESULTS AND DISCUSSION
       Fig.2 shows some representative chromatograms taken during the course of one day
of the  10 day field study. Only a few of the identified peaks are annotated for clarity,
concentrations are given as ppbC.The normal method of operation on site was to analyze the
integrated samples, from the tower manifold, hourly from 08:00 to 20:00 and then to take
one more integrated sample from 24:00 to 01:00. During the rest of the time, canister
samples collected during the day as well as can blanks and calibration standards were run.
One other mode of operation of the concentrator was also possible. This was  to sample
directly out of the glass manifold onto the cryotrap. Since the mass flow controller on the
concentrator  was set at lOOml/min, a sample integrated directly in this manner would take
some 4.5 minutes to collect.  Higher sample volumes with any of these different sampling
modes is subject to higher sampled amounts of water vapor.
       Once  the automated methods for a run of  continuous integrated  samples had been
                                           422

-------
programmed into the controlling computer, operator intervention was minimal. The most
immediate responsibility of the operator was to ensure that the cryogen tank did  not empty
during a crucial portion of the analytical cycle. Cryogen usage by  the system was
approximately 30-35 samples per 160 liter cryogen tank, i.e. it was necessary to switch tanks
every day and a half or so.  On site, the cryogen tanks were situated outside of the mobile
laboratory, for part of the day in direct sunlight. The potential cryogen usage may have been
even better than indicated.
        Peaks  in ambient air samples were  identified by their retention times in comparison
with known multicomponerit standards.  Several ubiquitous peaks in the real samples also
served as reference peaks in conjunction with the HPChem Station software.  Retention time
variability was in large part due to the relative complexity of the temperature program
employed for the field study. Retention times for over sixty compounds were determined,
Detection limits of quantified components were of the order of 0. IppbC or less.  System
blanks, as determined by sampling equivalent (450ml) volumes of  either N2 gas (from liq. N2
bleed-off) or from the zero-air generator were satisfactory and reproducible over time. When
the Entech  concentrator was first received,  a persistent low molecular weight interferant,
bleeding off from some of the solenoid valves in the unit  had to be repeatedly baked out. The
sample to sample hold-up within the integrating canister was judged to be minimal by
observing the repeated return to low VOC levels of the late evening samples, although this
was not directly tested for.  The Simmons Park field site was  however, the cleanest of the
three sites that were monitored during the study. Canister samples taken at the other,  more
urban, sites were routinely  cleaned (three evacuation and  flushing cycles while being heated
to 50 C) and blanked.

SUMMARY  AND CONCLUSION

       Consideration of the acquired data set is beyond the scope of this presentation. The
described instrumentation proved to be a reliable and trouble free means of acquiring an
extensive field data set  with relatively low man-power needs. Over 150 GC-FID runs plus
some 20 or so GC-MSD runs were made during the two week study. Several modifications
and refinements to the overall chromatographic procedure suggested by our experience
remain to be iplemented, but appear to be achievable within  the described framework.

Acknowledgements
       The authors thank Mr Thomas Tamanini and the staff of the Environmental Protection
Commission of Hillsboro County for their co-operation and interest. This  work was
supported by the EPA as part of the SOS Southern Oxidant Research Program on Ozone
Non-Attainment (SORP-ONA).

REFERENCES
!• Rethinking the Ozone Problem in Urban and Regional Air pollution. National Research Council. National
Academy Pre«, Washington, D.C., 1991.
                                          423

-------
2. W.L. Chameides, R.W.  Lindsay, J. Richardson andC.S. Kiang, "Tlie role of biogenic hydrocarbons in urban
photochemical smog: Atlanta as a case study," Science 241, 1473-1475 (1988).

3. D.R. Cronn. R.A. Rasmussen, E. Robinson and D.E. Harsch, "Halogenated compound identification and
measurement in the troposphere and lower stratosphere " J. Geonhvs. Res.. 82, 5935 (1977),

4. J.P. Greenberg and P.R. Zimmerman "Nonmelhane hydrocarbons in remote tropical, continental and marine
atmospheres", J. Oeop|iys. Res,. 89, 4767 (1984),

5. J. Rudolph, K.P. Muller and R. Koppmann, "Sampling of organic volatile* in the atmosphere at moderate and
low pollution levels", Anal.  CJiim^cjik 236, 197 (1990).

6.K. Orob and G. Grob,  "GLC mass-speclroinetric investigation of C6-C20 organic compounds in an urban
atmosphere.  Application of ultratrace analysis on capillary columns', J. Chroinaloer. 62,  1 (1971).

7. E.D. Pellizari, F.E. Bunch, B.K. Carpenter and E. Sawicki, "Collection and analysis of truce organic vapor
pollutants in ambient atmospheres ",  Environ. Sci. Techno!.. 9, 552, (1972).

8.J.M.  Roberts,  R.S. llutte, F.C. Fehsenfeld, D.L. Albrillun and R.E. Sievers, " Measurements of anthropogenic
hydrocarbon concentration ratios in the rural  troposphere: discrimination between background and urban sources"
Almosph. Environment. 19, 1945 (1985).

9. N. Schmidbauer and M.  Oehme,  "Comparison of solid adsorbent and stainless steel canister sampling for very
low ppt-concentrations of aromatic compounds (> Q) In ambient air from remote areas",  Fresenius Z.  Anal.
Chem..  331. 14(1988).

10. I.F. Pankow, "Gas-phase retention volume behavior of organic compounds on the sorbent poly(oxy-m-
terphenyl-2', S'-ylene", Anal. Chem.. 60, 9SO (1988).

1 l.E.D. Pellizzari and K.J. Krost, "Chemical transformations during ambient air sampling for organic  vapors",
Anal. Chem.. 56. 1813(1984).

12. J.F. Walliog, J.E. Buingarner, D.J. Driscoll, C.M. Morris, A.E. Riley and L.H.  Wright, "Apparent reacliun
products desorbed from Tenax used to sample ambient air",  Almo.s.  F.iivironineiit. 20, 51 (1986).

13.H Rothweiler, P. A.  Wage: and C. Schlatter, "Comparison of Tenax TA and Carbotiap fur sampling and
analysis of volatile organic compounds in air", Atmos. Environment. 2SB, 231 (1991).

14. H.B. Singh, L.I. Salas,  A.J. Smith and  H. Shigeishi, "Measurements of some potentially hazardous organic
chemicals in urban environments", Atmosph.  Environment. IS, 601  (1981).

15. J. Rudolph, F.J. Johnen, A, Khedim and O. Pilwat, " The use  of automated 'On Line' Gas Chromalogrnphy for
the monitoring of organic trace gases in the atmosphere at low levels" Intern. J. Environ. Anal. Chem.. 38,  143
(1990).

16. D.B. Cardin and C.C.Lin "Analysis of selected polar and non-polar compounds in air using  automated 2-
dimensional chromatography" Proceedings 'Measurement of Toxic and Related Air Pollutants', EPA/A&WMA
Symposium, Durham, North Carolina, 1991.

17. D.J. Cooper, WJ. Cooper, W.Z. de Mello,  E.S. Saltzman and R.G. Zika "Variability in bJogenic sulfur
emissions from Florida wetlands"  in  Bioeenic Sulfur in the  Environment: E.S. Sallzmanand W.J. Cooper ,Eds.,
ACS Symposium Series 4393, ACS Washington DC, (1989)
                                                   424

-------
LIQUID	VENF
 FILTER
                 II - HAF1CM WAFIR MCWViM. MODULE

                 13 - HIOI vtxuc oiiramic rwr
                 13 - HEGAflOUE OHCCEMC FOCUSIW
                                                                               INIERNAL
                                                                               STANDARD
                                                                                                  OR
                                                                                            CALIBRATION
                                                                                              STANDARD
     fig la) Schematic of ELA 2000 concentrator and Ib) of the real time integration device
            ON.Y8P5IAI319TOPR
            r«CES3«)V TOR 2«a .
            TOFUJ.AS»M\E
            AUOUOT AT leeOQMN
                                                                4610
                                                                             MAS FLOW CCNTPCLLBI
                                                                             SETFCRAOXTUXUS
                                                                             R_cw CF ee-ia» CGWN
                                                                             FCO MONrrCf»J3 CANGTW
                                                                             PPESSLPEATSCULW
             Tinouanop
             TUBE TO CBTAN
             NTHHATH)
COITMXXB FEAOOLTT OF
aow SETPONT, ACTU«L
                                                  425

-------
s



eooo -
> °
•4 OOi
; I



•
O -
J































1
fi
[
1








1















Q
I *
1 1 I

WJUjJi

                                                       .
                                                                 20 Sep 09:00

     •
                                                               20 S«p 16:00
                                                               20 Set, 19 00
                            !   I
[i f





-s !
^UukLj^ 	 1 ,

/•>'.? 2.  KrpnstHtaUrt clinimatns'urii* '"*«' I/WM'/IJ? llie count of one day til Simimms
Tillllprl  l'l,iii,l,i
                                          426

-------
         ON-LINE MONITORING OF  NITROUS  OXIDE
           FROM COMBUSTION SOURCES USING  AN
       AUTOMATED GAS CHROMATOGRAPH  SYSTEM


                          Jeffrey V. Ryan and Shawn A. Karns
                            Acurex Environmental Corporation
                                    P.O. Box 13109
                       Research Triangle Park, North Carolina 27709


ABSTRACT
      The combustion of fossil fuels has been suspected as a major contributor to measured increases
in ambient nitrous oxide (N2O) concentration.  Characterization of N2O emissions from fossil fuel
combustion and associated pollution control techniques has been hindered by  a grab sampling artifact
where N2O is actually generated in the sampling vessel in the presence of SOX, NOX, and moisture. To
truly assess the N2O emissions from fossil fuel combustion, a near real-time measurement device is
required.  To accomplish this, a gas chromatograph (GC) equipped with an electron capture detector
(BCD) was configured and automated.  The  system is capable of detection levels below ambient
concentrations and a practical quantifying range of 0.1 to 200 ppm.  A pre-column backflushing system
negates the effects of interferants present in fossil fuel combustion process emissions. The automated
system is capable of a measurement every eight minutes  and has been used to evaluate the N2O
emissions from a variety of combustion sources, fuels, and pollution control techniques.

INTRODUCTION
      Nitrous oxide has  been a great concern to the combustion community largely  because the
combustion of fossil fuels has been proposed as a potential contributor to measured increases in ambient
N2O concentrations.1A3 This increase is of serious concern because N2O is considered a "greenhouse"
gas due to its infrared (IR) radiation absorptive properties as well as an active participant in stratospheric
ozone depletion mechanisms.4
      The measurement of nitrous oxide (N2O) from combustion sources has been performed using a
variety of methodologies including both grab sampling and on-line monitoring techniques. Grab samples
collected are  normally analyzed using gas chromatography methods.  On-line monitoring techniques
include gas chromatography, non-dispersive infrared (NDIR), Fourier-transform infrared  (FTIR), and
tunable diode infrared laser (TDIR) real-time analyzers. Each of these methods, has its own advantages
and more often than not, disadvantages.
      Grab sampling methods are appealing from a cost and convenience stand point however, the
        of the sample has been  demonstrated to be compromised under most common sampling
             A grab sampling artifact has been observed where nitrogen oxides (NO,), sulfur dioxide
       and moisture, present in grab sampling containers, react to produce N2O.   Nitrous oxide
generation in grab sample containers  approaching 200 ppm has been observed.6
      On-line, real-time N2O analyzers are desirable for obvious reasons however, the commercial
availability of state-of-the-art combustion process monitoring equipment is limited. Of those available,
detection levels may be insufficient, and elaborate conditioning systems are routinely required. Many
°f the on-line combustion emission monitoring techniques available are research-oriented.819  A non-
dispersive infrared (NDIR), developed at the University of California, Irvine  Combustion Laboratory,
^vas used to characterize the N2O emissions from the combustion of pulverized coal in utility boilers.10
Similarly, a tunable diode infrared laser (TDIR) analyzer was developed by EPA's Air and Energy
Engineering Laboratory (AEERL) to monitor N2O emissions from fossil fuel combustion test facilities.
                                          427

-------
       Much of the data reported on N2O measurements from fossil  fuel combustion sources were
obtained using grab sampling methods conducive to the sampling artifact.7 Realizing  that these N20
emissions data reported were at best suspect,  the EPA-AEERL conducted  a series of tests, performed
by Acurex Environmental, characterizing the nitrous oxide emissions from pilot- and full-scale fossil fuel
combustion facilities. '    During  these tests, the limitations of the on-line  gas chromatograph/electron
capture detector (GC/ECD) monitoring system used were identified.  The on-line GC/ECD system was
susceptible to interferences present in the flue  gases measured.  Memory effects from moisture and S02
resulted in detector baseline instability as  well as chromatographic difficulties. These effects had a direct
impact on detector sensitivity, often raising detections levels to values above actual N2O concentrations
present in the gas  streams measured.
       The EPA-AEERL felt that the reliable, on-line measurement  of nitrous oxide from fossil fuel
combustion sources was important to the continued characterization of N2O  emissions. For EPA-
AEERL's Combustion Research Branch.  Acurex Environmental developed a GC/ECD analytical system
and procedure suitable for the on-line measurement of N2O from fossil fuel combustion sources.  The
development of the system required negating the effects of interferences present in combustion process
emissions; configuring the instrument for automated operation; and improving the linear working range
of N2O emission quamitation.

EXPERIMENTAL
       The GC/ECD analytical system developed uses a precolumn backflush  method to isolate  the
interfering flue gas components.  The  system is automated by using the timed  event commands
associated with  the GC operation/data acquisition system  to control and activate the sampling/valving
hardware.  Quantitation of N2O is accomplished by relating integrated peak areas to a least squares linear
regression  of logarithmicly transformed calibration variables (peak area and N2O concentration).  The
system requires that a paniculate free, moisture conditioned, sample stream be delivered to the system
under positive pressure.   A schematic diagram of the analytical system is  presented in Figure 1.  The
analytical conditions of the GC/ECD system are presented in Table 1.
                     Figure 1. Automated, On-line GC/ECD N2O Monitoring System.
                                            428

-------
                 Table 1.  GC/ECD analytical system equipment andcondirions.
             Gas Chromatograph - Hewlett-Packard Model 5 SWA
             Integrator - Hewlett-Packard Model 3392A
             Timed Sample Event Controller - Hewlett-Packard Model 19505A
             Detector -     ^Ni constant current cell electron capture detector maintained at 300 °C
             GC Oven Temperature - Isothermal, 50 °C
             Canier Gas - 5 or 10% methane in argon (P5, P10)
             Precolumn  - 6 ft (1.8 m) x 0.125 in. (0.32 cm) O.  D.  stainless steel,  packed with
             HayeSep D - 100/120 mesh support.  Carrier How of 30 cc/min (head pressure - -30
             Analytical Column - 12 ft. (3.7 m) x 0.125 in. (0.32 cm) O. D. stainless steel, packed
             with Porapak Super Q - 80/100 mesh support Carrier How of 30 cc/min (head pressure -
__ -40 prig). _ _____ __

BACKFLUSH METHOD
      The backflushing method uses a single, 10-port valve to divert/direct the flow of carrier and
Mmple gas streams through the chromatographic system.  A schematic diagram of the 10-port valve
system is presented in Figure 2.  The 10-port valve can be operated in two positions or modes. In the
"off" or backflush position (diagram 2a), the precolumn is backflushed by carrier 2 to a vent (ports 10,
P- 6. 8 consecutively).  The analytical column, supplied by carrier 1 (ports 5 and 7 consecutively), is
interfaced to the detector.  A 1 cc sample loop, bridged by ports 3 and 4, can be charged with the sample
stream (ports 1 and 2 consecutively).  In the "on" or analyze position (diagram 2b), the valve is aligned
*o that carrier 1 purges the sample loop onto the precolumn (ports 5, 3, 4, 6 consecutively). The effluent
°f the precolumn is routed to the analytical column and on to the detector (ports 9 and 7 consecutively).
Canier 2 is vented via ports  10 and 8. The sample stream is vented via poro 1 and 2, Once the analyte
of interest (N2O) has eluted from the precolumn onto the analytical column, the valve is returned to the
backfiush position, the  flow through the  precolumn  reversed and the interfering sample components
       from the precolumn.
       An electronically controlled air actuator was used to automate valve switching. Control of the
       system was accomplished by interfacing the GC and integrator w a timed event control module
that converted digital commands from the integrator to time controlled electrical switches.
       To further aid in analytical system automation, a solenoid valve, installed upstream of the 10-port
valve sample loop, allows continuous purging of the sample loop until the time of analysis. The valve
    controlled so that just prior to analysis, the solenoid valve was closed, sample flow was stopped,
    the sample loop was equilibrated to atmospheric pressure. At the time of backflushing, the 10-port
                             Figure 2. 10-Port Valve Schematic Diagwn.
                                             429

-------
valve was returned to the off position and the solenoid valve opened, restoring How to the sample loop.
The system was also capable of unattended, continuous operation by incorporating the programmed timed
events into a separate program capable of automatically re-initiating the sequence of timed events.

CALIBRATION AND LINEARITY
      The linearity  of the GC/ECD system was evaluated with varied concentration N2O in nitrogen
span gases ranging from 0.514 to 128 ppmv.  The detector response to N2O (area counts/ppm NjO)
exhibited decreased sensitivity relative to increased concentration.  This effect tends to limit  the linear
working range of quantitation.  The linearity  of the detector was evaluated using two mathematical
approaches; a least squares linear regression of the calibration variables, concentration and peak area,
and a least squares linear regression of the transformed (logarithmic) calibration variables.  A comparison
of these two approaches are presented in Table 2. The approaches are compared by back-calculating the
concentration of each calibration standard and determining the percent bias from the known value.

             Table  2.  Mathematical approaches to evaluate detector linearity.
Known Concentration
(ppm)
0.514
0.97
1.99
5.03
9.85
19.4
40.4
80.1
128
Percent Bias
Lin. Reg
-705.9
-319.5
-120.1
-8.8
15.2
19.5
13.2
4.1
-3.4

Trans. Lin.
-9.6
2.2
1.2
6.5
5.7
3.6
0.1
-2.9
-5.6

Reg







	
      The linear regression of the transformed calibration variables was effective in minimizing the
relative error of calculated concentrations. Less than 10% bias was observed over the entire range. By
calibrating in a narrower concentration range, more specific to anticipated emission concentrations, the
relative error can be reduced further.

SYSTEM PERFORMANCE
      The automated, on-line  GC/ECD system was  evaluated extensively on a number of diverse
EPA/AEERL fossil fuel combustion test facilities.   The system was used to monitor N2O emissions
from the combustion of various coals during  parametric SO2 reduction tests.  N2O concentrations
measured ranged from 0.5 to 10 ppm.
      The on-line GC/ECD system was used extensively during a series of selective non-catalytic NOX
reduction (SNCR) tests. During these tests, additives such as ammonia and urea were injected into the
combustion test facility to reduce NOX emissions. The on-line measurements were used to compare fyO
emissions with and without NOX control. The N2O concentrations measured ranged from 0.5 to 35 pp«.
Similarly, the on-line GC/ECD  system was used to characterize the N2O emissions from a selective
catalytic NOX reduction (SCR) pilot-scale test facility. Nitrous oxide concentrations were measured both
before and after the catalyst evaluated.  Measured concentrations ranged from 0.5  to 3 ppm.
      The GC/ECD system was used to assist the AEERL in the development of their TDIR instrument
During the development of the TDIR system, the on-line  GC/ECD system was relied upon to determine
the actual flue gas N2O concentrations for performance evaluation purposes.
                                            430

-------
       The GG/ECD system was also evaluated under ambient conditions.  The system was used to
assess the N2O mass emissions resulting from the open hearth combustion of coal.  In China, the open
hearth  combustion  of  coal  comprises  a significant  portion  of  all coal burned.   These ambient
measurements were used to assess the magnitude of the  mass contribution of nitrous oxide to the
environment from this combustion source. The N2O concentrations measured were only slightly above
ambient concentrations.  However, the GC/ECD analytical system was sensitive enough to resolve this
100 - 200 ppb relative increase.
       During on-line analyses, span or performance checks were conducted on a routine basis. These
checks, used to evaluate method accuracy and precision, were conducted at various times during the
measurement process. Figures 3 and 4 present results of span checks conducted during representative
ambient and source monitoring activities. Overall, the accuracy and precision levels achieved during
various on-line monitoring requirements were consistent The type of combustion source monitored did
not appear to effect method performance.  Accuracy of span checks, expressed as percent bias, was
consistently  less than ±15%.   The precision  of replicate span checks, expressed  as percent relative
standard deviation (RSD), was consistently less  than 10%.

SUMMARY AND CONCLUSIONS
       The GC/ECD backflush method developed was found to be suitable for the measurement of
nitrous oxide from a variety of combustion sources and applications. In addition, the method was found
to be equally suitable for on-line monitoring or grab sample analysis purposes.  Analytical interferences,
present in combustion process effluents, were negated  through the  use of a backflushing technique.
                                       AUTDMAnDHUANALnW
                                   •PAD CMC* AOCUIUCY-M f
                       \'
                                       IW     )K     100
                                       BAMPlf DURATION (mfauM)
                                      ssssss?
                       19 CHOC MCCTDM-HUTOM.il COIL
                           Figure 3.  Illinois No. 2 Coal. Down Fired Furnace.
                                       AUTOMATE) WO AMALTM
                                        *F AN CMOK ACCWUCr
                        OJ

                        07
                          tom**    KAMI
                                          11«*l    11/IMt    IU1MI    11/14KI
                                            TEST DATES
                                             liSSSSm •'"•ofmanH .IHOFUNOMI
                             Figure 4. Ambient Air Testing. China Coal.
                                            431

-------
Common flue gas components such as O2, CO, CO2, NOX, H2O, SO2, unburned hydrocarbons (THC),
and ammonia (NH3) were found not to interfere with the analytical procedure. Method accuracy (*
bias) and precision (% RSD) were determined to be < ± 15% and < 10%, respectively.  The method was
found to be suitable  for the quantitation of N2O concentrations ranging  from  0.100 to 200 ppm.
Ultimately, the procedure was approved as an AEERL Recommended Operating Procedure (ROP).
      Using this  method for  on-line monitoring purposes allows a semicontinuous measurement
approximately every 8 minutes. The system can be easily incorporated into most  continuous emission
monitoring sample delivery/conditioning  systems.  The  only  requirements being  the  removal of
paniculate and moisture from the sample stream by a refrigeration condenser.  The sample stream should
be diverted to the analytical system prior to further moisture conditioning by a desiccant.
      The non-linear response of the detector to nitrous oxide at low concentrations was minimized
through use of a logarithmic transformation of the calibration variables.  The transformed data are used
to derive a least-squares linear regression.

ACKNOWLEDGEMENTS
      The work described in this paper was performed by Acurex Environmental Corporation under
EPA contract 68-DO-0141. The EPA Project Officer was Bill Linak of the Air and Energy Engineering
Research Laboratory - Combustion Research Branch.

REFERENCES
1.  D. Pierotti, R.A. Rasmussen,  "Combustion as a source of nitrous oxide  in the  atmosphere,"
Geophysical Research Letters. 3(5): 265-267 (1976).
2. W.M. Hao, S.C. Wofsy, M.B. McElroy, "Sources of atmospheric nitrous oxide from combustion,"
Journal of Geophysical Research. 92(D3): 3098-3104 (1987).
3.  R.F. Weiss, H. Craig, "Production  of atmospheric nitrous oxide by combustion,"
Research Letters. 3(12): 751-753 (1976).
4. V. Ramanathan, et al,. 'Trace gas trends and  their potential role in climate  change," journal Jif
Geophysical Research. 90(D3):  5547-5566 (1985).
5. L.J. Muzio, et al., "Errors in  grab sample measurements of N2O from combustion sources,"
39: 287-293 (1989).
6. W.P. Linak, et  al., "Nitrous oxide emissions from fossil fuel combustion," Journal of
Research. 95(D6): 7533-7541 (1990).
7.  J.V. Ryan, R.K. SrivasUva, EPA/IFP Workshop on the Emission of Nitrous Oxi(^ fr™
Combustion. EPA-600-9-89-089, U.S. Environmental Protection Agency, Research Triangle Park, 1989.
8.  W.S. Lanier, S.B. Robinson, EPA Workshop on IsUO Emission from Combustion. EPA-600-8-86-035,
U.S. Environmental Protection Agency, Research Triangle Park,  1986.
9.  J.C. Kramlich. ct al.. EPA/NOAA/NASA/USDA N7O WORKSHOP Volume I: MeasyT™""* Stud&
and Combustion Sources. EPA-600-8-88-079, U.S. Environmental Protection Agency, Research Triangle
Park, 1988.
10. T.A. Montgomery, et al., "Continuous infrared analysis of N2O in combustion products," JAP£&
39: 721-726 (1989).
11. RE. Briden, D.F. Natschke, R.B. Snoddy, "The practical application of tunable diode laser infrared
spectroscopy to the monitoring of nitrous oxide and other combustion  process stream gases," presented
at  1991 Joint Symposium on Stationary Combustion NO^ Control. Washington, DC (March 1991).
12. R. Clayton, et al,. N2O Field Study. EPA-600-2-89-006, U.S. Environmental Protection Agency,
Research Triangle Park, 1989.
13. Recommended Operating Procedure No. 45: Analysis of Nitrous Oxide from Combusrio" SourCCJ?
EPA-600-8-90-053,  Environmental Protection Agency, Research  Triangle Park, 1990.
                                           432

-------
COMBINED SUPERCRITICAL FLUID CHROMATO-
GRAPHY/MICROSUSPENSION  MUTAGENICTTY
ASSAY OF ENVIRONMENTAL TOBACCO SMOKE
Delbert J. Eatough, Todd D. Parrish, Eric S. Francis,
Gary M. Booth, Milton L. Lee and Edwin A. Lewis
Departments of Chemistry and Zoology, Brigham Young
University, Provo, UT  94602
      Capillary  supercritical  fluid chromatography  (SFC)  has been used  with  a
microsuspension modification of the reverse  mutation Salmonella assay and, UV, FID,
nitrogen-,  nitroso-  and N-nitroso  specific detectors to  evaluate the mutagcnicity of
environmental tobacco smoke fractions. With the on-line Salmonella reverse suspension
assay, the mutagenicity of various fractions of a complex mixture can be quickly evaluated
and, with the on-line array of detectors combined with the mutagenicity assay, the possibility
exists for some of the mutagenic compounds to be directly identified.

      The effluent from the SFC is bubbled directly into 5 uL <* DMSO and 500 uL of
acetone. The acetone is then blown off and the microsuspension bioassay performed on the
DMSO solution.   Supercritical  carbon dioxide  only allows recovery of 44±7%  of the
mutagenicity of an environmental tobacco smoke condensate sample. Supercritical carbon
dioxide modified with 13% acetone or 15% tetrahydrofuran allows recovery after the
chromatograpnic separation of 76±5% of the original mutagenicity of the ETS  sample.
Modification of the supercritical carbon dioxide with 10% methanol allows recovery of all
of the mutagenicity of the environmental tobacco smoke condensate. The majority of the
chromatographically separated mutagenicity is associated with higher molecular weight, more
polar compounds.

INTRODUCTION

      Data in the literature indicate that exposure to environmental tobacco smoke may
lead to the development of lung cancer".  Several studies have shown that the  relative
amounts of many  of the toxic and mutagenic compounds are  higher in environmental
                                      433

-------
 tobacco smoke as compared to tobacco smoke condensate2-4.

       Extensive data is available on the identification of mutagenic compounds in tobacco
 smoke condensate5. However, there have been few reports on the identification of mutagens
 in environmental tobacco smoke particles'-10 and little information is available on mutagens
 in the  gas  phase of environmental tobacco  smoke11.  Current  data suggest  that the
 mutagenicity of environmental tobacco smoke particles is comparable to, or less than, that
 of tobacco smoke condensate and other important classes of environmental pollutants such
 as ambient particulate matter, emissions from home cooking,  coke or wood burning
 emissions and diesel exhaust12-". However, environmental tobacco smoke appears to be the
 main contributor to the mutagenicity of particles in indoor environments where smoking is
 present7*1"1.

        Several investigators have reported on the mutagenicity of environmental tobacco
 smoke particles using a variety of Salmonella tester strains*"11.  Two investigators1*44 have
 shown that most of the mutagenicity in environmental tobacco smoke particles is found in
 the chemical fraction containing heterocyclic nitrogen bases and that the mutagenicity of the
 PAH or nitro-PAH fractions is less than that observed from other sources such as diesel
 exhaust14-22 or wood smoke2"4.  Wesolowski et al." have reported preliminary data on the
 mutagenicity of both the particulate and gas phases of aged environmental tobacco smoke.
 The results suggest  the presence of nitroarenes in the sample and  indicate that these
 compounds may be important principal mutagens in aged environmental tobacco smoke.

       Identification  of toxic airborne pollutants has focused on the  study of organic
 compounds which are amenable to separation by gas chromatography, e.g. PAC, nitro-PAC
 and volatile organic compounds. Mutagenicity studies have  demonstrated the importance
 of polar, labile, semi-volatile and nonvolatile organic compounds. There is currently very
 limited  data on these classes of pollutants.   Supercritical fluid chromatography (SFC) is
 ideally suited for the analysis of thermally labile and polar compounds in environmental
 samples25.

       Chromatographic techniques can  sometimes be directly  combined  with various
 bioassays  to  establish on-line  methods  of bioassay-directed  fractionation.    Many
 Chromatographic procedures, including liquid chromatography (LC)2"9,, gas chromatography
 (GC)30, thin layer chromatography3102,  and gel chromatography31 have previously been
 combined with  mutagenicity  and other bioassays  with  varying degrees  of success.
Supercritical fluid extraction (SFE), an extraction method related  to SFC,  has also been
successfully combined with bioassays34*35. Prior to this study, SFC had not yet been coupled
 to a bioassay.

      Although other Chromatographic techniques have been combined with bioassays, their
effectiveness has been limited.  Some of these limitations can be overcome because of the
unique capabilities of SFC  These advantages include the fact that supercritical CO2 expands
and bubbles out of the collection solvent, thus leaving the e luted compounds trapped in the
fraction collection solvent  This eliminates the large quantities of solvent associated with
liquid Chromatographic techniques. The  advantage of SFC  over GC is the relatively low
                                        434

-------
 temperatures involved in SFC that allows analysis of volatile and heat labile compounds, and
 provides ease of sample collection.   SFC also offers the  possibility of adding solvent
 modifiers to the carbon dioxide to enhance the separation of polar and high molecular mass
 compounds36.   SFC also can  be interfaced with most GC and LC detectors because
 supercritical carbon dioxide is compatible with both types of detectors. In addition to the
 flame ionization detector (FID)  and ultraviolet absorption detector (UV), which are the
 most widely used detectors in SFC, selective detectors such as the mass selective detector,
 thermionic detector, sulfur chemiluminescence detector, and thermal energy analyzer have
 all been successfully interfaced with SFC25.  The TEA is a chemiluminescencc detector that
 is specific towards nitro- and nitroso-containing compounds37.  Thus, capillary SFC is ideally
 suited for the analysis of compounds in complex environmental samples because of its high
 resolution capabilities and the lack of interferences from the mobile phase when  directly
 combined with a bioassay.

 EXPERIMENTAL METHODS

 SFC Fractionation.  A Lee Scientific Series 600 supercritical fluid chromatograph (Dionex,
 Lee Scientific Division, Salt Lake  City, UT) was used  for  all  analyses.  The SFC was
 combined with a ChiraTech Model  203 variable UV-Vis  absorption detector (Linear
 Instruments, Reno, NV) with a 200-nm ID fused silica capillary tube as the flow cell  Other
 detectors used  to  characterize  the environmental  tobacco  smoke  condensate samples
 included an NPD (Detector Engineering and Technology, Walnut Creek, CA), and a Model
 543 Thermal Energy Analyzer (TEA) (Thennedics, Woburn, MA). Restrictors for the SFC
 system were either porous ceramic frit (Dionex, Lee Scientific Division) or tapered integral
 restrictors38. Columns used were 5 m x 50 jim ID coated  with either j?-cyanobiphenyl
 modified silicone phase (Reese  et al., in  preparation)  or a polyethylene glycol phase,
 Superox® 0.639.  Mobile phases consisted of 100% carbon dioxide or carbon  dioxide
 modified with 5-15% of the following  organic  modifiers: acetone,  tetrahydrofuran, and
 methanoL

 Microsuspension Bioassay. The microsuspension technique previously reported by Kado**41
was used with minor modifications for all assays in this study. Salmonella typhimiuium strain
TA98 (supplied by Dr. Bruce Ames,  Berkeley, CA) was grown in Oxoid nutrient broth
 (Oxoid Dmited, Basingstoke, England) for about 12 h with rapid  shaking.  Cells  were
centriruged (3500 rpm at 20'C, 20 min) and  then resuspended  in 1/10 of the original volume
in Vogel and Bonner medium E (instead of phosphate-buffered saline5) giving approximately
 IxlO10 cells/mL The S9 was obtained from livers of Aroclor 1254-induced Sprague-Dawley
rats (Molecular Toxicology, Annapolis, MD).  The 10% S9 mix was prepared as described
by Ames et aL*1.

      For the microsuspension assay, the following ingredients were added, in sequence, to
 13x100 mm sterile test tubes kept on  ice:  5 \iL of the test sample in DMSO, 0.1 mL of
concentrated bacteria, and 0.1 mL of S9 mix or Vogel and Bonner medium E The  tubes
were incubated in the dark at 37s C with rapid shaking, and  after 90 min the tubes were
placed in an ice bath. A total of 2.0 mL of molten soft agar containing 90 nmol of histidine
and biotin was added to each sample.  Following Vortex mixing, the samples were overlaid
                                        435

-------
 on minimal glucose agar plates. The plates were then incubated for 48 h at 37° C and the
 revertant colonies were counted manually.  Strain markers and positive (500 ng BAP) and
 negative controls (5 /iL of DMSO) were routinely determined for each experiment

 SCF • Bioassay Coupled Analyses. Samples were introduced into the SFC by means of a
 newly developed solid phase injector (Koslti et al., in preparation).  One p.L of the sample
 was applied to the platinum wire of the injector with a 5-|iL on-column syringe and the
 solvent was allowed to evaporate under ambient conditions or under a gentle stream of
 nitrogen.  The wire was then rotated and sealed into the injector, the oven was brought up
 to the operating temperature, and a chromatogram was obtained. The solid phase injector,
 equipped with a 5m x 50um ID deactivated fused silica retention gap was connected to the
 analytical column by means of a low dead volume butt connector.  A 200-um Li flow cell
 was connected between the column and the restrictor with butt connectors for on-line UV
 monitoring of the chromatogram43. The sample fractions from the SFC were collected for
 the bioassay at the restrictor end by bubbling the effluent into 5 pL of DMSO and 0.5 mL
 of acetone.  After each fraction was collected, the acetone was evaporated off under a
 stream of nitrogen or helium leaving the solutes in the DMSO.

 APPLICATIONS OF THE COMBINED SFC/MICROBIOASSAY TECHNIQUE

 Pure Compounds.

       The recovery of mutagenicity of a pure compound during the SFC separation was first
 evaluated. The mutagenicity of 2-nitropyrene was unaffected by the SFC separation, Figure
 1.   Two  nitre-containing  compounds:  2-nitrofluorene  (low activity) and  2-nitropyrene
 (moderate activity) were separated and collected in soft agar and subjected to the combined
 SFC/mutagenicity test   The  two  compounds were separated  with baseline resolution.
 Biological activity could be correlated with compound identity  (determined by retention
 time) and amount (determined by peak area, e.g. see Figure 1).

 Coal Tar Standard Reference Material (SRM 1597).

       The coal tar SRM was a medium grade crude coke tar which contained approximately
 8 |ig of starting material equivalents of coal tar per p.L of solution tested44. The sample was
 provided by Dr. Stephen Wise43 of the National Institute of Standards and Technology
 (NIST) in Gaithersburg, MD.   Fractions of the coal tar SRM 1597 were collected at
 predetermined times where the UV-Vis absorption  (wavelength set at 252 nm) was at or
 near baseline, as shown in Figure 2.  The percentage of total activity in each coal tar fraction
 is given in the insert  in Figure  2.  The SFC separation coupled  with the microsuspension
assay quantitatively recovered the mutagenic activity of the coal tar SRM that was placed
on the injection wire. Direct introduction of the coal tar SRM into the microsuspension
assay yielded 508±43 revertants per plate/jiL, while the summation of fractions collected
from the SFC and  then introduced  into the microsuspension assay yielded 599 ± 20
revertants per plate/fiL. The majority of the mutagenic activity was located in SFC fractions
4,5 and 6, Figure 2. These later (slowly eluted) fractions contain many of the nonpolar high
molecular mass PAH.  This finding is consistent with  other investigators who have done
                                        436

-------
 similar analyses by LG*27'29. Other studies have also shown4* that the basic fraction of coal
 tar is mutagenic.  This fraction (aromatic amines and nitrogen heterocycles) was excluded
 from SRM  1597 during its preparation. The results obtained with SRM 1597 have been
 discussed in detail47.

 Sidestream Tobacco Smoke.

       Whole condensate samples of fresh, diluted side-stream tobacco smoke (ETS) were
 collected from 1R3F research cigarettes (University of Kentucky) smoked according to the
 FTC standard burn cycle in a 30-mJ Teflon chamber48. The condensate sample was collected
 at liquid nitrogen temperatures in a trap containing a small plug of silanized glass  wool to
 increase the collection surface for both gases and particles37. The collection efficiency of the
 cryogenic trap for volatile compounds was determined37. The material collected in the trap
 was extracted  into dichloromethane.   The condensate sample was evaluated both as
 recovered and after clean-up by passing the recovered samples through approximately 5
 grams of alumina (Brockman activity II to III) and eluting with 200 mL of acetone before
 SFC analysis.

       Samples of the alumina cleaned  environmental tobacco smoke condensate have been
 analyzed using SFC/(FID-NPD-TEA)37. Examples of the total organic, nitrogen-, nitro-, and
 nitroso-organic compound specific  analyses of these samples are  shown in  Figure 3.
 Concentrations of nitro-, Figure 3C, and nitroso-, Figure  3D, containing compounds are
 much lower than the concentrations of the major nitrogen containing compounds.  The
 concentrations of the various tobacco specific N-nitrosoamines have been quantified37.

       Direct introduction of the whole ETS condensate  into the microsuspension assay
 showed a linear dose-response curve. From this dose-response curve, it was determined that
 ETS yielded 250 revertants per uL of ETS condensate.  This is equivalent to approximately
 125,000 revertants per cigarette, which is comparable  to the results of others (118,800
 revertants per cigarette obtained by Ling18; 240,000 revertants per cigarette obtained by
 Lofroth9; 91,000 revertants per cigarette obtained from the data of McCurdy21) for side-
 stream tobacco smoke.  As shown  with the coal tar, use of the microsuspension assay
 increased mutagenic sensitivity approximately 4-fold over the values18 determined from the
 plate incorporation method. Table I gives the results of placing 3 |iL of either the alumina-
cleaned or whole ETS condensate on the injection wire and using 100% CO2 as the mobile
phase. When the genotoxic activity of  the effluent was compared to the activity remaining
on the injection wire, it was determined that only 44±6% and 58% of the genotoxic activity
was extracted from the wire for the alumina-cleaned and whole samples, respectively. The
lack of complete recovery of the mutagenicity in the SFC separations can be attributed to
the very polar nature of the tobacco tars and the inability of CO2 to remove these from the
injection  wire.  In an attempt to quantitatively recover the  activity from the injection wire,
we used solvent modifiers.

Use of Modifiers in the Analysis of ETS Samples.

      Solvent modifiers are a  means  of recovering polar compounds which cannot be
                                        437

-------
 recovered because  of the limited solvating  ability of 100% CO^ even at high densities.
 Wong et al.34 used 5 different arrangements of modifiers in SFE to increase the recovery of
 several aromatic compounds.  One of the major drawbacks of modifiers is the response
 generated in many detectors49.  For example, the major modifier effect when using the UV-
 Vis detector was baseline drift43.  Although the  addition of modifiers  greatly limited the
 chromatographic analysis of whole ETS condensate samples, we  attempted  to determine
 which modifiers enhanced the quantitative recovery of the ETS mutagenic activity.

       Table I shows the results of adding either 13% acetone, 15% tetrahydrofuran (THF)
 or 10% methanol to supercritical C02.  The addition of 13% acetone improved the activity
 recovery efficiency to 78%,  This was a 20% increase over 100% CO2. The addition of 15%
 THF yielded similar results (74% recovery).  The addition of 10% methanol to the C02
 permitted quantitative recovery of the mutagenic activity of ETS.  The percent of the total
 mutagenicity in the whole  ETS condensate  sample sequentially  removed in the various
 fractions is illustrated in Figure 4.

       Treatment of the whole environmental tobacco smoke condensate with alumina
 results in recovery of 70±3% of the total mutagenic activity of the sample from the alumina
 column. An average of 44±6% of the total mutagenicity is recoverable from the column and
 extractable from the direct probe with supercritical CO2.  The  remainder of the material
 which can be eluted from the column is recoverable from the SFC  column using acetone as
 a modifier.  The activity of the alumina column cleaned ETS sample is the same whether
 the sample  is  analyzed directly by the microsuspension bioassay or chromatographically
 separated with acetone modified CO2. This suggests that no significant mutagenicity is lost
 in the application of the cleaned  ETS sample to the direct probe.  The fraction of the
 mutagenicity in the alumina column cleaned ETS sample increases with increasing retention
 time (0-20, 20-40 and 40-60 minute cuts for the data illustrated in Figure 3) on the column
 with only CO3 as the eluent or with the addition of acetone as a modifier, Figure 4.  This
 suggests that the mutagenicity is associated with the more polar compounds in the alumina
 column treated sample.  For example, the majority of the CO2 recoverable mutagenicity in
 the cleaned sample is contained in Cut 3, Figure 4. This cut contains mainly nitrogen-, nitro-
 and nitroso-organic compounds, Figure 3.

       The fraction  of the mutagenicity that can be recovered in the SFC separation with
just CO2 as  eluent increases from 44% to 58% if the sample is not pre-treated with the
 alumina column. Likewise, recovery  of  the mutagenicity  with  acetone modified COj
 increases from 68%  of the total mutagenicity to 78%  of the  mutagenicity.  A comparable
 increase is seen with THF modified CO2. Addition of methanol to the CO2 eluent allows
 complete recovery of the mutagenicity in the environmental tobacco smoke condensate
sample. The data suggests that the concentration of volatile mutagenic compounds in the
fresh ETS sample is very low.  About 26% of the mutagens in the environmental tobacco
smoke condensate sample are sufficiently polar that the addition of methanol to the CQj
eluent is required to move the compounds through the column.  The compounds which can
only be eluted using methanol  modified CO2 must be strongly hydrogen bonding organic
compounds.  Poly-substituted hydroxylated nitroaromatic and hydroxylated nitro polycyclic
aromatic compounds2* would be examples of compounds which would be expected to exhibit
                                        438

-------
 this behavior.


        The bioassay-directed SFC fractionation of ETS is important because it combines
 state-of-the-art analytical capabilities with biological assays.  ETS is a complex mixture and
 is a common contributor to indoor air pollution wherever smoking occurs.  Epidemiological
 studies indicate that  there is  potentially an increased risk  of developing lung  cancer for
 nonsmoking  individuals who  live with  smokers3.   Several  studies have been  done to
 determine the mutagenicity of the ETS complex mixture.  These studies include the use of
 the microsuspension assay to determine the mutagenicity of ETS collected in both indoor
 environments and in smoke chambers1*19. The ability to couple SFC to the microsuspension
 mutagenicity assay will assist in assigning mutagenicity to specific compounds or classes of
 compounds in ETS fractions.  The results reported here indicate that even the most polar
 organic mutagens can be identified by this procedure.


 ACKNOWLEDGEMENT


        This research was supported by the Center for Indoor Air Research.

 REFERENCES

 1.      DHHS (1986) "The Health Consequence* of Involuntary Smoking." A Report of the Surgeon General.. 332 pp.

 2.      NAS (1986) "Environmental Tobacco Smoke. Measuring Exposure and Assessing Health Effects." National
        Research Council. National Academy Press, Washington, 337 pp.

 3.      Saracci R, Riboli E. (1989) "Passive Smoking and Lung Cancer Current Evidence and Ongoing  Studies at the
        International Agency for Research on Cancer." Mutat. Res. 222,117-127.

 4.      Guerin M.R., Jenkins R .A., Tonkins B.A. (1992) The Chemistry of Environmental Tobacco Smoke: Composition
        and Measurement. Max Eisenberg, Series Editor, Indoor Air Research Series, Center for Indoor Air Research,
        Lewis Publishers, Boca Raton.

 5.      DeMarini  D.M., Dallas M.M. and Lcwtas J. (1989) "Cytotoxicity and Effect on  Mutagenicity of Buffers in a
        Microsuspension Assay," Terat. Carcin. and Mutaeen.. 9,287-295.

 6.      Bos R.P. and Henderson P.Tn. (1984) "Genotoxic Risk of Passive Smoking." Rev. Environ. Health. IV, No. 1,161 -
        178.

 7.       Husgafvel-Pursiainen K., Sorsa M., Moller M., and Benestad C (1986) "Genotoxicity and Potynuclear Aromatic
        Hydrocarbon Analysis of Environmental Tobacco Smoke Samples from Restaurants."  Muta genesis. 4,287-292.

 8.       Lewtas J. (1989) "Genotoxicity of Complex Mixtures:  Strategies for the Identification and Comparative
        Assessment of Airborne Mutagens and Carcinogens from Combustion Sources." Fundamental ADD!. Tox.. 10,571-
        589.

9.       Lofroth G., Burton R.M., Forehand L, Hammond S.K., Sella R.I_ Zwerdinger R.B. and Lewtas J. (1989)
        "Characterization of environmental tobacco smoke," Env. Sci. Tech.. 23, 610-614.

 10.      Lofroth G., and Lazaridis G.  (1986) "Environmental Tobacco Smoke:  Comparative Characterization by
        Mutagenicity Assays of Sidestream and Mainstream Cigarette Smoke." Environ. Mutaeenesis. 8,693-704.

11.      We&olowski JJ., Wang Y.Y., Hanson C.V., Haas R., Flessel P., and Hayward S. (1986) "Indoor Air Quality
        Measurements:  Emerging Technologies" Proceeding of the EPA/APCA Symposium on Measurement of Toxic
        Air Pollutants. EPA, 1-1.

12.      Austin A.C., daxton L.D. and Lewtas J. (1985) 'Mutagenicity of the Fractionated Organic Emissions from Diesel,
        Cigarette Smoke Condensate, Coke Oven and Roofing Tar in the Ames Assay."  Environ. Mm a yen  7,471487.

13.      Lioy PJ-, Avdenko M., Harkov  R., Atherholt T., Daisey J.M. (1985) "A Pilot Indoor-Outdoor Study of Organic
                                              439

-------
         Paniculate Matter and Paniculate Mutagenicity." JAPCA. 35, 653-657.
 14,     Williams K., and Lewtas J. (1985) "Metabolic Activation of Organic Extracts From Diesel, Cote Oven, Roofing
         Tar, and Cigarette Smoke Emissions in the Ames Assay." Ejiviron^iitagenesis. 7, 489-500.
 15.     Georghiou P.E., Blagden P., Snow  DA., Winsor L. and Williams D.T. (1991) "Mutagenicity of indoor air
         containing environmental tobacco smoke: Evaluation of a portable PM-10 impactor sampler," Environ. Scj. Tech-
         25, 1496-1500.

 16.     Kado N.Y, McCurdy SA, Tesluk SJ., Hammond S.K., Hsieh D.P.H., Jones J. and Schenker M.B. (1991)
         'Measuring personal exposure to airborne mutagens and nicotine in environmental tobacco smoke," MuJaJjOJl
         Res..2
-------
  32.      Bjorscth A., Eidsa G., Gcthcr J., Landmark L and Mollcr M. (1982) 'Detection of Mutagens in Complex Samples
           by the Salmonella Assay Applied Directly On Thin-Layer Chromatography Plates," Science. 215, 87-89.

  33       Rao T.K., Allen B.E., Ramey D.W., Eplcr J.L, Rubin I.E., Guerin M.R. and Clark B.R. (1981) "Analytical and
           Biological Analyses  of Test Material from the Synthetic Fuel Technologies.  Use of Sephadex LJI-20 Gel
           Chromatograpby Technique for the Dioassay of Crude Synthetic Fuels," Mutation Res.. 85,  29-39.

  -4       Wong J.M.. Kado N.Y., Kuzmicky PA., King H.-S., Woodrow J.E., Hsieh D.P.H. and  Seiber J.N. (1991)
           "Determination of Volatile and Semivolatile Mutagens In Air Using Solid Adsorbents and  Supercritical  Fluid
           Extraction," Anal. Chem.. 43,  1644-1650.

  -<       Yu X, Wang X., Bartha R. and Rosen J.D. (1990) "Supercritical Fluid Extraction of Coal Tar Contaminated Soil,"
                 n Sci and Tech.. 24,1732-1738.
 -5       Schmitt WJ., and Reid R.C (1986) "The Use of Entrainers in Modifying the Solubility of Phenanthrenc and
           Benzoic Acid in Supercritical Fluid Carbon Dioxide and Ethane," Fluid Phase Eauilib.. 32, 77-99.

 ,7       Eatough DJ., Francis E^., Lewis EJ\. and Lee M.L (1991) "Determination of nitrogen containing compounds
           in environmental samples by supercritical Quid separation," Measurement of Toxic and Related Air Pollutants.
           Proceedings, 1991 EPA/AWMA International Symposium, Volume 1, 799-804,

 -a       Guthrie EJ.  and Schwartz H.E.  (1986) "Integral  Pressure  Restrictor for Capillary Chromatography," L
 ^"       ^mmatogr. Sci.. 24, 236.
          Verzclc M. and Sandra P. (1973) "Superox, a High-temperature Stationary Phase in Gas Chromatography," £
 3        ChianiajagL, 1». U1-119.
          Kado N.Y., Langley D. and Eisenstadt E. (1983) "A Simple Modification of the Salmonella Liquid Incubation
          Assay. Increased Sensitivity for Detecting Mutagens in Human Urine," Mutation Res.. 121, 25-32.

          Kado N.Y., Guirguis G.N., Flessel C.P., Chan R.C, Chang K.-I. and Wesolowski JJ. (1986) "Mutagenicity of Fine
 41"      r<25  Mra) Airborne  Panicles:  Diurnal Variation in Community Air Determined by a Salmonella Micro
          preincubation (Microsuspension) Procedure," Environ. Mutagcn,. 8, 53-66.

          Ames  B.N., McCann J. and Yamasaki E. (1975) "Methods for detecting carcinogens and mutagens with the
 42~      saimonella/mammalian-microsome mutagenicity test," Mutation Res.. 31, 347-364.

          Fields S.M., Markides K.E. and Lee M.L. (1988) "Ultraviolet-Absorption Detector for Capillary Supercritical Fluid
 43'      Chromatography with  Compressible Mobile Phases," Anal. Chem.. 60, 802-807.

          May W.E., Benner B.A., Wise SA., Schuetzle  D. and Lewtas J. (1992) "Standard Reference Materials for
 **"      Chemical and Biological Studies of Complex  Environmental Samples," Mutation Res.. 276, 11-22.

          Wise S.A., Benner B.A., Byrd G.D., Chester  S.N, Rebbert R.E. and Schantz M.M. (1988) "Determination of
 **'      Polycyclic Aromatic Hydrocarbons in a Coal Tar Standard Reference Material," Anal, Chem.. 60, 887-894.

          Kosuge T., Zenda H., Nukaya H., Tenada A., Okamoto T., Shudo K.. Yamaguchi K., Itaka Y. and Sugimura T.
                 "Isolation and Structural Determination of Mutagenic Substances in Coal Tar," Chem. and Pharm. Bull.
                  , 30,1535-1538.
          Parrish T.D., Francis E.S., Booth G.M., Eatough DJ. and Lee M.L (1992) "Supercritical Fluid Chromatography
47.       coupled With the Salmonella Microsuspension Mutagenicity Assay," submitted.

          Eatough D J-, Benner C.L, Bayona J.M., Richards G., Lamb J.D., Lee M.L, Lewis E.A and Hansen LD. (1989)
48.       "Chemical Composition of Environmental Tobacco Smoke. 1. Gas-Phase Acids and Bases." Environ. Sci. Tcchnol..
          23(6), 679-687.
          Berger T.A., Borra C, Fields S.M., Lcyendecker D. and Raynie D.R. (1990) "Mobile Phases," in M.L Lee and
49.       K.ETMarkides (Eds.) Analytical Supercritical Fluid Chromatoyraphv and Extraction. Chromatography Conf. Inc.,
          Provo, LT, pp. 99-107.
                                                      441

-------
TABLE I.  Mutagenlcity of SFC Effluent (With or Without Solvent Modifier) of 3 |iL of Environmental
Tobacco Smoke Condensate; Microsuspension Assay; TA98, +S9.
ETS Sample    Modifier

Cleaned        100% CO2

               Fraction I*

               Fraction 2d
Whole
               Net Revertants/3 \iL>
               Effluent
               252±39

               46±7

               95± 8

Fraction 3d     166±54

13% Acetone   446±99

Direct*

100% CO2      363±73

13% Acetone   578±35

15% THF      453±19

10%MethanoI  656±20

Average

Direct'
Injection Wire
NAb
NA
NA
NA
19±9

258±39
147±65
158±35
o±o-


Total
NA
46±7
95±8
166±54
465±99
480+30
621 ±55
725 ±95
611 ±52
656±20
653±71
639±35
&
39%'
7%<
15%'
25%'
bS%'
73%c
58%
78%
74%
100%
100%
100%
       The benzo[a]pyrene (concurrent positive control) activity was 442±38 revertanls/0.5 jig.
       NA = Not determined.
       Expressed as the average percent of the total revenants/3 pL in the whole condensate sample.
       Revertants/3 (iL in three equal fractions of the cleaned ETS condensate with 100% CO2 eluent.
       The net revertants were less than four standard deviations above the spontaneous response, Le., <12
       revertants above the background.
       Revertants/3 \iL determined by direct analysis of the condensate.
                                             442

-------
                          SFC Effluent
                A   Direct
             1500
100


 •ill


 BO

 70


 so


 £C


 40


 3C


 20

 10
       c
       m
       DC
       *-
       O
                                         10
                   15
              20
           25
                             Amount OF  2-Nitropyrene (ng)
      Figure 1. Mutagenicity dose-response of 2-nitropyrene; A. directly introduced into the microsuspension assay,
      TA 98, and B. after SFC separation and introduction into the microsuspension assay, TA 98.
                 30
60
90
120
150
                               Time(minutes)
   Figure 2. SFC chromatogram of coal tar SRM 1597 showing the fractions (along with a representative
   molecule located within each fraction) collected for mutagenidty testing. The insert is the percent mutagenic
   activity in each of the 6 fractions; TA 98.
                                         443

-------
                       A: FID Detector
   •      tf     M     M

                Tin* (
                       C: Nltro Detector
         10
                     14     44
                 Tin* (mln«1«tl



                                                                B: NPD Detector

•     1*     »    tt     4*     M     **
                 D: Nitroao Detector
Figure 3, SFC chiomaiogram of aa i
using; A. FID detection, B. NPD detecraa, C TEA aimxtetectioa (pyrohner at 60CTQ, D. TEA nim»o-
detection (pyrotyzer at 900"C).  Superm a6 piuse, 5 m i 50 IUB Ld. cohmta (O25 tin fita). 100% carton
dtuxtde, 100*C, 80 aim then 3 aon mia'  Ceranuc Jnt injecnon, 1 pi.
         —    20
          eo
               10
          C
          0>
          O

         I      o
                     Cut f Cut 2  Cut 3 Acct.  CO2   THF  MeOH
                            Chromatographic           Alumina Retained
                         Fraction After Alumina           Compounds
    Fifure 4.  Muugeniaiy proflk sJ>owin| the percent muugeax tcmitf MoamUy raaoved by eacfa of tb« 7
    fracuotu of envitoameaul to^nrrp

-------
                          AIR MONITORING DURING DRUM REMOVAL
                             ACTIVITIES USING A FIELD PORTABLE
                              MICROCHIP GAS CIIROMATOGRAPH
                 Lawrence P. Kaelln, Renata Wynnyk, Maria Pueyo and Stephen Blaze
                                Roy F. Wcslon, Inc., REAC Program
                                  GSA Depot, Building 209 Annex
                                     2890 Woodbridge Avenue
                                         Edison, NJ 08837

                                         Michael Soleckl
                       National Oceanographic and Atmospheric Administration
                                     GSA Depot, Building 18
                                     2890 Woodbridge Avenue
                                         Edison, NJ 08837

                                       Dwayne Harrington
                      United States Environmental Protection Agency (U.S. EPA)
                                     GSA Depot, Building 209
                                     2890 Woodbridge Avenue
                                         Edison, NJ 08837


ABSTRACT
        Dual capillary column, dual microchip  thermal conductivity  detector (j^TCD) field-portable gas
chromatographs (FPGCs) were deployed at two Superfund  sites to monitor  fugitive emissions during drum
removal activities.  The FPGCs permit rapid on-sitc analysis of grab air samples for the presence of volatile
organic compounds (VOCs). Air samples were collected using a vacuum  box of simple design and stored in
inert teflon air sample bags.  Minimum detection limits (MDLs) in the 20-50 parts-per-billion  by volume
(ppbv) were achieved by concentrating samples one-hundredfold (lOOx) using a portable dual adsorption trap
sample concentrator.  Analysis time per sample, including  concentrating, was typically under ten  minutes.
Seven to 20 on-sitc and off-site locations were routinely sampled during site drum removal activities. The U.S.
EPA on-site-coordinator (OSC) could be immediately informed if VOCs were detected in the air samples and
appropriate corrective actions could be taken initiated.
       The  dual  column, dual ^TCD  configuration  of the FPGC  permit  the  use of "correlation
chromatography* techniques to enhance  peak identification.   Correlation chromatography allowed  the
compound  library, containing the response  factors and retention indices  for one hundred VOCs, to be
normalized using a small subset of three or more VOCs contained in a Held calibration standard.  Numerous
VOCs detected in the air samples could be tentatively identified even though not present in the field standard.
Standard Operating  Procedures (SOPs) have been developed on the field sampling and analysis of ambient
air samples, along with quality assurance and control (OA/QC) protocols.
       The microchip FPGC, along with the sample concentrator and vacuum box sampler, provides a simple,
rapid and reliable way to monitor fugitive emissions of VOCs during drum removal activities. On-site  FPGC
analysis compared well, both qualitatively and quantitatively, to confirmatory samples analyzed via TO-1, TO-2
and TO-14 methods on two different gas chromatograph/mass spectrometer (GC/MS) systems.

INTRODUCTION
       FPGCs have been used to generate rapid on-sitc analysis at  Superfund sites throughout the United
States.   FPGCs have been  used to delineate the extent of environmental  contamination, assess  removal
activities and  monitor fugitive  emissions during site remediation efforts.(W>
                                               445

-------
         Simple on-site sampling and analytical  systems were required to monitor fugitive emissions at two
 Superfund sites. The sampling regimen had to be flexible to adjust to changing wind patterns, scope of site
 activities and site locations at which the drum removal activities were to occur. The analytical system had to
 be flexible to rapidly screen numerous air samples that were poorly characterized in terms of the VOC species
 present.  Rapid analysis was required to initiate corrective actions that would reduce the release of fugitive
 emissions during the drum removal activities.
         Two case studies will be discussed to highlight the flexibility of the on-site analytical system. The sites
 varied significantly in their size, sample  load and local.  Both sites required on-site analysis with rapid sample
 turnaround time.

 METHODS AND  MATERIALS
         The vacuum box sampler is a commercially available rugged shipping case that has undergone several
 simple  modifications.  The only necessary requirements that the box must have are an airtight gasket sealed
 lid, a vacuum release vent and a latch to close the box (Pelican Case Model  #1300 or equivalent). The foam
 liners and any other materials are removed from the inside of the box.  Two sets of stainless steel quarter-inch
 outer diameter (SS  1/4" O.D.) one-way quick-connect bulkhead fittings (Swaglok Cat 4 SS-QC 4-S-400, of
 equivalent)  are mounted through the side of the vacuum box.  Lengths of Teflon tubing are  attached to the
 quick-connect bulkhead  fittings as shown in Figure 1.  A personal sampling pump (Gilan Model #HFSll3i
 or equivalent) with  a flow rale of two liters per minute (2 L/min) is attached to one of the outside  fittings-
 A Teflon lined air sample bag is attached to the other fitting, inside the box. The box is closed and scale"-
        The pump is activated which evacuates the box.  As the box is evacuated the air sample bag is
 with ambient air.  The pump is stopped once the bag is full.  The vacuum is broken by opening the vacuum
 release vent  and the air sample bag is removed. The one-way quick-connect valves will prohibit the loss of
 sample from the sample bag while  it is being removed. The vacuum box is very easy to construct, simple to
 operate and  reliable.  It can be used for ambient air, soil gas, and confined space sampling.
        The air samples in Teflon-lined  air sample bags are concentrated one-hundred fold (lOOx)  using »
 field-portable dual adsorption trap sample concentrator. The sample concentrator was built by Louisiana State
 University (LSI!) and has two traps, each packed with Tenax and Spherocarb (80/100 mesh). A sample pu^P
 pushes sample  onto one of the traps at room temperature. The sampling period and flow rate are adjusted
 so that a known volume of sample is placed onto the trap. The  trap is then rapidly heated to 240 "C «£"
 backflushed with helium  to thermally desorb the sample VOCs off the trap and into a gas-tight syringe.
 sample syringe is submitted to the P200 FPGC for determination  of VOCs.  By knowing the volume pl
 onto  the  trap  and the volume desorbed and backflushed  into the syringe, a concentration factor  can
 calculated.
        The  sample concentrator has been successfully used on compounds ranging in volatility fro""
 chloride  to o-xylene.  Minimum detection limits (MDLs) for air samples can be lowered to the 20-50
 range by using  the sample concentrator. Sample concentration typically take two to five minutes per ^a
 with the dual trap configuration allowing a sescond sample to be concentrated on the second trap while I"
 first trap returns to room temperature.
        The  concentration is  manually  operated and  is  of simple  design.   It  can  be fabricated
 commercially available parts at a cost of $2,000-13,000. It operates under 110 VAC power, although LS
 also built  12  volts  DC battery-operated units.
        The  Microsensor Technologies, Inc. (Fremont, CA, USA)  Model P200 FPGC employs dual &
 columns and  dualpTCDs permitting the use of "correlation chromatography" techniques. A software P
 (M2001 v2.2) was written by LSU which uses correlation chromatography to update the retention time
 (RTIs) and the^TCD response factors (RFs) of 100 VOC compounds in the peak identification library
 on a calibration standard of three or more VOCs.  As a result, VOCs present in the sample but  not P
in available field calibration standards can be tentatively identified  based on library RTIs and Rps
These tentatively identified compounds (TICs) are library estimates only but have been found  to
reliable when compared to GC/MS confirmatory analysis.  The dual analytical capabilities of the
allows one column to act as the confirmation column of the second, thereby increasing the level of
                                                446

-------
in the software peak identification  routines.  The M2001 v2.2 software rum on a Macintosh SE computer.
TV F200 FPGC can also operate using the IBM-PC based software EZCKROM, which is provided with
purchase of the P200. EZCHROM does not use correlation chromatography techniques, but is a very flexible
Microsoft Windows 3.0 based software package.
        The^TCDs of the P200 FPGC are universal detectors responding to any compound with a different
heat capacity than the helium carrier gas. The dual capillary columns are 4-meter narrow-bore, high-resolution
columns.  A homologous series of n-alkanes is used to normalize the RTU of the two columns.  This step is
essential for the  use of correlation chromatography.  The two columns are of different polarity (OV17,
OV1701), which will elute the VOCs species compounds and yield different RTts for each column.  A second
standard of mixed  chlorinated and  aromatic  hydrocarbons  is  used to update the RFs of the jiTCDs.
Calibrations are performed in  the field daily to ensure proper VOC identification and quantification.  The
M2001  software provides complete documentation  of instrument  conditions, calibration  data  and sample
results.

        Case Study #\
        A small 2-acre site (Figure 2) in New York was contaminated with benzene, toluene and methyl ethyl
ketone (MEK), as well as various other chlorinated solvents. The site was a solvent blending operation which
had illegally disposed of wastes in numerous underground tanks  and leeching pools located on-site.  Several
dozen  drums  of wastes  were illegally buried.   Site  soils were grossly contaminated with groundwater
contamination  determined from previous extent of contamination studies.
        The U.S. EPA requested on-site air monitoring during emergency drum removal activities. The on-site
monitoring had to yield rapid data to inform the VS. EPA OSC in the event  that VOCs were released during
removal activities.  Site activities would be curtailed if VOCs were detected  and corrective actions would be
immediately initiated by the OSC.  Seven on-site and off-site locations were selected to be sampled during
drum removal  activities.  The locations were sampled every hour and immediately submitted to the on-site
P200 FPGC For  VOCs  analysis.   Several Summa  canister grab samples were taken  for TO-14 GC/MS
confirmatory analysis and compared well, both qualitatively and quantitatively, with the P200  data.

        Case Study *2
        A large 200-acre industrial site in New Jersey (Figure 3) had several hundred thousand buried drums
on site.  The site had operated since the 1950s and had legally buried drums and other wastes in approved on-
site landfills.  Over the years the groundwater became contaminated and forced the closure of nearby
residential drinking wells.  The U.S. EPA determined, that the  drum& would have to be  removed without
adversely affecting the air quality of the neighboring residential developments.
        A study was undertaken to test drum-removal procedures at 10 on-site test pits. Air samples were
collected hourly at up to 20 on-site  and off-site locations during  drum removal and  other soil  intrusive
activities.  Samples were immediately  submitted to the on-site P200 FPGC for determination  of VOCs. The
OSC would be immediately  notified if the VOCs, especially benzene, were above the action limits so that
corrective actions could be initiated.   Fifty or more samples  were collected daily with ten percent (10%)
selected for confirmatory analysis.
        Confirmatory analysis was accomplished by collecting air samples from one-liter air sample bags and
manually loading them onto adsorbent  tubes (Tenas/CMS) far a modified TO-l/TO-2 GC/MS analysis to be
performed at an off-site  laboratory. Table 1 compares the P200 and off-site  GC/MS results.
        In addition, on-site  confirmatory  analysis  was performed using  the Viking Spectra  Trak 600
transportable GC/MSon a select number of samples. Five-liter air sample bags were collected and placed onto
the Spectra Trak oWs internal adsorption cartridge. The cartridge was thermally dcsorbed into the GC/MS
system and screened for VOCs using a modified TO-14 GC/MS protocol. Table 2 compares the P200 and on-
site GC/MS results.

CONCLUSIONS
        Air monitoring  during drum removal or  other site activities can be accomplished on-site using
instrumentation thai is commercially  available. The vacuum box sampler allowed for flexibility in selecting
                                                447

-------
sampling locations as wind patterns and site locations varied. The sample concentrator can be fabricated from
commercially available parts to lower the  MDLs to the 20-50  ppbv range.  The Microsensor P200 FPGC
permitted  the  rapid  on-site  analysis  of  air  samples for VOCs.  The  P200 software uses correlation
chromatography techniques allowing the tentative identification of VOCs not present in the on-site calibration
standard.   The dual analytical capabilities of the P-200 FPGC yields a  higher level of confidence in  the
identification of VOC species compared to single column and detector FPGCs.  The on-site data allowed site
removal activities to proceed rapidly with the knowledge that any fugitive emissions released would be quickly
detected by the on-site sampling and analytical systems.  SOPs have been developed  for the on-site sampling,
analysis and QA/QC protocols for ambient air monitoring.

REFERENCES
"       P. Clay and T. Spittler,  The Use of Portable Instruments in Hazardous Waste Site Characterizations,'
        in Proceedings of the National Conference on Management of Uncontrolled  Hazardous Waste Sites.
        HMCRI, Washington,  D.C., November, 1982, pp. 40-44.

2)       L. Kaelin, D. Mickunas, R. Wynnyk and T. Pritchett, "Fenceline Air Monitoring  at a Superfund Site
        Using a 16 Channel Gas Chromatograph  with an Argon lonization  Detector," in Proceedings of the
        1991 U.S. EPA/AWMA International Symposium on "Measurement of Toiric and  Related  aif
        Pollutants".  Air  and Waste Management Assoc., Durham, NC, May, 1991, pp. 747-751.
                                               448

-------
           TABLE i. COMPARISON OF TENAX/CMS ADSORPTION TUBE GC/MS
          T-Ql/T-02 ANALYSIS AND MJCROSENSOR P200 FPGC SCREENING DATA
SAMPLE
DATE
                                       Benzene
GC/MS
P200
      Toluene
GC/MS       P200
B13418
D13418
H3418
113418 DUP
B13423
C13423
D13423
E13423
D13429
D13447
F1S447
D13546
D13474
F13474
D134SO
D13462
F13480
F13480 DUP
D13492
F13492
D13471
D13498
F13498
F13498 DUP
D13491
D13522
E13522
E13424
D13509
F13511
D13528
01/18/92
01/28/92
01/28/92
01/28/92
01/29/92
01/29/92
01/29/92
01/29/92
01/30/92
01/30/92
01/30/92
01/31/92
01/31/92
01/31/92
02/03/92
02/03/92
02/03/92
02/03/92
02/04/92
02/04/92
02/04/92
02/05/92
02/05/92
02/05/92
02/05/92
02/06/92
02/06/92
02/06/92
02/07/92
02/07/92
02/07/92
51»
5>
8^fl
3.4"
4,4"
4^"
NCf^
56
63
7 $**
3-ff"
4-rf1'
gjrffl
8.

ND*4 ND"1' ND1" ND"' NDf1' ND™ ND*1* NDfl) Ntfl> NDf1' ND"' Ntf1' ND'" Ntf" NC*1J ND*11 NE*» ND"> Ntf" ND-" ... Ntf" NDf" ND^5' ND^" ND'" ND**' ND'' ND"" ND-5' ND'" ND" ND-" ND131 1h^«B ND"' ND^' ND^B NDf!) NDf!) ... NEP ND'*' ND^S> NDf5) ND*n ND"*' M#> 47.2 15.0 10.5 2.dJ) 783 46^ NDflJ 50.9 13.2 ND"1 4.lf3} 3.8^" 45.6 l&g 20.7 29.4 22J 9.0 47?) ND1" 75.0 17^ 12.0 12.4 2j(P ND"1 55.2 31.8 17,0 87.1 35.0 NlV^ NC^'ty NcVn .... Mrt[5) ND'^1 ND"' Ntf" Ntf" Ntf*5 ND"* NDf1' NDf" NDf5' NDf}* NDf5' Ntf5* — NDfJ) ND*J] ND1'5 ND^ Ntf" — Ntf5' ND"S) ND^ Ntf^ ND1*1 NC^ NC^^ All concentrations are in parts^pcr-bttlion by volume (ppbv). (1) None detected at MDL - 2.5 ppbv 1 None delected at MDL - 5,0 ppbv 1 Below quantitation limit at QL = 5.0 ppbv ('} Below quantilalion limit at QL * 10.0 ppb c" None detected at MDL - 20 ppbv 449


-------
           TABLE 2. COMPARISON OF VIKING SPECTRA TRAK 600 GC/MSTO-14
               ANALYSIS AND MICROSENSOR P200 FPGC SCREENING DATA
 Sample No.     Date
Viking
                                       Benzene
P200
All concentrations in pam-per-btllion by volume (ppbv)

0)      Below Minimum Detection Limit (MDL1< 30 ppbv
(I)      None detected at MDL • 20 ppbv
                                      Toluene
Viking
P200
D13499
D13505
E13506
C13523
D13522
C13526
D135IO
B13512
D13532
D13513
D13515
D13534
B 13536
E13527
C13S42
G13546
B13547
D 13548
H13541
F1355I
C13553
E13561
F13561
02/06/92
02/06/92
02/06/92
02/06/92
02/06/92
02/07/92
02/07/92
02/07/92
02/10/92
02/10/92
02/10/92
02/10/92
02/10/92
02/11/92
02/11/92
02/11/92
02/11/92
02/11/92
02/12/92
02/12/92
02/12/92
02/12/92
04/02/92
BMDL™
BMDL
BMDL
BMDL
BMDL
BMDL
BMDL
BMDL
BMDL
BMDL
BMDL
BMDL
BMDL
BMDL
BMDL
BMDL
BMDL
BMDL
BMDL
BMDL
BMDL
BMDL
BMDL
ND*
ND-
ND
ND
ND
ND
ND
ND
ND
ND
ND
ND
ND
ND
ND
ND
ND
ND
ND
ND
ND
ND
ND
BMDL'"
BMDL
BMDL
BMDL
BMDL
BMDL
BMDL
BMDL
BMDL
BMDL
BMDL
BMDL
BMDL
BMDL
BMDL
BMDL
BMDL
BMDL
BMDL
BMDL
BMDL
BMDL
150
ND*
ND
ND
ND
ND
ND
ND
ND
ND
ND
ND
ND
20
ND
ND
ND
ND
ND
ND
ND
ND
ND
33
                                         450

-------
                       VACUUM  BOX  SAMPLI'R
       GASKET SEAL
                                                                 - i 4" o D VACUUM LINE
                                                                   TEFLON TUBING
                                                                     z
                l l  O.D
                SAMPLING LINE

1/4" S.S  BULK HEAD FITTINGS WITH
ONE-WAY QUICK CONNECT VALVES
Figure 1. Vacuum Box Sampler

-------
                          NEW  YORK  SITE
               OFF-SITE

            /,
              /
                 /
                   /

               BURIED
               DRUMS

I




QUONSET
PfPE BLDG

.






\
(
5
         LEGEND

          E3 UNDERGROUND TANK
           ©  LEACHING POOLS
          - -FENCE
           ®  SAMPLE LOCATION
   GRAPHIC SCALE
ZG         0    10    20
Figure 2. New York Sampling Locations.
                                    452

-------
r
f-
                                                                                                       Nl'iW  .IKKSKY  SITE
                                    GRAPH!'

i RAILROAD
 snr BouNtjABv
.BOUHDARY FtUCK
 SAMPLE LOCATION
                           Figure 3. New Jersey Sampling Locations

-------
             CONTINUOUS REAL-TIME FORMALDEHYDE MEASUREMENTS
                         IN AMBIENT AND TEST ATMOSPHERES

                           Thomas J. Kelly and Gerald F. Ward
                                         Battelle
                                     505 King Avenue
                                Columbus, Ohio 43201-2693

                                  Christopher R. Fortune
                             ManTech Environmental Technology
                        Research Triangle Park, North Carolina 27709

ABSTRACT
   This paper presents examples of continuous formaldehyde measurements made in a variety of
ambient air  and test environments, using a recently developed sensitive and continuous  monitor.
The monitor functions by scrubbing gaseous formaldehyde from air into an aqueous stream, forming
a derivative  in 1:1  stoichiometry  with  the formaldehyde, and  measuring that  derivative  by
fluorescence. The limit of detection of the monitor is 0.2 ppbv with a time response of about 45
seconds, with no significant interferences.  The high sensitivity of the monitor has been applied in
measurements of  low ppbv indoor and outdoor formaldehyde concentrations  at ground level, in
airborne measurements in field studies for acid rain model validation, and in tests of air purification
systems intended for use in museums and other buildings.  In  addition, the monitor has been applied
in studies requiring  measurements of elevated levels of formaldehyde (i.e., > 100 ppbv), by adjust-
ing  monitor  settings away from optimum values to reduce the monitor's sensitivity.   Studies con-
ducted with  reduced sensitivity include validation of chamber  formaldehyde levels in testing of a
bioprobe sensor for formaldehyde,  measurements of formaldehyde emissions from various gas
burner designs, and measurement of emissions from construction materials.  This paper provides
examples of the results from each of these studies.

INTRODUCTION
   Measurement of formaldehyde (HCHO) in the atmosphere  and in indoor air is of interest because
of its toxicity, including suspected carcinogenicity in humans.  In the atmosphere, formaldehyde is
both a primary emission from combustion processes, and a secondary product of hydrocarbon oxida-
tion.  Formaldehyde produces free radicals upon photolysis, contributing to the formation of  ozone
and other oxidants.  Formaldehyde is  also emitted from a variety  of man-made materials, contri-
buting to elevated indoor concentrations. Measurements of formaldehyde in air are commonly made
by derivatization with 2,4-dinitrophenylhydrazine (DNPH),e-«- J but that is a time-integrated sam-
pling  method not amenable to real-time analysis.  Spectroscopic methods are available, but generally
involve large,  complex,  and expensive instrumentation.  Smaller and less  complex continuous
HCHO analyzers have been developed, based  on scrubbing of gaseous HCHO into aqueous solution
for subsequent analysis.2"6 However, those monitors have various limitations in terms of reliability,
cost of reagents, time response, or sensitivity.  The monitor used in  this study combines some  of the
best features of those previous monitors with an improved detection method to achieve sensitive and
reliable HCHO measurements.7'8  The  purpose of this paper is to demonstrate the reliability and
utility of continuous formaldehyde monitoring, by showing examples of recent measurements.

EXPERIMENTAL
   The continuous formaldehyde monitor used in this study  has been fully described elsewhere,7'1
and has undergone  extensive  field testing.8-9   Briefly, the monitor is based on the collection and
                                            454

-------
derivatization of formaldehyde in aqueous solution, with detection of the derivative by fluorescence.
The monitor employs the Hantzsch reaction, the cyclization of an aldehyde, an amine, and a j3-dike~
tone,  to form the fluorescent product,10'11 but achieves higher sensitivity than previous instruments
using this approach by using UV light for excitation rather than the visible  light used previously
(U.S. patent pending).  The improved fluorescence sensitivity allows use of a simple but efficient
glass  coil scrubber for collection of HCHO from the gas phase, rather than the complex and  some-
what  unreliable porous tube diffusion scrubbers  used previously.3-4   The  monitor has a detection
limit for formaldehyde of 0.2 ppbv,  with a time response of about 45  seconds.  The monitor is com-
parable in detection limit to previous real-time HCHO monitors, but provides faster time response
with a simpler and more reliable sampling arrangement, and with simple and inexpensive reagents.
   A valuable feature of the monitor is that several operational parameters can be manipulated from
their optimum values to reduce the sensitivity of the monitor.  This provides flexibility in  operation
and makes the monitor applicable to high levels of HCHO, as well  as to the low ppbv levels for
which it was originally designed.  Among the parameters which can be adjusted are sample air flow
rate,  reagent composition, reaction time,  reaction temperature, and fluorometric  sensitivity  via
shutters and filters.  Discussed below  are several examples of studies in which continuous formal-
dehyde monitoring was valuable, both at low  atmospheric levels and at high levels in laboratory
studies.

RESULTS
   Low-Level Measurements. The capability  for continuous HCHO monitoring down to sub-ppbv
levels has been used in several studies.  One example is shown in Figure 1 which shows indoor  and
outdoor HCHO measurements from  a U.S. EPA field study in Columbus, Ohio.  In this field  study,
the wet chemical monitor was housed in a  small trailer parked at a  residence in Columbus,  Ohio;
measurements  were made from the  morning of June 20 to the morning of June 30,  1989. Sample
air was drawn into the trailer through a three-way valve by a sampling pump.  Air  was drawn for
alternate 30-minute periods through a length of  1/4-in, O.D. Teflon tube extending above the roof of
the house, or a comparable length of tubing extending through a fitting into the house.  The monitor
sampled the incoming air downstream of the valve. In addition, zero  air (UHP, Matheson) was sup-
plied  in excess to the monitor for  6 minutes centered on the hour,  each hour of the field  study.
Thus  the monitor sampled indoor air for 27 minutes, outdoor air for  27 minutes, and zero air for 6
minutes sequentially.  The resulting  average values arc plotted in Figure 1.  Note that the indoor air
HCHO concentrations greatly exceeded the outdoor concentrations.  This was generally the case and
required that the sensitivity of the wet chemical monitor be reduced  somewhat in order to keep the
indoor values onscale while maintaining enough sensitivity to  measure the outdoor values.   Indoor
values which were still  offscale are shown as diamonds in  Figure 1.   The  outdoor data never
exceeded 7 ppbv and averaged 3.3 (±1.5) ppbv.  The outdoor HCHO concentrations were consider-
ably lower in  the final 2 days of the  study, following passage of a  cold front, than earlier  in the
study. Indoor levels were also lower during this period due to increased ventilation of the home.  A
strong diurnal pattern in the outdoor HCHO was observed, with minimum  average values of about
1.5 ppbv at 7 a.m.,  and maximum values averaging over 4 ppbv  in late morning and  evening.
Comparison of averaged real-time HCHO data  with DNPH samples  from this study indicated good
agreement.
   A second example of low-level continuous HCHO measurements is drawn  from use of the moni-
tor aboard Battelle's  G-l aircraft in a  field  study to evaluate regional acid deposition models.  The
monitor was flown on the G-l on 12 flights between May 3 and May  21, 1990.  Figure 2 shows the
results of one such flight in which the aircraft  remained  within the boundary  layer for most  of the
flight, but also conducted  two vertical profiles up to 3.8 km altitude.  That  flight originated  in
Columbus, Ohio, and  covered portions of Kentucky and Ohio.  The two vertical profiles were made
                                            455

-------
500 km and  about 2  hours apart, over the  southern Kentucky border and over northwest Ohio,
respectively.  Figure 2 shows  both aircraft altitude and HCHO concentration,  plotted versus time
(GMT), and illustrates that HCHO levels of about 2 to 5 ppbv were observed in the boundary layer.
The highest levels were observed during the later portions of the flight, which occurred during mid-
aftemoon.  Both vertical profiles indicate HCHO  levels dropping off sharply above the boundary
layer.  Thus HCHO shows a vertical profile that resembles those found for NOX, SO2, and aerosol
particles, pollutants known to  have a boundary-layer source.  Other flights in the  study  showed
similar HCHO levels in clear air, but levels consistently below 1 ppbv were observed on all flights
conducted in rainy situations.
   Further measurements of low HCHO levels were made in the Atlanta Ozone Study,9 where the
monitor was used for  2 weeks  at a ground site in  South Dekalb, Georgia.  Automated zeroing and
calibration  were implemented four times daily during this period.   Figure 3  shows an example of
one day's data from the Atlanta study.  The monitor gave very stable response throughout the study,
as indicated by a relative standard deviation of 6.1 percent for 62 calibrations.  The ambient data
showed HCHO levels  consistently <0.2 ppbv between  10 p.m. and 6 a.m. each day, with daytime
values up to 13 ppbv and averaging about 4 ppbv.  During precipitation events daytime HCHO con-
centrations  were reduced, and lower concentrations were observed on cool, cloudy days than on hot
hazy  days.   Daily maximum  concentrations  usually occurred around midday, with a  secondary
maximum in the evening.
   A final example of low-level HCHO measurements is from a laboratory test of the efficiency of
adsorbent media, intended for air purification in the National Archives II building under construction
in College Park, Maryland.  In this test the sorbent media were placed in a test apparatus, consisting
of a duct through which passed air doped with constant pollutant levels.  HCHO was introduced into
the upstream air flow and  was monitored  with the continuous analyzer downstream of the tested
media for a period of 80 hours.  The monitor was zeroed and calibrated at intervals  during the
study, and was also  used  to  sample the  background HCHO level in the  test air entering the
apparatus.  The target downstream level was 4 ppbv, however, the monitor's high sensitivity showed
that downstream levels never exceeded 0.4 ppbv, indicating that the adsorbent media not only met
but exceeded the study requirements.
   High-Level Measurements.  Three recent studies have required continuous formaldehyde mea-
surements at levels from 100 ppbv up to 2 ppmv.  One such study involved measurement of emis-
sions  of HCHO from  a variety of gas burner designs, including several designed to minimize NQi
emissions.  For this study, a burner was lit and allowed to stabilize at temperature, and then placed
inside a stirred  17 m3 chamber, from which air was sampled by the continuous HCHO monitor and
several oxides of nitrogen analyzers.  The concentrations of HCHO and nitrogen species were moni-
tored  for up to 2 hours.   Use of the continuous monitor allowed the evolution of HCHO to be fol-
lowed in real-time in  the same way that is commonly done for nitrogen species.  The key finding of
this study was that the burners designed for low NOX production did indeed  reduce NOXI but also
produced up to ten times as  much HCHO as did the standard burner.
   A second example  of high-level measurements is use of the monitor to confirm and track HCHO
levels prepared in a chamber for testing of a bioprobe sensor for formaldehyde.  For those tests, the
monitor's sensitivity was turned down so that levels up to 2 ppm could be measured.  HCHO levels
were  prepared in the known chamber volume by vaporization of known quantities of HCHO solu-
tion,  and the resulting gaseous concentrations were then checked by  the real-time monitor.  The
monitor provided  rapid, independent verification  that  the  prepared chamber HCHO levels  were
within 5 percent of the target levels of 0.5,  1.0, and 2.0 ppmv, and  also monitored the decay of
HCHO in the chamber, allowing test-average HCHO values to be rapidly determined.
   The final and most severe extension of continuous HCHO monitoring to high levels occurred in
testing of HCHO emissions from a common construction material. The material was subjected to
                                           456

-------
static  chamber tests at elevated temperatures, and to dynamic chamber tests in which routing and
bending operations were conducted, simulating installation of the material.  In the dynamic tests, the
monitor sampled chamber air continuously, with HCHO levels up to a few ppm.  The continuous
measurement gave rapid feedback of information on the progress  of the test, and allowed emissions
from successive individual portions of the material to be resolved temporally.  These  measurements
can be used  to determine emission factors per unit of material for each of the operations conducted.
In the static  chamber test, HCHO levels up to 20 ppm were observed. It was necessary to dilute a
flow of air from the chamber by 1:10, in order to reduce the concentration to the 1-2 ppm range for
measurement.  The monitor allowed the emission of HCHO from  the material to be determined as a
function of time and, since temperature increased slowly throughout the test, also to some extent as
a function of temperature.  Data from these measurements will be used to estimate product emission
rates and the potential for human exposure to such emissions.

CONCLUSIONS
    The examples presented here illustrate the broad applicability of continuous, real-time monitoring
of HCHO.  Although the applications shown are diverse, the factor common to all is that continuous
monitoring provided advantages in sensitivity,  speed, and/or cost relative to the more  common
integrated DNPH method.  Only continuous monitoring could have provided the high sensitivity and
time response  required  for the airborne HCHO measurements.   The ground-level  measurements
illustrated here also benefitted greatly from the rapid response and sensitivity of continuous analysis;
definition  of diurnal and short-term  variations would likely  have  been  impossible  with DNPH
campl"1?' an^ at *)est wou^ kave  *)een very expensive due to the  manpower requirements of DNPH
sampling'and analysis. The inexpensive and immediate indication of HCHO concentration is a great
advantage of continuous monitoring,  allowing evaluation and control of ongoing experiments.  For
 xarnple the  performance of the adsorbent media during the test could be observed in real-time, and
^Devaluation of HCHO from the gas burners  could be related for the first time to  corresponding
continuous measurements of the nitrogen species.  In the tests of the bioprobe, continuous HCHO
  onitoring provided an immediate go/no-go  decision on  the  accuracy  of the  prepared test
concentrations,  eliminating  the  delay  inherent in  the DNPH  method.    Similarly, continuous
  onitoring of HCHO in  the materials tests provided a direct measure of emission rates, and allowed
Jhe installation  test procedures to be conducted rapidly and  efficiently. Time-integrated methods for
fTCHO measurement are effective and  well-established, but it is clear that  continuous  real-time
HCHO monitoring is now  well  enough developed to provide  more rapid,  sensitive, and cost-
effective measurements in many applications.
l     D. Grosjean and K. Fung, Anal. Chem.. 54, 1221 (1982).
\'    R  R. Miksch, D.  W. Anthon, L. Z.  Fanning, C. D. Hollowell,  K. Revzan, J. Glanville,
      AuaL_OiejiL, 52, 2118 (1981).
_     P. K. Dasgupta, S. Dong, H. Hwang, H.-C. Yang, and Z. Gensa, Atmos. Environ., 22, 949
      (1988).
            .
      S. Dong and P. K. Dasgupta, Environ. Sci. Technol.r 2J., 581 (1987)
        .                                                .            .
 *    A. L. Lazrus, K. L. Fong, J. A. Linda, Anal. Chem.. £Q, 1074 (1988).
 *    C. R.  Fortune,  D.  H. Daughtrey,  Jr., and W.  A. McClenny,  "Development of a portable
      continuous monitor for trace levels  of formaldehyde in air", Paper 89-81.2, presented at the
      82nd Annual Meeting of the Air and Waste Management Association, Anaheim, California,
      June 1989.
                                           457

-------
 7.   T. J. Kelly, R. H. Barnes,  and W. A. McClenny, "Real-Time Monitors for Characterization
     of Formaldehyde in  Ambient and Indoor Air",  in  Measurement of Toxic and Related Air
     Pollutants. Proceedings of the 1989 EPA/AWMA International Symposium, EPA Report No.
     600/9-89-060, Air and Waste Management Association, Pittsburgh, PA, pp 43-50 (1989).
 8.   T.  J.  Kelly, and  R.  H.   Barnes,  "Development  of Real-Time  Monitors for  Gaseous
     Formaldehyde",  Final report to U.S. Environmental Protection Agency, EPA/600/3-90/088,
     83 pp, November 1990.
 9.   C. R.  Fortune, "Continuous monitoring of formaldehyde during the Atlanta ozone precursor
     study", paper 91-68P.12, presented  at  the  84th  Annual Meeting of  the Air and Waste
     Management  Association, Vancouver, B.C., June  1991.
10.   T. Nash, Biochem. 5_5_, 416-421 (1953).
11.   S. Belman, Anal. Chim.  Acta.r 22, 120-126 (1963).
          60
                                       JUNE 20 to 30. 1989
         30 -
         40 -
         30 -*
         20 -
         10 -

                                                                  INDOOR
                                                                                     /
                                                                OUTDOOR
W
           06:00   06:00   06:00   06:00   06:00   06:00   06:00   06:00   06:00   06:00   06:00

                                          TIME OF DAY
               Figure 1. Continuous indoor and outdoor HCHO measurements,
                           June 20-30, 1989, Columbus, Ohio.
                Diamonds represent periods when indoor levels were offscale.
                                          458

-------
M:50:58
                      15:52:58
                                                                 17:56:48
                          I         I
                     Atlanta, Georgia
                     August  11, 1990
                              1654:58
                         nme(lO-s avBrage)

Figure 2.  Continuous airborne HCHO measurements, May 11, 1990,
          over Ohio and Kentucky.  Time  shown is GMT.

  1.3

  1.2

  1.1

  1.0


>  0.9



  0.7

  0.6

  O.S

  0.0
                       11:08:00   11:12:00   11:16.00   11:20:00  12:00.00  12:04:00
                                           Time
           Figure 3.  Continuous HCHO measurements in the Atlanta, Georgia, area,
                   August 11, 1990. Automatic zeroes and spans are shown.
                                Time indication is dd:hh:mm.
                                                                        18:58:48
                                            459

-------
      Session 11
   Quality Assurance
Shri Kulkarni, Chairman

-------
     ACCURACY ASSESSMENT OF EPA PROTOCOL GASES
                              PURCHASED IN 1991
                   Easter A. Coppedge, Thomas J. Logan, and M. R. Midgett
                           U.S. Environmental Protection Agency
                                     Mail Drop 77-A
                           Research Triangle Park, North Carolina
                 Richard C. Shores, Michael J. Messner, Robert W. Murdoch,
                                   and R. K. M. Jayanty
                                 Research Triangle Institute
                                   Post Office Box 12194
                           Research Triangle Park,  North Carolina
jiVBSTRACT
       One area of concern for the U.S. Environmental Protection Agency (EPA) is the reliability of
compressed gas standards used for calibration and audits of continuous emission monitoring systems.
BPA's regulations require that the certified values for these standards be traceable to National Institute
of Standards and Technology (NIST) Standard Reference Materials or to NIST/EPA-approved Certified
Reference Materials via a traceability protocol.  This manufacturer assessment was conducted to (1)
document the accuracy of the compressed gas standards' certified concentrations and (2) ensure that the
compressed gas standards'  written  certification  reports  met  the documentation requirements of the
protocol. All available sources were contacted and the following gas mixtures were acquired: (1) 300
ppm SOj and 400 ppm NO in N2 and (2) 1500 ppm S0j and 900 ppm NO in N2.
       The results indicated that the average differences  for S02  were 0.8 and  1.5% and that the
Associated standard deviations of the differences were 2.8  and  3.7% for the 300-ppm and  1500-ppm
concentrations, respectively. The average differences for NO were 0.2 and 0.3% and the associated
standard deviations of the differences were 1.0 and 1.4 % for the 400-ppm and 900-ppm concentrations,
respectively.
       The results show that 94% of the manufacturer-reported cylinder gas concentrations are within
j-5% of the true concentration.

jNTRODUCnON
       The U.S. Environmental Protection Agency (EPA) has established quality assurance procedures
for air pollution measurement systems that are  intended to reduce the uncertainty in environmental
measurements.  One area of concern is the reliability of compressed gas standards used for calibration
and audits of continuous emission monitoring systems.  EPA's regulations require that the certified
values for these standards  be traceable to National Institute of Standards and Technology (NIST)
Standard  Reference Materials (SRMs) or to NIST/EPA-approved Certified Reference Materials via a
traceability protocol.1"* The protocol was published originally in 1978 and revised in 1987.
       Seven  accuracy assessments of compressed gas standards have previously been conducted6"*.
These standards were prepared  and analyzed by gas  specialty manufacturers according to the EPA
protocol. The results of this assessment will be referred to as "Cylinder Audit No. 8."  The purposes
nf the assessment were (1)to document the accuracy of the standards' certified concentrations and (2)
to ensure that the standards' written certification reports met the documentation requirements.  All
                                           463

-------
 available sources were contacted and the following gas mixtures were acquired: (1) 300 ppm SOj and
 400 ppm NO in N2 and (2) 1500 ppm SOj and 900 ppm NO in N2.
        The results  of this audit can be used as an indicator of the current status of the accuracy of EPA
 protocol gases as a whole, but should not be regarded as a final statement.  Individual results should
 not be taken as definitive indicators  of the analytical capabilities of individual manufacturers.

 EXPERIMENTAL METHODS
 Purchase of Compressed Gas Standards
        Nine specialty gas manufacturers indicated that they provide standards that are prepared and
 analyzed  according to the EPA-required  protocol.  These manufacturers are listed below.
        Air Products
        Airco Industrial Gases
        Alphagaz Liquid Air
        Liquid Carbonic
        Matheson Gas Products
        MG Industries
        National Specialty Gases
        Scott-Marrin,  Inc.
        Scott  Specialty Gases
        Compressed gas standards sold under the brand names of National Welders, Union Carbide, and
 Linde are represented  by National Specialty Gases.  Research Triangle Institute (RTI) conducted this
 audit and used a third-party buyer to  purchase and receive the standards.  This was done to ensure that
 gases of typical quality were obtained for the assessment. The price of a standard ranged from $315
 to $599 with an average price of $461.

 Analytical Procedures
       The  cylinders  were  grouped  according  to  their reported concentration (high and  low
 concentrations), and the cylinder contents  were analyzed by  group.   RTI measured the pollutant
 concentrations of the  compressed gas standards by using instrumental monitors (IMs):  ultraviolet
 fluorescence for SOj and chemiluminescence for NO.  Both calibration  standards (NIST SRMs) and
 compressed  gas standards were sampled without dilution through a stainless steel,  Teflon and glass
 sampling manifold.  Sample flow through  the manifold was controlled by stainless steel solenoid valves,
 a needle valve, and a  digital timer.   Flow through the manifold  remained constant during both IM
 calibration and cylinder audit analysis by maintaining a constant manifold pressure using a Heise gauge
 and the compressed  gas cylinder regulator. The sample manifold allowed both the S02 and NO IMs to
 analyze cylinder gases  simultaneously. Excess  cylinder gas was vented from the laboratory through
 appropriate exhaust  vents.   The voltage outputs  from the instruments were recorded by a data logger.
 Concentration  calculations were made with averaged voltages from the data logger.
       Multipoint calibrations were conducted with NIST SRMs.  Linearity of the instrument's response
 was evaluated  by using the multipoint calibration data.  During analysis,  the concentration of each
cylinder gas was measured three times. Before and after each cylinder gas analysis, NIST SOj and NO
SRMs were sampled by both the SO, and NO IMs.  This routine provided data on the IM stability both
before and after the cylinder  gas analysis.  Concentrations were calculated as specified by the EPA
protocol procedure1. This procedure ratios the response of the IM when sampling the NIST SRM to
it's response when sampling the cylinder's contents.  The NIST SRMs were also used to determine if
the presence of SOj affected the response of the NO IM or if the presence of NO affected the response
of the SOj IM.  This interference test was necessary because the NIST SO^ and NO SRMs are single-
component (i.e., S02 or NO, in Nj) gases and the cylinder gas being analyzed contained both SQj and
NO in N2. The IMs were first calibrated with single-component NIST SRMs, and then the interference
                                             464

-------
 response was tested by blending the S02 and NO NIST SRMs, generating a multicomponent gas.
        Concentrations tested were similar to the cylinder gases analyzed. The results indicated that the
 response of the NO IM was not affected by the presence of SC^; however,  the response of the SOj IM
 was affected by the presence of NO.  The manufacturer of the ultraviolet fluorescence SOj IM reported
 that the lack Of Oj in the gas being analyzed caused the SO^ IM to respond to the presence of NO. The
 resultant linear regression  of the true concentration (ppm SQ, in multicomponent gases) onto the
 indicated concentration (ppm  S02 in single-component gases) yielded a slope of 1.05 and an intercept
 of 18 ppm-  This correction was applied to all the indicated SOj IM concentrations during the analysis
 of these multicomponent gases.

 RESULTS AND  DISCUSSION
 Results of Accuracy Assessment
        The  results of Cylinder Audit No.8  are summarized in Table I.   The accuracy of  a
 manufacturer's certified concentration is defined as the percent difference between the manufacturer's
 certified concentration and RTI's corresponding mean measured concentration. The average differences
 for SOz were O.8  and 1.5% with associated standard deviations of the differences of 2.8 and 3.7% for
 the 300-ppm and 1500-ppm  concentrations, respectively.  The average differences for NO were O.2 and
 O.3% with associated standard deviations of the differences of 1.0 and  1.496 for the 400-ppm and 900-
 ppm concentrations, respectively.  In general, 72% of the results fell within the ±2% range, and 94%
 of the results fell  within the ±5% range.
      The trend  of  the  data would suggest that  the accuracy  of the manufacturers' reported
 concentrations is improving.

 Uncertainty Estimates in Audit Results
     In  estimating  the uncertainty in the compressed gas cylinder concentrations that were determined
 during Cylinder Audit No. 8,  several sources of error, both random and systematic, were considered.
     I. Uncertainty in the NIST SRMs
     2. Error in measuring  the effect of NO presence on  the SOj measurements
     3, Lack of linearity of the IMs
     4, Memory effects of the IMs and uncertainty in correcting for these effects
     5. Variability in repeated measurements on the same cylinder gas
     The first four sources  of uncertainty combined  to an estimated total  of less  than 2% at a 95%
 confidence level.  The estimated relative standard  deviation was less than \%.  The fifth source of
 uncertainty, repeated measurements of the same cylinder, is negligible because the relative standard
 deviation was less than 0.2% in each case.  This 2% uncertainty estimate dictates that a difference
 greater than 2% between the audit concentration and the manufacturer's reported concentration should
 be regarded as statistically  significant.   More  specifically, results of an error analysis of the audit
 process indicated that for NO  at 400 and 900-ppm, differences greater than 1.1% may be regarded as
 statistically  significant; for S02  at 300 and  1500 ppm, differences greater than 1.3% and  2%,
 respectively, may  be considered statistically significant.

 Confirmatory Analyses
     As a confirmatory check of results, four compressed gas  standards were analyzed by  another
laboratory using the same EPA protocol. These cylinders were selected because of either high or low
percent differences between RTI results and the manufacturer's  certified concentrations.  The second
laboratory's  results agreed to within 0.6% of RTI's measured values for NO  and to within 0.8% of
RTT$ measured values for SO^ The good agreement between RTI and  the second laboratory for these
four cylinders suggests that  the other concentrations determined  by RTI are also accurate.
                                              465

-------
 Documentation
     An  important part of the protocol is the requirement for proper documentation in the written
 certification reports and the labels.  The manufacturers' reports and labels were reviewed to determine
 if the documentation requirements were being followed.  All  of the gas manufacturers'  provided the
 following information on  the  certification reports: cylinder ID number,  certification concentration,
 balance gas, lab and analyst ID, and 3 significant digits.  However, Matheson was missing the cylinder
 pressure and reference standard data; and  Liquid Carbonic was missing the certification and expiration
 dates, certification period in months, reference standard data, protocol statement and analyzer readings
 on their certification reports.
       All of the gas manufacturers' provided the following information on the labels:  cylinder ID
 number, certified concentration and balance gas.  However, the  following items were missing from
 some labels:

 Required Documentation on       Manufacturers Missing Documentation:
 Certification Reports
 Cylinder Pressure                 Alphagaz, Liquid Carbonic, Scott Specialty
 Certification Date                 Matheson
 Expiration Date                   Liquid Carbonic
 Ref. Standard Data                Airco, Alphagaz, Liquid Carbonic, Matheson,
                                  MG Industries,  Scott Specialty
 Protocol Statement                 Airco, Liquid Carbonic (Air Products and
                                  National Specialty cited 1978 protocol
 Lab and analyst ID                Airco, MG Industries, Scott Specialty
                                  (Liquid Carbonic and Matheson used only initials)
       Alphagaz performed SO2 analysis on a Tracor Atlas 825R-D hydrogen sulfide gas analyzer with
 an 856 total sulfur hydrogenator and a furnace operated at 1265°C and performed NO analysis on a
 Beckman 951A chemiluminescence analyzer.  One MG Industries cylinder contained only  350 psig
 rather than the 1800 psig reported on the certification report.
     The protocol specifies that some compressed gas standards are certified up to  18 months; others
 not specifically listed are certified for only 6 months. Because the multicomponent compressed gas
 standards analyzed as part of Cylinder Audit No. 8 are not specified in the protocol, the certification
 should be valid for only 6 months.

 Acknowledgements
    This work was funded by EPA under Contract Number 68D10009,  RTI Project No. 4960-013.
The  information contained in this  paper does not necessarily reflect the policy of the  U.S.
Environmental Protection  Agency.  The authors appreciate the assistance  of the third-party buyers,
Alliance Technologies Corporation, under the direction of Stan  Sleva. The authors also appreciate the
confirmatory analyses that  were conducted by Entropy Environmentalists,  Inc., personnel under the
direction of J. Ron Jernigan.
                                             466

-------
1- "Procedure 1. Quality Assurance Requirements for Gas Continuous Emission  Monitoring Systems
Used  for Compliance Determination,"  U.S.Environmental  Protection  Agency, Code of FederaJ
           Title 40, Part 60, Appendix F, 1987.
2- "Quality Assurance Requirements for State and Local Air Monitoring Stations (SLAMS)," U.S.
Environmental Protection Agency, Code of Federal Regulations. Title 40, Part 58, Appendix A, 1987.

3- "Quality Assurance Requirements for Prevention of Significant Deterioration (PSD) Air Monitoring,"
U.S. Environmental Protection Agency, Code of Federal Regulations. Title 40, Part 58, Appendix B,
iy87,

*• "Procedure  for NBS-Traceable Certification of Compressed Gas  Working Standards  Used for
Calibration and Audit of Continuous Source Emission Monitors (Revised Traceability Protocol No. 1),"
June 1987 in Quality Assurance  Handbook for Air Pollution Measurement Systems, Volume III,
Stationary Source Specific Methods. Section 3.0.4, U.S. Environmental Protection Agency, EPA-600/4-
'7-027b.

5- "Procedures for NBS-Traceable Certification of Compressed Gas and Permeation Device Working
Standards Used for Calibration and Audit of Air Pollution Analyzers (Revised Traceability Protocol No.
2)," May 1987 in Quality Assurance Handbook for Air Pollution Measurement Systems, Volume' II,
Ambient Air Specific Methods, Section 2.0.7, U.S.Environmental Protection Agency, EPA-600/4-77-
* /«.

^ R;C. Shores, C.E. Decker, W.C. Eaton, and C.V. Wall, Analysis of Commercial Cylinder Gases
OLaiipc Qrirfg. ft]|fvr pjnjde. and Carbon Mnnnode at Source Concentrations: Results of Audit 5.
tfA-eoO/S4-81-OSO, NT1S-PB-82-118-654, U.S. Environmental Protection Agency, Research Triangle
ParV mot
    , 1981.
I' .R'C- Sho«s. F. Smith, and D.J. von Lehmden, Stability Evaluation nf Sulfur Dioxide. Nitric Oxide
aflfl£aibon Monovjfteq.^ift cylinders. EPA-6QQ/S4-84-Q86, U.S. Environmental Protection Agency »
Research Triangle Park, 1984.

*• R.S. Wright, E.L. Tew, C. E. Decker, D. J. von Lehmden, and W. F, Barnard, "Performance
 U(Uts of EPA protocol gases and inspection and maintenance gases,* IAECA, 37:284 (1987).
 •  *.S. Wright, C.V. Wall, C.E. Decker, and D.J. von Lehmden, "Accuracy assessment of EPA
Protocol gases in 1988," JAPCA, 39:1225 (1989).
                                           467

-------
                  Table I.  Relative percent differences" between manufacturer-
                    certified concentrations and RTI-measured concentrations.
Specialty Gas Manufacturer
Air Products
Airco Industrial Gases
Alphagaz
Liquid Carbonic
Matheson
MG Industries
National Specialty Gases
Scott-Manin
Scon Specialty
300 ppm
S02
2.7
2.4
5.1
0.8
2.3
-3.1
1.3
-1.9
-2.6
400 ppm
NO
1.0
1.4
-0.2
-2.0
1.0
-0.2
0.5
0.5
0.2
1500 ppm
SO2
0.3
-1.7
11.0
0.9
0.7
1.0
0.8
0.9
-0.1
900 ppm
NO
0.4
0.2
-2.2
2.6
-0.4 ,
1.9
-0.3
0.1
0.3
* Relative percent difference (RPD) = Manufacturers Cone. - RTI Cone. X 100
                                                 RTI Cone.
                                           468

-------
        PREPARATION  OF PERFORMANCE EVALUATION
        AUDIT SAMPLES FOR THE DETERMINATION OF
                            IMPURITIES IN CFCs
                                   Shirley J. Wasson
                                 Shrikant V. Kulkarni
                                  Craig O. Whitaker
                        Center for Environmental Measurements and
                                   Quality Assurance
                                Research Triangle Institute
                            Research Triangle Park, NC 27709

                                          and

                                    Dale L. Harmon
                      Air and Energy Engineering Research Laboratory
                           U.S. Environmental Protection Agency
                            Research Triangle Park, NC 27711
ABSTRACT
     Chlorofluorocarbon (CFC) refrigerants at room temperature are usually gases. In closed containers,
they exist in two phases, liquid and gas, exerting a pressure equal to the vapor pressure of the refrigerant
at the ambient temperature. Preparing audit samples that require spiking a matrix CFC with another CFC
as an impurity presents an  interesting challenge.  This problem of adding a measured amount of
contaminant CFC in a single  phase was solved by condensing the contaminant refrigerant in a sampling
loop using a six-port sampling valve operating at dry ice temperatures. A calibrated amount of sample
could then be delivered with relative ease into the  audit sample container and chased with the matrix
refrigerant for a reproducible and complete transfer.  Due to excellent vigilance over leaks, the precision
and accuracy of such sampling was demonstrated adequately.

INTRODUCTION
     Chlorofluorocarbon (CFC) compounds have been used abundantly in refrigeration apparatus because
of their unique properties.  Because these compounds have been linked rather firmly to stratospheric
ozone depletion, however, their production will be phased out during this decade.  Meanwhile, the large
body  of refrigerant chemicals currently in use industrially and domestically  must be managed as
conservatively as possible. Reclamation is one  way to do this. In order to set limits on the amount of
contaminant which may be present in the mass of the reclaimed refrigerant and still be usable, the Air-
Conditioning and Refrigeration Institute  (ARI) has  promulgated Standard 700-88.'   This standard
 omewhat loosely addresses  how these contaminants should be measured.
     As a test on the bounds  set by ARI Standard 700-88, several field studies have been done. In 1988,
  study2 by the Environmental Protection Agency (EPA) on refrigerants from mobile air conditioners
Attempted to set contaminant levels for  recycled refrigerant equivalent to those levels found in
Automobile air conditioners that had traveled about 24,000 km (15,000 miles) with no further addition
*f refrigerailt In 1990, EPA conducted an evaluation of CFC-12 in domestic refrigerators in an effort
°  establish similar reasonable and workable contaminant levels for the recycled refrigerant for use in
                                          469

-------
 domestic refrigerators. This objective was not achieved because of concerns associated with the methods
 of analysis for the contaminants in these difficult refrigerant matrices. In 1991, another field study1 was
 sponsored, this time by ARI. This work consisted of collecting and analyzing refrigerants in existing
 industrial equipment as a basis for judgements concerning future levels of acceptable contaminant
 standards for recycled refrigerant. The plans were to sample equipment generally 3 to 6 years of age
 that had not had a further addition of refrigerant. ARI is seeking to establish a level of contaminant that
 can be tolerated by an operating system without causing failure.
      Because of previous difficulties with the analytical methods recommended by ARI Standard 700-88
 and used in the three studies discussed above, EPA initiated an adjunct study4 of some of the analytical
 methods to coincide with the latest study by ARI.  Performance evaluation samples were to be produced
 and distributed to four analytical laboratories who do these procedures routinely, including the laboratory
 conducting the analyses of the field samples.  Data were to be generated on  the analysis for
      •   an impurity refrigerant in a matrix refrigerant,
      *   moisture level, and
      *   high boiling residue level.
      As a quality assurance (QA) support contractor of EPA, Research Triangle Institute (RTI) was
 requested to make the performance evaluation audit (PEA) samples and evaluate the data from the
 participating laboratories. There were four matrix refrigerants with vastly different physical properties,
 thus presenting an interesting challenge.

 EXPERIMENTAL
     The refrigerants chosen for the  ARI  study  were CFC-11, CFC-12,  HCFC-22,  and CFC-502.
 Pertinent physical data for these compounds are shown in Table I.  As can be seen, at room temperature
 they exhibit vapor pressures in a range from less than 100 kPa to more than  1000 kPa.  The challenge
 was to reproducibly and quantitatively introduce  contaminant impurity refrigerants with  high vapor
 pressures into matrix refrigerants which may have higher or lower  vapor pressures than the impurity
 introduced.

                                    Table  I.  Refrigerant data.
Refrigerant
11
12
22
502
Formula
CC1,F
CC12F2
CHClFj
CHClFj/CClFjCFj
Boiling
Poinl
f°C)
23.8
-29.8
-41
-46
Melting
Point
f°O
-111
-158
•160
NA§
Liquid
Density
P/mL f°O
1.487 (20)
1.2930 (30)
1.177(30)
1.217 (25)
Vapor
Pressure
kPa f°Q
92.4 (21)
584 (21)
949(21)
1056 (21)
   Not available.
   The procedure usually employed, preparing a stock solution and dispensing it in individual sampling
containers, could not be followed because of the partitioning problem.  Thai is, the contaminants
introduced into a two-phase stock solution will partition between the gas and the liquid.  If the first
sample is  dispensed from the liquid phase, the remaining solution will redistribute between the liquid
and gas phases.  A second sample from the liquid phase will now contain contaminants at a different
                                             470

-------
   ncentration from the first sample.  Each subsequent sample will have the same problem. Since this
   undesirable in a project where all samples are required to be substantially equal, the method described
co
is u
here was chosen
 Preparation
    A protocol was established for introduction of the three contaminants into each sample cylinder.
 Schematics were created and apparatus assembled. Trial runs were conducted to find problem areas.

 Apparatus and Materials
  v   fhc system for preparing the audit samples is shown in Figure 1.  The connections between the
 CFC gases and the sample cylinder were made through a six-port valve containing a removable sampling
 i   n  Success rested upon a vacuum system which could achieve vacuums down to 3 to 4 mm of Hg,
   Ha gauge which was accurate to 1 mm of Hg. Other apparatus consisted of a calibrated Eppendorf
 ^  tte  for  direct  water  measurement,  a calibrated glass  syringe  for direct high boiling  residue
 Plp^ surement, and balances which could read several kilograms to 0.1 g and several hundred grams to
 run g  T"6 ^^ boih'ng residue used for spiking was Sunisco Refrigeration Oil, 3GS viscosity 150, and
 h   water was deionized.   Two  refrigerants, CFC- 12 and HCFC-22, were  chosen for the impurity
  f 'eerants.  Cooling was achieved with dry ice.   Other  apparatus needed was  a thermometer, a
 **   meter. Teflon® thread-sealing tape, and tools to remove the valves from  the sample cylinders and
 ^^ ake the  gas connections. Sampling loops, 2 and 5 mL, in conjunction with the six-port valve, were
 l°  A to introduce the impurity refrigerants into the matrix refrigerants. The sample cylinders were 55
 use7oQl mL) steel  bottles with needle valve closures and blowout plugs (2860 kPa).
in3
nnerating Conditions
***   Aj| parts of the protocol were conducted at room temperature except during the measurement and
    rtduction of the impurity and matrix refrigerants into the sample cylinder.  When the procedure
^   \vcd the impurity refrigerants CFC-12 and HCFC-22, it was conducted at -78°C (-109°F), dry ice
"1VO rature, at which all the CFCs are liquids.  This allowed use of fixed volume sampling loops for
tern^>Cantitative introduction of the refrigerant impurities.
**rOC  Since all contaminants were to be introduced via volume devices (i.e., pipettes, syringes, and
     ..   loops), these devices required calibration using the material of interest. The pipette and glass
Sa!?£ tne cyijn(jer vaive ciose^ ^ ^t cylinder
EaChhed fronl the manifold-  WorkinS quicUy. the valve was removed from  the neck of each sample
detacn   ^^ moisture and high boiling residue (oil) contaminants were then introduced in liquid form
cylinde ^ ^^ cylinder via calibrated pipette and syringe. The valve was replaced using new Teflon
dif    d the sample cylinder was connected to the system shown schematically in Figure 1. With  the
tape an  ^  ^ sample cylinder cooled to -78°C, the system was evacuated to the point of the valve
sanl   'sample cylinder. With the system isolated  from the vacuum,  the gauge was observed to check
                                              471

-------
for leaks.  If no rise in pressure occurred, the gauge was isolated, the sampling loop filled, the sampling
valve turned to the discharge position, and the sample cylinder valve opened (see Figure 3).
      Because the sample cylinder was also at -78°C, but with a greater volume than the loop, the
impurity condensate from the loop was drawn into the cylinder. The cylinder was now withdrawn from
the cold, and set on the scale. The matrix refrigerant was introduced until the sample cylinder was filled
to a predetermined weight
      Factors complicating the introduction of the contaminant and matrix refrigerants included ice
condensate collection on the cylinders  from the air, leaks, and  interference of the  connections with
accurate weighing of the sample cylinder during the filling process. Final weighing of the cylinders was
done at room temperature to circumvent the ice problems. Leaks were prevented by using precision
equipment and by constant tightening before material transfer. Toggle switches were kept out of the cold
as they were the most susceptible to leakage. To circumvent connection interference with the weighing
process, the sample cylinder was set on  the scale with the connections in place.  This weight was then
compared with  the cylinder empty weight. The difference was then added to the target weight to get
a net target weight as close as possible to the weight desired. Although icing complicated this process,
it was possible to get reasonably close target net weights by this method.

RESULTS

Calibrations
      Calibrations of the pipette and syringe produced densities consistent with expected values for the
water and the refrigerant oil.  Calibration of the sampling loops with CFC-12 and HCFC-22 did not
produce densities consistent with the American Society of Heating, Refrigerating and Air Conditioning
Engineers' (ASHRAE's) published values3 at -78°C (-109°F).  For instance, for CFC-12 at -78°C the
2 mL sampling loop when filled should have weighed 3.238 g according  to the literature values. An
average of three weighings established a value of 2.797 + 0.015 g.  The 5 mL loop weighed 6.890 +
0.026 g net, when filled. Similar discrepancies were observed in the weights established for HCFC-22.
      Calculations were made  to determine if volume shrinkage of the steel sampling loop at -78*C
could account for the discrepancy. The calculations showed that the volume of the 2 mL loop shrank
to  1.99 mL at dry ice temperatures.  This was negligible compared to the discrepancy being observed.
      Measurements were then made with water at room temperature  to  establish the volume of
refrigerant being measured.  These established volumes of 2.14 and 5.14 mL for the 2 and 5 mL loops,
respectively. Thus a measure of the dead volume (0.14 mL) of the six-port valve emerged. The dead
volume was unusually large because the valve was custom-ordered with pathways between ports as large
as  possible to keep flow unrestricted.  Determination of loop volumes and  weights  gave densities as
shown in Table U.  The values as determined in the RTI laboratory were used to calculate recoveries
on the audit samples.

                    Table n.  Experimental vs. published refrigerant densities.


                                   Densities (g/mL)*
CFC-12
HCFC-22
1.32 + .02 1.16 + .01
1.619b 1.511"
      Measurement performed at -109°F (-78°C).
      Literature value published by ASHRAE (see reference 5).
                                              472

-------
CONCLUSIONS
      This  project demonstrated that  condensable  gases  such as CFC-12  and HCFC-22 can  be
   antitatively measured as liquids and quantitatively transferred to audit sample cylinders via sampling
||!L«  Further, it demonstrated that difficulties associated with working at dry ice temperature, such as
•     ondensing out of the air and leakage, can be overcome.  The density values produced, however, do
IC t  orrespond to  literature values. This remains a topic for future investigation.
       Air Conditioning and Refrigeration Institute.  "1988 Standard for Specification for Fluorocarbon
       Refrigerants Standard 700," Arlington, VA, 1988,

       Weitzman, Leo, "Evaluation of Refrigerant from Mobile Air Conditioners," EPA-600/2-89-009,
2'     (NTIS PB89-169882), February 1989.

       Air Conditioning and Refrigeration Institute:  Phase I Field Tests, work-in-progress.

       Wasson, S.  "Quality Assurance Project Plan for the Production and Analysis of Performance
4'     Evaluation Audit Samples to Validate/Assess Selected Analytical Methodologies for Recycled
       Refrigerant Contaminants:   An Adjunct  Project with  the  Air-Conditioning and Refrigeration
       Institute's Phase I Field Tests," work-in-progress, January 1992.

       Stewart, Richard B., Richard T. Jacobsen,  and Steven G. Penoncello. ASHRAE Thermodynamic
5-     properties  of Refrigerants.   American Society of Heating, Refrigerating and Air-Conditioning
       Engineers, Inc.: Atlanta, GA, 1986.
                                              473

-------
AN Connection I    I impurity
                                                    Sample
                                                    Cylinder
                  Figure 1. Diagram for tyttem.
                                                         SwagWok*
                                                       ANCom«cton
                   Figure 2. Vacuum manifold.
      Portion A: To FU Loop

             Irrpurty R«frig«ranl
ToSunpl*
CyOndtr -4
     Sample IMP  A

                 Matrb
                  PMltton B: To Empty Loop
                                                        Vacuum
               ToSampI*
                    SurpltLoap  A

                                MM
                                RcfrfQtrMt
          Figure 3. Sample Injection configuration*.
                              474

-------
                      ENSURING DATA QUALITY VIA
PRELIMINARY ANALYSIS OF MEASUREMENT ERROR VARIABILITY

                               Leonard A. Stefanski
                              Department of Statistics
                          North Carolina State University
                              Raleigh, NC 27695-8203

ABSTRACT
    Knowledge of experimental and/or measurement error variance(s) is useful in planning
experiments. This is illustrated  with two examples. The first is a textbook example of
determining sample size in order that a test for the equality of  two means has specified
power.
    The second example arose in the course of studying SO] removal efficiencies of calcium
hydrates in coal fired boilers.  The objective was to determine the relationship between
removal efficiency and porosity and surface area of the hydrates. Because there is a strong
relationship between porosity and surface area,  even small measurement errors in these
variables make it difficult to isolate their effects on removal efficiency. An estimate of the
Cporosity, surface area) measurement error covariance matrix was obtained from multiple
measurements on one hydrate.  This was used to guide selection of subsequent hydrates
with similar porosities (surface areas) and different surface areas (porosities) for further
testing.
INTRODUCTORY REMARKS
    Data are collected to provide information to serve as a basis for reasoning  and infer-
ence.  It is generally the case  that "reasoning and inference" entail statistical analyses of
the data.  It follows that at this level of abstraction, data quality is a function of the infor-
mation content of the data relative to the objectives of the intended statistical  analyses.
    As defined here, data quality refers not to individual datums, but rather to the col-
lective. Thus it is possible for a set of data to have poor quality even though  individual
(iaturns may be of the highest possible quality; and conversely, a data set may  be of high
quality even though individual datums are not.
    The distinction between the quality of individual datums and the quality of the data is
useful, for it makes apparent that for purposes of inference, data quality is more important
than datum quality, although obviously  the latter ia a component of the former.  The
distinction is clear whenever  datum quality is limited, say by measuring technology or
natural variation, for then it  is evident that data quality cannot be improved simply by
improving datum quality.  This, in turn, highlights the importance of study design and
replication as mechanisms for improving data quality.
    With regard to experimental research, study design refers to the set of treatments to
be studied, that  is, the experimental conditions to be tested and the order or structure in
which experimental conditions are tested.  Replication, or sample size, refers to the number
of tests (or runs) at each experimental condition.
                                        475

-------
     In this paper I describe two situations in which knowledge of experimental error vari-
 ance gained from prior experiments is used in the planning of subsequent experimental
 work.
     The first is a hypothetical example of the use of an estimate of the experimental error
 to determine sample size for an experiment with two treatments. In this simple setting
 the information in the data is proportional to sample size. Thus determining sample size
 to enable meaningful comparisons between the treatments is equivalent to ensuring that
 the data contain sufficient information to meet the objectives of the statistical analysis.
     Following this I describe a more complicated example where a preliminary estimate of
 measurement error variability was useful in selecting the set of experimental conditions for
 an experiment in the study of SO] removal efficiencies in coal-fired boilers via limestone
 injection. The objective of the research was to estimate the effects of porosity and surface
 area of the injected limestone on removal efficiency.  The planning ensured that the calcium
 hydrates tested would be informative for this purpose.

 COMPARING TWO TREATMENTS
     Consider the problem of comparing two population means, px  and /jy, based on n
 measurements of each, say {X\ , . . . , Xn] and [Yi , . . . , Yn}. For this example I assume that
 interest lies in testing whether or not py > px + AO or HY  < I*Y + AO  where AO is a
 known quantity.

 The Statistical Model
     A simple statistical model for this problem postulates that

                         Xi,...,Xn  iid Nonnal(/Jx,  a2),
                          Vi,...,r»  iid Normally,   Hx + AO         HI : /*y < px + A0.               (1)
    For example, we might be interested in testing pre- and post-mitigation indoor radon
concentrations (pCi/L). Let /j0 and n\ denote the average pre- and post-mitigation radon
levels. We suppose that interest lies in determining whether or not p\ is > or < fyo where
100(1 — 0) is the hypothesized percent reduction achieved by mitigation,  e.g., $ = .1 if we
are testing for at least a 90% reduction. Then under the assumption of lognormal variation
in the measurements of radon concentrations, our experimental hypotheses have the form
in (1) where A0 = - ln(.l) and Xi , . . . , X „ and YI, . . . , Yn are the natural logarithms of
the pre- and post-mitigation measurements.
Determining Sample Size
    When er3 is known, H0 is rejected in favor of Hj when Y-X exceeds a critical value c.
The cutoff c is determined by the requirement that that the probability of falsely rejecting
HO be small.  This probability is  commonly denoted a and is  usually  in the range .1 to
                                       476

-------
 .01.  For our example the appropriate constant is c = AO + zi-a^/2
-------
 the effects of porosity  and surface area.  The more likely situation is that some of the
 scatter is due to measurement error variability and some is due to true departures from an
 exact relationship between the two variates. An assessment of the respective contributions
 of each source of scatter is required for informed experimental planning, in this case the
 selection of sorbents for further study.
     The problem to be resolved is whether or not surface area is an exact linear function of
 porosity for the hydrates under investigation, and if not, how to select hydrates for further
 testing hi a way that allows for estimating the effects of porosity and surface area. In order
 to resolve this problem it is necessary to have an estimate of the covariance matrix of the
 measurement errors in porosity  and surface area.
     An estimate of the (porosity, surface  area) measurement error covariance matrix was
 obtained from multiple measurements on one hydrate. These are referred to as the valida-
 tion data below. The estimated covariance matrix was used to guide selection of subsequent
 hydrates with similar porosities and different surface areas and similar surface areas and
 different porosities.

 The Statistical Model
     The true values of the variates whose co-linearity is in question are represented  by
 the  2x1 vectors U^ i = 1, . . . , n. The measured values of the variates are denoted by Xtt
 t =  1, . . . , n.  It is assumed that
where Z\, . . . , Zn are independent random vectors having a common normal distribution
with mean Qjxi and covariance matrix ft, i.e.,
The unobserved UiB are regarded as fixed unknown parameters just as in a functional
errors-in-variables model, see Puller1 .
     The validation data are represented by Wj, j = 1, . . . , fc, where
The ZjS are assumed to be independent and identically distributed with common distri-
bution N(02 x i , fl) . It is also assumed that X\ , . . . , Xn are independent of W\ , . . . ,
     The null and alternative hypotheses to be tested are
               HQ :  MVU is singular      HI :   MW  is nonsingular

where
superscript *T' denotes transpose, and the overbar and dot subscript indicate averaging.
                                        478

-------
A Test of Ho Versus HI
     Define the sample covariance matrices

               and

                                         1    k
     The test statistic is
where >lwiv ig t^6 Cholesky decomposition of Afww and A^fS) denotes the smallest eigen
value of the matrix B. Large values of F* indicate departures from H0 in the direction of
Hi.
     The suggested test procedure is to reject HO when F* is greater than the the 100(1 -a)
percentile from the F-distribution with k — 1 and n — 1 degrees of freedom, Fn-i,k-i,i-a-
Analysis of the Hydrate Data
     The method described was applied to the calcium hydrate data described earlier yield-
ing an F* statistic of 76.36 which is highly significant (p-value=.0004) giving strong evi-
dence of departures from co-linearity between surface area and porosity.
Implications for Future Conversion Experiments. The highly significant F statistic
justifies searching for pairs of hydrates that have similar porosities (surface areas) and
different surface areas (porosities). The suggested strategy for selecting hydrates for future
conversion experiments is to select pairs of hydrates having the same or similar surface
areas (resp. porosities) and porosities (resp. surface areas) as widely divergent as possible.
At the very least the difference between members of the chosen pairs should be statistically
distinguishable.  This is determined as follows.
     Let Xi be a 2 x 1 vector containing the measured surface area and porosity values for
the i411 member of a selected pair (»' = 1, 2). The two hydrates are significantly different if
where c = ^F2|s,.M9 = 792.00 or c = ¥*>.».••• = 164-37 for significance at the .001 or .01
level respectively.
    For example two candidate pairs are hydrates (14, 25) and (10,30), the first pair having
similar surface areas, the second similar porosities.  For  these two pairs, A(Xu,Xt&) =
796.72 and A(^io, A"30) = 26, 137.23. Thus both are acceptable.
References
1. W. A. Fuller, Measurement Error Model*, Wiley, New York, 1987, pp 2-3.
                                        479

-------
     CO
     d
    in
    d
  CO
  o
  l_
  o
  0_
    CN
    d
                        X

                         X
                 x
               X
                                     X X
      0    10    20   30   40    50    60   70   80    90   100
                      Surface Area,  m2/g
Figure 1. Scatter plot of porosity and surface area for twenty-seven calcium hydrates.
                               480

-------
         QUALITY ASSURANCE FOR AN ALTERNATIVE ANALYTICAL
            METHOD  FOR HIGHLY CONCENTRATED VOST  SAMPLES


                         Joseph D. Evans
          Science Applications International  Corporation
              10240 Sorrento Valley Road, Suite 204
                       San Diego. CA 92121

                          Darrel  Halsell
                  Analytical Technologies, Inc.
                        11 East Olive  Road
                       Pensacola, FL 32514

                           John Hawkins
                  Analytical Technologies, Inc.
                        11 East Olive  Road
                       Pensacola, FL 32514


antirce  sample collection by the  volatile organic sampling train
rvOST)  was designed for  incineration  processes which are highly
 fficient.   Consequently,   it  is   intended   to   collect   low
  ncentrations  of  volatile organics and  concentrate them onto a
  rtax sorbent tube.  Analysis is  performed by total  desorption of
 H  sorbent cartridge directly into GC/MS  instrumentation. Because
   taminants  are collected  on a Tenax  tube with  a much higher
Cj Qrption  capacity  than GC/MS   detector quantitation,  accurate
   Dound  quantitation  is often  impossible  when  collection has
C°reeded  instrument  capacity.   While  other  sampling  technologies
eJt?at for  volatile compound  collection, the  VOST method  is widely
e  %  £Or  collection  of  volatiles  even  when  concentrations may
use  j   ideal  analytical   conditions.     Approved  alternative
eXC7vtical  procedures  are  not   currently  available when GC/MS
an?uration occurs. This  paper  proposes  an alternative method  that
s    used during  the analysis of VOST samples  collected from a
           i,ag  burning project,   when  contaminant  concentrations
           GC/MS  quantitation   capacity.   The  method  employed
            into a Summa polished canister, followed by appropriate
dcso      jjgfore analysis.  As a part  of this  alternative method
d  Ytional  QA/OC operations were  instituted to ensure data would be
   eptable for  an RREL category  II project.
                                 481

-------
 INTRODUCTION

 An evaluation of volatile emissions was required for an EPA project
 whose objective was to determine the gaseous emissions and residual
 ash created  by open  field burning of  pesticide bags  and  to assess
 the potential environmental impacts of these  by-products1.  Testing
 was conducted in a specially constructed burn shed to simulate open
 field burning. SW-846 method 0030 was used for collecting volatile
 emissions  produced during the test burns2.  The analysis  of VOST
 samples   collected   by   the   referenced  methodology   produced
 concentrations of volatile contaminants too high for standard GC/MS
 quantitation,  as  confirmed during an  audit of  the laboratory
 conducting these analyses.  While exact concentrations were unknown
 it appeared  as if some  compounds were between levels of  5,000 -
 40,000 ng.  The GC/MS calibration range for these analyses was  100
 - 1,000 ng.

 As a result of these findings it was necessary to consider options
 for the analysis of the collected VOST  samples.  These samples have
 a six week holding time  and because problems were not discovered
 until three  weeks after  samples had been collected, alternative
 analytical procedures needed to be implemented almost immediately.
 Summarized below are the  options  considered for several alternative
 analytical procedures.   Briefly  outlined  are some of the good  and
 bad points of each option.

 1}   Lowering GC/MS  Detector voltage:   While this  is  simple to
 perform and could effectively prevent the detector from saturating,
 it does  not  address the  problem of  overloading  the adsorption
 column which is used prior  to GC/MS injection.

 2)    Methanol Extraction  of  VOST Tubes:    Theoretically this
 technique  sounds  possible and  it could  be  performed  by  any
 qualified analytical laboratory but there is a very  limited amount
 of supporting data, concerning this technique.  In addition,  based
 on previous  contractor   experience,  it  does not  appear  as  if
 methanol effectively  extracts  all compounds from Tenax.    Several
 compounds have a different solubility in methanol and affinity  for
 Tenax  which  could  affect  their extraction  efficiency.   This
 procedure would require extensive validation because there are over
 40 compounds in  the  8240  procedure  whose extraction efficiency
 would have to  be verified.    In  addition  it is  believed that
 methanol would  be ineffective at  extracting the charcoal  in  the
 second tube.

 3)  Desorption into  Tedlar Bags or "Summa Passivated"   Stainless
 Steel Canisters:   This  procedure requires  a  laboratory who  has
experience with  collection and  analysis of  volatile samples in
Tedlar Bags or Canisters. Once desorbed, samples could be injected
 into the GC/MS at various concentrations until the proper dilution
was achieved.  There  could be  some problems with condensation or
 reaction with the wall  of the  Tedlar bag  and because of this
 possibility emphasis was  placed upon the use  of "Summa" canisters.
                                482

-------
 4)  Splitting of Sample after Desorption:  This procedure requires
 a laboratory who has proper equipment and supporting documentation.
 While it  is not as variable  as the Tedlar  Bag/"Summa"  Canister
 technique described above which  allows  several  opportunities for
 sample analyses, it appears as if fewer questions would be raised
 concerning its validity if  performed by the proper laboratory.  It
 does offer some additional  opportunity for more than just a single
 analysis by saving the larger fraction of the split if the smaller
 fraction still  saturates the detector.   By performing  a double
 split samples could be diluted by as much as 100 to 1.

 Discussing each of these approaches with the selected laboratories,
 both  the  splitting  technique  and  desorption  technique  were
 r-onsidered  acceptable.    Only  one  laboratory  had  experience
    forming tne sajnpie  splitting technique and could not handle the
 increased sample load within the holding time for  analysis.   The
  iternative  "Summa" Canister  technique  was therefore  chosen not
 a_iy Because of  laboratory experience but because  it allowed for
 Greater variability for multiple sample injection.   While it was
  ot an EPA approved procedure, the QA Officer and Technical Project
 Manager at RREL agreed that it was the best available alternative.

 EXPERI MENTAL

 cw-846 Method 5040 describes the desorption of VOST tubes collected
 f om the standard VOST Train (Method 0030). Contents of the sorbent
   rtridges  are  spiked  with  an  internal  standard and  thermally
 ca orbed for  10  minutes at 180o  C with organic  free  nitrogen or
         at a flow rate of approximately 40  ml/min.
    was determined  for this project, that  collected  contaminants
   •an the VOST tubes were saturating the  GC/MS detector and may even
    overloading the GC/MS adsorption trap.   For this reason it was
   ressary to modify Method 5040 in order  that  detected compounds
n   id be  accurately and  precisely quantified.  In summary,  the
°   onunended  alternative  used  by  ATI  who  was subcontracted  to
fB°f  rB, the  analyses,  was to  desorb the  VOST cartridge into  a
Pc mma Passivated" canister followed by analysis  of  the canister
   <«a method TO-143.   While this procedure  had been  performed in
U    oast no  data  existed  to confirm its  reliability.   Presented
t  i ow is a summary describing the proposed  method and associated QC
13  ed  to evaluate the resulting data.


                         SUMMARY OF METHOD

    •liar to Method 5040 the thermal desorption unit is a clamshell
Sl*ir    Collected  VOST  tubes  are  desorbed following  method
ne ffications into an empty, clean,  "Summa Polished",  canister.
aOSC* *•  	 . _i	J —  »v*t4 1» AJ^ i*»4 ^V\ anv%v>Av*v>4 4 +A  1 ««*»«« 1 M **£ W««.v« M-^^-BB **. .>£ __> J
gpecj.    T tube ig spiked with appropriate levels of benzene-d6 and
^a°  ibenzene-dlO. Acceptable recovery of these deuterated compounds
ettl* between 50-150%.  If recovery for  a particular  sample falls
   ~    this range the analysis was repeated.
                                483

-------
 Initial  calibration of the  GC/MS is performed similar  to SW-846
 Method 5040.   However, like the analysis of the  actual  samples,
 calibration standards are first desorbed  into  a  "Summa"  canister
 then  injected  onto the  GC/MS  system.    Because  actual  samples
 contained high concentrations of contaminants, VOST tubes had to be
 spiked at levels which were similar to  sample  concentrations (as
 high as  10,000ng for each 8240 compound).

 A three  point calibration curve for the  compounds  of interest,  as
 defined   in  the  QA  Project  Plan,  was  established  by  spiking
 appropriate concentrations  into a  clean VOST  tube followed  by
 desorption  into a designated clean canister (cleaned per Method TO-
 14).   Once desorbed  into the canister,  sample analysis proceeds as
 per  method  TO-14 with  purge and trap into  a sorbent column  and
 subsequent  GC/MS  analysis. Acceptable  relative  standard  deviation
 for  the  calibration  curve response factor for each analyte is + or
 -  30%.  Verification of this calibration curve is performed with a
 QC check sample.   A Tenax  tube is spiked  at  a mid-level  range
 within this  calibration  curve  followed  by  desorption  into a
 canister and analysis by GC/MS.  Acceptable recovery ranges for all
 compounds of interest are between 70-130%.  This check is run every
 12 hours prior  to   the start  of a  new  set of  analyses.  If  all
 compounds do not  fall  within this recovery  range the spiking and
 desorption  of an additional  VOST tube is repeated.  In the  final
 report compounds that did not meet QC specifications  were flagged.

 Collected field blanks were also analyzed.  As specified  in the QA
 Project  Plan one  field blank  from each  set  of  test  burns  was
 analyzed.  Tenax tube blank  cartridges were  run every 12 hours  to
 demonstrate  that   the  entire  analytical  system  is  free   of
 significant contamination.  In addition  field  audit  samples  were
 also  analyzed.   Prepared  in the field,  these  samples contained
 benzene  and toluene  spiked  from gas  cylinders and subsequently
 collected on the VOST tubes.

 Quality  Control  procedures were  followed  as specified in Method
 5040,  however,   as   noted above,  calibration  was  performed  by
 desorbtion  of  a VOST  tube  within  the  working  range  of  the
 instrument,  between lOOng -  lOOOng on column.   Cartridges  were
diluted by 10:1 for the Thimet bag burns  and  20:1 for the Atrazine
 bag burns.  These dilutions were based upon initial  sample analyses
performed on the VOST cartridges.


                            PROCEDURE

 1) Calibration and tuning of GC/MS per method specifications.

2) Run Tenax tube blank sample every 12 hours.

3) Prepare  VOST  spike (QC Check  Sample)  at  approximately SOOOng
 (expected dilution  10:1,  on column  concentration  SOOng)  of  8240
compounds of  interest. Also  spike  with deuterated  benzene and
deuterated ethylbenzene at 2500ng.
                                484

-------
4)  Sample  canisters  used  for  this  procedure  were  prepared in
accordance with method TO-14.  10% of these canisters are routinely
"blank checked"  to ensure canister integrity. Because a VOST tube
blank which includes desorption into an evacuated canister, will be
performed  every 12 hours a separate canister blank  will  not be
requi red.

5) Desorb  sample tubes,  spiked  with 2500ng of deuterated benzene
and  ethylbenzene,  into  a  pre-cleaned evacuated  canister.  Final
canister  pressure  will  not  exceed  2  atmospheres  and  will  be
recorded for every sample.  Once desorbed, canister analysis will
proceed as described in Method TO-14.

6)   individual   samples   that  do   not  meet  internal   standard
specifications  will be  re-run  one  time.  If  internal  recovery
standards are still not within the specified range after a second
analysis,  data  from  that  sample  will  be  flagged in the  final
report.

CONCLUSIONS

Results from the QC checks performed as part of the analyses showed
the  method  to be both precise  and accurate.   In summary  the QC
Checks included:

     1)  Matrix  spikes of blank  Tenax tubes  using  certified gas
     cylinders  performed  in  the  field  under   conditions  which
     mimicked actual sample collection.

     2)  Surrogate  spikes  of deuterated  benzene  and deuterated
     ethylbenzene included with each sample analyzed.

     3) Laboratory and field blanks to ensure no  sample or sample
     container contamination.

     4)  A  three point  calibration  curve by  spiking   and  then
     desorbing a blank Tenax  tube  with all volatile compounds of
     interest as specified per method 8240.

     5) A QC check standard run every 12 hours. This QC check was
     prepared in the same manner as the calibration standards and
     was   spiked   with   compound   concentrations   which   were
     approximately at mid-range levels on the calibration curve.

It should  be noted that ATI did  not use  the  flash evaporation
technique specified in Method 5040 when the calibration curve was
first prepared.   Rather, ATI injected methanolic standards onto
blank Tenax tubes for the higher concentrations and used both the
flash evaporation technique and methanol injections for the lower
concentration  standards. These  results  showed  that the  flash
evaporation compared favorably with the methanol  injections.

Calibration curve and calibration QC check criteria were achieved
as specified, so that  individual  response  factors were within + or
                                485

-------
 -  30%  of  the  average  response  factor.   The  only  significant
 compound found  in the blanks  was methylene  chloride which was
 determined  to   be  a   laboratory   contaminant  and   resulted   in
 questionable data in reference to methylene chloride concentrations
 found  in the samples.   Presented below are  results of field spike
 data  and  surrogate  spike  data.    These  data  also  indicate the
 reliability and  acceptability of the  proposed  method.
                               FIELD SPIKE RESULTS
                                (values in ng)
 Compounds

 Benzene
 Toluene
                       True valne

                       4300
                       4600
       4510
       4640
      4110
      4570
                      RESULTS OF SURROGATE SPIKE FOR VOST ANALYSES
 Spiked
 Coiponads

•tit-benzene
tdio-ethylbenzene
                 t Recovery
                  Ranges

                 78-111
                 62-114
itds-Tolnene         96-104
it Broiofluorobenzene   92-108
it 1,2 Dichloroetbane-di 94-146
Control
Liilts

50-150
50-150

88-110
86-115
76-114
f Hi thin
Control
Llilts

32
32

33
33
32
lOotside
Control
Liilts

0
0

0
0
1
it
   Spiked onto the VOST Tenai tnbe prior to desoiption.
   Spiked into the GC/HS purge and trap apparatus.
In  conclusion  it  should  be  noted  that  results of  the  QC  data
indicate that  this method appears to be  an acceptable alternative
for  analysis  of VOST samples when  concentrations exceed normally
acceptable levels. As previously stated  several  alternatives have
been proposed  and while a complete method validation study  has not
been performed these data suggest this method to be  a reasonable
alternative  which  could  be  performed  by  several  analytical
laboratories.   In addition this  scenario presents a format  for QA
corrective action  which needs to occur  when  unexpected problems
happen  during  the course  of a project.
                                   486

-------
REFERENCES

1    U.S.  Environmental  Protection Agency  (RREL),  Field  Test of
     open Burning  of  Pesticide Baas in Farm Fields. Final Report,
     (August  1991)

2    EPA SW-846,  3rd  edition,  "Test Methods for Evaluating Solid
     waste:   Physical/Chemical,"   (November 1986)

3    U.S.  Environmental  Protection Agency (AREAL), Compendium of
     Methods  for  the  Determination of Toxic Organic Compounds in
     Ambient  Air,  1988


ACKNOWLEDGEMENTS

The authors wish to thank Mr. Don Oberacker of  EPA's Risk Reduction
v aineering Laboratory for his support and help in conducting the
   lyses  required  to complete  this  study which aided  in  the
validation of the  resulting data.
                                487

-------
 OZONE EPISODES IN  ATLANTA, GEORGIA: ANALYSIS
    OF AIR  QUALITY DATA GATHERED  DURING THE
   SUMMER OF 1990 USING AN OBSERVATION BASED
                                      MODEL
                       Carlos A. Cardelino and William L. Chameides
                          School of Earth and Atmospheric Sciences
                              Georgia Institute of Technology
                                  Atlanta, Georgia 30332
                                      Larry Perdue
                             Environmental Protection Agency
                        Research Triangle Park, North Carolina 27711


ABSTRACT
    During the summer of 1990, an eight week field sampling program was undertaken by U.S. EPA
to characterize the chemistry of ozone pollution episodes in Atlanta, Georgia. The field study included
hourly measurements of speciated hydrocarbons, NO,, ozone, CO, and meteorological parameters.
Diagnostic analysis of the data by an Observation Based Model of Urban Ozone Photochemistry indicate
the following:   1. The need  for high-sensitivity  NO  instrumentation to characterize the NO,
concentrations in urban settings during the afternoon hours; 2. The importance of isoprene, a natural
hydrocarbon, in photochemical smog episodes in Atlanta; and 3. The effectiveness of NO, emission
control in limiting ozone episodes in Atlanta,  However, because of limitations in the 1990 field study,
the above conclusions, especially with regard to the effectiveness of NO, emission control, should be
viewed as preliminary

INTRODUCTION
   While uncertainties remain in our understanding of tropospheric photochemistry, the basic set of
reactions that  lead to O3 production  has been identified.  These reactions involve the oxidation of
hydrocarbons and other volatile organic compounds in the presence of nitrogen oxides (NOJ and
sunlight.1-2 Despite the fact that the roles of hydrocarbons and NO, as tropospheric Oj precursors have
been firmly established, the development of an effective strategy for reducing ozone concentrations from
photochemical smog by controlling anthropogenic emissions of these precursors has proven to be
problematic." An indication of this difficult situation is the estimated 140 million people that live in
areas that currently do not comply with the National Ambient Air Quality Standard for ozone.4
   In the past,  emission-based air quality models have played a central role  in determining ozone
precursor relationships within a given urban area and, by extension, in the development of a strategy
for ozone abatement.   These models use emission inventories and  a numerical  representation for
transport and photochemistry in the urban boundary layer to predict precursor and ozone concentrations
within a given air shed.  However, because there are, at present, significant uncertainties associated
with  emission inventories  as  well as  numerical representations of boundary layer dynamics and
transport, the application of emission-based models to the ozone abatement problem has not yet proven
to be definitive.
   Recognizing the very significant scientific challenges inherent in using emission-based models to
determine ozone abatement strategies, we have developed an alternate approach using an "observation-
based" model (referred here as the OBM). Because the model uses observed precursor and ozone
                                          488

-------
concentrations as input, it has the advantages of being independent of emission inventories and not
requiring the simulation of boundary layer dynamics. In addition, and in contrast with the operation
of current emission-based models, the OBM is relatively easy to implement and very fast to operate.
On the other hand, because the model does not predict ozone concentrations, it is diagnostic rather than
prognostic  and can  not be used  in a predictive mode to determine  the exact amount of precursor
reduction needed to bring an area into attainment.
    In this  paper, the OBM is discussed and then it is applied to an actual chemical data set gathered
in Atlanta,  Georgia to show how this model can aid in analyzing  the data and in the design of an ozone
abatement strategy.

MODEL FORMULATION
    The Observation-Based Model has been formulated to closely follow the Incremental  Reactivity
concept of  Carter and Atkinson.7 However, in this case, observed concentrations rather than emissions
are used to drive the calculations. Specifically, we use hourly hydrocarbon, carbon monoxide, nitric
oxide, and ozone concentrations measured  as  a function of time at a  given site as input into a
photochemical box model which calculates the ozone forming potential at this site.  Following Carter
and Atkinson,8 the net amount of ozone formed and NO consumed over a 12-hour period (for example,
from 0700  to 1900 hours) is adopted as a measure  of the ozone forming potential at the site and we
define this  model-calculated quantity as:
    In Equation (1), the superscript "s" is used to denote the specific site where the measurements were
made, HQ denotes the concentration of hydrocarbon species "i" measured at site "s" as a function of
time over the 12-hour period, NO the observed concentration of nitric oxide at the site, and Q, and CO
that of ozone and carbon monoxide.
    The principal goal of the OBM is to determine the sensitivity of the ozone photochemical production
to changes in precursor concentrations.  To accomplish this goal, the OBM is first used to compute
source functions of the observed quantities that drive the model (i.e.  HQ, NO, Oj and CO). These
source functions represent the contributions from emissions and transports to the concentrations of the
observed chemical species at a given site. Then, values for P*OJ-NO are calculated for hypothetical cases
when: 1) the concentrations of the individual hydrocarbon species (HQ are reduced by a small amount,
AHCjj 2) the concentration of NO is reduced by a small amount, ANO; and 3) the concentration of CO
is reduced by a small amount, ACO. To obtain the required reduction in precursor X (i.e., HQ, NO
or CO), the sources function of precursor X is reduced by the specified amount as a function of time
of day. We represent the ozone-forming potential at site "s" for these hypothetical cases by F0s- w>(X -
 AX).
    Following Carter  and Atkinson,7 we  can define  the Relative  Incremental  Reactivity (RIR) of
precursor X at site "s" as the % change in ozone produced per % change in precursor abundance, thus
giving a relative measure of the effectiveness of reducing the emissions of one compound or group of
compounds over that of another compound or group of compounds. The RIR for precursor X at site
"s" is given by
                       RIRm(X)  - -  qj-K>   _                   (2)
                                                   AX
                                                   X
    Finally, if ozone and precursor concentrations are measured at multiple sites, an area-averaged RIR
function for each precursor can be defined by equation (3) where "NS" is the total number of sites and
X is used to represent the relevant precursor (i.e., HCJt NO or CO).
                                            489

-------

                       _
                       Rfiffi -
    It is important to note that the functions RJR as defined by equations (2) takes into consideration:
(a) The full effect of the whole reaction mechanism and not only the reaction rates of the organic
molecules with OH and other intermediate radicals; and (b) the behavior of the chemical system under
realistic conditions, since the system is driven by observed quantities.

THE 1990 ATLANTA DATASET
    During July and  August  of  1990 a field sample  program  was undertaken by U.S. EPA to
characterize the chemistry of ozone pollution episodes in Atlanta, Georgia. The chemical data consisted
of 47 hydrocarbons, NO, NOj, CO and O3. The meteorological parameters measured were: arobknt
temperature, relative humidity, wind speed and direction, precipitation and solar radiation. These data
were obtained on an hourly basis at six location within the Atlanta Metropolitan Area. Three of these
stations: Georgia Tech, M.L. King and Fort McPherson, were located within a radius of 5 miles from
downtown Atlanta. The other three stations were located as follows: Mars Hill to the NW and at about
30 miles from downtown Atlanta, Tucker to the NE at about 14 miles, and Dekalb to the SE at abort
8 miles from  downtown Atlanta.
    The Observation Based Model was applied to each individual station during ozone event days. An
ozone event day occurred when an ozone exceedance (ozone concentration of 120 parts per billion per
volume or higher)  was registered at any one of the six locations described above. In addition to the
application of the OBM to individual days, the model was also used with average data for ozone event
days during the month of August.
    There were three ozone event days during July (days 7, 8 and 9) and six ozone event days during
August (days 4, 15, 19, 21, 28, and 29). The OBM was applied during daylight hours (fromTQQ LT
to 1900 LT)  and  requires hourly  concentrations of hydrocarbons, NO, CO, O,  and  temperature,
Unfortunately the chemical data was not always available and we could only simulate five days during
August, namely days 15, 19, 21, 28 and 29. Consequently, our results are only pertinent to these five
ozone event days during the second half of August 1990.                                .^u.
    Missing hourly values were treated differently for nitric oxide NO that the other chemical specks.
As we describe later, the ozone chemistry in urban areas is very sensitive to NO afternoon values. The
NO instrument used by EPA was, in most cases,  not sufficiently sensitive to delect NO during «e
afternoon hours in  Atlanta, In these instances, a surrogate value of 0.25 ppbv was used. For all olhef
species, missing hourly values were obtained by spline interpolation.  To represent average conditions,
the data from the  five ozone event days  studied here were geometrically averaged, This procedure
minimizes the impact of extreme values that may have been caused by anomalous episodes at a given
site which may not have been representative of the actual conditions in the area surrounding the site.
    To facilitate the analysis of this data using the OBM, we segregated the hydrocarbon! sped* wo
two general categories: i.e. a natural category for those species emitted by trees and other v^e^™*1
and an anthropogenic category for those species emitted by cars, factories and other human activito.
Of the 47 hydrocarbons measured in Atlanta, isoprene was the only compound identified as
from natural sources. The remaining 46 species are entirely of anthropogenic origin. Typically
the anthropogenic hydrocarbons have the highest concentrations during the morning rush hours,
isoprene concentrations are low in the morning and tend to peak in the late afternoon.  These difference*
in temporal patterns have a major effect on the photochemical production of ozone.
    In  addition to the aggregation of hydrocarbons into natural and  anthropogenic  sources,!!*
anthropogenic hydrocarbons were further apportioned into mobile sources (on road vehicles and other
                                             490

-------
vehicles) and stationary sources (combustion, manufacturing, waste treatment and waste disposal, fuel
use, incineration and burning). This allocation was done using the U.S.  1985 NAPAP speciated
hydrocarbon inventory which is based on emissions estimates for the entire country* rather than Atlanta
and therefore is only a qualitative estimate.

RESULTS AND DISCUSSION

RIR Area Average
    Figure 1 shows the Relative Incremental Reactivities (RIR) computed by the OBM for six groups
of  ozone  precursors:  NO,  anthropogenic hydrocarbons (AHC), hydrocarbons from mobile  sources
(MHC), hydrocarbons from stationary sources (SHC), natural hydrocarbons (NHC), and CO. The RIR
functions  were obtained using geometrically-averaged data for the  five ozone event days in August
studied here. The OBM was first used to compute the RIR functions for each individual location and
for each group of ozone precursors. Then, the area average for each one of the  six groups of ozone
precursors was obtained using formula (3). The results show that ozone production is more sensitive
to changes in NO than to changes in anthropogenic hydrocarbons. This result suggests that a strategy
based on controlling NO, emissions appears to be more effective than a strategy based on controlling
anthropogenic emissions of hydrocarbons. The results  also«show that  controlling mobile sources of
hydrocarbons is more than twice as  effective as controlling stationary sources, while CO has very little
impact  in ozone production. In addition, Figure 1 shows the  importance of natural  emissions in the
Atlanta area. Even though the isoprene concentrations comprise a small part of the total hydrocarbons
budget, the  ozone sensitivity  to  natural hydrocarbons is comparable  to  that of anthropogenic
hydrocarbons. An alternative way  to compute  area averages was also used.  In  this technique, area
averages are obtained for individual days, that is equation (3) is applied to RIR values obtained for a
specific day. Once the area averages are collected for all the ozone event days, an arithmetic average
is performed. This new average represents the area average for the period of the ozone event days. The
values obtained by this alternative method were similar to those displayed in Figure 1.
     for Individual Hydrocarbons
    An interesting application of the OBM is the calculation of RIR values for individual hydrocarbons.
These individual RIR values can then be used to identify which hydrocarbons are most important in
producing ozone  in an urban area and thus deserving of the primary  focus in the development of
emission inventories and the implementation of emission controls.
    Table 1  shows the RIR values for the top 10 anthropogenic hydrocarbons for the Atlanta area. The
combined reactivity of these 10 compounds represents 62% of the total anthropogenic reactivity and
suggests that the xylenes, iso-pentane, 1-butene, and trans-2-butene arc the major contributors to ozone
formation during ozone event days in the Atlanta area.
     at Individual Stations
    The RIR functions computed at each station for each of the five individual ozone event days
indicated a consistent picture for three stations (i.e., M.L. King, Fort McPherson and Tucker) with
daily RIR values similar to those shown in Figure 1, but significant variability for the other three sites
(i e., Mars Hill, Georgia Tech and Dekalb).  For example, at the Mars Hill and Georgia Tech sites
the RIR(NO) values on August 21, the RIR(NO) values were less than zero (i.e., -0.811 and -0.457
respectively), while all other days had positive RIR(NO) values.  The negative RIR(NO) values were
caused by the anomalously high NO concentrations recorded at these two sites on this day. On August
21  the afternoon NO concentrations recorded for Mars Hill and Georgia Tech were always above 2
ppbv,  while on all other days the recorded NO concentrations usually were below 1 ppbv. These high
NO concentrations caused the RIR(NO) values for the two sites on August 21 to be negative. The cause
 f these anomalously high NO concentrations is not known.  The other four stations did not show any
unusual behavior on August 21 and the meteorological conditions on August 21 were quite similar to
                                            491

-------
 those encountered on the other ozone event days studied here.
       On August 15, the Defcalb site showed an interesting anomaly. On that day, the RIR(NO) value
 was 1.644 while the average RIR(NO) value for the remaining ozone event days was 0.305. The NO
 measurements for that day showed a single isolated peak at 1500 hours of 10 ppbv. This peak, whose
 origin is also not known, caused the large RIR(NO) value calculated for this day.

 Ozone sensitivity to NO measurements
    To gain a better understanding of the sensitivity of the calculated RIR  values to the uncertainties
 in the NO measurements, model runs were carried out for the data of August 19 at the Georgia Tech
 site with different assumed surrogate NO values (which largely controls the  NO concentrations used in
 the model during the afternoon). The surrogate NO values used in this sensitivity study were: 0.25,
 0.50,1.00,1.50,2.00, and 2.50 ppbv. The corresponding RIRfNO) values obtained were 0.821,0.509,
 0.268, 0.077, -0.069, and -0.309, respectively.   Clearly the calculated RIR(NO) values are quite
 sensitive to the surrogate NO value assumed and thus on the exact sub-ppbv concentration of NO in
 the afternoon.  Our calculations indicate that an accurate determination of the efficacy of NO, emission
 reductions on ozone concentrations in urban areas will require NO measurements using instrumentation
 with limits of detection well below 1 ppbv.

 CONCLUSIONS
    The application of the Observation Based Model to data obtained during  ozone episodes in Atlanta,
 Georgia snowed the usefulness of the model in the analysis of data collected during ozone event days
 and the potential to aid in the  developing of control strategies in urban areas. The OBM requires
 accurate measurements,  since it is based exclusively on observed quantities. Particularly important in
 this regard is  high-sensitivity NO measurements during  the midday  and afternoon hours.  Another
 important characteristic of the OBM is its ability to study ozone sensitivity to individual hydrocarbons.
 In case of the Atlanta  1990 dataset, the natural hydrocarbon isoprene was found to be the single most
 important hydrocarbon controlling ozone production.  A small group of anthropogenic species (iso-
 pentane, xylenes, 1-butene, propene, and trans-2-butene) were also found to be important.

 REFERENCES
 1. Haagan-Smit, A.  L, Chemistry and physiology of Los Angeles smog, Tnd. Eng. Them.. 44, 1342-
 1346, 1952.
2. Seinfeld, J.  H., Urban air pollution: State of the art, Science. 243, 745-752,  1989.
3. Chock, D. P., and J. M.  Heuss, Urban ozone and its precursors,  Environ. Sci. Technol.. 21,1146-
 1153, 1987.
4. Friedman, R. M.,  J.  Milford, R. Rapoport, N. Szabo, K. Harrison,  S. V. Van  Aller,  R. W.
Niblock, and J. Andelin, Urban Ozone and the Clean Air Act: Problems and Proposals for Change* 160
pp., Office of Technology Assessment, United States Congress, Washington,  D.  C., 1988.
5. Lindsey, R. W,, and W.  L. Chameides,  High-ozone events in Atlanta, Georgia, in 1983 and 1984,
Environ. Sci. Technol.. 22, 426-431, 1988.
6. Environmental Protection Agency, National ambient air quality and emission  trends  report. 1990.
Rep. EPA-450/4-91-023, Environ. Prot. Agency, Office of Air Qual. Plann. and Stand., November
 1991.
7. Carter, W. L., and R. Atkinson, Computer modeling study of incremental hydrocarbon reactivity,
Environ. Sci. Technol., 23, 864-880,  1989.
8. Carter, W.  L., and R. Atkinson,  An experimental study of incremental  hydrocarbon reactivity,
Environ. $cj. Technol.. 21T 670-679,  1987.
9. J. Wagner and M. Saeger, personal communication, 1991.
                                            492

-------
Table 1 RIR Functions calculated for Atlanta August 1990
	 Top 10 individual anthropogenic hydrocarbons
Species
1- iso-pentane
2. m & p xylene
3. 1-butene
4. propene
5. trans-2-butene
_6; o-xylene
7- ethene
_J^ 2-methyl-2-butene
9- 1,2,4-trimethylbenzene
JO_Jrans-2-pentene
Relative Incremental Reactivity
0.0197 ± 0.0075
0.0154 ± 0.0046
0.0132 ± 0.0031
0.0127 ± 0.0021
0.0083 ± 0.0013
0.0075 ± 0.0020
0.0071 ± 0.0011
0.0069 ± 0.0010
0.0062 + 0.0016
0.0060 ± 0.0010
             0.5
             0.0
    1 Relative Incremental Reactivity computed by the Observation Based Model using the data
    3 in  Atlanta,  GA  during August of 1990.  RIR functions are shown  for NO, anthropogenic
 ocarbons (AHC), hydrocarbons from mobile  sources (MHC), from  stationary sources  (SHC),
«ral hydrocarbons (NHC), and for CO.
                                         493

-------
    QUALITY ASSURANCE PLANNING FOR  STATIONARY
                      SOURCE FIELD SAMPLING
                       Merrill D. Jackson and M. Rodney Midgett
                           Source Methods Research Branch
                      Methods Research and Development Division
               Atmospheric Research and Exposure Assessment Laboratory
                         U.S. Environmental Protection Agency
                           Research Triangle Park, NC 27711
ABSTRACT
     Stationary source stack sampling procedures arc used to determine the amount of emissions
as required under the Resource Conservation Recovery Act, Appendices VIII and IX, and the
Clean Air Act Amendments (CAAA) of 1990, Title HI.  Sampling procedures are costly and require
much planning and time to complete. Most effort on implementing quality assurance (QA) in the
past has centered on (he analytical and laboratory portion of the test. However, the laboratory
result, no matter how good, is only as good as the field sample that has been presented.
     Errors occurring during field sampling might not be discovered until after the sampling phase
of the test is completed and after samples are in the analytical phase. This could result in another
expensive sampling trip. One way to reduce the chance of errors is to have and  follow a QA plan.
This  paper describes the  planning phase for the field study, errors that may occur  during the
sampling phase, and how the  QA plan might prevent or minimize errors during field sampling.

INTRODUCTION
     Stationary source field sampling is usually expensive. Not only is there the  cost of getting the
equipment and personnel to the site, but also the need to adjust the plant's schedule and personnel
to accommodate the sampling team.  The results of poor sample handling may not be evident until
the analytical laboratory has run the samples. Then it is too late for corrections. A proper quality
assurance (QA) program, however, will help to identify most problems either  before or as they
occur. This permits correction in the field while the sampling team and equipment are still or
location. We will discuss where problems occur in the field and how they may be corrected.
     Stationary source field sampling involves several phases, that include the  following:

            1. Planning and design of the field sampling test
              A. The emissions to be sampled
              B. Sample volume needed
              C. Use of the results

            2. A pretest site survey
              A Possibly collecting a pretest sample
              B. Determining locations of sampling ports and  logistics

            3. Pretest preparation
              A. Sampling media cleanup and quality control (QC) checks
              B. Auditing equipment for proper operation
              C Packing for shipment to the field
                                        494

-------
            4. Site pretest preparation
               A.  Placing equipment
               B.  Checking operation of equipment

            5, Sampling
               A. Keeping records
               B. Labeling of samples
               C. Maintaining custody control

            6. Transferring of samples to laboratory
               A.  Packaging of the samples
               B.  Shipping by proper means
               C. Timing to maintain samples

    e 6 items are all procedures includes in a QA\QC plan. The total planning for the test would
    include the  QA/QC for laboratory activities; however, this paper addresses QA for the
sampling only.

EXPERIMENTAL PLANNING AND IMPLEMENTATION
Banning and Design
     The QA plan should be prepared by the technical staff and reviewed by appropriate QA
Personnel before the survey visit.  It should describe all sampling plans and  associated QC
Procedures. The data quality objectives for the field test should be in place before the survey and
 nould include, as a minimum, the reason for the test (e.g. required for compliance with some
d gulations). Other data quality objectives might be: (1) selecting the compounds to be tested; (2)
wh :er/ninin? tne level of detection that will be required to demonstrate compliance; (3) determining
 nether this level of detection can be met by the combination of the analytical  finish (e.g. gas
 l°mat°graphy/mass spectroscopy), the sampling flow rate, length of time of sampling, and
   eee   concentration in the stack; and (4) ensuring an adequate number of sampling points
  °/or replicates and an adequate number of duplicates for proper statistical evaluation.  During
   pretest survey, some of the objectives may need to be modified.
       Survey
     T*U'  •
arri      S*te visit is made to confirm tnat tne test plan can be carried out once the sampling team
   ves On site. Some of the following problems have been discovered during pretest surveys.

     *• The plant cannot continuously operate for the length of time required for collecting a full
        sample.

     2- The stack sampling ports are not in the  locations required by the compliance agency.

     3- Continuous monitors are not operating or the inlet ports are in the wrong location.

     4- There is insufficient room on the sampling platform for full isokinetic sampling.

te?t°diQA plans are designed to help locate these types of problems. After the pretest visit, the
com     may need to be corrected to allow for either a higher flowrate, selection of a different
ort  °uUnd for sapling or an interrupted sample U. collection of half a sample one day and the
   er half the next day.  However, we do not recommend the splitting of sampling days. Sampling
                                          495

-------
ports and platforms may have to be added at the proper stack locations. The continuous monitors
can be repaired or relocated. If these problems are not noted and evaluated before the sampling
team arrives, the sampling may have to be postponed, with resultant cost to the customer. A stack
test was performed as a piggy back to another test.  This test was delayed by 2 days because the
prime  contractor  did  not  check the  availability  of electrical power.  The electrical power
requirement was 20-20 amp circuits, however the stack only had 4-15 amp circuits on it. Extra time
was expended to get two portable generators to the site. A proper pretest site visit with a QA plan
would have identified this problem. During another test, where the stacks would be unaccessible
during testing, some continuous monitors required attention before sampling could begin. A QA
pretest audit revealed the problem in time  for corrective action before testing began.u

Pretest Preparation
     The sampling media must be checked to determine the background levels of compounds of
interest in them. These levels must be below the detection limit; if they are not, then corrections
in the cleanup procedure must be made. For example, in running a volatile organic sampling train
(VOST) test3 for a Resource Conservation and Recovery Act trial burn, the tubes must contain less
than the total organic limit defined in the QA/QC procedures for hazardous waste incineration.4
The  media must be  properly packaged so that it will not deteriorate nor be contaminated in
shipment.  The sampling containers, if needed, should be designed to  collect  the proper size
sample, to allow the proper placement on the sampling train, and  to be compatible with final
shipping requirements.  All measuring devices must have had their calibrations checked and must
be certified that they are correct within the limits allowed.  If flow meters are not correct, the
resulting data can  have a major  bias. For example, if a flow meter were off by 10% and the
destruction and removal efficiency (ORE) calculation was just 99.99%, the DRE could be changed
to 99.98%. That would result in a costly failure for the permittee.  This is why most contractors set
up their trial burns to  show 99.999%. This way,  a  10% error would  only change the DRE to
99.998%. Furthermore, incorrect temperatures in the probe and in locations of the train can result
in loss of the  sample;  for example,  compounds  will not  collect on XAD-2 resin used in the
semiVOST.5 Instead the compounds will pass through the resin if the temperature is too high;
whereas, if the probe temperature is  too low, the compounds condense in the probe and never
reach the  sampling train media.   Similar problems with incorrect temperatures  occur with the
VOST train sampling medium.  The validity of the entire sampling test could be lost if the
temperatures in the sampling train are not  correct

Site Pretest Preparation and Sampling
     The QA plan details the permissible allowances on each parameter that must be measured
and/or recorded during the sampling period.  It includes conditions that are  not actually part of
the sampling but still must be met if the sampling is  to be valid, such as the correct temperature
of the burner; determination of excess oxygen present; continuous emission monitors for gases such
as carbon monoxide, carbon dioxide, and hydrocarbons; and proper waste feed flows.  For the
sampling train itself,  several  parameters must be met for a successful trial burn.
      Probably  the  most important  test performed on the train  is the leak  test   This  test
demonstrates how much outside air is drawn into the train.  It must be preformed both before and
after the sampling run. The effect of incorrect temperature on the train was discussed in the
previous subsection.  Location of the sampling train is also critical to  the success of the  test. It
must be located in the part of the stack where flow is as consistent as possible. This requires that
the port be a certain distance away from flow interferences, such as bends, a change in diameter,
or from the  exit plane.  A certain number of samples must be collected for permit requirements,
usually three complete  sets  (for example, a set  is a probe wash,  filter, and XAD-2 resin for
                                           496

-------
semiVOST sampling). With the scmiVOST train, three sets are usually sufficient because the
analysis can be repeated in the laboratory; however, the VOST does not allow repeat analysis, so
an extra sample or two should be collected. To collect a proper volume of sample, an adequate
flow rate and length of time must be established for sampling. If the flowrate is either too low or
high, it can prevent compounds of interest from being collected on the sampling media. Therefore,
a proper flowrate must be  established that is acceptable with the time allotted to obtain the
required total sample volume. In the field, the proper procedure must be followed for handling
foe sample.  If blank samples are to be  collected, the type must be specified, as well as the
procedure for handling them. Field blanks are usually carried to the stack and are opened to the
ambient air for the same length of time that the actual sample tubes are exposed. Trip blanks are
carried to the field but are never opened. The number of each required, depends on the total
number of samples to be collected and the length of the test. Usually  one or two trip  blanks are
sufficient for the test, whereas, the field blanks are required at least once a day. Recordkeeping
for a complete site testing program should be detailed. It is very difficult, if not impossible, to recall
what was actually done in the field once you are back in the laboratory if complete records are not
kept.
     The  QA plan also details the  proper procedures to follow if problems arise and how a
determination for corrective action is made during field tests. Usually the project manager (PM)
must be contacted for direction and approval of changes. The plan should specify whether the PM
    be on site, or whether and how the PM can be contacted. Sometimes, the  compliance agency
    need to be contacted.  The QA plan must spell out in detail who should contact the agency's
representative and the proper ways of doing it.  Any procedural changes made in the field must be
documented  for future assessments.

Transfer of Samples
     Once the samples are collected, they still could not be valid if the proper procedures are not
Allowedin packing and shipping the samples to the analytical laboratory. The semiVOST samples
must be placed in correct containers (glass jars for the liquid washes, glass containers for the
Paniculate and the sorbent module is capped). They must be cooled, usually on ice for shipping.
Most sampling tests require that  a chain of  custody be maintained,  so that any errors can be
Pinpointed to the personnel performing that step.  Every sample must  be labeled and numbered.
y16 numbering system will be designated in the test plan. The samples must also be returned to
  e laboratory within a specified time period to prevent deterioration.  Failure to adhere to these
conditions can result in samples that will produce invalid and indefensible results.

SUMMARY
     We have discussed the ways in which a stack sampling test can be protected from failure by
u.se of several techniques. Also, we considered the complete test, from planning through pretest
site visit, preparation of sampling media, the actual sampling, and the transfer of samples to the
analytical laboratory.  These techniques are used as a matter of course by all good sampling crews
collecting samples from stationary sources. Most of the techniques are included in the field test
PLan.  QA identifies the check points and  limits requireed to determine potential  troubles. The
goal of QA is problem preventation.  Planning quality management into projects and following
good QA/QC procedures is technical common sense.

OTHER SOURCES OF INFORMATION
  .   The U.S, EPA has provided a series of handbooks to aid the permit writer in evaluating the
!"»! burn plans and then the results.4-** These handbooks include most of the QA that should be
Deluded in the trial bum planning.
                                          497

-------
 DISCLAIMER
     The information in this document has been funded wholly or in part by the United States
 Environmental Protection Agency.  It has been subjected to Agency review and approved for
 publication.  Mention of trade names or commercial products does not constitute endorsement or
 recommendation for use.

 REFERENCES
 1. F.W. Sexton and D.E. Lentzen, Audit of the Vulcanus Incineration Ship Prior to the August
   1982 PCB Burn. Mobile. Alabama. EPA-600/7-83-023, U.S. Environmental Protection Agency,
   Research Triangle Park,  1983.

 2. D.G. Ackerman, J.F. McGaughey and D.E. Wagoner, At-Sea Incineration of PCB-Containine
   Wastes Onboard  the M/T Vulcanu^ EPA-600/77-83-024,  U.S.  Environmental Protection
   Agency, Research Triangle Park, 1983.

 3. Validation of the Volatile Organic Sampling Train fVOST) Protocol. EPA-600/4-86-014, U.S.
   Environmental Protection Agency, Research Triangle Park, 1986.

 4. Oualiry^^surance/Quality Control (QA/CO Procedures for Hazardous Waste Incineration.
   EPA/625/6-89/023, U.S. Environmental Protection Agency, Washington, DC, 1990.

 5. Laboratory and Field Evaluation of the Semi-VOST (Semi-Volatile Organic Sampling Trainl
   .Meihod, EPA-600/4-85-075, U.S. Environmental Protection Agency, Research Triangle Park,
   1985.

 6. Permit Writer's Guide to Test Burn Data - Hay^rdous Waste Incineration. EPA/626/6-86/012,
   U.S. Environmental Protection Agency, Washington, DC, 1986.

7. Guidance on Setting Permit Conditions and Reporting Trial Burn Results - Volume II of the
   Hazardous Waste Incineration Guidance Series. EPA/625/6-89/019,  U.S. Environmental
   Protection Agency, Washington, DC, 1989.

8. Hazardous Waste Incineration Measurement Guidance Manual - Volume III of the Hazardous
   Waste  Incineration  Guidance Series. EPA/625/6-89/021, U.S. Environmental Protection
   Agency, Washington, DC, 1989.
                                         498

-------
                 DATA VALIDATION GUIDANCE  FOR
             AMBIENT AIR MEASUREMENT METHODS
                                      Ann Rosecrance
                                  CORE LABORATORIES
                           10205 Westheimer, Houston, TX 77042


ABSTRACT
       The validation of analytical data is important in ambient air measurement activities to assess the
quality of the data generated and determine the effectiveness of the monitoring system. Data validation
is the process of determining the compliance of analytical data with established method criteria and
regulatory specifications. This paper provides guidance for the validation of GC and GC/MS data for
volatile organic compounds in ambient air using EPA air toxics methods.  It also presents a summary
« quality control requirements for volatile air toxics methods.  The methods included in this study are
I°-l, TO-2, TO-3, and TO-14 from EPA's Compendium of Methods for the Determination of Toxic
Organic Compounds in Ambient Air.1 A comparison of quality control requirements for the volatile
90 toxics methods with other EPA GC/MS methods for volatile organic analysis of water and waste
        is also provided.  This  illustrates that a uniform approach  to data validation can be used  for
        of different matrices analyzed by similar analytical methods.
INTRODUCTION
      The U.S. EPA and other agencies have developed many methods for the analysis of chemical
species in a variety of matrices by various analytical techniques.  Each method defines the specific
requirements associated with the  use of the method,  which may  be further  defined in the quality
assurance project plan.  The analysts in a production laboratory and the reviewers of analytical data
mu« be familiar with the requirements of all of the analytical methods that are  routinely used in order
to ensure  that the applicable requirements are met for each  analysis.  With the large number of
analytical methods available, it is easy to become confused on the specific requirements of each method.
  urther, since environmental sample data may be used as legal evidence, and  data can be potentially
           if not in compliance with established  expectations,  it is critical that each analysis and
        data are in  full accordance with the method requirements and project specifications.
      Data  validation activities determine if analytical data are in compliance wilh the analytical
       requirements and project specifications.  Data validation documentation developed by the U.S.
         other state agencies for  specific programs are used as standards for data validation.1-3-4
        publications have provided method  comparisons and data validation guidance for multiple
organic analysis methods for GC and GC/MS  analysis of volatiles, semivolatiles, and pesticides/PCBs
 |i dnnking water, wastewater, solid  waste, and hazardous waste.*-* Additional method comparisons and
Jata validation guidance have been provided for inorganic methods of metals analysis by AA and ICP.1
  is paper provides an overview of the quality control requiren«Jvt& for several analytical methods from
~*'A s Compendium of Methods for the measurement of volatile organic chemicals in ambient air.
         are guidance for the validation of data from several volatile organic analysis methods and a
        approach that can be used to validate data from any analytical method.

Data Validation
     ,      	> provide assurance that data are adequate	
essentially a question and answer process to determine if the data meet both the analytical method
                                           499

-------
 requirements and the project specifications. The three major questions to assess are:  were the required
 quality control (QC) elements included, were they included at the required frequency,  and were the
 required acceptance criteria met.

 Data Validation Approach
        The recommended approach for validating data starts with the preparation of a summary of the
 required QC criteria for each method in use.  The varied QC requirements for each  of the methods of
 interest are then readily available and can be compared to the other methods in an easy to reference
 format. Revisions or additional methods can be included as needed. This approach  is straightforward
 because it is based on QC elements which are common between methods.  Detailed method documents
 are  used  for reference when needed to clarify specific requirements.   The data validation process
 proceeds  by closely following the sequence of the analytical procedure.  Data generated from any of
 the methods are reviewed for compliance with each applicable QC criteria. Using summary charts that
 provide the required criteria and checklists that record compliance with the criteria, the data validation
 process can be performed effectively and efficiently for multiple analysis methods.

 Quality Control Elements
       The types of analyses that are subjected to data validation are method quality control, sample
 specific quality control, and other quality control.   Method quality control consists of all of the analyses
 necessary to prepare for the sample analyses and that are common to the sample batch.  This includes
 instrument tuning, calibration, blanks, and laboratory control standards.  Sample quality control are the
 items that are specific to each sample. This includes internal standards, surrogate spikes (if used), and
 the identification and quantitation of target analytes and tentatively identified compounds.  Other quality
 control consists of additional analyses that are necessary to perform the analyses and use the data.  This
 includes container certifications, field blanks, field replicates, detection limit determinations, precision
 and accuracy measurements, and performance evaluation samples.

       Tuning.  Tuning/instrument performance  checks  ensure that GC/MS  mass assignments and
 relative ion intensities are in accordance with the established method performance criteria.  Tuning data
 are evaluated for the analysis of the correct compound, at the required concentration and frequency, and
 within the required relative ion abundance criteria.  Relative ion abundance criteria are presented in each
 of the analytical methods.   A summary of tuning requirements is provided in Table I.   Note that
 Methods TO1 and TO2 utilize perfluorotributylamine (FC43) while the other GC/MS methods utilize
 bromofluorobenzene (BFB).  Tuning data that do not meet the required relative ion abundance criteria
 should be evaluated to  determine if the deviation is significant and would impact the sample results.

       Initial Calibration.  Initial calibration ensures that the instrument is capable of generating
acceptable qualitative and quantitative data at the initiation of the analysis. Initial calibration data are
evaluated for the analysis of the required analytes, at the required number of levels and concentrations,
at the required frequency,  and within the required response factor and linearity criteria.  GC data are
also  evaluated  for  chromatographic  efficiency  and  the  acceptability  of retention time window
determinations.  A summary of initial calibration requirements are provided in Table I.  Note that the
initial calibration requirements vary between methods.  Initial calibration data that do not meet the
required criteria should be evaluated to determine  if the deviation is significant and would impact the
sample results, and if qualification of the data is needed.

       Continuing Calibration.  Continuing calibration  ensures that the instrument is capable of
meeting the qualitative and quantitative measurements established in the initial calibration.  Continuing
calibration data are evaluated for the analysis of the required analytes, at the required concentrations,
within  the required  frequency, and within the required response factor  and precision  criteria. A
summary of continuing calibration  requirements are provided in Table I.  Note that the continuing
                                             500

-------
 calibration requirements vary between methods.  Continuing calibration  data that do not meet the
 required criteria should be evaluated to determine if the deviation is significant and would impact the
 sample results, and if qualification of the data is needed.
                Blanks ensure that the existence and magnitude of laboratory background contamination
 does not interfere with the sample analyses. Blank data are evaluated for the analysis of the correct type
 of blank, at the required frequency, and within the required criteria for acceptable background levels.
 A summary of the blank requirements are provided in Table I. In general,  the contamination in the
 method blank should be no higher than the detection limit. If unacceptable contamination exists in the
 method blank, then all associated sample data should be carefully evaluated to determine if the sample
 data are affected  by  the background contamination. If affected, the sample data should be qualified
 appropriately.
                Quality Control.  Sample data are evaluated for adherence to a number of criteria in
 order to determine the acceptability of the sample results.   Sample collection and analysis times are
 evaluated to determine if analytical holding times were met.  The sample internal standard areas and
 retention times are  compared to those in  the corresponding calibration standard to ensure  that the
 instrument  response was  stable.  Retention times of found target analytes are compared to retention
 times of the corresponding standard to ensure that identifications by GC retention time are acceptable.
 Mass spectra for found target analytes are compared to standard mass spectra to ensure that the major
 ions present in the  standard are present in the sample  mass spectra within comparable relative ion
 abundances.  The mass spectra for tentatively identified  compounds are reviewed to ensure that mass
 spectral identifications are acceptable.  Quantitative results are checked for correctness of calculations
 and for appropriate  units; found target analyte concentrations should be within the calibration range.
 The  reported results are reviewed to ensure that they fully agree with the raw data and  that the
 appropriate quantitation or detection limits were used. Other criteria, if applicable, should be evaluated
 for each sample analysis.  Sample results should be reviewed for adherence to the associated project
 specifications and reporting requirements.  Sample data that do not meet any of the required criteria
 should be qualified appropriately.

        fltfrgr Quality Control. Other quality control analyses are those associated with the preparation
 of the sample collection device and the analytical system. Sample collection devices are evaluated for
 the presence of background contaminants, for their ability to allow recovery of the target analytes, and
 to assure that they do not leak. For example, methods that utilize canisters require canister certification,
 humid air certification, and leak tests.  Additional field quality control measures include field blanks,
 replicates,  and backup  samples to  measure  field contamination,  field precision, and   sample
 breakthrough, respectively.  The analytical  system is tested to establish that required  method detection
 limits can be achieved and that acceptable precision and accuracy data can be obtained.  Data should
 t>e available to support the achievement of the reported detection limits, and to demonstrate that results
 for replicates and spikes  (audit samples) meet  the method  requirements for precision and accuracy.
 Additional  laboratory  quality control  measures include performance evaluation samples to assess
 laboratory performance.  Data should be examined  to determine if the quality control checks were
 performed at the required frequency and to ensure that the results obtained  were acceptable.

Data Validation Documentation
       Data validation  activities are documented on standardized forms  such as  the data review
checklists provided in Figures 1 and 2.  The forms are used to report the adherence or lack of adherence
to each of the required quality control criteria. Any major deficiencies identified should be documented
in a detailed report describing each deficiency and its potential impact on the sample results. Qualifiers
for data in question should be in accordance with the project specifications and  they should be clearly
defined.  Examples  of qualifiers used in EPA Data  Validation Procedures2 are: (R), the results are
                                              501

-------
 rejected due to serious deficiencies in quality control criteria;  (J), the associated numerical value is an
 estimated quantity because certain quality control criteria were not met; (N), presumptive evidence of
 presence of material; (U) the material was analyzed for but not detected; and (UJ), a combination of
 U and J.  Recommendations for further action should be  included in  the data validation report, in
 addition to an  overall assessment of the data.

 CONCLUSIONS
        With the large number of analytical methods that are available for the various sample matrices
 and regulatory program applications,  laboratory analysts and data reviewers are required to be familiar
 with QC requirements that may sometimes vary with each method to be utilized.  The information
 presented in this paper summarizes the QC requirements for several  volatile air toxics  methods and
 compares those requirements to similar analytical methods for other matrices. This comparison provides
 laboratory  analysts with a tool for addressing the specific requirements of each method utilized and for
 ensuring that the QC requirements of the intended method are met. This information is not intended
 as a replacement for the analytical  methods, but is a reference to remind laboratory analysts and data
 reviewers of the critical  quality control requirements  of each analytical  method.   Data validation
 guidance for volatile organic analysis methods is provided which allows data reviewers to use a single
 approach for validating data from similar analytical methods.

 REFERENCES
 t.     W.T. Winbeny, Jr.,  N.T. Murphy and R.M.RJggin, Compendium of Methods for the DetermjflfttJPB of Toxic
       Organic Compounds ia Ambient Air. EPA 600/4-89/017, U.S. EPA, Research Triangle Park, June 1988.

 2.     Quality Assurance/Quality Control Guidance for Removal  Activities: Sampling OA/OC Plan and Data Validation
       Procedures. EPA 540/G-90/004, U.S. EPA, Washington D.C., April 1990.

 3-     Laboratory Data V«lid.tion Functional  Guidelines for Evaluating Organics Analyses. U.S. EPA. 1988.
4.     Standard Operating Procedures for Quality Assurance Data Vali^*tion of Analytical Peliverableg - Qrnuiicff- New
       Jersey Department of Environmental Protection and Energy, 5.A.13, October 1991.

5.     A.E.Rosecrmnce, "Data Validation Guidance for Multiple Organic Analysis Methods, * in Proceedings of the 1991
       Water Pollution Control Federation's Specialty Conference on An^lvt'c** Compliance and Data Objectives. Durham,
       August 1991.

6.     A.E.Rosecnnce, 'Data Verification Guidance for GCandGC/MS Environmental Analyses,* i
       1992 HazTech International Environmental Conference . Houston, 1992.
7.     A.E.Rosecnnce, D.Demorest, L.Kibler, 'Data Validation Guidance for Inorganic and Radiochemical Methods,'
       presented at the 5th Annual New Mexico Hazardous Waste Management Society Conference, Albuquerque, Match
       1992.

8.     Interim Guidelines and Specifications for Preparing Quality Assurance Project Plans. QAMS-005/80, U.S. EPA,
       Washington D.C., December 1980.

9.     Methods for the Determination of Qryanic Compounds in Drinking Water. EPA  600/4-88/039, U.S.  EPA,
       Cincinnati. December 1988, Method 524.1.
l°-     Maboft for Omnk Chcmiol Analysis of Municinal and Industrial Wastewater. U.S. EPA, Appendix A to40CFR
       Part 136, Vol. 49, No. 209. October 26. 1984. Method 624.

1 ' •     Test Method* for Evaluating Solid Waste. Physical/Chemical Method*. SW-846, U.S. EPA, Washington, DC, Third
       Edition, November 1986, Method 8240.

12-     Statement  of Work for Organic* Analysis. Multi-Media Multi-Concentration. U.S.  EPA Contract Laboratory
       Program. OLM01.0, August 1991 Revision, VotatjJes Method.
                                                502

-------
            Table I.  COMPARISON OF QC REQUIREMENTS FOR VOLATILE ORGANIC ANALYSIS METHODS
(^^"^x. Method
Requirement ^"^N^
TUNING
Frequency
Criteria

1C: Level*
Criteria (%RSD)

CC: Frequency
Criteria <%D)

BIX: Frequency
Criteria

SPIKES (%R»covery)
REPUCATES (%RSD)
INTERNAL STDS.
Criteria
ANALYTE ID
TOT
FC43
Daily
Table 2

3
LSF

Daily
±20%

Before
<10ng

NS
< 20-28%
1 eiOOng
±3. SD from
mean
RTandMS
T021
FC43
Daily
Table 2

3
LSF

Daily
±20%

Before
<10ng

>75%
< 20-25%
1 @100ng
±250 from
mean
RT and PUS
T031
NA
NA
NA

4 + blank
LSF

4-6 hrs
NS

NS
NS

90-110%
<5%
NA
NA
RT
T014'
BFB
Daily
Table 4

3 + War*.
NS

Daily
NS

Before
ec;
3 ions ±20%
82401'
BFB
12 hrs
Table3

S
<30%

12 hrs
±25%

12 hrs
In Control

Varies
Method QC
Limits
3 @ 50 ugA-
NS
RRT ±0.06;
lorn > 10%
±20%
CLP12
BFB
12 hrs
Table 1

5
<20.5%

12 hrs
±25.0%

12 hrs
10%
±20%
NA: Not Applicable; NS: Not Specified; 1C: Initial Calibration; CC: Continuing Calibration; LSF: Least Square Fit
Note: Table number* refer to the corresponding method document.

-------
Ml
MHAMFTZH
JOWCAtt

HTOCHWJM
TUMW
• ft*4Ulnd M*ip«und>
» C«m«t frmnnr'
• criMta mttF


• lb«*>dWnll?




• U HHlvni pnunl




• Cunnt fmf wnoyr




• Cirrmlrnmmy>
• CrfwimM?
MUCATH




• b«rin< ftwuMoyl
• OdlHtoiMir
FTMODC


vn






























IATARE\
[

KO






























rrew CHECK
U4HLT1H UC1MQ
lAtl* ANALVZEE

ouAunn






























>UST
D


COKHCNTt






























Figure 1.  Data Validation Checklist for
          Method Quality Control Review
                504

-------
SAMPLE DATA REVIEW CHECKLIST
uuHrm
urmoo
JOWCAlt

rnocmuM
HOtMMTM
• HtMng *•» •<•<>
wnviALCTAWum
• AnMwhHnMur
• MtTmHNiiMur
mum TAMCT AMirm
• KTMWTl ««Nn InJHI
• Ut imniinlilimm
• OwnHWIon MmM7
. Oo«*— .-W*,«^f
1WTAnVB.V DWimD COMMWMM

pMluWMHhdT
• *«U«taiiOK7
• ttoMIMUll MIT«t>
ANALTMOC
• WMMn MM pntofl
• AwnptoUOClMlltM
.IKWVUU.I
rtMl*l«UM*
W*f««H«
DVOITBMTA
* AITMI trim nw uu>
• *»iini'ni m tin i-
OIM^R OPI^WW

nrvirwn>*v

n*






















• AMPLE NO.
DATI COCUCTED
OATIII) HIEPABtO
OATIISI ANALVnO
MO






















ouAunn



























COMMENTS






















OATl

Figure 2.  Data Validation Checklist for
          Sample Quality Control Review
                  SOS

-------
           METHOD EVALUATION OF THE DRAFT
                      STATEMENT OF WORK
              FOR ANALYSIS OF AMBIENT AIR -
           AIR TOXIC SEMIVOLATILE COMPOUNDS
                      FOR THE SUPERFUND
             CONTRACT LABORATORY PROGRAM
Ralph J. Sullivan, Michael Zimmerman, Steven M. Pankas, and Judith E. Gebhart
IGF Technology Inc.
2700 Chandler Ave., Building C
Las Vegas, NV 89120
ABSTRACT
The U.S. EPA has developed a draft of the "Statement-of-Work (SOW) for the Analysis of
Air Toxics at Superfund Sites" as an integral part of the Contract Laboratory Program
(CLP). Specific quality assurance (QA) and quality control (QC) measures are key features
of the SOW. The QA/QC activities associated with sample analysis are intended to
document laboratory and method performance. Performance evaluation samples (PESs)
are an important element in an external performance evaluation monitoring program. The
draft method has been evaluated during the preparation and analysis of PESs. Analytical
results of preparing and analyzing  samples for semivolatile compounds sampled on
polyurethane with XAD-2 resin sandwiched in a cartridge (PUF/XAD-2) are presented.
Over  100  compounds  including   pesticides,   polynucleararomatic  hydrocarbons,
polychlorinated  biphenyls, amines,  phenols, and other semivolatile convpovrnds  are
discussed. Preparation includes (1) cleaning and assembling PUFs, XAD-2 resin, and glass
cartridges,  (2) preparation of loading solutions,  surrogates,  and  standards,  and  (3)
extraction and concentration of semivolatile compounds for GC/MS analysis. The analytes
of the preliminary target compound list (TCL) were extracted by Soxhlet extraction using
an ethyl ether:  hexane mixture.  The more than 100 compounds were detected and
quantified in a single chromatographic run.

INTRODUCTION
The US EPA has developed a "Statement of Work for Analysis of Ambient Air" for die
Contract Laboratory Program1.   As part  of the Superfund program, semi-volatile
compounds were proposed to be measured after collection using a polyurethane/XAD-2
resin sandwich.   The semi-volatile compounds include pesticides, polynudeararomaric
hydrocarbons (PAHs), polychlorinated  biphenyls  (PCBs), and  other semi-volatile
compounds such as chlorinated benzenes, phenols, and amines. The PUF/XAD-2 type of
sampler  has been  demonstrated as  applicable to  measuring polynucleararomatic
hydrocarbons2 (PAHs),  pesticides3, chlorinated benzenes4, phenols4-*,  PCBs6, and other
                                   506

-------
semivolatile compounds in separate studies. No reference was found which showed that
all of these compounds could be detected and measured in the same sample.

The IGF Quality Assurance Technical Support Laboratory was tasked with development of
PESs to support the QA activities of the Superfund CLP program.  Studies related to PES
development, production, and use are ongoing  to ensure that these samples are of high
quality and high reliability.  A good PES will evaluate the ability of the laboratory and
method to:

        Identify compounds
        Quantify analyte concentrations accurately
        Avoid sample contamination

To meet these needs, PESs with long-term predictable stabilities are essential. In addition,
inclusion of diagnostic and indicator compounds in the PESs can assist the laboratory in
its procedures when the recovery results of certain compounds are observed.  Therefore,
the experiments which are described below were designed to determine which compounds
can be used for laboratory/method evaluation and diagnostic purposes. The TCL analytes
with their contract required quantitation limits (CRQL) are listed in Table I. For this work,
the PCBs were limited to one isomer from each congener group.  The compounds were
mixed together and spiked onto PUF/XAD-2 cartridges, extracted and analyzed. Tests were
completed to show the reproducibility, extraction recovery efficiency, and storage stability
over a 64 day period of time.

EXPERIMENTAL
The sample preparation and  analysis is diagramed in Figure 1.  Cartridges and PUFs were
obtained from General Metals (Atlanta, GA), XAD-2 was obtained from Supelco (Bellefonte,
PA), and analyte compounds were obtained from the EPA (QA Materials Bank, RTP, NC).
The initial PUP cleanup consisted of compressed rinsing 50 times in each of three solvents:
toluene, acetone and diethyl etherAexane (1:19 v/v). Following the initial cleanup, the
PUF plugs were placed in a  Soxhlet apparatus and extracted with 500 mL of acetone for
16 hours at approximately 4  cycles per hour. Following the acetone extraction, PUFs were
extracted with 500 mL of diethyl ethenhexane (1:19 v/v) for an additional two hours. The
extracted PUF plugs were placed in a vacuum oven at room temperature and pressure and
purged with nitrogen to remove the solvent. The XAD-2 resin (50-60 grams) was extracted
twice  with methylene  chloride for 16 hours and dried in the same manner as the PUF
plugs.  Cartridges were assembled as  shown Figure 1. These were wrapped in hexane
rinsed aluminum foil and sealed in glass jars, and stored refrigerated until used.

TCL analytes were divided into groups: acids and bases.  These groupings (A and B) are
also shown in Table I. Because the standard mixtures (obtained from EPA) contained some
non- TCL compounds, these compounds were also analyzed. These additional compounds
are marked with an asterisk in Table I. In addition to the 100 TCL compounds,  20 non-
target compounds were tested.
                                      507

-------
    ASSEMBLE
    CARTRIDGE
                         PRE-SAMPLE
                        SURROGATES
                              SPIKE

                            ANALYTES
                              POST-SAMPLE
                              SURROGATES
STORE
STORE
STORE
                  DRY
       SOXHLET
     EXTRACTION
                KD
             CONCENTRATION
                     NtTROQEN
                    SLOWDOWN.
                                               ,N2
                                                    ADO
                                                   INTER MAL
                                                  STANDARDS
                                                                   ANALYZE
                  Figure 1 -- SAMPLE PREPARATION AND ANALYSIS

Three "pre-sample" (pre-spike) surrogates (100 ^g in 1 mL of methylene chloride), 2j
fluorobiphenyl, nitrobenzene-ds, and p-terphenyl-d)4J were spiked into the clean assemb
canridges.  In the preparation of PESs, no air sampling was performed. To simulate
sample loading, the cartridges were spiked with 1 mL of various concentrations of the aci
and base mixtures. The canridges were wrapped in hexane-rinsed aluminum foil, se<|le
in glass jars, and stored  in  a  refrigerator (4°C)  for a  specified storage time.  Be
extraction, the samples were  spiked with 100 Mg each of five "post-sampling" (post-spi
surrogates:  phenol-ds,  2-fluorophenol,  2,4,6-tribromophenol,  anthracene-d,0,
benzo(a)pyrene-d]2.

Samples were extracted by Soxhlet extraction using 500 mL of ethyl etherhexane (1 =9 J
         The solutions were dried with anhydrous sodium sulfate and concentrated
Kuderna-Danish (KD)  evaporation.  The final concentration to 1 mL was accompli*
using nitrogen blowdown.

Analyses were performed with a Finnigan INCOS 50 GC/MS/DS system equipped
Vanan 3400 GC and Finnigan A2005 Autosampler. Splitiess Injections of 1 ^ *** '^0
with ruU scan acquisitions over a range of 35-510 m/z with El at 70 eV/sec scans.  »
columns were used: J&W DB-5, 30 m, 0.25 mm ID at 28 cm/s He carrier velocity and J»
                                       508

-------
DB-5.625, 30 m, 0.25 mm ID at 28 cm/s He carrier velocity which was later changed to
37 cm/s carrier velocity.  The gas chromatograph was programmed; 45 °C hold for 4 min,
8°C/min to 280°C and hold 15 min.

Prior to each analysis, 20 yL (40 j;g) of internal standard was added to 1 mL each sample
extract.   The  internal  standards  were:  l^-dichlorobenzene-d^   naphthalene-ds,
aceiiaphthene-d]0, phenanthrene-d,0, chtysene-d]2, and perylene-d12 at  a  concentration
equivalent to 40 yg/mL. Method blanks analyzed with each run showed no contamination
with target analytes. Each blank was spiked with the pre-sample surrogates and post-
sample surrogates and extracted in the same manner as the samples.

Calibration was performed by analyzing two separate solutions: one containing known
concentrations of the acidic compounds and one containing known concentrations of basic
compounds.   Concentrations were typically 10, 25, 50, 100, and 200 yg/mL with the
50 ug/mL concentration used as the continuing calibration standard.

RESULTS
Recoveries were generally very good, as shown in Table I. The lowest recoveries were
observed with the phenols and amines. Concentration of analytes by KD and nitrogen blow
down caused  the largest losses. The reason for the loss was thought to be evaporation
during nitrogen blow down. No losses were observed due to mixing of the acid and base
mixtures.

The mixing of endrin aldehyde with the other compounds apparently caused this compound
to degrade and it was not observed during analysis.  Oxychlorodane and benzidine were
not tested.

Method detection limits (MDL) were calculated by multiplying the standard deviation of
the results of samples spiked at 10 and 50 yg/mL by 3.1. The results at 50 ygAnL were
about 2-4 times higher than the values at  10 jjg/mL which are shown, in Table I.
Comparison of the MDL with the calculated injection weight for each analyte shows that
the method can easily detect the analytes at the CRQL levels for most compounds.

The percent relative standard deviation values show the reproducibility is good for all
compounds with the exception of 13 analytes. These 13 compounds, especially the amines
and phenols, show analytical problems for water and soil analyses. It was no surprise that
the same type of analytical problems are observed using the Air Toxic SOW.

Stability  studies were performed by analyses after storing the sample refrigerated at 4*C
for 2,4,8,16,32, and 64 days. In most cases, the data show the samples to be stable for
the two month period studied.  These studies are continuing and data wUl be collected at
128 days and  256 days.  Those compounds which showed instability are indicated in Table
I with a Y.
                                      509

-------
                                      TABLE I
                             TARGET COMPOUND LIST
                                                              % Recovery
Compound5

AMINES
Aniline
Benzidine
2-Nitroaniline
3-Nitroaniline
4-Nitroaniline*1
4-ChIoroaniline
p-Biphenylamine
2-Naphthylamine
N-Nitroso-di-n-propylamine*
N-Nitrosodiphenylamine*

CHLOROBENZENES
1,2-Dichlorobenzene*
1,3-Dichlorobenzene*
1,4-Dichlorobenzene*
1,2,4-Trichlorobenzene*
Pentachlorobenzene
Hexachlorobenzene
                      Solna  CRQL CRQLb  MDLC   55d    lle      11
                      Type ng/m3     ag ng/uL   AVE   A^E %RSD>
                         B
                         B
                         B
                         B
                         B
                         B
HEXACf-fLORO COMPOUNDS
Hexachlorobutadiene*          A
Hexachlorocyclopentadiene      A
Hexachloroethane              A
183
 37
B
B
B
B
B
B
B
B
B
B
73
73
73
73

73
183
183


20
20
20
20

20
50
50


5 10
7
127
XY
NOT TESTED
8 87
7 51
12 82
6 24
3
3
6 68
5 81
94
49
77
19


69
85
5
41
46
74
316

6
4

XV
XY
XY
X
X
Y

50
10
3
3
3
2
6
4
60
59
59
70
81
86
60
59
59
69
79
84
10
11
11
7
5
3

37
37

10
10
3
3
8
67
53
62
64
68
62
13
10
8
   *  A Indicates acidic solution and B indicates basic solution.

   b  An injection weight was calculated using a 273 ms sample volume, concentrating the sample to 1
      mL, and injecting 1 uL

      Method detection limit.

      Average of 55 samples taken after 0, 2, 4, 8, 16, 32, and 64 days of storage.

   e  Average % recovery of 11 samples taken with no storage.

      surr means a surrogate compound.

   8  % relative standard deviation of 11 samples with no storage time.

   h  Q is  the qualifier where X indicates compounds for which the method it questionable tnd Y
   i
indicates unstable compounds over the 64 day storage period.

* indicates non-target compound.
                                        510

-------
                                   TABLE I
                           TARGET COMPOUND UST
                                                    	% Recovery
                          Soln  CRQL CRQL   MDL    55    11     11
 rnmoound                liES ng/m3    ng np/t/L   &VE  AVE  %RSD   _g
 PJ5THALATES
 bis(2-Ethylhexyl)phthalate      A    37     10    10   107   102     10
 Dimethylphthalate             A    37     10     3    82    86      2
 Diethylphthalate              A    73     20     5    81    83      4
 Butylbenzylphthalate          A    37     10    11    99    98      9
 di-n-Butylphthalate            A    37     10    10    94    95      7
 di-n-Octylphthalate            A    37     10    22   102   106     21

 ETjiiSS
 bis(2-Chloroethyl)ether        B    37     10     3    54    55     20
 bis(2-Chloroethoxy)methane    B   183     10     3    71    71      9
 bis(2-Chloroisopropyl)ether*    B                  9    66    67      8
 4-Chlorophenyl-phenylether*    B                  6    82    81      5
 4-Bromophenyl-phenylether*    B                  6    90    90      4

 PAHS
 Naphthalene                  B    37     10     2    70    69      8
 2-Methylnaphthalene          B    37     10     1    80    80      5
 Phenanthrene                 B    37     10     4    86    89      4
 Acenaphthene                B    37     10     3    77    79      4
 Acenaphthylene               B    37     10     3    73    76      3
 Anthracene                   B    37     10     4    83    87      4
 Anthracene-dio'Surr                               4    69    65     25
 Benzo(a)anthracene           B    37     10     6    88    88      5
 Benzo(a)pyrene               B    37     10     8    93   101     24
 Benzo(a)pyrene-d,2-surr                           6    93    89     22
 Benzo(b)fluoranthene          B    37     10    14    97   102     22
 Benzo(e)pyrene               B    37     10    15    94    98     22
 Benzo(g,h,i)perylene           B    37     10     8    91    90     22
 Benzo(k)fluoranthene          B    37     10    11    93    97     21
 Chrvsene                     B    37     10     2    83    85      5
 Dibenz(a,h)anthracene         B    37     10     9   104   107     28
 nibenzofuran*                B                  2    83    85      3
Fluoranthene                  B    37     10     5    91    91      5
pluorene                     B    37     10     3    79    79      6
indeno(l,2,3-cd)pyrene        B    37     10     6    98   100     25
SIrene                       B    37     10     6    89    90      8
2-Chloronaphthalene*          B                  2    78    78      4
                                    511

-------
                               TABLE I
                        TARGET COMPOUND LIST
                                                   % Recovery
                        Soln  CRQL  CRQL  MDL   55    11      11
Compound               Type ng/m3    ng ng/fjL  AVE  AVE   %RSD   Jg
                                            4   36    35     22
                                            3   38    34     33    X
                                           11   84    98     21
                                            2   56    56     9
                                            3   63    62     9
                                            6   62    66     6
                                           40  252   280     28    X
                                            7   76    75     6
                                            4   64    64     8
                                            4   54    53     13
                                            7   87    88     5
                                            7   82    83     5
                                           16   76    87     12
                                            7   91    93     5
                                            6  116   106     32    X
                                           22   14    24     58    X
                                            2   16    14     48    X
                                           30   30    51     38    X
                                            3   82    84     7
                                           10   72    80     8
                                            4   83    83     3
                                            2   87    90     6
                                            3   87    85     2
                                            4   86    84     4
                                            4   81    74     4
                                            5   71    61     18
                                            6   81    73     8
                                            8   78    78     10
                                            8   68    65     12
                                            8   62    68     25
                                            7   90   86      9
                                            5   95   91      3
                                            6   98   94      9
                                            5   88   98     10
                                            5   87   92      5
PHENOLS
Phenol
Phenol-ds-surr
Terphenyl-d]4-surr
2-Methylphenol
4-Methylphenol
2-Nitrophenol
4-Nitrophenol
2,4-Dichlorophenol*
2,4-Dimethylphenol
2-Chlorophenol*
2,4,5-Trichlorophenol
2,4,6-Trichlorophenol
Pentachlorophenol
4-Chloro-3-methylphenol
Tribromophenol-surr
2,4-Dinitrophenol
2-Fluorophenol-surr
4,6-Dinitro-2-methylphenol
o-Phenylphenol
PCBs
2-Fluorobiphenyl-surr
2-Chlorobiphenyl
2,3-Dichlorobiphenyl
2,4,5-Trichlorobiphenyl
2,2',4,6-Cl4-biphenyl
2>2',3,4,5'-Cls-biphenyl
2,2',4,4',5,6'-Cl6-biphenyl
2,2',3,4',5,6,6'-Cl7-biphenyl
2J2',3,3',4,5',6,6'-Cl8-biphenyl
2,2',3,3',4,4',5,6,6'-Cl9-biphenyl
Decachlorobiphenyl
CHLORINATED PESTICIDES
4,4'-DDD
4,4'-DDE
4,4'-DDT
Aldrin
alpha-BHC

A


A
A
A
A
A
A
A
A
A
A
A
A
A
A
A
A


A
A
A
A
A
A
A
A
A
A

B
B
B
B
B

183


183
183
73
183

73

183
183
183
183

73

183
183


146
146
146
146
293
146
146
293
366
366

146
146
146
146
146

50


50
50
20
50

20

50
50
50
50

20

50
50


40
40
40
40
80
40
40
80
100
100

40
40
40
40
40
                                512

-------
                                  TABLE I
                          TARGET COMPOUND LIST
                                                          Recovery
 alpha-Chlordane
 Bendiocarb
 beta-BHC*
 cis/trans - Permethrin
 delta-BHC*
 Dichlorvos (DDVP)
 Dicofol
 Dieldrin
 Folpet
 gaimna-BHC
 gamma-Chlordane
 Heptachlor
 Heptachlor Epoxide
 Isophorone
 Methoxychlor
 Oxychlordane
 propoxur (BAYGON)
 Resmethrin
 Ronnel

 pjfffiR PESTICIDES
 Aldicarb
 Captan
 Chlorothalonil
 Chlorpyrifos
 DactKal (DCPA)
 Diazinon
 Endosulfan I
 Endosulfan II
 Endosulfan Sulfate*
 Endrin
 Endrin Aldehyde
 Endrin Ketone
 Mirex
 Parathion
                          I>£g ng/m3    Eg ng/^L  AVE  AVE  %RSD  _g
Nitrobenzene
Nitrobenzene-ds-surr
2 4-Dinitrotoluene
B
A
B
A
B
A
A
B
A
B
A
B
B
A
B
A
A
A
A
A
A
B
A
A
A
B
B
B
B
B
B

A
A
A
146
183

183

183
183
146
183
146
146
146
146
37
146
183
183
183
183
146
183
183
183
183
183
37
37

37
37
183
B
146
37
37
40
50

50

50
50
40
50
40
40
40
40
10
40
50
50
50
50
40
50
50
50
50
50
10
10

10
10
50
146
40
10
10
IDL
'ML
5
4
6
2
5
5
7
5
4
4
5
7
6
2
7
55
AVE
87
91
83
74
89
66
72
91
93
92
90
93
90
75
93
11
AVE
75
100
86
77
93
87
79
101
94
94
74
98
87
75
96
11
%RSD
17
6
4
12
8
4
13
12
7
8
16
5
15
7
5
NOT TESTED
9
8
5
8
3
4
4
4
2
6
7
8
9

16
40
8
10
10
4
86
77
88
12
91
70
96
92
82
107
94
96
109

47
4
106
64
83
75
93
73
94
18
101
78
95
91
86
108
93
96
107

48
91
106
65
87
85
6
7
3
161
11
7
3
5
6
8
8
7
7
157
22
95
8
10
33
9
X

13
                                   513

-------
                                   TABLE I
                           TARGET COMPOUND LIST
                                                          % Recovery
                           Soln  CRQL  CRQL   MDL   55   11      11
Compound                Type ng/m3     ng ng/uL  AVE  AVE   %RSD

2,6-Dinitrotoluene*            A                    3   84   92       4
4-Nitrodiphenyl               A    183     50      6   96  100       6
OTHER COMPOUNDS
Acetophenone                B     37     10      8   65   66       8
BenzoicAdd*                A                  60  146  107      36
Benzyl Alcohol                A     37     10    11   53   55      12
CONCLUSIONS
The Air Toxics SOW has been tested on 132 semivolatile compounds. Ninety-eight target
compounds, 20 non-target compounds, six internal standards, and eight surrogate standards
were tested. Included in these compounds were:

                             COMPOUNDS TESTED

                  Chlorinated Pesticides               27
                  Other Pesticides                    15
                  Chlorinated Benzenes                6
                  Phenols                           20
                  Amines                           11
                  Ethers                             5
                  Esters                              6
                  Poly Aromatic Hydrocarbons         22
                  PCBs                             10

The method was satisfactory for 125 compounds and questionable or unsatisfactory for 13
compounds. The problem compounds were: benzoic acid, 2,4-dinitrophenol, 4-nitrophenol,
4,6-dinitro-2-methylphenol,   aniline,   4-chloroaniline,  3-nitroaniline,  4-nitroaniUne,
2-naphthylamine, p-biphenylamine, endrin aldehyde, aldicarb, and endrin aldehyde. Seven
compounds showed instability over time during the  tests: aniline, 4-chloroaniline,
3-nitroaniline,  4-nitroaniline, N-nitrosodiphenylamine, hexachlorocyclopentadiene, and
propoxur.  Endrin aldehyde apparently reacted in solution and decomposed in the presence
of the other compounds.

ACKNOWLEDGEMENTS
The authors acknowledge the support of the Rebecca Colgate who prepared the samples
for analysis. The United  States Environmental Protection Agency has funded this project
under Contract 68-D-90041,  Russ  McCallister, Task Monitor, and Jim Barron, Project
Officer,  Analytical  Operations Branch,  Office of Emergency and Remedial Response.
Although the PES production and distribution is funded by the EPA, this paper has not
                                     514

-------
been subjected to Agency review and therefore does not necessarily reflect the views of the
Agency.   No official endorsement should be inferred.   Mention of trade  names  or
commercial products does not constitute endorsement or recommendation for use.

REFERENCES
1. R. McCallister, E.I. Boulos, W.T. Winbeny, and L. Foreland, "Development of a 'Stateraent-of-Work (SOW)
for  the Analysis of Air Toxics At Super-fund Sites'  as Part of the Contract Laboratory Program (CLP)*,
frocMdina of the 1990 EPA/A&WMA International Symposium - Measurement of Toxic and Related Air
pollutants. May 1990, Raleigh, NC, p336.

2. J.C. Chuang, S. W. Hannan, and N.K. Wilson, "Field Comparison of Polyurethane Foam and XAD-2 Resin
for Air Sampling for Polynuclear Aromatic Hydrocarbons', Environ. Sci. Technol.. Vol. 21, No. 8,1987, p798.

3. R.M. Riggins, Method TO10 - "Method for the Determination of Organochlorine Pesticides in ambient Air
using Low Volume Polyurethane Foam (PUF) Sampling with Gas Chromatography/Electron Capture Detector
(GC/ECD)", Compendium of Methods for the Determination of Toxic Organic Compounds in Apbient Air.
EPA-600/4-84-041, Apr. 1984.

4 T. Bidleman,  M.T. Zaranski, and G.W. Patton, "Development  of Collection Methods for Semivolatile
Organic Compounds in Ambient Air", EPA/600/4-87/042 fl»B88-140272-l. Dec 1987.

5. T.F. Bidleman, G.W. Patton, and L. McConnell, "Development of Collection Methods for Chlorophenols in
Ambient Air", Final Report, Agreement No.  P-7953(1301)-1146,  Battelle Memorial Institute, Columbus
Division, Nov. 1988.

6. R.M. Riggins, Method TO4  - "Method for the  Determination of Organochlorine Pesticides and
polychlorinated biphenyls in ambient Air*, Compendium of Methods for the Determit"^ rf
           in Ambient Air. EPA-600/4-84-041. Apr. 1984.
                                           515

-------
               THE EVOLUTION OF THE NATIONAL
                      DRY DEPOSITION NETWORK
                   QUALITY ASSURANCE PROGRAM
                                       Selma S. IsU
                                    Cheryl A. Boehnke
                                  Charles G. Manos, Jr.
                           Environmental Science and Engineering
                                      P.O. Box 1703
                                    Gainesville, Florida
 ABSTRACT
    The EPA National Dry Deposition Network (NDDN) includes fifty sites throughout the United
 States that provide continuous ozone and meteorological data.  Filter packs are used at each site to
 determine atmospheric concentrations of dry deposition constituents. All continuous data are transmitted
 to and managed at ESE's Data Management Center (DMC) in Gainesville, Florida.  Filter packs are
 exchanged weekly and exposed filter packs shipped to ESE's Gainesville laboratory for analyses.  An
 increase in data volume and usage over time has necessitated a Quality Assurance Program with the
 flexibility to evolve with the project. A dynamic QA program also provides the opportunity for constant
 improvement by modification of existing audits to increase effectiveness, and by shifting focus to more
 critical areas of the project through initiation of new audits.  This paper describes the evolution of the
 NDDN QA program by discussion of modifications to existing audits and reasons for implementation
 of new audits.

 INTRODUCTION
    The National  Dry  Deposition Network (NDDN) was  established in 1987 for the purpose  of
 estimating dry  deposition fluxes and spatial and temporal trends of various acidic air pollutants at
 designated locations throughout the continental United States. Meteorological data, in conjunction with
 land use and site characteristic data, are used to estimate deposition velocities. Dry deposition rates are
 then inferred from measured concentrations of pollutants  and the estimated deposition velocities.
 Accompanying  wet deposition rates at selected sites are also calculated based on precipitation chemistry
 and rainfall amount.
    Fifty NDDN sites are currently operational with 41 located in the eastern half of the United States,
 and 9 located in the western half.  Five of the sites are collocated and provide data on overall precision
 of the dry deposition estimates and related measurements.  Continuous ozone,  wind speed (vector and
 scalar), wind direction, standard deviation of wind direction, temperature, delta temperature, relative
 humidity, solar radiation, rain, surface wetness, and filter pack flow are measured at each site. All
 continuous data are reported as hourly averages consisting of a minimum of 9 valid S minute averages
per hour. Weekly concentrations of sulfur dioxide (SO;), paniculate sulfate (SOj'), paniculate nitrate
 (NO;), paniculate ammonium (NH J), and nitric acid (HNO3) are measured by emplacement of a 3-stage
 filter pack operated at a constant rate of flow.
    Weekly precipitation samples are collected at sites  located  more than  50 Km from  National
Atmospheric Deposition  Program/National Trends Network (NADP/NTN) or other  federally funded
precipitation monitors. Wet deposition samples are analyzed for pH, conductivity, acidity, NO$, SOj,
                                           516

-------
 NHJ, chloride (Cl% nitrite (NC$), calcium (Ca2+), magnesium (Mg2t), sodium (Na+), and potassium
 (K+).
     The purpose of the NDDN QA program is to ensure the precision and accuracy of final results.
 To accomplish this goal, it is necessary to audit both the final results and all intermediary steps involved
 in the generation of final data reported to the client. Since certain operations are more critical than
 others to the production of precise,  accurate data, a QA program must focus more effort on these
 critical areas. This paper describes the initial NDDN QA program and discusses how the program has
 evolved  to concentrate effort on critical areas to improve its effectiveness.

 THE ORIGINAL QA PROGRAM
     The initial NDDN QA audits were classified into two categories:  (1) laboratory operations and data
 audits and (2) field operations and data audits. The following is a brief description of the initial audits
 and, when applicable, the deficiencies of each audit.

 Laboratory Audits
          Acceptance Audit. The filter acceptance audit reviewed the acceptance test results for the
Teflon*, nylon, and Whatman filters used in the filter packs to ensure that only batches of filters which
met the acceptance criteria were used for sample collection.
           of Custody Audit.  Chain of custody forms for selected sites for the entire quarter were
reviewed to determine completeness of the shipping, receiving and installation dates for filter packs.

    jypceabilitv Audit.  This audit followed sample and QC data from the point of measurement via
ion chromatograph (1C) analysis into the Chemical  Laboratory  Analysis  and Scheduling System
(CLASS), an  inhouse data management system, through calculation of analyte concentrations.  Five
percent of all  samples collected during a quarter were  randomly selected for audit purposes resulting
in the audit of virtually 100% of all filter  pack data batches. A data batch consists of results for all
samples (including QC samples) analyzed  during an 1C  run.  The error rate for data transfers into
CLASS was zero.  Differences in concentration between raw data obtained from 1C analysis and data
jn CLASS were frequently noted. All differences, however,  were insignificant with no effect on the
final concentrations and were due to either rounding differences between the two programs, or to the
CLASS program forcing the calibration curve through  zero.  The most  significant findings from this
audit  over time were minor documentation errors or lack of specific documentation.

Field Audits
                Audit.  This audit traced continuous measurement data for all sites for 5 randomly
selected days during a quarter from their point of origin in the field through downloading via modem,
ingestion, and validation procedures to the final data contained in the field database. Although the audit
covered the entire data management process,  focus was mainly on data transmission and ingestion.  A
major component of this audit involved direct comparison of data obtained via modem (primary data
source) with data contained on site printouts and site diskettes (secondary data sources). An extremely
small percentage of electronic transmission errors  (0.01 %) were detected in data acquired by modem.
    Within a short time, it was evident that the majority of the original audits were focusing on areas,
such as electronic data transmissions, that were verified to be relatively problem free while other aspects
Of the  project were either not addressed or addressed inadequately.  After a thorough review of the
original QA program by the Project Manager, the QA Division, the EPA Project and QA Officers, am
'mproved comprehensive NDDN audit system was established. Both the laboratory and field traceabilit;-
                                             517

-------
 audits were modified, and additional audits focusing on more critical areas with greater potential for
 error were implemented. The current QA program is dynamic with continuing modifications to improve
 existing audits, and initiation of new audits as necessary.

 THE CURRENT QA PROGRAM
     All but one of the present NDDN audits are divided into the two categories of laboratory operations
 and data, and field operations and data.   The one exception, the flow verification audit, reviews a
 combination of both laboratory and field data.  The following is a brief description of the component
 audits in each category.

 Laboratory Audits

     Filter Acceptance and Chain of Custody Audits,  These audits have not been revised and are
 performed as previously described.

     Traceabilitv Audit. This audit is essentially the same as the original audit except that the number
 of batches audited has been reduced. Twenty percent of all batches analyzed per quarter are audited
 instead of 5 % of all samples.  This revision eliminates excess review of batches while still ensuring
 that data transfers and manipulations are conducted properly.  Also, acceptance criteria have been
 established for evaluating differences that may arise in concentrations when transferring data into the
 CLASS system.  Use of these criteria eliminate review of insignificant differences in concentrations.

     Quality Control Chart Audit. QC charts are produced quarterly by the Chemistry division.  These
 chans present the results of all QC data for the quarter for each analyte for both dry and wet deposition
 analyses. The audit consists of review of the charts for identification of outliers.  Explanations of how
 the outliers were handled are evaluated for thoroughness and acceptability.

    Life History Audit.  A life history audit is conducted once or twice yearly, and traces samples from
 a selected  week within a quarter  from media testing and preparation through chemical analysis to
 inclusion into the validated database.  Although emphasis is placed on performance of the component
 procedures, pertinent systems audits are also conducted.  The format of a life history is flexible so that
 the auditor can concentrate on problem areas  and/or expend effort  on the more important aspects of
 laboratory operations that may not have been covered by the previous audits.

 Field Audits

   Field Calibrator Audit.  Correct calibration of all sensors  and equipment such  the mass flow
controllers of the filter packs is the first critical process in the NDDN project. If sensors and equipment
are not calibrated properly,  all data collected afterwards will  be affected.   Although  an  external
performance audit is conducted at all sites annually, an internal systems and performance audit of all
calibration activities has also been implemented. A different site and  calibrator is audited each quarter.
Because  of the importance of the calibration procedure, its documentation, and  maintaining proper
operation of instrumentation, the following  two audits have also been implemented.
   Calibration Pata Audit. Twenty percent of all calibration files are audited each quarter. The audit
consists of a review of all calibration data including calibration results, summaries, and the pre and post
certification results.
                                              518

-------
        Fgilyre Audit. The QC failure audit is a review of all reported problems with the sensors and
 equipment at the sites, and the actions taken to resolve  them.  Problems not addressed in a timely
 fashion are investigated, as well as the validity of corrective actions.

    Traeeabilitv Audit. This audit has evolved from the review of all data for 5 randomly selected days
 during a quarter to the review of selected monthly batches. Field data are validated in monthly batches
 and five percent of all batches per quarter are audited.  Half of the audit batches are selected randomly,
 and the remaining half are selected from batches requiring a high degree of human interaction.  Each
 monthly data batch is accompanied by a Continuous Data Review Form (CDRF) which documents all
 changes made to the database during the  validation process.  Each transaction documented on the
 selected CDRFs is verified by review of the corresponding  database.  Undocumented or inadvertent
 changes to the database are detected by correlating data source flags with CDRF entries. Data source
 flags indicate the mode of entry for each datum into the database.  A point by point scan of the audit
 data is also conducted in order to detect inconsistent or suspect values that have not been flagged. In
 addition, instrument/sensor problem reports, external and mail-out audit results are reviewed to verify
 that this information has been addressed during validation.
    The above stated modifications to this audit eliminate point by  point comparison of  data from
 different sources.  The accuracy of the electronic transmission procedure is still verified by comparison
 of the daily averages (obtained from  the primary vs. secondary  sources) for the various parameters.
 The validation process is of critical importance in the submittal of accurate final results.  Validation also
 requires a significant amount of human interaction with the database such as manual entry,  updates to
 database and decisions on data quality. Since these interactions are the most common sources of error
 as  well, the modifications ensure that the majority  of  effort is  now  focused on review of these
 procedures.  Overall conformance to standard operating procedures is also monitored.

 Combination Field and Laboratory  Data Audit
          Verification Audit. This audit reviews both field flow data gathered at the sites and validated
at the DMC, and atmospheric concentration data (microgram/m3 data) calculated in the laboratory after
analysis of filters for the specified analytes (microgram/filter data).  The audit consists of three parts:
(1) All manually entered field data such as filter pack on/off dates and times are compared with the
actual data recorded on the field forms. Because manual entry errors at this stage can affect calculation
of final results, all  entries are audited, (2) The total hours of operation for a filter pack as well as the
valid hours of operation and the average weekly flow are recalculated for randomly selected audit sites
and weeks, and  (3) The volume of air sampled and the atmospheric concentrations of analytes are
recalculated via an independent program.   The flow verification audit is a final step in  ensuring the
accuracy of the results presented to the EPA.

CONCLUSION
    The existing  NDDN QA program is a modification and an  expansion of the QA program initiated
at the onset of the project.  The program has undergone a series of  changes over time in order to be
more effective in ensuring  the submittal of accurate results.  The program  continues  to evolve as
information gathered from current audits are incorporated to improve the system.  A quality assurance
program must be a dynamic process to be a successful program.
                                             519

-------
           CUSTOMER/SUPPLIER ACCOUNTABILITY
                 AND  QUALITY ASSURANCE (QA)
                    PROGRAM IMPLEMENTATION


                                  Ronald K. Patterson
                               Quality Assurance Manager
                Atmospheric Research and Exposure Assessment Laboratory
                          U,S. Environmental Protection Agency
                      Research Triangle Park, North Carolina 27711

 ABSTRACT
       Quality assurance (QA) and quality control (QC) are the basic components  of a QA
 program, which is a  fundamental quality management tool.  The quality of outputs and services
 strongly depends on the caliber of the communications between the "customer" and the "supplier".
 A clear understanding of customer needs and expectations is essential to selecting and applying
 suitable QA and QC. Planning, implementing, and assessing all play a major part in the quality of
 final outputs.  A clear understanding of the customer/supplier relationship and the functional roles
 played by each is essential  to a successful  QA program.  This paper identifies, clarifies, and
 simplifies the  quality management responsibilities  of the customer  and the supplier.  The ideas
 presented are applicable in all work environments, including research and development (R&D).

 INTRODUCTION
      The  pursuit to achieve products and services that are of high  quality has gained much
 recognition over the  last two decades; and more recently, the importance of quality management
 has received significant attention in the workforce.  A solid quality assurance (QA) program is a
 fundamental quality management tool. The purpose of a QA program is to prevent problems that
 could threaten the quality of the  work or work products generated for  a  project; to provide
 mechanisms for corrective action; and to produce work products that meet or exceed the needs and
 expectations of the customer.  A QA program consists of two components: QA and quality control
 (QC).  Knowing who is responsible for QA and who is responsible for QC is often not clear,
 especially in the research and development (R&D) field. One way to look at each component of
 this type of program is to consider QA as a management function and QC as a technical function.

      The  relationship between the customer and the supplier, and the roles they play, is very
 important to a successful QA program.  The customer is responsible  for project QA. and the
supplier is responsible for project QC.  The concept of customer  and supplier is not used in the
 U.S. Environmental Protection Agency (EPA); however, the concept is helpful when defining the
 functional roles and responsibilities of key individuals involved in a QA program.  The quality of
 final outputs depends greatly on the frequency and effectiveness of the communications between
 the customer and the  supplier.

 PROJECT PLANNING
      Because the customer's responsibility is to  provide QA of all products and services,  it
becomes necessary to formulate a plan for implementing each project. Project planning, then, is
                                        520

-------
 ^ QA function.  At a minimum, the customer must communicate the following to the supplier in
 a documented form:
              Customer identification
              Customer expectations of quality
              Project funding
              Project objectives
              Intended use of the project output
              Delivery requirements for the project output
         •    Acceptance criteria for the project output
       The criteria for accepting project outputs are very important.  These criteria should be used
 to evaluate the design proposal submitted for approval by the supplier. The agreed-upon criteria
 will be used to assess the ongoing work and the final product.  Each of the above represents a
 customer input specification or  requirement that the supplier must address when designing the
 project.

 Project Assessment and Corrective Action
       The customer is responsible for project management, which includes keeping abreast of all
 project activities (assessment)  and overseeing and resolving problematic areas (corrective action).
 project assessment and project corrective action,  then, are QA functions.  The customer should
 address, as part of the planning documentation, intentions for project assessments, based on the
 "acceptance criteria for the project output" previously mentioned.  Plans  for assessing projects
 should include (1) a schedule  of anticipated customer audits, (2) peer reviews, and (3) site visits.
 The customer must be committed to giving timely feedback to the supplier and must be prepared
 to take corrective  action, when necessary.

 Project Design
       The supplier is responsible for designing the project. Project design, then, is a QC function.
 The supplier must base the project design on the specifications and  requirements documented by
 the customer. The design prepared by the supplier must address, at a minimum, the following:
         •   The question,  problem, or hypothesis
         •   Systems requirements
         •   Systems output requirements
         •   Training, facilities, site, and safety requirements
         «   Implementation, reporting, and delivery schedules

 PROJECT IMPLEMENTATION
       The supplier is responsible for implementing the project.  Project implementation, then, is
 ^nr function. The supplier must address the following under project implementation:
         •   Sampling approach and sampling standard operating procedures (SOPs)
         •   Analysis approach and  analysis SOPs
         •   Data acquisition approach and data acquisition SOPs
         *   Data processing  approach and data processing SOPs
         *   Data validation approach and data validation SOPs
       Some of the more typical SOPs involve:  shipping/handling, custody, standards preparation,
calibration, QC checks, corrective action, and acceptance testing. Some organizations use protocols;
and in such cases, the customer may wish to require the supplier to define the differences between
a protocol and an  SOP.
                                           521

-------
 Systems Assessment and Corrective Action
       The supplier is responsible for assessing project systems. Systems* assessment and systems
 corrective action, then, are QC functions. These types of assessments are necessary to determine
 whether systems are in (or out) of control. Systems assessments should be performed on a frequent
 schedule to ensure timely corrective action, when warranted.  Corrective action by  the supplier
 focuses on the systems operating under the project. This focus is much more narrow than that of
 the customer, who must give consideration to the entire project.

 PRIMARY CHANNELS OF COMMUNICATION
       In  the EPA, the  customer communicates  through the  Statement  of Work or Work
 Assignment description.   The supplier communicates through the QA Project  Plan  (QAPP).
 Actually, the QAPP is the project QC plan. This point is often missed. The QAPP must address
 the three areas of QC discussed  above:
        *    Project design
        «    Project implementation
        *    Systems assessment and corrective action
       The QAPP must be based on the needs and expectations of the customer.  The customer
 and supplier must reach an understanding regarding the requirements and the delivery capabilities
 of the supplier.  This is an iterative process. Until there is agreement and approval is granted by
 the customer, no work should be initiated.

       The customer is required to review and evaluate all project outputs delivered by the supplier.
 This may, in turn, warrant changes in  the customer's project specifications, requirements, and
 expectations. These changes,  which are usual, must  be reflected in the QAPP.  The feedback
 resulting from the assessments should  be  on a frequent basis to avoid major surprises and to
 prevent problems.

 THE RESEARCH ENVIRONMENT APPROACH
       In the environment where basic  and applied research are the organization's  mission, the
 customer/supplier relationship  is  not as  well defined.  The problem is exacerbated when a single
 individual is appointed to oversee both functions. However, this is not a problem because the roles
 and responsibilities of the customer and supplier, discussed above, will not drastically change in this
 situation.

       Figure 1 describes the QA Program Implementation Process and depicts the key customer/
supplier roles and responsibilities. When the customer and supplier responsibilities reside with the
same  individual,  that individual must document and  provide all the applicable information (as
 required from both the customer and the supplier) to a second party  (normally the  supervisor).
The required information should be communicated  in a  research proposal.  However, some
organizations may prefer a separate proposal document. In either case, the supervisor will assume
the role of "surrogate customer" and will indicate (by  signature) the acceptance of the proposed
research as a planned output of the organization.

SUMMARY
       An organization's QA program is a management tool.  The relationships described here
identify and clarify the roles and responsibilities of the customer and supplier, whose  roles are to
deliver quality goods and services (outputs).  For any project, the QA program must be value-
added. A good QA program should be designed to prevent quality-threatening problems. A good
QA program should help the customer manage the quality of the work and the work products and
                                          522

-------
should help the supplier meet or exceed customer needs and expectations.  When the supplier is
able to bring a cost effective, innovative approach (and/or unique expertise/facilities) to a project,
that approach could result in improvements that exceed the customer's expectations.  Both the
customer and the supplier should experience a "win-win" working relationship. These goals are just
as valid in a research environment, as they would be in a manufacturing or servicing situation.
                                           523

-------
                               CUSTOMER
                                    1
                               Statement of Work
                                    or
                               Work Assignment
                                    JL
        Project Planning
*.#£,  ctT^
                  oJtput    Output
                        Acceptance
                          Criteria
                                t
                                 SUPPUER
                                 Work Plan or
                              Research Proposal
                                     t
                                QA Project Plan
                                     t
              (QC)

              Project
              Design
                                   (QC)

                                   Project
                               Implementation
 Output
         Sampling
 SOPs
  or
Protocols
           pling      Analysi
                                                          (QA)

                                                   Project Assessment
                                                      .
                                                                   JVdaet
                                                                 t
                       (QC)


                     Systems
                   Assessment

terns Scr
irements Re
1
6
-------
            Session 12
SS Canister Cleaning and Techniques
     R.K.M. Jayanty,  Chairman

-------
                A TECHNIQUE FOR CLEANING SUMMA* CANISTERS
                  AND THE SUBSEQUENT EFFECTS OF STORAGE
                            ON CANISTER CLEANLINESS
            Carl L Shaulis, David A. Brymer, Larry D. Ogle, and Barry E. Lands
                                  Radian Corporation
                                  8501 MoPac Blvd.
                                   P.O. Box 201088
                               Austin, Texas 78720-1088

ABSTRACT
      SUMMA* polished canisters are frequently used to collect ambient air samples for the
analysis of volatile organic compounds (VOCs) by GC/Multidetector (GC/MD) or GC/MS. The
compounds of interest are often in the high parts per trillion volume to low parts per billion volume
  »bV? ^nccntration range. At these concentrations, canister cleanliness at the time of sample
collection is of paramount importance.
      This paper describes the hardware and methodology used to clean canisters to the low ppbV
•evel, the instrumentation needed to verify canister cleanliness on a production basis, and the effect
   storage on canister cleanliness prior to deployment into the  field. Several sets of cleaned
canisters, stored under various conditions, were tested for background contamination over a period
°ftime. The study variables included canister pressure, storage gas (nitrogen or air), and humidity.
1 «u study shows that humidity over  time is the single largest source of variability in canister
cleanliness.

INTRODUCTION
      SUMMA» polished  canisters are a popular and  useful  whole air sampling device for
collecting ambient air samples to  determine volatile organic  compound (VOQ concentrations.
p5* Campling devices  must be cleaned to acceptable levels between sampling episodes.  The
^mpendium Method TCM41 stipulates a cleaning  criteria of 02 ppbV for each target compound
fad the USEPA Urban Air Toxics Monitoring Program, which uses Compendium Method TO-123,
048 an acceptance criteria of <30 ppbV-C.'  Several papers have demonstrated the use of vacuum
    air or nitrogen purge based systems to adequately clean canisters to these levels.4  However,
    documentation exists on the  shelf life of cleaned canisters under varying conditions.  This
    r describes a high volume cleaning and blanking operation and the effect of canister storage
   canister cleanliness.

             AND TECHNIQUES
      The canisters are cleaned  by using Ultra High Purity (UHP) Nj (humidified and dry),
     n, and heat. The automated cleaning system consists of:  two NAPCO 603 convection oven,
     l 2 and 3-way 24V non-latching valves, one 2-valve 15 L canister, equipped with a dip tube
       d with 2 L of organic free water, one oilless vacuum pump, one two-stage (oil) vacuum
wx°& one liquid nitrogen dewar,  and one Ashcroft (-30" Hg to +30 psig) test gauge. Various
r*™ponents are controlled  by a program on a personal computer and a 24 position I/O relay
••oard. After the canisters are attached to the appropriate tubing inside the ovens, the computer
    Ini lA«k^1^ *.•	      .   .*    •*     »   f   • „*__._ .I __	A*-__^ __.*.^«BWA l^nlr *«l«A4fcVc frA IVtmrA
                                        527

-------
 purged with humid N2, isolated for a period of time to "steam clean", purged with humid N2 again,
 evacuated, pressurized with dry Nj, and after the ovens have cooled to near room temperature the
 canister valves are closed. The cleaning system can simultaneously clean either six 15 L or up to
 twelve 6 L or 2,8 L canisters during one 3.5 hour cleaning cycle.
       Each canister is pressurized to 30 ±3 psig with dry UHP nitrogen and analyzed for non-
 methane  organic compound (NMOC) concentration.  The cleaned canisters are analyzed in
 accordance with  USEPA Method TO-12 methodology using  a Shimadzu  14-A GC capable of
 simultaneously blanking four canisters. A load volume of one liter on this blanking system provides
 instrument detection limits of 0.3 ppbV-C.  This system is capable of blanking over 250 cans in a
 40 hour work week.  Two percent  of the canisters blanked are subsequently analyzed  using a
 GC/MD system to obtain full  speciation  data.  This analysis provides confirmation of the TO-12
 results and provides speciated information to assess compliance with compendium method TO-14
 blanking criteria.
       The canisters are then stored under positive pressure using dry UHP nitrogen until the day
 prior to field deployment. The canisters are then evacuated, vacuum leak tested, and shipped to
 the field. A shelf life of 30 days was selected for canister storage.  After the 30 day period,  the
 canisters are recertified as clean (NMOC <3.0 ppbV-C) prior to field deployment.

 EXPERIMENTAL DESIGN
       This study was designed to: 1) evaluate the described canister cleaning and blanking system
 for effectiveness, 2) evaluate the 30 day shelf life (for cleaned canisters) for reasonableness, and
 3) determine the effects of various storage conditions on canister cleanliness. All canisters used
 in this study  were taken from  a large canister  pool, which had historically been used to  collect
 ambient air samples.  The canisters  had been cleaned according to current protocol, filled to 30
 psig with dry UHP N2,  and blanked to a level of < 2.5 ppbV-C The mean of the initial blanking
 concentrations was 0.3 ppbV-C, assuming 0.00 ppbV-C for all non-detects (NDs).  Twelve test
 groups of six canisters each were then set to the test conditions listed in Table I. Thus, a full
 factorial design was established using  diluent gas (N2 or air), humidity (0 or 70%), and canister
 storage pressure (-14, 0, or 30 psig) as the variables. Time was a continuous variable with at least
 2 measurements over a minimum of 20 days. A value of 0.0 ppbV-C was used for all NDs data
 during the statistical data interpretation.
       To evaluate the  reasonableness of the 30 day shelf life,  the test group representing normal
 storage conditions (IP) was analyzed at 0,30, and 60 days after being brought to test conditions.
 Most of the other test groups were analyzed at 0,15, and 30 days.  The canisters stored at 0 and -
 14 psig were  brought  to  positive pressure with dry N2 or air (1-8 hrs) prior to analysis  and
 subsequently returned to their  original test conditions after analysis.

 RESULTS AND CONCLUSIONS
      The performance of the instrumentation used for cleaning and blanking SUMMA* canisters
 was assessed by reviewing two months worth of historical NMOC data.  The mean measured
 NMOC concentration for routine cleaning blanks over a two month  period was .09 ppbV-C. Over
 98% (773/783) of the canisters during this time period met the 3.0 ppbV-C acceptance criteria.
      Table II lists the mean,  standard deviation, and range for each of the  twelve test groups.
These data show that the test groups which used evacuated canisters and a humid diluent gas have
somewhat higher measured concentrations.  An Analysis of Covariance (ANCOVA) analysis was
performed to statistically evaluate the effects of each study variable on canister cleanliness.  Time
                                           528

-------
and state (humid or dry) were determined to influence canister cleanliness more than the other
factors as shown in Table III.  A Tukey's Studentized Range (TSR) test confirmed that the mean
concentration under humid storage conditions, 7.2 ppbV-C, was significantly greater than the mean
concentrations under dry conditions, 0.5 ppbV-C.  Several of the test canisters using a humid air
or nitrogen matrix were further analyzed by a GC/Multidetector system to verify that the measured
concentrations were a function of canister cleanliness and not system contamination and to identify
the contaminants. The majority of the measured contaminant concentration was represented by
acetone, n-propanol,  and 1-butanol.
      Only the data from 0% relative humidity (RH) test groups were further evaluated to test
for the effect of canister pressure,  diluent gas, and  time  on canister cleanliness.   A second
ANCOVA analysis using the dry data showed  that canister pressure is a significant variable in the
determination of canister cleanliness.  Tukey's Studentized  Range test confirmed that canisters
stored under a vacuum (mean concentration = 9.0 ppbV-C)  were significantly different (alpha =
0 05) than those canisters stored at ambient (mean concentration =1.0 ppbV-C) or positive (mean
concentration =  2.4 ppbV-C) pressure. No statistically significant differences were found between
using air or N2 as the diluent  gas or with storage time.
      The  measured concentrations of test group IP,  reflecting routine storage  conditions,
demonstrate the reasonableness of a 30 day shelf life for cleaned canisters (Table IV).  The mean
concentration for test group IP was 0.4 ppbV-C at time 0 and 0.3 ppbV-C after the 30 day storage
period.  These data show that a 30 day shelf life for cleaned canisters is appropriate when stored
at 0% RH in a clean N2 or air matrix under ambient or positive pressure. The data also show that
the humidity of the diluent gas and canister storage pressure are the two most significant variables
affecting canister cleanliness.

RECOMMENDATIONS
      Canister cleaning techniques must continue to be improved in order to increase canister
cleanliness under a variety of storage conditions (including humid conditions).  Each cleaning
technique and storage matrix also needs to  be evaluated  for effects on sample recovery and
precision. This is especially important for polar compounds or other compounds routinely observed
in cleaning blanks.

REFERENCES
1  Compendium Method TO-14, "The Determination of Volatile Organic Compounds (VOCs) in
   Ambient Air Using Summa* Passivated Canister Sampling and Gas Chromatographic Analysis",
   U.S. EPA Office of Research and Development, May 1988.

2. Compendium Method TO-12, "Determination of Non-methane Organic Compounds (NMOC)
   in Ambient Air Using Cryogenic Pre-concentration and Direct Flame lonization Detection
   (PDFID)," Quality Assurance Division,  Environmental Monitoring Systems Laboratory, U.S.
   Environmental Protection  Agency, Research Triangle Park, May 1988.

3  T.L- Sampson, Radian Corporation, Research Triangle Park, NC, personal communication,
   1992.

4  L.D.  Ogle, "Comparison  of Cleaning Techniques  for  SUMMA® Polished  Stainless  Steel
   Canisters" in Proceedings of the 1991 U.S. EPA/A&WMA International Symposium.  Air &
   Waste Management Association,  Pittsburgh, 1991, pp. 519-525.
                                          529

-------
                              TABLE I: EXPERIMENTAL DESIGN
TEST GROUP
1 (E)vacuated
1 (A)mbient
1 (P)ositive
2 (E)vacuated
2 (A)mbient
2 (P)ositivc
3 (E)vacuated
3 (A)mbient
3 (P)ositive
4 (E)vacuated
4 (A)mbient
4 (P)ositive
PRESSURE
(psig)
-14
0
30
-14
0
30
-14
0
30
-14
0
30
DILUENT GAS
N2
N2
N2
AIR
AIR
AIR
N2
N2
N2
AIR
AIR
AIR
HUMIDITY
(%RH)
0
0
0
0
0
0
70
70
70
70
70
70
ANALYSES *
(DAYS)
0, 40, 70
0, 50, 80
0, 30, 60
0,20
0,20
0,20
0, 15, 30
0, 15, 30
0, 15, 30
0, 15, 30
0, 15, 30
0, 15, 30
• The experimental desifn orifuaUy called for 0. 30. and 60 day analyse! for test group #1 and a 0, 15, and 30 day analytical scheme lot all other
teat troupt. The listed analytical design represents the actual measurement dates (to tbe nearest multiple of 5) due to scheduling difficulties.
                        TABLE II: ANALYTICAL RESULTS IN PPBV-C
TEST GROUP
1 Evacuated
1 Ambient
1 Positive
2 Evacuated
2 Ambient
2 Positive
3 Evacuated
3 Ambient
3 Positive
4 Evacuated
4 Ambient
4 Positive
MEANCONC
1.0
0.03
03
1.4
0.08
0.1
2.7
22
3.4
28.7
12
5.1
STANDARD
DEVIATION
2.6
0.08
0.5
3.9
03
02
4.7
1.4
Z7
75.6
1.6
33
RANGE
ND-1U
ND-03
ND- 1.6
ND - 13.7
ND-1.0
ND-0.6
ND- 15 .5
0.8 -5.1
0.5 - 10.7
ND-305
ND-4.7
ND - 10.6
SAMPLE SIZE
18
18
18
12
12
12
18
18
18
18
18
18
                                              530

-------
                        TABLE III: STATISTICAL RESULTS
VARIABLE
DILUENT
GAS
HUMIDITY
PRESSURE
JTIME 	
TIME'STATE
ALL DATA
P- VALUE
0.0921
0.0605
0.1100
0.1047
0.023
ALL DATA
CONCLUSION*
NOT SIGNIFICANT
NOT SIGNIFICANT
NOT SIGNIFICANT
NOT SIGNIFICANT
SIGNIFICANT
DRY
DATA
P- VALUE
0.8576
NA
0.0455
0.3191
NA
DRY DATA
CONCLUSION'
NOT SIGNIFICANT
NA
SIGNIFICANT
NOT SIGNIFICANT
NA
, Statistical significance based upon 95% confidence limit.
              TABLE IV;  POSITIVE DRY NITROGEN (TEST GROUP IP)
CANISTER NUMBER
CAN1
TAN 2
rAN3
rAN4
rAN5
CAN 6
TIMEO
1.03
0.00
0.00
0.67
0.00
0.24
30 DAYS
0.08
0.67
0.22
1.61
0.14
0.27
«ODAYS
0.34
0.00
0.00
0.90
0.00
0.00
                                       531

-------
            THE EFFECT OF WATER ON RECOVERIES IN SORBENT TUBE
                           AND SUMMA CANISTER ANALYSIS

                                     Joseph M. Soroka
                                       Robert Isaacs
                                        Gerald Ball
                             Roy F. Weston , Inc., TAT Contract
                            1090 King George Post Road, Suite 407
                                 Edison, New Jersey 08837

                                     Rajeshmal Singhri
                                     Thomas Pritchett
                               Environmental Response Branch
                         Office of Emergency and Remedial Response
                            U.S.  Environmental Protection Agency
                                  2890 Woodbridge Avenue
                                 Edison, New Jersey 08837

ABSTRACT
      The Environmental Response Team/Technical Assistance Team (ERT/TAT) uses a custom
developed method for air analysis. The use of a dual bed Tenax/Carbon Molecular Sieve sorption tube
allows the analysis  of all target analytes in Methods TO-1 and TO-2 with good recoveries.  For the
analysis of Summa  canisters with high levels of CO2 and methane, which may interfere with GC/MS
analysis using liquid nitrogen trapping, aliquots may be spiked unto these tubes with minimal retention
of the CO2 and methane gases.  For samples with high water content, freezing of the cold trap is a
significant problem.  We  have demonstrated that, even for samples which do not exhibit cold trap
freezing, a significant loss of recovery for some analytes is noted due to the coelution of water.  This
"water suppression" effect has been reported by other laboratories as well. Several approaches to
alleviate  the effects of water   will be discussed including:  1. modification of the cold trap,  2.
modification of the sorbent tube, 3. the use of nafion dryers and 4. purging of the sorbent tubes.

INTRODUCTION
      Precise and accurate analysis of volatile organic compounds in ambient air is highly crucial. The
Clean Air Act requires sensitive and comprehensive analysis of air quality both indoors and outdoors.
Accurate knowledge of ambient levels is important for the Superfund and RCRA programs, especially
for site assessments, cleanup and removal actions and remedial operation. Fast and effective analyses
is necessary for emergency responses in order to assess the public risk and ascertain the effectiveness
of the response.
      In air  toxics samples,  water is often collected, but not analyzed.   Water is almost always
collected at humid or rainy outdoor sampling locations, and even in large-volume  indoor air samples.
The U.S. EPA's Environmental Response Team (ERT), based in Edison, New  Jersey,  collects air
samples at hazardous waste sites, emergency responses, and indoor air applications.  In providing
analytical support to the ERT, the ERT's Technical  Assistance Team, or ERT/TAT, has tried several
approaches to reduce the effects of water in air samples.

EXPERIMENT \\t
      Thermal desorption of sorbent cartridges is a well known  and accepted technique for the
sampling and analyses of volatile organics in air.  The Environmental Response Branch, Office of
Emergency and Remedial Response, has developed the use of a multi-bed sorbent cartridge for the
                                            532

-------
 sampling of volatile organics. 150 mg of Tenax TA (35/60 mesh) and 150 mg of Carbonized Molecular
 Sieve (CMS, 60/80 mesh) are loaded into a 6 mm by 120 mm long glass tube. The original choice of
 these soibents was based on the sorbents used in EPA method 624, a purge and trap method for the
 analyses of volatile organics in water.  The tubes are conditioned with a nitrogen gas how at 240°C for
 twelve hours prior to use.
       In sampling, sample flow is through the Tenax and then into the CMS portion of the tube. The
 use of the multi-bed sorbents, Tenax and CMS, allows for the analyses of those organics which have
 low retention volume on Tenax, but can be retained sufficiently on the CMS and allow for sorption on
 the Tenax of those compounds which have low desorption efficiencies on the CMS.  EPA Methods TO-
 \ and TO-2 use single bed cartridges with Tenax and charcoal, respectively.  Our method allows the
 simultaneous analysis of most, if not all,  the compounds in both TO-1 and TO-2.
       Samples are analyzed by thermal desorption and cryogenic trapping of the tube samples, followed
 by cryofocusing onto the head of a fused silica capillary column, and analysis by GC/MS1.  The analysts
 of the loaded sorbent tube is schematically illustrated in Figure 1.  The sorbent tube is inserted into
 the desorption oven of a Tekmar Model 5010GT Automatic Thermal Desorber interfaced with a Hewlett
 Packard Model 5996C GC/MS , with the Tenax side downflow of the CMS,  i.e. to allow a backflush
 off of the tube into the analytical stream.  The tube is heated to 240°C to desorb all  the analytes into
   liquid nitrogen cold trap held at -160°C,  which is subsequently heated to flash the analytes to a second
 cold trap,   cryofocusing the analytes to the head of the  analytical  column. The sample is introduced
 On the GC column by flash heating the second trap,  and then analyzed via GC/MS. Cold trap 1  is
 packed with glass beads.  Once introduced into the GC column (0.32 mm x  30 meter, Restek RX-5,
 programmed at 8°C/min after an initial temperature of 5°C for three minutes), the  sample is analyzed
 yja GC/MS and quantified using the data system. Several variations are available commercially for this
 configuration, including the use of a single cold trap packed with different sorbents and the  use of
 electrothermal cooling as opposed to cryogenic liquid cooling.
       For Summa canister samples with high levels of carbon dioxide and/or methane (which would
 /.ause plugging of the analytical train due to freezing of these gases in  the cold traps at - 160X1), an
 aliquot of each canister is first adsorbed on a Tenax/CMS tube, which does not adsorb carbon dioxide.
       Table 1 details 29 volatile organics regularly analyzed in our laboratory using this method.

 •THE EFFECT OF WATER ON Am TOXICS ANALYSIS
       During a major survey in 1991, ERT/TAT experienced severe losses of samples taken during
 ijigh humidity events. The high water content in the  tubes resulted in freezing of the cold  traps with
 Consequent loss of analyte recoveries. For several samples with no apparent freezing in the cold trap,
   c j^e experienced  significant losses in  recoveries for several analytes which we attribute as also due
    high water content in the samples.  Figure 2 illustrates average  recoveries for the analysis of  16
 rnatrix spike samples  analyzed over a period of several months. While recoveries for most analytes are
 Satisfactory (70 -130%), recoveries for several analytes with retention times in the range of 5.5 to 7.5
   inutes,  as well  as, the  most volatile  organics including  chloromethane  and  vinyl chloride, are

 ^   Figure 3 illustrates the GC/MS Total Ion Chromatogram (TIC) of several sorbent tubes spiked
   "th 10 nL of a gaseous standard, while  scanning from  15 to 250  amu in order to  monitor the elution
  f water.   The water elutes not in a peak, but in a profile beginning shortly after the 1 minute scan
 Helav  The water elutes at a constant rate UP to about weril minutes, and then increases steadily  in
 -  tensity until it is exhausted, typically between 6 (for a "dry" tube) and 9 minutes (for a fresh tube).
 r- nsecutive analysis of the  same tube demonstrates that the "dry"  tube profile  remains essentially
    hanged with successive use.  Thus,  if the same tube is spiked with standards for calibration,
 ^^sistent water profiles are obtained allowing good  calibrations.  Our observation  is that when the
p°n  ^jy of the water profile increases above a certain area count (above the maximum intensity in the
                                              533

-------
 profile for the "dry" tube), response of the GC/MS detector is depressed.  Since the water profile
 intensity reaches this critical point after 5.5 minutes only those analytes which coelute after that time
 are affected.  For most samples the water profile will abruptly end by 1.5 minutes;  thus, later eluting
 analytes are not affected.  However, we have successfully demonstrated that for highly humid samples
 with consequent high water loads on the tube, this water profile may extend throughout the GC/MS run
 affecting recoveries of most, if not all, analytes during  the sample analysis.
       Referring back to Figure 2, low recoveries are probably due to two different effects. The early
 eluters are  low because water saturates the CMS, reducing the sites  available for adsorption  and
 desorption of the compounds that use CMS as  an adsorbent.  Hie low recoveries in the toluene -
 tetrachloroethene region are the result of water suppression at the peak of the water profile.

 APPROACHES TO WATER
       We have identified four approaches to mitigate the effect of water on the analysis. These include:
 1. Modification of the cold trap, 2. modification of the sorbent tube,  3.  the use of nafion dryers and
 4. purging of the sorbent tubes. We report here some of our preliminary efforts in this area; we expect
 subsequent papers will address each of these areas in greater detail.

 Modification of cold trqp
       We have explored the use of an alternate packing for the cold trap, one which would allow the
 use of higher temperatures with good recoveries for the analytes of interest  but temperatures which
 would be high enough to avoid trap freezing with very high humidity samples. The use of an alternate
 packing with high hydrophobic properties would also allow purging of water from the analytical train
 prior to analysis.
       Figure 4 illustrates the recoveries obtained at two spiking levels  for a cold trap packed with
 Carbopack B/Carbosieve SHI. This packing is expected to have hydrophobic properties.  Acceptable
 recoveries are obtained at -IWC for all analytes at the 2 and 20 nL levels (note that these results are
 for non-humidified samples).  Figure 5 illustrates that at alternate cold trap temperatures as high as (PC,
 most analytes exhibit acceptable  recoveries.   Carbon  tetrachloride,  with  this packing,  shows low
 recoveries, however.  We intend to explore the use of this packing at temperatures as  high as room
 temperature.
 Modification of the sm*^ nt
       Preliminary results we have obtained with several alternate multi-bed sorbent tubes  show
 promise as candidates for future study. We will report on our results in the future.

 The use of Nafion drvcrs
       Method TO-14, a Summa canister method, details the use of nafion dryers to remove water from
 the sampling train prior to  analysis.   A major disadvantage to this approach is the lose of polar
 compounds (eg, acetone, MEK) across the membrane with the water.  We have done some preliminary
 work in interfacing a dryer between the sorbent tube oven and the Tekmar cold trap valve with limited
 success.  Because these components are in the heated  zone of the system, and also as a result that the
 dryers are  in line  with a very high temperature gas stream, we have experienced decomposition and
 "meltdown" of the membrane. We expect to explore this approach in the future.

 Sorfacnt tube
       One of the most successful approaches to minimize the effect of high humidity in samples has
been to purge the sorbent tubes prior to analysis with dry carrier gas.  Preliminary work in the lab
demonstrated that recoveries for lab standards were acceptable even after purging of tubes with more
than 2L of dry air.
                                              534

-------
       Figure 6 illustrates the results obtained for the analysis of ten standards which were analyzed
over a period of several months, by spiking a new tube with a 10 nL standard, purging it with 1800 ml
of ultra zero air at a rate of 30 ml/min, and then analyzing the tube under the same conditions as the
samples.   Recoveries were in the  70-13096 range  for all  the early  eluters except chloromethane
(6S.4%)> although the precision for chloromethane and vinyl  chloride was not good.  Low recoveries
were seen again in the toluene - tetrachloroethene region of the chromatogram, although they were about
10% higher than  the average matrix spike illustrated  in Figure 2.  Most significantly, the use of the
purging procedure resulted in a higher percentage of successful analysis under conditions which would
have resulted in freezing of the cold  trap with loss of all recoveries.

CONCLUSIONS
       We have identified four approaches to mitigate the effect of water on sorbent tube analysis.
Very promising results were obtained with the use of an alternate packing in the cold trap; however,
we have not had the opportunity to test this trap on real samples to date. Our preliminary evaluation
of alternate sorbent tube packings also shows promise. Purging of tubes prior to analysis has resulted
in very satisfactory results.  We expect to report on further evaluations of these methods in future
papers.
1
    R  M. Riggin, Compendium of Methods for the Determination of Toxic Organic Compounds in
    ftiCPt Air. EPA 600/4-84-041, U.S. Environmental Protection Agency, Research Triangle Park,
April 1984.

DISCLAIMER
       This paper does not necessarily reflect the views of the U.S. EPA, and no official endorsement
should be inferred.  Mention of trade names of commercial products does not constitute endorsement
or recommendation for use.
Table 1' Retention times for typical analytes.

#      ANALYTE                TIME (min^
1.  Chloromethane
2.  Vinyl chloride
3*  Chloroethane
4.  Trichlorofluoromethane
5.  i,I-Dichloroethene
6   Methylene chloride
7   t-l,2-Dichloroethylene
g!  1,1-Dichloroethane
9.  Bromochloromethane
10. Chloroform
11. 1,1-Trichloroethane
12* i'2-Dichloroethanc
tf. Carbon tetrachloride
14] Benzene
15. Trichloroethylene
                                  1.2
                                  1.3
                                  1.6
                                  1.9
                                  2.4
                                  2.7
                                  3.3
                                  3.6
                                  4.6
                                  4.7
                                  5.3
                                  5.5
                                  5.8
                                  5.8
                                  6.8
                                                           ANALYTE         TIME
16.    Dibromomethane           6.8
17.    Bromodichloromethane      7.0
18.    Toluene                    8.7
19.    1,1,2-Trichloroethane       8.9
20.    Tetrachlorethene            9.8
21.    Chlorobenzene             10.7
22.    Ethylbenzene               11.2
23.    Meta & para-xylenes        11.4
24.    Styrene                    11.9
25.    Ortho-xylene               12.0
26.    1,1,2,2-Tetrachloroethane    12.5
27.    p-Bromofluorobenzene      12.7
28.    Chlorotoluene              13.4
29.    Meta-ethyltoluene           13.6
                                             535

-------
              Corrlw/dMorb
                                              hr Dm
                                                  2   QUADRUPOLE
                                                     DE
                                                       ETECTOR
   THERMAL DESORPTION
    GCIMSANALYSIS
           TAT GC/MS
                                     G*S CHROMATOGRAPH/
                                     MASS SPECTROMETER
Pl»»re I.   SchciMtic of Iht/nuJ dcxxpuoc CC/MS intlylidl IMJI.
  .
 I*
                         UNPURGED SAMPLES
             I 1 i I 6 1 I I 9 (l'l 113 I I'sIlV I 19  211 23 I 25 27 29
              2   4   6   A   10  12 14 16  18  20 22 24  26  28
                         COMPOUND NUMBER
     [ igurf 2.   Avcnfe* nulrli ipike recovtrkt for 16 wmpiel over • thne montN period. CLMQ-
             cliloroineihMe. VC-.lnyltkluibifc, TCA-I.1.3 uklilotocUiiM, l-UUCttmeiilanxlheM.
                                    536

-------
        U***d
                         FRESH TUBE
        r
                         "DRV"  TUBE
       n
                         SYSTEM  BLANK
         1.0    2.0    3.0    1.0     S.D     6.0     7.0     0.0

                    KITENriON TIME (MINUTES)   —-)
           Total ion chronulo|rami illuurwinf water profilei for frtjh Ind dried Tctuu/CMS lutoei

           Ipllud willi 10 nL or lucoui UuuUrd; QC/MS tanned from 1] u 330 AMU.
110


100


 K)


 M


 JO


 ,:  I
                 Cirbopack B/Cirboilavt Trip, -160C
r\i
\L
                                                    •  2.0 nl
                                                    *  20.0 nl
         1    3    B    7    10   12  14   18    18   20   23   25   29
           24    6    B    11   13   15   17   19   22   24  26

                          •Compound Numbsr
          4.   Ptnxnl rKurarlci fof 2 u«l 20 nL of |uuu uudvdi iplked on Tcnu/CMS,
              Cirt»|»ck/Cul>oiicv> cold imp 1. u -lifTC.
                                537

-------
                        fiei it Dlff««m Ttmpentuts

160
140
120
100
                          .9   11  13   15   17   19  22  24   26   29
                                                                                                             N - 10; AUG-OCT, 1981
                 6   B    10   12   14   16  IB   20   23   25  27
                    COMPOUND NUMBER

Fi|>ra}.    root* reoovcrta fa 10 .L of JMCOIU mndAidi yitoj on Tna./PM V CutaftfU-
          Cvtmicw old trap I, u wiout unpenuuei.
                                                                                  ::
                                                                                      120
                                                                                      110
                                                                                      100




                                                                                       .
                                                                                       -.

                                                                                       .
                                                                                         Fi[«n 6.
                                                                                                                                     •  PURGE SPIKES
                                                                                                                COMPOUND NUMBER
                                                                                                      itt rcrovtriei to 10 Toiu/CMX lutel Ipjtal Will 10 nL of (ueoui lUndnil I
                                                                                                            .tLoTdorlir pria louuljm, d.UK
-------
                A  CRITICAL EVALUATION OF TO-1 and TO-2
                METHOD FOR THE ANALYSIS OF AMBIENT AIR
                       VOLATILE ORGANIC COMPOUNDS
               Anne Sensel Williams  and Steven A.  Guest
                              Tekraar Company
                               PO Box 429576
                          Cincinnati,  OH  45242
ABSTRACT
There are several methods available for the analysis of ambient air samples.  TO-
1 and TO-2 collect  the sample onto an adsorbent packed tube.  After a specified
volume of  air  La  pulled through the tube, it  is thermally  desorbed.   During
thermal desorption,  the  analytes  are  swept off the hot adsorbent and  onto  a
cryogenic trap.  Variations to both methods were studied and evaluated.

Two types of secondary traps were examined. An ambient adsorbent (Tenax/Silica
Gel/Charcoal)  trap was used.    The special problem this  trap poses for  the
permanent gases was evaluated.  The traditional method of concentration using a
glass bead packed cryogenic trap was also  assessed.

Recovery and reproducibility data  from this system  (Tekmar 6000 and 6016)  was
reported using  the  502.2 series analytes. Chromatograms of an indoor and outdoor
air sample are illustrated.

INTRODUCTION

The growing field of ambient air analysis is placing more and more demands on the
available  methods.    The  Toxic Organic series  contains two  classic  thermal
desorption methods.  TO-1 and  TO-2 require the  air sample to be passed through
an adsorbent trap.   The analytes of interest are retained on the adsorbent bed
until  they are released  during thermal  desorption.   The  analytes are  then
transferred to a secondary cryogenic trap.

In order to increase flexibility of the  analysis, an adsorbent packed trap was
examined as a  secondary trap.   The six permanent gases are a challenge in any
analysis, but particularly in this configuration. The entire analyte list from
method 502.2 was used.  The adsorbent trap was compared to a more traditional
cryogenic  trap.    The evaluation  was  done on  a  Tekmar  AEROTrap  6000/6016.
Reproducibility of the system  was  performed to  validate the  new instruments.

The AEROTrap 6000  is  a thermal desorber capable of desorbing one sample tube.
It  contains an internal  trap  which  can   either be cryogenically  cooled or
maintained at  ambient temperature.  The AEROTrap 6016  is an autosampler which
thermally desorbs  up to sixteen tubes and interfaces to  the 6000.  The analytes
desorbed from the sample tube are transferred onto an internal trap in the 6000.

Xeka*r AEROTrap 6000/6016 Conditions

      Sample Desorb                 1/4" Carbotrap  t 325°C
                                    1/2" Tenax      : 225°C
      Internal Trap                 Varied
      Trap Preheat                  220°C
      Trap Desorb                   225°C  for 4 tnin.
      6000 Line and Valve           200°C
      6016 Line and Valve           175°C/200°C
      Cryofocusing Module           Cooled to  -190°C
                                    Inject 200°C for 0.75 min.
                                     539

-------
Reproducibility of System

The reproductbility of the system was checked by analyzing eight 1/2" stainless
steel (SS) tubes filled with 2g of Tenax.  The internal trap was a Tenax/Silica
Gel/Charcoal trap.  The deoteotor was a Hewlett-Packard 5970 USD equipped with
a 30m 0.25mm I.D.  DB-5  column.  A chromatogram from the reproducibility study is
shown in  Fig.  1.  Table  1 liatB the peak  numbers with assigned  names.   The
reproducibility of the system is also illustrated  in Table 1.  The chromatogram
shows good peak shape  and resolution.  The reproducibility ranged from 20% BSD
for trichloroethene to 1.6% for chlorobenzene.  The average RSD value for all the
compounds was 5.3%.


Analysis of the Permanent Oases

The analysis of the six permanent gaaes (dichlorodifluoromethane, chloromethane,
vinyl chloride, bromomethane, chloroethane, and trichlorofluoromethane) was then
attempted on the  6000/6016 and  a Tracer  Hall  detector.   The gases were spiked
onto a 1/4" Carbotrap 300 (Supelco) tube using a flash evaporator.  The secondary
trap used was a Tenax/ Silica Gel/charcoal trap.  The first sample gave higher
response than the next two  samples.  After stopping the run to check the system,
the runs were allowed to continue.  This  first run had higher recovery, but the
recovery decreased on subsequential runs.  It was discovered  the run with higher
recovery values had lower trap standby temperatures.  The trap standby parameter
is  the  temperature  which  the  trap must  reach   before  the  next sample  is
transferred onto  the  trap.   This prevents a sample  from poor  recovery due to
breakthrough of the analytes through the adsorbent.

The trap standby temperature  is normally set to 30°C, but if the room is cool the
trap may  already be 21°C  if there  is an interruption in the cycle.   Table 2
illustrates two different  trap standby settings.   The RSD's for the 30 C standby
range from 136% (chloromethane) to 29% (dichlorodifluoromethane). Decreasing the
trap standby to  21°C lowered some of RSD  values but  raised  other values.  The
chloromethane RSD was  lowered to  59% while the dichlorodifluoromethane RSD was
raised to 50%.

A Cryofocusing Module was installed on the injection port to isolate the problem.
The Cryofocusing Module cools a section of the column to subambient temperatures.
The analytes are then refocused on the head  of the column during the desorption
of the secondary trap.  They are  then injected into the gas chromatograph in a
tight slug.

Table 3 compares  the RSD's using a  standby temperature of  21°c  and a standby
temperature of 35°C with a Cryofocusing Module.    The RSD's improved and ranged
from 9.2% (trichlorofluoromethane) to 22% (bromomethane}.  This indicates that
the different trap standby temperatures allow  the  analytes to migrate different
depths into the  trap.   The poor  RSD  values were  caused by  the integration of
broad peak  shape and resolution,  not   an actual  loss  in  analytes.    The
Cryofocusing Module allowed the analytes to refocus on the head of the column,
improving peak shape and resolution and therefore integration.

To further solidify this conclusion,  a cryogenic trap was installed in the 6000.
The trap was an  1/8"  piece of glass-lined tubing  filled with 60-80 mesh glass
beads.  Neither the Cyrofocuaing Module or 6016 were used (the sample tubes were
one at a time).   The trap was cooled to -190°C.  Table 4 shows the RSD's or the
permanent  gases  on   the  cryogenic trap.     The  RSD's  ranged  from  2.6%
(trichlorofluoromethane) to 4.6%  (dichlorodifluoromethane).

The whole 502.2  series was spiked  onto  a 1/4"  Carbotrap 300 tube.   This was
desorbed onto the cryogenic trap.   The  detector used  was  a  Flame lonization
Detector (FID).   The chifomatogram is shown in  Fig. 2,  A comparison  of the same
standard directly injected  onto the column at the same concentration is shown for
comparison.
                                      540

-------
CONCLUSIONS

The AEROTrap 6000 and 6016 produced excellent reproducibility from position to
position.  The  reproducibility of the permanent gases is good if a cryogenic trap
is used.  An ambient adsorbent trap provides good recovery of all compounds in
the 502.2  series  except the permanent gases.  These gases  can  be improved by
employing a Cryofocusing Module.

FUTURE WORK

Tekmar has developed a new concept in trap cooldown, called TURBOCool.  TURBOCool
uses CO, to cool an adsorbent trap to subambient temperatures to improve trapping
efficiency.  Utilizing several column types,  there was a remarkable increase in
peak  shape and  resolution of  the permanent  gases  using  TURBOCool.    It  is
anticipated that TURBOCool will  yield similar results on the 6000 and negate the
need for a Cryofocusing Module.



                                    TABLE  1
                     List of compounds in 502.2A standard
                       Reproducibility of 6016 and 6000

PEAK f            COMPOUND NAME                       % RSD

  1               1,1-Dichlorethene                    14.3
  2               Dichloromethane                      17.4
  3               t-l,2-Dichloroethene                  9.9
  4               1,1-Dichloroethane                    6.2
  5               c-l,2-Dichloroethene                  5.3
  5               2,2-Dichloropropane                   9.7
  7               Bromochloromethane                    4.2
  7               chloroform                            3.4
  8               1,1,1-Trichloroethane                15.2
  g               1,2-Dichloroethane                    3.4
 10               1,1-Dichloropropene                   2.6
 H               Benzene                               2.9
 11               Carbon Tetrachloride                  6.7
 12               1,2-Dichloropropane                   2.0
 13               Trichloroethene                      20.3
 13               Dibromomethane                        3.1
 14               Bromodichloromethane                  2.4
 15               t-l,3-Dichloropropene                3.6
 16               c-1,3-Dichloropropene                 6.9
 17               Toluene                               2.5
 17               1,1,2-Trichloroethane                 2.2
 18               1,3-Dichloropropane                   3.2
 19               Dibromochloromethane                  2.6
 20               1,2-Dibromomethane                    3.1
 2i               Tetrachloroethene                     1.3
 22               Chlorobenzene                         1.6
 23               1,1,1,2-Tetrachloroethane             1.6
 24               Ethylbenzene                          1.8
 25               m,p-Xylene                           16.1
 26               Tribromomethane                       2.5
 27               Styrene                               2.7
 28               o-Xylene                              2.4
 29               1,1,2,2-Tetrachloroethane             3.4
 30               1,2,3-Trichloropropane                2.2
 31               Isopropylbenzene                      2.2
 32               Bromobenzene                          1.9
 33               n-Propylbenzene                      1.9
 33               2-Chlorotoluene                      12.0
 34               4-Chlorotoluene                       2.6
                                      541

-------
  35
  36
  36
  37
  38
  39
  40
  41
  42
  43
  44
  45
  46
  46
1,3,5-Trimethylbenzene
tert-butylbenzene
1,2,4-Trlmethylbenzene
1,3-Dichlorobenzene
aec-Butylbenzene
1,4-Dichlorobenzene
4-Iaopropyltoluene
1,2-Dichlorobenzene
n-Butylbenzena
I,2-Dibromo-3-chloropropane
1,2,4-Trichlorobenzene
Napthalene
Hexachlorobutadiene
1,2,3-Trichlorobenzene
      2.2
      2.0
    2.6
      2.0
      2.0
      2.8
      2.1
    17.7
      1.7
    14.5
      3.3
      8.9
      2.9
    13.4
TABLE 2   REPRODUCIBILITY OF OASES AT TWO STAHDBY TEMPERATURES
                                                 * USD
Dichlorodifluoromethane
Chloromethane
Vinyl Chloride
Bromomethane
Chloroethane
Trichlorofluoromethane
                  Trap Standby
                      30°C

                        29
                       135
                        62
                       105
                        40
                        30
   Trap standby
       21°C

         50
         59
         55
         73
         71
         78
TABLE  3  REPRODUCIBILITY OF OASES WITH AND WITHOUT
                  CRYOFOCUSINO MODULE
Dichlorodi fluoromethane
Chlororaethane
Vinyl Chloride
Brotnomethane
Chloroethane
Trichlorofluoromethane
                  Trap Standby
                      30°C
                No Cryofocusing
                     Module

                        50
                        59
                        55
                        73
                        71
                        78
RSD
         Trap standby
             21°C
  With cryofocuaing
        Module

               18
               11
                5.3
               22
               20
                9.2
TABLE 4  REPRODUCIBILITY OF OASES USIKO A 1/8" OLT OLASSBEAD TRAP
                    COOLED TO -190°C ON $000
Dichlorodi fluoromethane
Chloromethane
Vinyl Chloride
Bromomethane
Chloroethane
Trichlorofluoromethane
                       * RSD
                        4.6
                        4.1
                        3.1
                        3.4
                        2.9
                        2.6
                                  542

-------
 3!
(Q


 i
Abundance TIC: M036011.D

9000000 -
8000000 -

7000000 •


6000000 -

5000000 -

4000000 -
3000000 -
2000000 -
1000000-
0 -
2i

17
11




7

1 3 5




M

2




i



»


X
11


89






13

12





C


1

14


L
5

16


A _J
It.

22



18 21








1


-•-
g
2C







ULI




•*•





33




2






26


—
28
31




30

29









32







36

35

31










L


3840



37
|
I
1









9
41







^








2





46
44

43



X*



.
i
45












 4.00 6.00 8.00 10.00 12.00 14.00 16.00 18.00 20.00 22.00

-------
 Figure 2
240-1
220-;
200 -j
180-i
160-i
140-
120-
100-=
80-
60-
40-:
20-
5^17001










—1 — ' — I — i — i














502.2 Standard
Sample Tube: 1/4" Carbotrap 300
Trap: 1/8" GLT with glass beads
cooled to -190°C








Vvi
— n — i — i — i — i — i








u








uL
— r~~i — i— T










LL
























i
il
1












i \*j i » i_ —





















L
.
15
                   30   33   36  39
300"
280H
26O
240-
220-
200-

ISO-
I6O-
14O-
80-
6O
40-
20-
IUUOU,









1
















Direct Injection
(without gases)








VaJLJulJluL
n r* • ' i • • ' i ' • '
4812

















ti
4"











of 502.2
on FID








iL













11 I '
24

Standard











1


I
:






i r i — i — i— i — i — i — T—
28 32










J










IA__
' 1 ' ' ' 1 ' ' ' '
36 «0
     544

-------
   Stability of Multicomponent Gaseous VOC Standards in
                                    Cylinders
                                James J. F. McAndrew
                                 American Air Liquide
                         5230 S. East Ave, Countryside, IL 60525

                          E*rle R. Kebbekus and Raj Gajjar
                          Alphagaz Division of Liquid Air Corp.
                        19 Steel Road West, Moirisville, PA 19067
ABSTRACT
For reliable analyses of VOC's in air, it is essential to have multicomponent gaseous standards,
generally supplied in cylinders.  When a large number of components (41 for EPA method TO-
14, for example) are packaged in a single cylinder, a considerable advantage in convenience to
the user is obtained.  The stability of such a complex mixture is most readily assured at
concentrations in the ppm range. Results of stability studies on several Alphagaz VOC mixtures,
including one 41-component mixture, will be presented. No deterioration in concentration was
observed to within the analytical accuracy.  Dilution methods can be used to dilute ppm
mixtures to ppb level. Generation of 0.5 ppb  standards using a 500 ppb mixture and a
previously described dilution system will also be discussed,


INTRODUCTION
Gaseous mixtures can be prepared extremely accurately for use as calibration standards through
fee use of gravimetric techniques. Standards for VOC analysis can include large numbers of
components without compromising precision or accuracy, as was discussed in a recent
publication1.  in addition to the accuracy of initial preparation, it is necessary that standards
maintain their accuracy for several years, i.e., that they be stable. Various factors can lead to
deterioration of mixture concentration, such as polymerization, reaction of components with one
another or with impurities, reaction and/or adsorption of components on the container walls, etc.
Deterioration can be minimized by avoiding incompatible constituents, by control of preparation
parameters, such as total cylinder pressure, and of preparation procedures, such as cylinder
treatment (for mixtures in gas cylinders).

The intention of this paper is to present representative data obtained from Alphagaz in order to
give an indication of the stability of VOC mixtures. The standards were prepared for internal
use in Quality Assurance in the same way as mixtures prepared for external customers.   The
data were not collected exptessly to monitor stability, but rather were drawn from analyses in
which the mixtures were used as calibration standards in other analyses, performed over a
Period of one to two years.  Thus there are occasional gaps and variations in precision, which do
not significantly affect the overall conclusions.
                                        545

-------
 The data that will be presented cover a small number of cylinders. They can be supported by a
 variety of other studies in which the data set is less complete, either because of fewer
 components or a shorter time frame, and by a general body of experience.  Thus we believe them
 to be generally representative.  However, to demonstrate stability of a mixture is to observe a
 negative result (no change in concentration) and is never a "proof," as it is not possible to
 monitor every cylinder ever made with a given procedure. Our present level of success has been
 achieved by rejecting approaches that led to problems in the past and we are currently seeking to
 widen the range of constituents that can be successfully packaged in cylinders.

 Mixture Composition
 The present discussion will focus on mixtures prepared at concentrations of one to several ppm.
 As was discussed previously2 stability problems are generally least when mixtures are prepared
 at this level. Although lower concentration mixtures can be prepared, it is our opinion that it is
 preferable to avoid the occasional stability problems that can arise and use dilution methods to
 achieve lower concentrations if necessary.  The last section of this paper will present data
 obtained with a previously described dilution system^ which has now been used to generate 0.5
 ppb standards and is commercially available.

 One mixture contains 41 compounds in one cylinder which provides an obvious advantage in
 convenience to the user.  Several constituents (e.g. styrene) of this mixture have been reported
 to show stability problems in other containers,  but have proven stable in properly prepared
 aluminum cylinders.

 EXPERIMENTAL APPROACH
 Study of the stability of calibration standards over periods of the order of years poses some
 conceptual difficulties. The accuracy of an analysis, especially by GC, is usually founded upon
 an accurate calibration.  How, therefore, should one analyze the standard? Two main
 approaches suggest themselves: One is to compare the existing standard with one that has been
 freshly prepared; discrepancies indicate either a problem of stability with the older standard or a
 failure in preparation of the new one. A second approach is to select an internal standard that is
 assumed to be stable and to ratio the response of all other constituents it. This assumes that the
 relative response of the analyzer is constant for all species. It also has the effect of introducing
 any fluctuations in the response of the internal  standard to the results for all other species. In
 this paper, we use both approaches.  Every time a given standard is used for calibration of a GC-
 FID, a set of areas is obtained.  Because the response of the FID is relatively stable, it is possible
to ratio these areas to an internal standard and monitor the stability of the other species.  If a
 standard is used to certify a new mixture with all of the same constituents then a comparison of
the analytical results with the expected concentrations in the new cylinder (based on gravimetry)
gives an indication of the stability of the original standard.

 RESULTS
 I. EthyleneOxide
The results obtained in Figure 1 were obtained from a standard containing  IS ppm of ethylene
oxide and 16 ppm methane. Ethylene oxide has previously been reported to be unstable^
although the concentration was not specified. In Fig. 1, raw FID areas are  shown for analysis
dates over one year.  It can be seen that the  analyzer is rather stable, as the  observed fluctuations
                                          546

-------
                                                                in response are generally
      *»ow> T         •                  t         f                10% or less.  When the
      ««"» * — * — * - • — ; — * — • — - — - — • — ; — - — • — « — • — .   ethylene oxide response
      •"°« |                          1 5 ppm Ethylene Oxide      is ratioed to that of
   |  loooo |     .                                               methane, the  fluctuations
   §• "ao<> ^  *"        •   •   "   •   •  *  "  •   *   •   •  "  •   disappear essentially
   £  iwoo j                            i6ppmM«hmne          completely, allowing us
   E  1»°°» t  "  I   '   '   *   '   '   "  '  "  '   *   *   '  *  *   to conclude that they are
                                   **** x IOOOO        due to the analyzer and
                                                                ** standard is stablc at
                                                                this concentration. In the
                                                                graph the ratio is
                                                                multiplied by 10,000 to
                                                                allow it to be
       Figure .
       methane in nitrogen.
                                                                areas.
2A. 4 1 •Component Mixture: FID Area Ratios
Figure 2 show the response of 41 components, packaged in a single cylinder, over a period
exceeding one year. In this case the FID stability is not quite as good, so that it is necessary to
show only the results obtained after ratioing to an internal standard. Toluene was chosen as an
internal standard because we have a considerable history of trouble-free standard preparation
with this compound.  The benzene data are reasonably flat, indicating that essentially
equivalent results would have been obtained were benzene chosen instead (for example).
Independent results have been presented previously1 to show by comparison with an NIST
SRM that the analytical values of both benzene and toluene concentration (2 ppm) are in good
agreement with the gravimetric values. Each point is the average of 3-5 runs collected on the
day in question, the number of runs being determined by the need to obtain a sufficiently small
standard deviation for all of the species for which analyses were planned on that day. As the
data are drawn from actual quality assurance runs, not all compounds were of equal interest on
a given day. The error bars  shown represent one standard deviation and are only included for
those data points where this  is larger than the size of the marker in the Figure. Clearly, there
are excursions for some compounds on particular dates, for example 1,2,4-trichlorobenzene on
July 1 5, but these correlate with the occurrence of large standard deviations for the same
compounds. There is no trend in response for any species and all may therefore be considered
stable to within the accuracy of the data, which is better than ± 5% in most cases.

2B. 4 1 -Component Mixture: Comparison of two standards
In Figure 3 shows the results of comparing a 41 -component standard with 2 freshly-prepared
standards which were analyzed 7/8/91 and 1/10/92. Both were standardized against a mixture
prepared 1 1/1 1/90. The Figure shows the ratio of the gravimetric concentration introduced to
each new cylinder to the analytical result obtained for the same cylinder by comparing it with
the cylinder prepared in 1 990.  The deviation of this ratio from 1 .0 is influenced by:
deterioration of the standard cylinder, variation of the new cylinder from its
                                         547

-------
FID Response/Toluene

1 •• 1 J
. 	 .... t . . ...
f
t I
1 *

! ' t .
. « • 	 1 	 •
— » 	 ! 	 I 	 •

• * I
... 1
•
• •• i
'"T
... *
i
' " t *


* »» -f
* .» -r-
* 4. T
• •• ~
1.40 ^
1 m
1 »0 ,
i .00 -r
«T 1 i I •
1
1 ' f
i T . t i


T • = *
-I • • •

O.IO - ~
o.«o |

o.*o "
o.oo *
"'1

f .
• >» •
• jo 4-
,..i.
.,. 1
• Ot f
II -Nev l-Jul

	 • 	 • 	 fi 	 i 	 •
	 • 	 1 	 • 	 • 	 i
1 • i i

• • I

i
•
IS-Jul <-S«P 1-Oct I0-).n 3-f.b
                                                                       p-+ m-xytene
                                                                       benzyl chloride* 1.3-
                                                                        dkhlorobenzene
                                                                       o-xytene+I.UJ-
                                                                        tetrachbroethane
                                                                       I ,2,4-trimethyfeenzene
                                                                       1,2-dkhbrobenzene
                                                                       hexachbro-1,3-butadiene
                                                                       1,4-dkhbrobenzene
                                                                       UJ-trichbroethane
                                                                       1.3-dkhbroethane
                                                                       1.2-dkhbro-
                                                                       tetrafluoroethane

                                                                       1,3,5-trimethybenzene
                                                                       I ,2,4-trichbrobenzene
                                                                       styrene
                                                                       toluene
                                                                       chbrobenzene
                                                                       tetrachbrobenzene
                                                                       IJ-dkhbrodh/iene
                                                                       l.l-dkhbroetnane
                                                                       c-1,3-dichbropropane
                                                                       t-1,3-dkhloropropan*
                                                                       chloroform

                                                                       4-ethykokiene
                                                                       ethyfeenzene
                                                                       benzene
                                                                       trichbroethytene
                                                                       IJ-dibromoethane
                                                                       l.l.l.tnchloroethane
                                                                       I.U-triehloro-l.U-
                                                                       trifluoroethane
                                                                       orbontetrachlorid*
                                                                       dkhlorodifluoFomethant
                                                                       cte-U-dkhbroethane
                                                                       vinyl chbrid*
                                                                       ethykhbride
                                                                       methyl th bride

                                                                       nwuiyl bronwie
                                                                       nwthylenc chloride
                                                                       trkhbrofluoronwthane
Figure 2. Ratio of RD response to Toluene response for the
compounds tdicated on the right hand side
                                           548

-------
expected value and/or the combined imprecision of the new and the old cylinder analysis.
All of the ratios are within less than 5% of the expected value, except 1,1,1-trichloroethane and
styrene which deviate by 6% and 8% respectively after 14 months, which would be considered
acceptable for most purposes.
j

'

* 1/10/92
• 7/8/91

f
•""•:"-
   0.9
           ?    3
           4    1

                                                                                . |
                                                                                : i
    1.1
                                                                   1/10/92
•


) } | | 11 | :

' S *

1
I

* 7/8/91

1 1
r » =




i '

|
1 i >

    Figure 3. Comparison of gravimetric value introduced to freshly-made cylinders with
    their analytical values using an existing cylinder as a standard
                                          549

-------
 EPILOGUE: Dilution to sub-ppb level
 A dilution system based upon controlled flow of a standard gas and a dilution gas through a
 pair of critical orifices has been described previously^. The dilution factors for which
 performance was described were of the order of 1:50.  In order to use such a system for sub-
 ppb measurements using ppm level standards, dilution factors of the order of 1:1000 are
 required. Performance in this range has since been demonstrated. For Fig. 4, a 0.5 ppm
 standard was diluted to 0.5 ppb and 1.0 ppb using the critical orifice dilution system. This was
 compared with an N1ST SRM delivering a concentration of 5 ppb directly.  Similar results
 were obtained for all 18 components included in the SRM and  in the 0.5 ppm standard.


                      Critical Orifice Dilution System
                                   Toluene
              18-
              10-                        N18T Standard (5 PPS),
               e-

               4-
               a -         -  600il Dilution -of 600 PPB Standard
                    -  1000:1 Dilution of 500 PPB Standard
               O1	'	1—	1	L	
               01*..,
                           Concentration (ppb)

Figure 4. Comparison of signal generated by diluting a 500 ppb standard 500:1 and 100ft I
with chat obtained from a 5 ppb SRM.

References
1.  E. R. Kebbckus and A.S. Cristoforo The Clean Air Amendment of 1990 and VOC
Calibration Mixtures", presented at the Pittsburgh Conference, 1992.
2. J. McAndrew et al. "Gaseous Calibration Standards for VOC" Proceedings of the 1991
USEPA/A&WMA Interantional Symposium "Measurement of Toxic and related Air
Pollutants" A&WMA, Pittsburgh, 1992.
3. R. B. Denyszyn et al. "Toxic Organic gas Standards in high Pressure Cylinders" Proceedings
of the 1990 EPA/A&WMA International Symposium "Measurement of Toxic and related Air
Pollutants" A&WMA, Raleigh, 1990.
                                       550

-------
        Session 13
  Atmospheric Chemistry
Bruce W. Gay, Jr., Chairman

-------
   GASEOUS HYDROGEN PEROXIDE CONCENTRATIONS
                   IN  RALEIGH, NORTH CAROLINA
                                 Mita Du and Vtaty P. Anejn
                       Department of Marine, Earth md Atmospheric Sciences
                                 North Quotim Stale University
                                   Raleigh, NC 27695-8208

ABSTRACT
     Gas-phase tool peroxides and hydrogen peroxide (H2O2) were monitored in ihe ambient air at Raleigh
J|nng September 8 to September 15, 1991 , using the continuous dual-diannd fluorometric M^
no
                    peer   ,    ,                    -
norseradish peroxidas* method in downtown Raleigh, NC. Measurements weit also made of other photochemical
oxidants and trace gases (03. NO. NCfc. NOx, SO2, CO, HCHO) and meteorological parameters. Concentrations
of H2O2 snowed a diurnal variation with maximum concentrations in the afternoon (1400-1800) EST. The mean
5^observMons wasO^ppbandtherancewasbdw                              Tr* concentration
^H202 WK fc^md to be aSrte^y the^SKentradcw rfothw
« by meteorological parameters like temperature and solar radiation No evidence of decompositHio of H2O2 »y
S   was found.
,Crt  Hydrogen peroxide (H2O2) plays an important role in atmospheric chemistry as an oxidant of sulfur dioxide
2 in the aqueous phase when the pH is less than 4.5 (Ptnkett et al.. 1979; Martin and Damschcn. 1981); and a
»«ttt for the hydroxyl radical (OH) in the gas phase.  In addition to providing oxidizing capactty ol «*
environment, hydrogen peroxide U also considered 10 be < potent plant phototo«n(0affiieyetal., 1987),
     There are no known emission sources of hydrogen peroxide in the atmosphere and its presence in the
aunospnere is mainly due to the same  series of photochemical reactions leading to the formation ofpzonc m its
cr*tn termination step.  Thus the principal source of H2O2 is the bimolecular self reaction of HO2 (Table I.
equation 7).  Hydroperoxyl radical is formed as a result of photo-oxidation of formaldehyde (HCHO) and
Predominantly due to the reaction of  hydroxyl  radical with carbon monoxide (CO). The gas phase reactions
*' '<*ung atmospheric hydrogen peroxide concentrations are given in Table 1 (Claibom and Aneja. 1991).
Hn       "* react'oiw given in Table I, we see that H^Oi acts as a sink for the odd hydrogen (H. OH, HU2 -
"Ux) species. Thus information on  the behavior of hydrogen peroxide in the atmosphere can give an insight into
"* 'ree radical balance.
     Modeling studies suggest that the major factors affecting the rate of formation of gaseous H2O2 are the
    TOraudns of primary pollutants nitrogen oxides, volatile organic compounds and CO, together with solar
    ion. temperature and water vapor  content (Kleinman, 1986). But due to the shortage of field observations of
    !,, our understanding of the major factors that control its formation arc limited.
     In this paper we present an anaJ ysis of the ground-level measurements of H202 « «i urban site te. Raleigh,
     unng  the period September 8 - September 15, 1991 and compare and contrast it in relation to other
     pheric pollutants and meteorological variables. v

METHODOLOGY

        site
        site was located in downtown Raleigh. NC (35.9'N, 7i,TW. 126.8m). where one would expect higher
        J  concentrations of primary poDutants:  but it was far enough from any direct emission sources.
       	^«,t u** gase!Tusedforthe analysis were 03, NO. NO2. NOx, HCHO and SO2 and were
       using a Differential Optical Absorption Spectrometer (DOAS).  The data on carbon m^"™6 *JJ
       by North Carolina Denarnnera of Environmental Health and Natural Resources (Nt. D»™*«*  > "*
                                                    is representative of the overall meteorological
                                                          a.. *  jJ f   *!*A 1kT«t*i^%rt4l ^^IlITtlirif* list3

                                            553

-------
 Measurement of Gtteous Hydrogen Peroxide
       Ambient, gas-phase hydrogen peroxide was measured using continuous (luorometric analyzer based on the
 horseradish peroxidase method (Lazrus et al.. 1980).  The dual channel fluoromeiric analyzer measures total
 peroxides on one channel, and by specific enzymatic destruction of hydrogen peroxide, organic peroxides only on
 the second channel.  Gas phase total and organic peroxide were recorded on a chart recorder and extracted
 manually as 12-minute averages. These data were then consolidated into hourly averages.  The analyzer was
 calibrated once daily and the baseline checks were performed twice daily.

 RESULTS AND DISCUSSION
       During  the summer intensive of 1991 (September 8 - September 15) 188 hourly averaged hydrogen
 peroxide measurements were recorded. Gas-phase hydrogen peroxide ranged from below the level of detection to
 about 1  ppbv.  Field measurements of atmospheric H2O2 at various locations in North America, Europe, Brazil
 and Japan (Sakugawa et al., 1990) have shown ranges from  10 ppt to about 5 ppbv.  The average H202
 concentration for our entire period of measurement was 02 ppbv.
       Figure 1 illustrates the composited diurnal trend in the measured hydrogen peroxide and total peroxide
 concentrations.  The daily averaged hourly averages for the  entire data period  indicates that peak H202
 concentrations occurred between (1400-1800) EST and minimum  was observed between (0500-0800) EST.
       Examination of Figure 2 reveals that H2O2 concentration peaks about 2 to 3 hours after the peaks in ozone
 concentration and solar radiation are reached.  This can be explained by the competition for HO2 by NOx in the
 ozone formation, thus inhibiting the H2O2 production until NOx concentrations fall to a significantly low level to
 allow the self combination reaction of HO21 to generate H2O2.  Figure 3 supports this explanation.  These results
 also suggest that gaseous H2O2 is photochemically generated in the atmosphere.
      The relationship between H2O2 and atmospheric trace gas pollutants and meteorological parameters was
 examined to understand the factors affecting atmospheric hydrogen peroxide concentrations.
      Sakugawa ct al. (1989), have suggested that primary pollutant concentrations  and solar intensity are the
 primary factors controlling the concentrations of gaseous H2O2- HiOi concentration increases with a decreasing
 amount of primary pollutant concentration and increases with rising solar intensity.
      The relationships between H2O2 and other pollutants and  meteorological factors are shown in Figure 4.
 The results indicate that H2O2 is most highly correlated to ozone (r = 0.64).  This could be due to the fact that
 both ozone and hydrogen peroxide share the same diurnal trend. Also the major source of hydroxyl radicals
 (which are responsible for the production of hydroperoxyl radicals) is the photolysis of ozone in the presence of
 water vapor.
      H2O2 was also found to be significantly correlated  to temperature (r = 0.52) and solar radiation (r = 0.50).
 This is consistent with the modeling studies of Dodge (1988).  which indicate an increase in hydrogen peroxide
 concentration with increasing temperature. Sakugawa et al. (1989) have also observed a high H202 concentration
 associated with a high solar radiation in their field study in Los Angeles.
      H 2 O 2   was  also  found   to  be   negatively  correlated  to  the  primary  pollutants  CO
 (r = -0.35) and NOx (r = -0.20).  Stockwell (1986) showed that  H2O2 is extremely  sensitive to the rate of the
 reaction of NO2 with hydroxyl radical (OH) (Table 1, Reaction 12) because this reaction removes both NOx and
 OH radicals from  the pool of photochemical reactants. Thus consistent with other field studies (Sakugawa et al..
 1989)  we also observe a high concentration of H2O2 when all  the primary pollutants (NO, NO2, NOx, CO) are
 relatively low.
      H2O2 is positively correlated to formaldehyde (HCHO) (r = 0.33) which is  also consistent with modeling
 studies.  Calvert and Stockwell (1983) demonstrated that in polluted air, the production of free radicals from the
 photolysis of formaldehyde is the most important source reaction  of free radicals and thus the source reaction of
 HO2 radicals (Table 1. Reaction 1).
      Principal component analysis was performed to seek the  best fit regressors among the various parameters
 for H2O2. The data sets having one or more than one missing variables were omitted from the statistical analysis.
 The variables (12 in number) chosen as factors were H2O2. ozone, NO, NO2, HCHO, CO.  SC>2. temperature, dew
 point temperature, wind speed, wind direction and solar radiation, with n = 110. Five components were found to
 account for 83% of the total variance of the original data set (Table 4). The first principal component which
 explains 41.4% of the total sample variance consisted of ozone,  temperature and solar radiation as factor 1 group.
 The second principal component which explained an additional 13.8% of the total variance consisted of dew point
 temperature as the factor 2 group. The third principal component consisted of SOa, NO and wind direction and
 the first  three  principal components collectively explained -70% of the  total sample  variance.  The fourth
 principal component together with the first  three principal components accounted for 77% of the total sample
 variance and the factor 4 group consisted of NO2, H2O2 and CO.
     These principal components can provide interesting interpretation. The first principal component consisting
of ozone, temperature and solar radiation may be viewed as "photochemical activity".  The second pnnC'P*1
component has dew point temperature as its factor. It can be termed as "airmass type". The factor 3 group S02.
NO and wind direction may be regarded as "emission and dispersion of primary pollutants" and the factor 4 group
(NO2, CO, H2O2) as "pollutant concentration".
                                                554

-------
     A regression analysis was carried on HiOi using these four principal components (Table 5), The results
Indicate that "photochemical activity" is highly significant at the 95% level with R2 = 0.41. "Airmass type" and
.j^utwit concentration"  had  R2 « 0.09 and R^ = 0.07 respectively. Thus photochemical activity is most
important in controlling the concentration* of gaseous H2O2 hi the Raleigh utban environment.

SUMMARY
     H202 was measured  during September 8 - September 15,1991 in Raleigh, NC; and its mean concentration
*tofoundtobe02ppbwithafangeofbelowihclevdofdeiecti()nioabounppb.                      .
runn1"   concentrations   exhibited   a   diurnal   variation  with   highest Bevels   during
            EST when an ozone peak was also observed and temperatures and solar radiation were high
           «H2O2 is photochemicafly generated in die atmosphere.
fa_ °«r results indicate that ozone concentrations, temperature and solar radiation are the most important
|a«ors in controlling the concentration of gaseous H2O2-  Under these conditions of higher solar radiation,
wnipcrature  and CDs concentration there is a higher generation rate of radical species like hydroxyl and
^niydroxyl radicals leading to the increased formation rate of H2Q2-
     The concentrations of primary pollutants  is also an important factor for controlling S*86?"* H2"2
    	ion. Higher H2O2 concentrations is favored by lower concentntions of primary pollutants (NO2, NOx
         We did not have access to the amounts of non methane hydrocarbons in air which as shown by
urh»   ° studies (Calvert and Stockwell, 1983) may also be important for the generation of gaseous H2O2 in an
r™*11 .Polluted environment.  However the data on formaldehyde snowed a positive correlation to H2O2
     iion.
     The shortage of field observation of H2O2 and the lack of field observations of certain primary pollutants
       u6^ hydrocarbons limits our ability to determine the major factors controlling the formation of
       H202 in the atmosphere. Any statistical analysis performed on such a short data sei cannot be robust
       1* daia and longer periods of field observations on gaseous H2O2, primary pollutants and meteorological
         are requi red 10 improve our understanding of these factors.
                                                                                         .    f
      k s research has been funded through cooperative agreements with the University Corporation for
            esearch (S 9153) as pan of the Southern Oxidant Study (SOS-SCRP/ONA).
     ^^ J> G" "^ w- R- Stockwell, (1983), Acid generation in the troposphere by gas-phase chemistry.
   •  Uaibom, C. S., and V, P. Aneia, (1991),  Atmospheric H2O2 at Mt. Mitchell. North Carolina, J. Geophys.
  3  fe'96-18.77M8.787.
   "  ^T,ge' Ml c> <1989), A comparison of three photochemical oxidant mechanisms, J. Geophys. Res., 94,
  4  r.^i"5136-
   •  Gafftieyetal.. (1987), Beyond acid rain, Environ. Sci.TechnoL 21. 519-524.
   •  Kf'nman. L, I., (1986), Photochemical formation of peroxides in the boundary layer, J. Geophys. Res., 91,
     10,889-10,904.
  D-  Uzrus, A. L., G. L. Kok. J. A. Lind,  S. N. Gitlin, B. G. Heikes, and R. E. Shelter, (1986), Automated
  7  "uorometric method for H2O2 in air, Anal. Chem., 58, 594-597.
   •  Wattm, L. R., and D. E. Damschen, (1981) Aqueous oxidation of sulfur dioxide by hydrogen peroxide at
  8  £>WPH, Aunos. Environ., 15, 1615-1621.                                     tj  .     .., .     .,
     J-tJikett et al., (1979), The importance of atmospheric ozone and hydrogen peroxide in oxidizing sulfur
  9  ™oxide in cloud and rainwater, Attnos. Environ.,  13,123-137.                     ..
     Rockwell, W. R., (1986). A homogeneous mechanism for use in a regional acid deposition model, Atmos.
 !0  I™110"-. 20, 1615
     Sakugawa. H., and  1, R. Kaplan, (1989). HaO2 and 03 in the atmosphere of Los Angeles and its vicinity:
     Factors controlling iheir formation and their rote as oxidants of S02, J. Geophys. Res., 94, 12,957-12,973.
  '•  Sakugawa.  H. et al. (1990). Atmospheric hydrogen peroxide: Does it share a role wiih ozone in degrading
     «"• quality? Environ. Sci. Technol., 24, 1452-1462.
                                              555

-------
 Table 1. Gas-phase reactions affecting atmospheric hydrogen peroxide concentration.

 Perhydroxyl Radical Formation:
                  HCHO + hv  -» 2HO2- + CO                         (1)
                      Os + hv  -> O(1D) + O2                           (2)
                 O(1D)^H2O  -> 2OH.                               (3)
                   OH- + CO  -> HO2- + CO2                          W)
                      HCHO  -» HNOa + HC^ •  + CO                   (5)
                                                                     (6)
 Hydroperoxide Formation:
                 HO2- + HO2-  -*  H&2 + O2                           (7)
                 03 + terpenes  -»  H^ •*• carbonyls                      (9)
                              ->  ROOHn-C^                         (10)
Competing Reactions:
                  HCv + NO ->  OH-+NQ2                          <">
                  NO2 + OH' ->  HNOa                              H2)
Ozone Formation:
                    NO2 + hv ->  O(3p) + NO                          (13)
                   O(3P)+O2 -»  Os                                 (14)
iydrogen Peroxide Destruction:

                   H202 + hv -*  2OH-                              (16)
Gas-phase SO2 Oxidation:
                   C^ + OH- -»  HOSOj                             (17)
                HO5Q2-I-H2O ->  H2SO4                              f18)
                  SOj + H^ ->  H2SO4                             U9)_
                                     556

-------
   Pig 1.  Hourly averaged concentrations (SeptH-St-ptl 5}
Fig 2, (a) Hourly averaged diurnal variation or H2O2 and Ozone (9/8-9/15)


                         8       12

                            Tim*
-------
                                 Fig 4. Relationships between H2O2 and other pollutants and

                                        meteorological variables for the mesurement period

                                         (Sepffi-SeptlS).
 •
ft .
10-
         0.2     0.4    0.6    o'.B
                  ttat
                                                    ra-
                                                     :
                                                     -'
0.2
      Q.<    0.6
        K2tt
                                        2500


                                        2000-


                                       C 1500-


                                        1000.


                                         500-
0.2    a.t    a.t   c.
        Vfl
          0.2    0.4    0.6    0.6
                                               T 80-
                                               f
                                               M
                                               r
                                                 70
                                                  (I
                                                           0.2
     0.4     0.«
       nan
                                                                               o.s
                                                                                                    1000-
                                        500-
                                                                                                               0.2    0.4    0.6    0.
                                                                                                                        MM3

-------
           MODELING  OF CLOUD  WATER ACIDITY:
COMPARISON BETWEEN THEORY  AND  EXPERIMENTS


                    N.-H. Lin*. T. P. DeFelice2  and V. K.  Saxena1

                    'Department of Marine, Earth and Atmospheric Sciences
                              North Carolina State  University
                                 Raleigh, NC 27695-8208

                                ^Department of Geosciences
                            University of Wisconsin-Milwaukee
                                  Milwaukee, WI53201


ABSTRACT
  A kinetic cloud chemistry model (CCM) involving the aqueous phase chemistry of sulfur species and
aerosol loadings is developed in order to investigate the possible chemical pathways in determining Uw
acidity and chemical composition of cloud water. The solution chemistry involves SOi, HNOj, HU,
J2H?,?04' °3 ^ R2°2 gases and the oxidation of S(IV) by Os and H2O?.  The scavenging of acidic
JH2SO4 and HMO,), neutral ((NH4)2SO4 and NttjNOa), maritime (NaCl and KC1), and continental
U~aCO3 and MgCOa) aerosols are included in CCM. A new scheme is developed to investigate the
aependence of the acidity and chemical composition in cloud droplets upon their sizes. The model results
are compared with direct measurements made in clouds  at Mt. Mitchell, NC.  The data on cloud water
acidity with a temporal resolution  of 10 min are available.  Cloud droplet size distribution was
simultaneously measured using Forward Scattering Spectrometer Probe (FSSP). Case studies comparing
we model results with the observations are presented and the dependence of the chemical composition of
cioud water upon the droplet size is analyzed.

!NTRODUCTION
  . Clouds play an important role in removing and redistributing the atmospheric pollutants1-2'3. The
primary precursors to cloud acidity arc sulfur and nitrogen oxides. Experimental results4 have shown the
"Jean solute concentration varying with the sizes of cloud droplets.  Theoretical5 and modeling6 studies
«so suggested that the distribution of pollutants across the cloud droplet spectrum is due tp, microphysical
cl^H8868' HegP and Larson1 indicated that such size dependency may affect the sulf ate production rate in
jouos.   in ^5 study> a diagnostic cloud chemistry model is developed to simulate the cloud acidity due
dev i   nginS of aerosols and gases  by cloud droplets in open and closed systems.  A scheme is also
"cveioped to calculate the dependency of pH value and chemical composition in cloud droplets upon their
  *s-  Our model will help identify and Quantify the effect of individual chemical processes on the final
  '^ty of cloud droplets.
   £Ul> CHEMISTRY MODEL                                                u    crt
ann A  Oad chemistry model includes the absorption of trace gases, the oxidation of aqueous phase SQz,
and fe.f^Siog of acidic (H2SO4 and HNCb), neutral ((NH4)2SO4 and NHtNOa), maritime (NaCl
to]i,rt   5* and continental (CaCCb and MgCO3) aerosols. In this study, it is mainly considered that the
bv rS°° chemistry involves SO* HNOs, HC1, NH3, COa, Os and H^a gases and the oxidation of S(IV)
Jf ^3 and H2p2. The relevant chemical reactions with the equilibrium constants or rate expressions may
De fjund elsewhere".
of V^lftation, aerodynamic impaction, and Brownian diffusion are dominant mechanisms, in scavenging
      ospheric aerosols. For simplicity, it is assumed that all aerosols considered in this study are totally
       Wlthin to aqueous phase.  Consequently, at the instant of cloud formation, these are immediately
                 aqueous phase.
^j1^ Fftrmulntinn fnr n" ""*" System                                  L   .  ,
    !11 °Pen system, the gaseous concentrations are assumed to be constant. Based on chemical reactions
      5^ ,in this studv* and*6 A"^ of electroneutrality, when equiUbrium between gas and aqueous
            d cb°Ple* is established, the concentrations of all ions in the liquid satisfy the following
                                          559

-------
 [H+]  + [NH4+] + [CAT1-] + [CAT2+] = [OH-] + [C1-] + [HSO3-] + 2[SO32'] + 2[SO42-] +
 [HCOr] + 2[CO32-] ,                                                                    0)

 where CAT represents the dissolved but unreacted cations such as sodium, potassium,  calcium,
 magnesium, and so on. The concentrations of the ions in liquid can be expressed in terms of [H+], for
 example,


          rW  01 rrv
        :—p	[H
                                                                                        (2)

 In the above equations, K^ and PNHS  arc the Henry's law coefficient and concentration of the ammonium
 gas, respectively, and Kaj is the first order of dissociation equilibrium constant for Nrtytq).  The
 concentrations of other ions can also be expressed similarly.  By replacing the ion concentrations in Eq.
 (1) except for [H+] with the relationships such as in  Eq. (2), a cubic equation of [H+] is formed as
 follows:

 A[H+]3 + B[H+]2 + C[H+] + D = 0,                                                         (3)

 where A, B, C and D are functions of constants px and kx for the species x. The sulfate ion concentration
 implied in the coefficient B is calculated as follows:

 [SO42-], = [SO42-],.4, + (d[SO^-ydt)t.^ Ar,                                                  (4)
where A/ is the integrated time. Eq. (3) is solved iteratively for [H*] for each time step. The other ionic
concentrations are then calculated.

Model Formulation for  a Closed System
     In a closed system, for an air parcel without mass exchange with the environment, the total
concentrations of these gases in both gaseous and aqueous phases arc assumed invariable. This is a good
assumption when the air parcel is regarded as a reactive chamber and the relative importance of chemical

reactions involved can be investigated.  If Px represents the initial gaseous concentration and qx is the
aerosol mass concentration of species x, the following relationship shows the conservation of the mass
for species x when it dissolves into cloud droplets:
                                                                                        (5)

where L, R and T arc the liquid water content (LWC), the universal gas constant and the temperature of
cloud droplets, respectively. The Mx is the molecular weight of x. The [(x)] represents the concenration
of dissolved gas x. For instance, [(x)] is the sum of [NHsfaq)] and [NH4+]  for gaseous NHs, and the
above two states of NHs in aqueous phase can be expressed by Henry's law coefficient and equilibrium
constant based on the Henry's law and Eq. (2).  Therefore, for instance, the gaseous concentration of
NHj in Eq. (2) is replaced by the following relationship:
                                                                                        (6)

Similarly, the other gaseous concentrations can be expressed based on Eq. (5).
                                            560

-------
          Of Acidity In TnriiviH.ml Cloud Droplets
   in the above, the cloud water acidity is modeled for both open and closed systems. The pH values are
obtained by assuming all cloud droplets of an equal size. However, the solute concentration in individual
cloud droplets is dependent upon the cloud formation and growth processes, resulting in the dependence
or droplet acidity upon the droplet size,
   In Eq. (3), the coefficients A, B, C and D are rewritten by adding the subscript j for representing the
cloud droplet of radius rj . Considering the equilibrium between gaseous and aqueous phases in individual
cloud droplets, Eq. (5) can be rewritten as follows:
                                                                                        (7)

where Lj is liquid water content of droplet having radius r\. Any terms associated with LRT are rewritten
j« the sum of the contributions from individual cloud droplets. For instance, Eq. (6) is rewritten as
follows:
                                                                                        (8)
where the subscript j denotes the category of cloud droplets of size ij . The relationships for other gases
™* also modified following the above procedure. As a result, the above equation is expanded into m
equations for a cloud droplet size distribution which is categorized into m classes. For example, m is 25
™r a given cloud droplet size distribution. These 25 sets of equations are simultaneously solved using the
iteration method with the least square error within 0,1%.

RESULTS AND  DISCUSSION

Mod*1 fiimi'latinn ftf floudwater  Acidity
The i     ud chemistry model is a kinetic model and can be incorporated into any cloud dynamical model.
mWr? ¥r P116^'8 the cloud liquid water content and temperature in clouds as input meteorological and
com    ysical Pararaters. In order to test the cloud chemistry model, the temperature and liquid water
a c£m Jf6 assumed to be constant (288 K and 0.5 g m\ respectively) and the air parcel is assumed to be
   osed  system without mass exchange with the  surrounding environment.  The initial gaseous
c°ncentran'ons for 5 cases are listed in Table 1. The aerosol concentration is assumed to be 2 [ig nv3.
varii-  oxidati°n of SO2 by H2O2 and O3 is investigated in Cases 1-3. In Fig. 1 is shown the time
forTh °n«f to PH values. the sulfate ion concentrations produced by the oxidation of S(IV). The curve
   me PH value sharply drops from 4.89 to below 3.8 after about 5 min of reaction time, as shown in
           aue sarpy drops from 4.89 to below 3.  ater aout  mn o reacon  me, as sw
is'd" ^ By contrast, sulfate ions are increased to more than 80 *iM.  It is found that about 10% of SOi
2% !J°Jyed into the cloud droplets when H2C»2 is almost consumed for the oxidation of S(TV). Only about
rerna- ^ ls involved into the oxidation of S(IV). The pH value and sulfate ion concentration almost
Sttvf- constant when the concentration of H2O2 drops to near zero.  It is evident that the oxidation of
enfrl- ls Primarily accomplished by H2O2. Cases 2 and 3 include the same gases but for Case 3 the
H,0  m^ of to H202 and 03 is allowed. As a result, more than 95%  of SCfc is oxidized by entrained
thS.i?  °3 after 30 nrin of reaction time in Case 3, as shown in Fig. 2. When SO2« almost oxidized,
Ca «! -> -te 10n concentration for Case 3 is  more than four times that for  Case 2. The final pH value for
sienifi IS about 3'2 and is about 0.5 unit lower than that for Case 2. Obviously, entrainment of pollutants
   Tn^tiymodifies to cloud water acidity.                               ,  J         ...---.
resui?  ases 4 and 5 are explored the influence of scavenged aerosols on the cloud water acidity.  The
      ^shown in Fig. 3.  The sulfate and nitrate aerosols are major  contributors to the cloud water
    iv  Donate aerosols increase the  pH value, when they are just scavenged by cloud droplets.
   T  ' lncreased sulfate ions by the oxidation of S(IV) offset the above effect of carbonate loadings.
    neutrali2ed ammonium sulfate and nitrate aerosols reveal the moderate effect of acidifying the cloud
                                            561

-------
 water.  When they are scavenged by cloud droplets, the chloride aerosols can be converted to HC1 gas.
 However, the converted amount is extremely small due to very large Henry's law coefficient of HQ which
 is in the order of 103 M atrrr1.
    As shown in Fig. 3, the comparison of Cases 4 and 5 is similar to that of Cases 2 and 3, but the former
 includes the scavenging of aerosol panicles.  The difference in the pH values for Cases 8 and 9 is
 significantly larger than that for Cases 2 and 3, resulting from the addition of ammonium and carbonate
 aerosols in the former cases. The higher sulfate ion concentrations illustrated in Fig. 3 as compared to
 those in Fig.  2 are due to sulfate loadings.

 Dependence of Cloudwater Acidity upon Cloud Droplet Size
    In this study, the cloud droplet size distributions are prescribed by the Khigian-Mazin droplet size
 distribution.  The cloud droplet size spectra with respect to 5 liquid water content classes (0.1, 0.3. 0.5,
 0.7 and 1.0 g nr3) and 25 droplet size categories (from 0.35 to 32 ^im) arc evaluated.
    For simplicity, the microphysical processes between the cloud droplets are ignored.  The cloud droplet
 size distribution is assumed to be steady during the model simulation (about 10 min). Thus, the solute
 mass in each cloud droplet for species i is assumed to be proportional to the radius of the cloud droplet
    In order to test the dependency of the cloud droplet acidity on its size, the corresponding cloud droplet
 size distribution for the liquid water content of 0,5 g or3 is used as a representative distribution. The
 initial condition is assumed the same as that for Case 4. As a resuli, smaller droplets have higher pH
 values although the sulfate ion concentrations in them are much higher than in larger droplets, as seen in
 Fig. 4(a). When the droplet sizes are greater than 25 ton, the variation ofpH values with droplet sizes is
 not significant.
    The model simulation is also performed for the case in which the carbonate aerosols are excluded As
 seen in Fig.  4(a), the result is opposite to the previous one of full inputs. When  the droplet sizes are
 greater than 1.5 nm, the pH values change within only 0.2 unit The smaller droplets have higher acidity.
                                                  .
    By comparing the above two cases, the smaller droplets are found to be most sensitive to aerosol
 loadings, primarily resulting from their smaller volumes. Although the larger droplets are assumed to have
 more aerosols dissolved, their resulting pH values arc not sensitive to variation in droplet sizes. In Fig.
 4(b) arc shown the sulfate ion concentrations produced for these two cases.  It is found that the
 concentranons for the case of full inputs are only slightly higher than that for the other case for these
 droplets with radius larger than 3.5 urn, whereas, the former is about twice the latter for the smallest
 droplet. Nevertheless, the pH value for the smallest droplet for the former case is about 4.3 unit lower
 than that for the latter case. The dilution effect in larger droplets can be seen in these model simulations.
 ihe carbonate aerosols significantly neutralize the acid aerosols in the case of full inputs. The sulfate and
 nitrate aerosols are the dominant species to acidify the cloud droplets, especially for the smallest droplet.
     In the above case of no carbonates, the volume- weighed pH value over the cloud droplet size
 distnbudon is 3.40.  The bulk pH value as calculated  in Case 3 is at the same level, but slightly larger than
 the volume-weighed one. However, when the solute mass is assumed to be proportional to r2 and r3, the
 corresponding pH values are increased to about 3.42  and 3.43, respectively.
    For comparison between model simulations and experimental results,  the cloud microphysical,
 dynamical and chemical features during a cloud event of August 19, 1987 observed at Mt. Mitchell, NC,
 are studied.  In Fig. 5 arc shown the mean sizes of cloud droplet size distributions measured9 by the FSSP
 (Forward Scattering Spectrum Probe), and the corresponding pH values detected10 by a real-time CRAC
 (Cloud and  Rain Acidity/Conductivity Analyzer).  As seen from Fag. 5, the  pH values are strongly
 dependent upon the mean sizes of cloud droplets. The increasing acidity in cloud droplets during die last
 two hours of this cloud event is primarily due to decreasing liquid water content resulting from the
evaporation of cloud droplets at cloud dissipating stage. The corresponding ion concentrations, especially
 for sulfate and nitrate ions, dramatically increase, resulting from higher mixing ratios of pollutants to cloud
droplets. The dynamical and chemical features of a cloud are also dominated by the microphysical
 processes and the history of the air parcel producing such a cloud. The separation of individual cloud
droplets is technically difficult that the chemical composition and acidity are difficult to measure as ft
 function of measured upon cloud droplet sizes.  Our modeling study can help identify and quantify the
 effect of individual chemical processes on the final acidity of cloud droplets.

 CONCLUDING REMARKS
   The cloud chemistry model gives information regarding the dependence of the acidity in cloud droplets
 upon their sizes, the type of their distribution,  and  the importance of aerosol loadings. About 10% of
                                              562

-------
 gaseous SC>2 is in general consumed for producing the S(IV) and the sulfate ions. However, the addition
 or aerosols can dramatically alter the acidity in cloud droplets, especially for the smaller ones.  The
 scavenging of sulfate and nitrate aerosols is the most efficient mechanism to acidify the cloud rather than
 the oxidation of SC*2. It is feasible to link the our model with the dynamical cloud model, and thereby, lo
 further investigate the influences of the dynamical behavior of cloud droplets on the solute concentration
 and the resulting acidity.

 Table I. The initial condition for the simulation of
 acqueous phase chemistry in cloudwater.
Case
— — —
Gas
rv"\ f

1
	
concentration
ppm) 320
s®2 m
HN03 10
HC1
H202
a rv,.

50
T^ — : 	 • 	
2-
(ppb)
320
1
10
1
1
50
4*

320
1
10
1
1
50
 ar_ „   , —•*> »^««; as Case 2 but H^C** and Os
 "^remained in constant
 aiewS -ls^same^ Ca804 butH2°2"*
       °'~~n in constant
REFERENCES
ana '    Lln and v-K- Saxena, "In-cloud scavenging and deposition of sulfates and nitrates: case studies
  Q Parameterization," Atmos. Environ. (25A):2301-2320 (1991).
2 X] TJ
Arm   t"1 and v- K- Saxena, "Interannual variability in acidic deposition on the Mt Mitchell area forest,"
^maSt^DiarojL (25A): 517-524 (1991).

aboJ.K'iSaxena ^d N--H. Lin. "Cloud chemistry measurements and estimates of acidic deposition on an
    c cl°udbase coniferous forest," Atmos. Environ. (24A): 329-352 (1990).
4  l^  T
concln J^?°ne' R- J-  Charlson, D. S. Covert, J. A. Oregon and J, Heintzenburg, "Cloud droplets: solute
   '•wio-adon is size dependent," J. Geophvs. Res. (93): 9477-9482 (1988).
*-

AtmA«ABHe.B8 and p-  v- Hobbs, "The homogeneous oxidation of sulfur dioxide in cloud droplets,"
^UttiSfcJiQyaiQlL (13): 981-987 (1979).

atttiosSJ5°SSniann' W-D-Hal1 and H- R- Pruppacher, "A theoretical study of wet removal of
^oarrin    P°llutants. Pt. I: the redistribution of aerosol panicles captured through nucleation and
       on scavenging  by growing cloud drops," J. Atmos.  Sci. (42): 583-606 (1986).

^Uate^.2?8* and T- V- Larson, "The effects of microphysical parameterization on model predictions of
      Production in clouds," Tellus (42B): 272-284 (1990).
0,  b  f^\ *^
inflow of  ,!-ter and D-  J- Luecken,  "A simulation of sulfur wet deposition and its dependence on the
      ot sulf«r species to storms," Atmos. Environ. (22): 2715-2739 (1988).

;~ cloud?cFcIice i""1  v- K- Saxena, 'Temporal and vertical distribution of acidity and ionic composition
 99n"   coniparison between modeling and results and observations," J, Atmos. Sci. (47): 1117-1126
              and V. P. Aneia, "Chemical composition of clouds at Mt. Mitchell, North Carolina,
                  ): 41-53(1992).
                                             563

-------


      0  10 J«  M 40
                <•«•)
                              V  16  14 M  *« to i«
TtiM <•!•>
  Figure 1  Results of Case I. (a) pH viluc. (b)
  sulfttc ion concentration.





1
:- •







          TIB* mini
                                 tl«t (mini
 Figure 2. Comparison of Cases 2 (solid tine) and
 3 (dashed line), (a) pH value, (b) sulfate ion
 concentration.

                         «
                       ^ >«B
                       I
                    1   3
                       T .  .
        I,me  •••
                                 Ttet 
-------
      COMPUTER ESTIMATION OF THE ATMOSPHERIC
           GAS-PHASE REACTION RATE OF ORGANIC
 COMPOUNDS WITH HYDROXYL RADICALS AND OZONE
                        William M. Meylan and Philip H. Howard
                              Syracuse Research Corporation
                                      Merrill Lane
                                  Syracuse, NY 13210

ABSTRACT
       The Atmospheric Oxidation Program (AOP)  is a computer program that estimates  the rate
constant for the atmospheric, gas-phase reaction between photochemically produced hydroxyl radicals
(OH) and organic chemicals. It also estimates the rate constant for the gas-phase reaction between ozone
and olefinic/acetylenic compounds. AOP, which uses estimation methods developed by Atkinson and
co-workers, estimates  more accurate rate constants than the PCFAP (Fate of Atmospheric Pollutants)
program that is part of the U.S. EPA's Graphical Exposure Modeling System (GEMS). Due to its
superior predictive ability, the EPA is currently using AOP to evaluate the atmospheric fate of
compounds defined under Sections 4, 5 and 6 of the Toxic Substances Control  Act (TSCA).

INTRODUCTION
       Organic chemicals emitted into the troposphere are degraded by several important transformation
processes that include reaction with hydroxyl (OH) radicals or other photochemically-produced radicals,
reaction with ozone or direct photolysis1"*.  The dominant transformation process for most compounds
that occur in the troposphere is the daylight reaction with OH radicals3-4.  For some olefinic structures,
reaction with ozone is the major process7. The rates at which organic compounds react with OH radicals
Or ozone are a direct measure of their atmospheric persistence, and hence, their rates of reaction are
needed to develop exposure assessments and the ozone depletion potential for halogenated compounds.
       Rate constants have been  measured experimentally for only a small fraction of the organic
chemicals of environmental concern.  The rate constant for the gas-phase reaction with OH radicals has
fceen measured for less than 500 organic compounds4. Since experimental measurements can be difficult,
time-consuming and expensive, the ability to estimate rate constants has become increasingly important2
and estimation  methodologies  are of interest to regulatory agencies in preparing risk assessments of
chemicals released to the atmosphere5.   For example, when  experimental data are missing at the
screening level, the U.S. EPA must estimate OH radical rate constants for new and existing chemicals
included under Sections 4, 5 and 6 the Toxic Substances Control Act (TSCA)5-6. This  paper compares
   accuracy of two computer programs used to estimate OH radical and ozone rate constants.
           Methods and Programs
       Two separate estimation methods and computer programs have been developed, at least in part,
fcv research grants  sponsored by the U.S.  EPA.  Both programs  are based upon structure-activity
relationships (SARs) and rely solely on the structure of organic chemicals. They estimate rate constants
 t 25°C-  The first program is FAP (Fate of Atmospheric Pollutants) which was developed from the
combined methods  of Hendry, Kenley and Heicklen8-9.  FAP is part of EPA's Graphical Exposure
Modeling System (GEMS); the personal computer version of FAP is PCFAP.  The second program is
AOP (Atmospheric Oxidation Program) which is based on the methods of Atkinson and co-workers1'3-10.
Tt is currently used by EPA's Exposure Assessment Branch to evaluate chemicals under Sections 4, 5
  d 6 of TSCAS and by the German Environmental Protection Agency.
                                          565

-------
       Both  programs estimate an  overall  OH rate  constant by summing  individual OH  reaction
 pathways that include hydrogen abstraction from aliphatic C-H groups, OH addition to  olefms and
 acetylenes, and OH addition to aromatic rings.  PCFAP and AOP calculate hydrogen abstraction by
 different procedures; PCFAP uses a procedure based on bond dissociation enthalpies whereas AOP uses
 a procedure based on  substituent connections to CHj, CH2 or CH groups.  AOP adds several pathways
 not included in PCFAP such as hydrogen abstraction from OH groups and OH radical interactions with
 nitrogen, phosphorus and sulfur. In addition, AOP can detect difference in aromatic rings while PCFAP
 can not; for example,  PCFAP treats pyridine or triazine as benzene.
       Although time-consuming, it is possible to "hand-calculate" a rate constant using the methods in
 AOP and PCFAP given a thorough knowledge of the methods.  A much easier procedure is to enter the
 structure of a compound into a computer program as a SMILES (Simplified Molecular Input Line Entry
 System) notation, as in AOP and PCFAP. In both programs, a database of nearly 20,000 CAS Registry
 Numbers can be  used to automatically enter SMILES notations.  Once a SMILES in entered, AOP
 performs the calculation in less than one second.

       Accuracy of  Estimates for Reaction with OH Radicals.   A list of  448 compounds with
 measured OH rate constants was located using Syracuse Research Corporation's Environmental Fate Data
 Base  (EFDB)"'12. The bulk of this list was taken from a recent compilation by  Atkinson4.  The AOP
 and PCFAP programs  were then used to estimate rate constants for all 448 compounds and the estimates
 were  compared to the  experimental values. For the AOP estimations, 90% are within a factor of two of
 the experimental value and 95% are within a factor of three.  For the PCFAP estimations, only 49% are
 within a factor of two of the experimental value and only 66% are within a factor  of three. Since the
 range of experimental  rate constants  spans nearly six orders of magnitude, a statistical correlation was
 computed on a logarithmic basis. Comparing experimental to estimated value, AOP has a correlation
 coefficient (r2), standard deviation and mean error of 0.96,0.21 log units and 0.12 log units, respectively;
 PCFAP has a correlation coefficient, standard deviation and mean error of  0.51,0.80 log units and 0.52
 log units, respectively.  PCFAP is particularly inaccurate when estimating compounds containing
 phosphorus, sulfur (such as tniols, sulfides and aromatic  sulfurs), or  nitrogen (such as nitrites, nitro
 functions, aromatic nitrogens, or amines).  Figures 1  and 2 illustrate AOP and PCFAP's correlation with
 experimental values.
       Since most of the 448 compounds in  the experimental list were used to derive either the AOP
 or PCFAP methodologies, the accuracy suggested by the above statistics may not adequately describe
 the overall method accuracy. A more legitimate test of an estimation method is the ability to predict
 accurate values for an independent test set of chemicals that were not  used in developing the method.
 From the 448 compounds, 77 compounds were located that were not used to derive  either method. For
 the 77 compounds, AOP has a correlation coefficient (r1), standard deviation and mean error of 0.89,
 0.24 log units and 0.17 log units, respectively; PCFAP has a correlation coefficient, standard deviation
 and mean error of 0.44, 0.56 log units and 0.71 log units, respectively.  Table 1 lists a representative
portion of the 77 compounds.
       Chlorofluorocarbons  (CFCs) have raised an environmental concern due to possible destruction
of the atmospheric ozone layer.  Table 2 compares estimates from AOP and PCFAP to experimental
 values for various CFCs.   With the exception of  1,1,1-trifluoroethane, AOP produces much better
estimates.

       Accuracy of Estimates for Reaction with Ozone. AOP and PCFAP can estimate rate constants
for the gas-phase reaction between ozone and olefinic or acetylenic compounds. A list of 79 olefins and
acetylenes with measured ozone rate constants was located using Syracuse  Research Corporation's
Environmental Fate Data Base (EFDB)IUI.  Many from this list were taken from a compilation by
Atkinson and Carter7.  The AOP and PCFAP programs were then used to estimate rate constants for all
                                            566

-------
79 compounds and the estimates were compared to the experimental values.  Similar to the OH values,
the range of experimental rate constants for ozone spans nearly six orders of magnitude, so the statistical
correlation was computed on a logarithmic basis. Comparing experimental to estimated value, AOP has
a correlation coefficient (r2), standard deviation and mean error of 0.93, 0.42 log units and 0.27 log units,
respectively;  PCFAP has a correlation coefficient, standard deviation and mean error of 0.72, 0.88 log
units and 0.71 log units, respectively. PCFAP is particularly inaccurate for substituted olefins where the
substitutions are halogens or functional groups containing oxygen. Table 3 compares estimates from
AOP and PCFAP to experimental values  for various haloalkenes.

Conclusions
        AOP is clearly superior to FAP as demonstrated by its ability to estimate more accurate values
f r both OH radicals  and  ozone rate constants.  Leifer5'6 has critically evaluated the available SAR
methods for estimating OH radical  rate constants and  found the methods used in AOP (the Atkinson
SARs) to be the most accurate of all methods and applicable to the  widest number of structures. In
addition, the Atkinson SARs were  adopted by OECD (Organization for Economic Cooperation and
Development) in 1988 to be used as guidance when performing gas-phase transformation tests5. An
•  dependent evaluation has found the Atkinson SAR method and AOP software to produce generally
good estimates13.

REFERENCES AND BIBLIOGRAPHY

1   R  Atkinson, "Kinetics and mechanisms of the gas-phase reactions of the hydroxyl radical with
organic compounds under  atmospheric conditions,"  Chem. Rev. 85: 69-201 (1985).

2  R Atkinson, "A structure-activity relationship for the estimation of rate constants for the gas-phase
reactions of OH radicals with organic compounds,"  Intern.  J. Chem. Kinet. 19: 799-828 (1987).

-i  R  Atkinson,  "Estimation of gas-phase hydroxyl radical rate constants  for  organic chemicals,"
                . Chem. 7: 435-442 (1988).
 A  R AfV'nfinn- Kinetics and mechanisms of the gas-phase reactions of the hydroxyl radical with organic
             J. Phys. Chem. Ref. Data Monograph No. 1, Amer. Inst. Physics & Amer. Chem Soc., NY
 (1989).

 ,  A Leifer,  Determination of Rates of Reaction in the Gas-Phase in the Atmosphere. Theory and
 pLrij'/.<, r Rate of Indirect Photoreaction: Technical Support Document for Test Guideline S 796.3900.
 ppp 700/R-92-002, U.S. Environmental Protection Agency,  Office  of Toxic Substances, Exposure
 Assessment Branch, Washington, DC, 1992.

 f.  A Leifer,  netermination of Rates of Reaction in the Gas-Phase in the Atmosphere. Theory and
 p  ti'rf. A Bate of Indirect Photoreaction: Screening-Level Test Guideline $ 796.3900. Estimation of
 Tc^AnH-Order Rate Constant and Half-Life for the Reaction of Hydroxyl Radicals with Organic
 pr fflj^ig in the Troposphere. EPA-700/R-92-003, U.S. Environmental Protection Agency. Office of
       Substances, Exposure Assessment Branch, Washington, DC, 1992.
    R  Atkinson and W.P.L. Carter, "Kinetics and mechanisms of the gas-phase reactions of ozone with
    aric compounds under atmospheric conditions," Chem. Rev. 84: 437-470 (1984).

    nG Ilcndry a"H p A Kendrv. Atmospheric Reaction Products of Organic Compounds. EPA-56QA2-
                                             567

-------
79-001, U.S. Environmental Protection Agency (OTS), Washington, DC, 1979, pp 69-73.

9. J. Heicklen, "The correlation of rate coeffeicients for H-atom abstraction by HO radicals with C-H
bond dissociation enthalpies," J. Int. Chem. Kinet. 13: 651-665 (1981).

10. H.W. Biermann, H. MacLeod, R. Atkinson, A.M.Winer and J.N. Pittsjr, "Kinetics of the gas-phase
reactions of the hydroxyl radical with naphthalene, phenanthrene, and anthracene," Environ. Sci. Technol.
19(3): 244-248.

11. P.H. Howard, G.W. Sage, A. LaMacchia and A. Colb, "The development of an environmental fate
data base," J. Chem. Inf. Comout. Sci. 22:38-44 (1982).

12.  P.H. Howard, A.E. Hueber, B.C. Mulesky, J.S. Crisman, W.M. Meylan, E. Crosbie, D.A. Gray,
G.W. Sage, K.P. Howard, A.  LaMacchia,  R. Boethling and R. Troast,  "BIOLOG, BIODEG, and
Fate/Expos: New files on microbial degradation and toxicity as well as environmental fate/exposure of
chemicals," Environ. Toxicol. Chem. 5:977-988 (1986).

13.  M.  Miiller  and. W, Klein, QSAR in  Environmental  Toxicoloev-IV; J.L.M. Hermens  and A.
Opperhuizen. Eds. Elsevier Science Publishers, New York, 1991, pp 261-273.
Table L   Comparison of experimental and estimated OH radical rate constants for a
          partial list of compounds used to test the accuracy of AOP and PCFAP
              (rate constants reported in units of 10'1Z cnrVmolecule-sec)
                                     AOP
Experimental
PCFAP
2,2-Dimethylpentane
4-Methyloctane
n-Pentadecane
Isopropylcyclopropane
Cyclooctane
Pentane- 1,5 -dial
Cyclohexanone
2,5-Hexanedione
Hydroxyacetone
Methoxyacetone
1,1,1 -Trifluoroacetone
1-Pentanol
Cyclopentanol
2-Methoxyethanol
2,2,2-Trichloroethanol
2,2,2-TrifluoroethanoI
Ethyl n-butyl ether
Methyl tert-amyl ether
1,4-Dioxane
3-Methylfuran
3.22
9.95
17.87
2.85
11.16
46.9
12.55
5.82
2.31
4.87
0.109
7.77
12.78
11.18
0.29
0.25
18.5
6.13
26.4
106.6
3.37
9.72
22.2
2.84
13.7
23.8
6.39
7.13
3.02
6.77
0.0151
10.8
10.7
12.5
0.245
0.0955
18.1
7.91
10.9
93.5
1.56
5.70
7.47
3.25
4.62
47.5
2.92
1.35
3.17
10.62
0.0978
4.89
15.78
13.72
2.92
0.0475
19.2
2.38
36.0
5.1
                                           568

-------
Table 1.  continued.
                                    AOP
Experimental
PCFAP
Isobutyric acid
n-Propyl formate
Methyl trifluroacetate
n-Propyl propionate
n-Propyl butyrate
2-Butyne
Di-n-propyl sulflde
Dimethylnitramine
t-Butylbenzene
Acephenone
Benzyl alcohol
2,5-Dimethylphenol
2,6-Dimethylphenol
2-Nitrotoluene
1-Nitronaphthalene
1.80
2.89
0.216
3.07
4.16
29.29
24.0
2.88
5.08
1.61
7.99
115.4
54.1
0.81
2.7
2.00
2.4
0.05
4.0
7.4
27.4
20.0
3.84
4.60
2.74
22.9
80.0
65.9
0.70
5.4
2.81
1.32
1.48
1.68
2.24
1.81
2.50
0.20
5.29
5.10
7.98
30.2
30.2
30.1
34.0
Table IL Comparison of experimental and estimated OH radical rate constants for a
         list of chlorofluorocarbons.
             (rate constants reported in units of  10 u cmVmolecule-sec)
                                    AOP
  Experimental
 PCFAP
ChlorofluoromeUiane
1,1-Difluoroethane
1,1,1-Trifluoroethane
1 , 1 ,2-Trifluoroethane
1 -Chloro- 1 , 1 -difluroethane
1.1,1 -Trichloroethane
1 , 1 ,2-Trichloroethane
1,1,1 ,2-Tetrafluoroethane
1, 1-Dichloro-l-fluoroethane
l-Chloro-2,2,2-trifluoroethane
1 f2-Dichloro-2,2-difluoroethane
Pentafluoroethane
1 -Chloro- 1 ,2,2,2-tetrafluoroethane
1 , i.Dichloro-2,2,2-trifluoroethane
llBromo-l-chloro-2,2,2-trifluoroe thane
0.0315
0.0323
0.0108
0.0235
0.0036
0.013
0.332
0.0062
0.013
0.0239
0.008
0.0013
0.0052
0.020
0.016
0.0441
0.0034
0.0017
0.018
0.00358
0.0119
0.328
0.006
0.007
0.0162
0.026
0.0025
0.0102
0.0335
0.060
0.0164
0.114
0.0015
0.050
0.099
0.097
0.681
0.00057
0.0976
0.00361
0.239
0.000164
0.00104
0.00659
0.003
                                    S69

-------
(rale constants reported in units of

Vinyl fluoride
1,1-Difluorocthene
tram- 1,2- Difluoroethene
Thnuoroethene
Tctrafluoroeihene
Vinyl chloride
Hexafiuoropcopeoe
cis- 1 . M>ichloropropene
2-(Chlorofnethyl>-3-<:hk)co- 1
AOP
0.70
0.28
0,28
0.112
0.045
0.25
0.0112
0.0113
-propeoe 0.142
ru uzo raw constants lor naioai
10" cmVmolecule-sec)
Experimental PCFAP
0 70 on
0 19
0 ''I
0.14
0.092
0.24
0.0077 i:
0.015 i:
0.039 i:
on
on
.y(j
.90
.90
.90
1.0
            10
10*1 10^  10-" 10-"  10"
Figure 1. AOP estimates vs experimenui
         ''II rates (in ctnVinotecule-sec)
                                                     10"" 10""  10" 10""  10'" 10'   '0
                                                               Estimated
                               1 PCFAP estimates vs
                                  OH rates (in cmVmoIecuJe-sec)
                                       570

-------
    ISOPRENE EMISSIONS FROM WILLOW OAK TREES
                            Sarah A. Meeks, Bruce W, Gay, Jr.
                                  and Beverly E. Tilton*
                   Atmospheric Research and Exposure Assessment Laboratory
                                            and
                        Environmental Criteria and Assessment Office*
                            U.S. Environmental Protection Agency
                        Research Triangle Park, North Carolina 27711
ABSTRACT
    Measurements of isoprene emissions from 3-5 year-old willow oak (Quercus phellos) were mac=
 nder field conditions using a flow-through Teflon environmental chamber that enclosed the entire
U pling-  Emissions were sampled from early May through the summer and early fall of 1991.  Air
camples from the chamber containing the willow oak saplings were collected at exit ports directly into
Tedlar bags, cryogenically preconcentrated and analyzed by GC-FID. Isoprene was observed to be the
 rincipal organic compound emitted from the vegetation. A seasonal maximum was observed in late
P  -jj- fl^ may be associated with a phenological event in leaf development. Isoprene emissions were
found to be sunlight- and temperature-dependent, as other studies of isoprene emitters have  shown.
Isoprene was also measured from 30-year old willow oak trees using the static limb enclosure technique.
Isoprene emission rates were found to be reasonably comparable for the two techniques.  Experimental
procedures and results will be presented.
    Recently, there has been increased recognition of the need to understand better the role of biogenic
emissions in air chemistry, especially the chemistry of tropospheric ozone formation. Chameides et al. , 1
Crouse and Jeffries,2 and others have suggested that biogenic emissions may in some cases significantly
increase  model-predicted VOC  control requirements for ozone abatement.  Since  isoprene could
notentially play a greater role than the terpenes in ozone formation,3 additional data on emissions from
{najor isoprene-emitting species are needed.
    Survey studies by Zimmerman,4 Winer et al.5-6 and others,7 using brief sampling periods, have
 rovided some data on emissions of isoprene, as well as terpenes, from a wide range of vegetation
Pjieenous to ^ localized areas of study.  However, a lack of data on daily and seasonal variations in
'    rene emission rates and on the effects of environmental factors has hampered attempts to integrate
•soorene emissions into air quality modeling.  To date,  most modeling efforts have relied largely on
1 mission rate data for live oak seedlings (Quercus virginiana Mill.),  reported by Tingey et al.8 from
faboratory studies, for the development of algorithms for all arboreal isoprene emitters.  A broader
H tabase, including data obtained under field conditions, is needed to ensure accurate representation of
 n maior isoprene-emitting species. Results of field studies on isoprene emitters are especially needed
   determine whether emissions under field  conditions are  consistent with findings reported from
fhoratory controlled studies.
    Objectives of the study reported here were to measure isoprene emissions from willow oaks, a major
      :Lg ^d forest species of the southeast, under field conditions; and to identify the broad seasonal
^A d'umal patterns in those emissions.  Willow oaks have been included in surveys  of biogenic
   •   'ons but they have not been studied across a full growing season to determine patterns and ranges
           emissions.
                                             571

-------
EXPERIMENTAL METHODS
    The study was conducted from early May through early October of 1991. The willow oak trees
(Quercus phellos) used were 3- to 5-year-old saplings obtained from a local nursery and grown in
containers kept outside the research building.  Trees were watered daily and a dilute solution of a
complete fertilizer was applied weekly. For measuring isoprene  from the saplings, a flow-through
chamber system and short enclosure time were used to minimize plant perturbations and provide close
approximations of natural conditions. In addition, a few measurements were made of isoprene emissions
from a mature, approximately 30-year-old willow oak growing outside the research building, as well
as a one-time measurement of leaves excised from the mature tree and from the saplings. The branch
enclosure technique described by Zimmerman4 was used for measurements on the mature tree.  For
measurements on individual excised leaves, the leaves were supported on wet poly foam in a sealed
Tedlar bag and the bag was exposed to full sunlight outdoors.
    The flow-through chamber used to measure emissions from the saplings was a modification of the
method described by Winer et al.6 The chamber, cylindrical in shape, was constructed of 2-mil FEP
Teflon supported on an aluminum angle frame with a 65-cm diffusion ring mounted inside at the top of
the chamber to provide even dispersion of input air flow over the tree.  The chamber measured 112 cm
by  112 cm by 125 cm when open, and had a volume of about 500 L when closed and in use.  Zero
grade dry air, with no added humidity but with added CO2, was metered into the chamber at  170-180
L/min, or one air exchange per 3 min.
    For isoprene measurements, the chamber was placed over the tree crown and the film of the bottom
of the chamber was gathered and sealed against the tree trunk by tightly wound cording. Air flow was
directed down through the tree leaves and out of seven exit ports located at the bottom of the chamber.
Air samples were taken by attaching an evacuated 10-L Tedlar bag to one of the exit ports using a
Swagelok fitting and allowing the bag to fill as chamber air flowed from the port. Saplings were grown
in partial shade but sampled in sunlight. The tree and chamber were allowed to equilibrate for 10 min
before the first sample was taken, and then two more samples were taken at 5- to 10-min intervals.  The
dynamic flow system moderated temperature increases in the chamber, but there  was some increase,
which varied with solar intensity.  The temperature gradient between ambient and chamber air averaged
7 °C across  the study, and tended to be greatest around 1:00 p.m. local standard time (LSI).
    Except for the diurnal study, samples were taken around 1:00 p.m. LST to approximate  the time
of daily maximum isoprene emissions  reported by Ohta9 for  a Japanese live oak species (Quercus
serrata) and by Pierce and Waldruff10 using data in the U.S. EPA biogenic emissions inventory.  To
look at broad diurnal variations, measurements were made three or four times per day on 3 separate days
in summer 1991. A total of 83 measurements were made during the growing season. No samples were
taken  on rainy or fully overcast days.  Because of reported  relationships of isoprene emissions to
temperature  and light intensity, both temperature and photosynthetic photon flux density (PPFD) were
measured at  time of sampling. Air samples were analyzed for isoprene on a Hewlett-Packard 5890 gas
chromatograph using the system and method described by Seila et  al.8
    To calculate emission rate data on the basis of leaf dry matter, leaf dry mass was determined by
picking 20 leaves of representative sizes from the sapling and drying them to constant weight.  Then
leaves remaining on the sapling were counted and dry leaf mass for the whole sapling was extrapolated
from the value for the harvested leaves.  This procedure was repeated at intervals during the  study to
account for changes in leaf size, to look at changes in leaf moisture during the season, and to account
for reduced  numbers of leaves from harvesting and, late in the season, from leaf drop.

RESULTS AND DISCUSSION
    Table I shows an  overview of emission rate data  obtained from excised leaves from both  saplings
and the mature tree, from an enclosed branch of the mature tree, and from entirely enclosed saplings.
Only one observation  was made of sapling and mature leaves, but both were sampled  in bags  side-by-
                                            572

-------
side on the same day.  The emission rate of leaves from the mature tree was more than double that of
leaves from the saplings.  The table also shows that the isoprene emission rates from an intact branch
of the mature tree ranged from 32 (in partial shade) to 183 (in full sun) ng C (g dry mass)'1 h'1 (in July)
at 1:00 p. m.  LST. Isoprene emission rates from intact saplings varied from 26 jig, in May, to 253 /xg C
(a dry mass)"1  h"1, also in May. Notice the overall comparability of data for the three techniques.
    Data presented in Figure 1 are the emission rates from two saplings as measured by the flow-through
chamber technique. Measurements were made at or near 1:00 p.m. LST. This figure shows ranges and
averages of isoprene emission rates by month. Note that the average emission rates were highest in May
and in July.  Figure 1 also shows corresponding data on the temperature inside the chamber and on the
intensity of insolation as indicated by measurements of photosynthetic photon flux density, PPFD. Work
bv a number of investigators8'12>13 has shown positive correlations between isoprene emission rates and
temperature and between emission rates and PPFD. Temperature and PPFD are broadly correlated with
each  other, but PPFD can fall off rapidly when cloud cover passes over vegetation;  air and leaf
temperatures do not fall  as rapidly.   Temperature and PPFD strongly influence CO2  fixation and
 hotosynthesis, although carbon flow within leaves is also influenced by physiologic and environmental
factors.  Reports from Sharkey and coworkers12-14 indicate a coupling of photosynthesis and isoprene
 reduction. Still at issue is whether isoprene is emitted as it is produced, or whether it or its immediate
^recursors are stored in a metabolic pool in the leaf and emitted under a particular set of conditions, for
example, plant or leaf stress.14'15
    Even though average emission rates are nearly comparable in these data in May and July, note that
the efficiency of production of isoprene is greatest in May;  that is, the average and ranges of PPFD and
temperature are lower relative to emission  rates in May than in July. A number of factors may be at
  ork here. First, the efficient production of isoprene in May relative to temperature and PPFD indicates
    the phonological state of the plant may influence isoprene production. For example, the more rapid
  etabolism of the young, growing leaves may be a factor. Also, leaf moisture is higher in young leaves
Jhan in older leaves, ranging in this study from around 70%  in late April to around 48% by October.
I «af moisture has not been postulated  as a major influence on isoprene production and emissions, but
•tfc a roaJ011 factor m efficient leaf CO2 fixation and Plant metabolism. One report has indicated that
•creased relative  humidity in the  air enhances isoprene  emissions,13 possibly  because of increased
^matal conductance.  Finally, the cuticular layer on the upper leaf surface is thinner on young leaves,
 uch ti^t volatilization from the upper surface as well as emission through stomata on the lower leaf
S rface could occur and thus help account for relatively greater isoprene production early in the growing
Lason   The question of possible volatilization of isoprene from surface structures in addition to or in
 Ice of release through the stomates remains unresolved in the literature.8-12'15
    Scattergrams of the data, not shown here, indicate that the relationship of emission rate to light and
  moerature factors is curvilinear and not appropriately analyzed by linear regression. The scattergrams
 i    indicate that the relationship of temperature to isoprene emission rates may be tighter than that of
PPPD  to  emission rates.   Tingey  and coworkers*  reported  that  temperature and PPFD are
•    dependent; that is, they are interactive in a nonlinear manner relative to isoprene emissions. Ohta,9
  h  corrected some of his emission rates for temperature, using the equation formulated by Tingey and
      kers 8  found that the relationship of emissions to temperature  is log-linear.
°°WAn indirect way to look at effects of PPFD,  temperature,  and  plant-related factors is to look at
   mal variations in emission rates since incident radiation and temperature vary over the course of a
A     From an air quality standpoint,  what is more important are the diurnal patterns of isoprene in
  1 tion to ozone formation.  If isoprene emissions peak when ozone concentrations also peak, what is
*f   jative role of isoprene in ozone formation? Does isoprene under those conditions serve as an ozone
    ursor or as a potential chemical sink for ozone? What are the competing reactions and what are the
VreC   trations  of NOX, urban or rural, that would influence  the role of isoprene at midday?
                                             573

-------
    Figure 2 shows the broad diurnal variations in isoprene emissions for three separate days.  The
 values are averages of duplicate measurements from each of two saplings for June 11,  and from one
 sapling for August 22 and September 3. The patterns shown here are consistent with diurnal variations
 in isoprene emissions reported by Ohta9 from field measurements on live oak and predicted by Tingey
 and coworkers8 on the basis of their controlled experiments on a different live oak species.  The typical
 pattern is a rise in emissions through the morning, a maximum at midday or in early afternoon,  and a
 drop, sometimes  sharp, in emissions from mid- to late afternoon.  Note the temperatures and PPFD
 values  each  day  for respective emission measurements.   Comparison  of maximal emissions and
 accompanying temperature and PPFD emphasizes the rough correspondence between these factors and
 emissions. These curves not only show the broad diurnal pattern, but the seasonal changes in isoprene
 emission rates as well.   Ohta9 reported a seasonal maximum in September, but he was studying a
 Japanese species of live oak, under  the climatic conditions prevailing in Japan in September. It should
 be noted that live oak trees are evergreen species of oak in which leaf loss occurs but never totally and
 not just at one point in the year.  The findings of this present study corroborate the conclusion of Ohta,9
 however, that insolation, or PPFD, is not the chief determining factor.  Note from  Figure 2 that
 emission rates not only decline over the season, but that isoprene  production efficiency (production
 relative to incident radiation and temperature) diminishes considerably in later summer and early fall,
 a pattern also apparent in Figure 1.  As with diurnal variations,  the seasonal pattern in emission rates
 is of particular interest in relation to ozone formation.
    It is of interest to compare the emission rates found in this study with those reported for other
 isoprene emitters, especially other oak species. Table II summarizes emission rate data from a number
of field survey or  controlled physiologic studies.5'8'16"22 To provide a basis for comparison, emission
rate data are reported here as pg C  (g dry mass)'1  h'1, made more comparable by giving the emission
rates observed  at or near 30  °C, which has been  shown to be the  optimum temperature  for
photosynthesis.  As this summary shows, the data obtained in  this study are consistent with data reported
for  a number of isoprene emitters.

SUMMARY AND CONCLUSIONS
    In a study covering spring through fall 1991, isoprene emissions were measured from  willow oak
saplings, using a  flow-through Teflon  chamber.  Observed  emission rates are consistent with values
reported for a number of other isoprene emitters, including  a half dozen other oak species. As other
investigators have found for  other species, diurnal variations are seen in which maximal  rates  occur
shortly  after  midday.   Seasonal variations are also apparent, with a seasonal decline in emissions
occurring from mid- to late summer through early fall.  The relationships of isoprene emissions to
environmental factors  such as ambient  air temperature and photosynthetic photon flux density, which
have been indicated by controlled laboratory studies, are present but are less clear under field conditions
across a growing season than in short-term controlled experiments.  The air quality implications of the
range of emissions from willow oak found in this study merit attention, since emissions from young
saplings reached as much as 253 /ig C (g dry mass)"1 h"1 in spring. In addition, the implications of peak
isoprene emissions at midday, when ozone peaks also commonly occur, as well as the seasonally of
emissions relative to the seasonality of ozone,  merit consideration and investigation.  Finally, further
comparison is needed of emission rates from saplings and mature trees under field conditions, even
though measurements may be systematically biased by the different enclosure techniques required.  Such
a study is especially needed since the emission rates relied upon most in air quality models were obtained
from seedlings in  controlled laboratory experiments.
                                            574

-------
REFERENCES
i    W.L.  Chameides,  R.W.  Lindsay, J. Richardson, and  C.S.  Kiang,  "The role of biogenic hydrocarbons in urban
photochemical smog:  Atlanta as a case study," Science. 241: 1473-1475 (1988).
2    R-  Crouse and H. Jeffries, "The contribution of biogenic hydrocarbons,  carbon monoxide and methane to ozone
,-roduction in 33 urban areas," in Proceedines of the 1991 EPA/AWMA International Symposium on Measurement of Toxiq
  A g dated Alr Pollutants. VIP-21, Air & Waste Management Association, Pittsburgh, PA, 1991.
a   B Dimitriades, "The role of natural organics in photochemical air pollution," J. Air Pollut. Control Assoc. 31: 229-235

A   pR  Zimmerman, Testing of hydrocarbon emissions from vegetation, leaf litter and aquatic surfaces, and development
 ', —Ithivioloffv for compiling biogenic emission inventories. EPA-450/4-79-004, U.S. Environmental Protection Agency,
SsSrdi Triangle Park. 1979.
    A \x Winer et al. Investigation of the Role of Natural Hydrocarbons in Photochemical Smog Formation in California.
Final Report, Contract No. AO-056-31, California Air Resources  Board, Sacramento, CA. 1983.
    A Winer,  J- Arey, S. Aschmann, R. Atkinson, W. Long, L. Morrison, D. Olszyk, Hydrocarbon Emissions from
Y-^rion F"'"d in California's Central Valley. Final Report, Contract No.  A732-155, California Air Resources Board,
- ^*        yi A  lOftQ
Cocr&mefito, ^-*** i*0*'
    n Lamb H  Westberg, and G. AUwine and T. Quarles, "Biogenic hydrocarbon emissions from deciduous and coniferous
Les'in the United States," J.  Geoohvs.  Res. 90(D1): 2380-2390 (1985).

-------
 T»MrI.  b
•Moot from willow oak, neuurrd a!
                                                                                  900
          im p.«. LSI.
                     K C (| df> •••)•' b '
                              77-
                             IM»
                           «  l«

                                         j to
                                           h««
                                                •iKI
       .
                    I ho* ohwvod • J
Iwhic tl, Hrj>or1«J tooprtat rnikdon rale* from vcfrtaliuu.
M C d dry maaa) ' b '.

tpw-




Oregon .'iwrtm fmnymnm l^i-ugl i

Ltv* oik (CWmu nrjfiiuiWKi Mi// )
a (CWmu rfryMowi MU )
Cowl live .«k (ffwrrw agnf,,l,a Ntr)
Willow iU.I,
                                                                Out iknvn» fmol m "» '» and Umpmilurr I I > f«i iinmnu. inaw.

                                                                          Figure 1.
                                                                   S-00   9:00   tOrOO  11:00  1200   1410   2«J   3:00
                                                                 Diurnat »»h»Uom in noprtnt cmiMuon r»1r of willow (ink utplinK<>
                                                                 Numlwn. at d»U point* »r« phcHosyrrthrtw phottm flux drnMt)
                                                                            ttmprralurr (*t'l  »l lim» o( mrasuirmeni

-------
                 Session 14
  Remote Sensing FTIR Open Path Techniques
Thomas Pritchett and William Vaughan, Chairmen

-------
    OPERATIONAL CONSIDERATIONS FOR THE USE OF
                   FT-IR OPEN PATH TECHNIQUES
                      UNDER FIELD CONDITIONS
                                George M. Russwurm
                        ManTech Environmental Technology, Inc.
                         Research Triangle Park, North Carolina
ABSTRACT
      As the Fourier transform open path technique is used by more and more people, the need
for standardizing some of the operating features is becoming more important. There are many
proposed uses of the  FT-IR, but they all can be categorized as  either short-term,  intensive
monitoring programs or permanent installation, long-term monitoring. Various aspects of these two
monitoring philosophies are discussed in this paper. The four major topics covered are QA/QC
data, site selection, data acquisition, and 1$ and background spectra.

      Although the research described in this paper has been funded by  the United States
Environmental Protection Agency through  contract  68-DO-0106 to ManTech  Environmental
Technology, Inc., it has not been subjected to Agency review and therefore does  not necessarily
reflect the views of the Agency, and 'no official endorsement should be inferred.

INTRODUCTION
      As the Fourier transform infrared (FT-IR) spectroscopic technique for the measurement of
atmospheric gases is used by more and more people, standardization of operational procedures has
become critical. This operational standardization for a growing number of users is problematic
because the various instruments that are available have not been designed according to standard
specifications.   Nevertheless, the intercomparison of  different  instruments  using  similar
interferometers has been favorable, as has the comparison of the open path technique to older,
more mature measurement devices. Therefore, the standardization process should be guided by
a consideration of the measurement and instrument parameters that are important to the quality
of the data, as well as the  ancillary operational information that is necessary to produce data of
defensible and known accuracy and precision.
      The many proposed uses  for the  FT-IR open path technique all fall into two major
categories: permanent installation for long-term measurement and temporary installation for short-
term, intensive measurements. Although these two  measurement applications  require  similar
QA/QC procedures and operational techniques, they are not completely overlapping. Perhaps the
most significant difference is that for the short-term measurement operation the field-gathered
QA/QC data must Iar8ety be compared to data that is acquired under laboratory conditions.  It
is not likely that the intensive program will be conducted for a long enough time to acquire a self-
contained set of data. This paper describes four aspects of field operation using the FT-IR. They
are QA/QC data, site selection, data acquisition, and  IQ or background spectra.

QA/QC DATA
      The  prime purpose for the QA/QC data is to provide the end user  with  sufficient
information about the instrument operation to determine the quality of the experimental data. As
  minimum, the user must (1) determine a frequency or wavelength by using a known reference,
/2) determine  a return beam intensity, (3) measure the atmospheric waler vapor pressure, (4)
                                        579

-------
 obtain data with a short cell that contains a mixture of gases, and (5) determine the total time
 required to perform these activities.
       A first consideration when using a frequency or wavelength standard is determining whether
 any shifts have occurred.  However, additional information is gained if the full width at half-
 maximum of a set of selected absorption lines is also recorded.  When narrow lines as those
 produced hy methane are used, this parameter should give a true determination of the resolution
 of the instrument. This information together with the peak positions of a set of lines actually
 determines the overall effectiveness of the FT-IR.  This data is conveniently collected from the
 single beam spectra, but it is recommended that the data be taken from the absorption spectrum
 if that is the one used in analysts. It should be noted that this procedure will not  determine
 whether the light source has changed its operating temperature or the detector its sensitivity.
       Water vapor and path length play an important part in the overall return intensity.  Qearly,
 when the path  length becomes great enough, the return intensity must fall off as the square of the
 distance.  For  small ranges it is to be expected that the  total integrated absorbance due to water
 vapor and carbon dioxide is linear with the path length. For a fixed path length the return intensity
 may not be linearly related to the vapor pressure of water alone.  Therefore, to use the total return
 intensity as a diagnostic tool, a library of data must be obtained.
       The use of a short cell filled with a mixture of gases may be the most convenient way to
 obtain any data concerning the wavelength and resolution stability of the instrument. If appropriate
 mixtures are used, the data could cover most of the wavelength region. The cells can be sealed to
 ensure the integrity of the mixture.
       Perhaps the most difficult  aspect of planning a QA/QC program is determining the
 appropriate amount of time to spend on acquiring the data. It will probably be necessary to spend
 more of the total available time acquiring QA/QC data for a  short, intensive study than for a
 permanent installation, long-term effort. As a general rule, however, a reasonable length for the
 QA/QC segment of a sampling study would be one that requires no more than 25% of the total
 time available  for the short, intensive effort and  no more than 15% of the time available for the
 permanent installation.

 SITE SELECTION
       The long-term, more or less permanent Installation in a region where large excursions ia
 water vapor pressure can be expected may pose some  difficulties when the retroreflectors are
 situated.  It is reasonable to expect  the vapor  pressure to change from 5  to 30  torr at many
 installations. This implies that there will be occasions when larger portions  of the  spectrum are
 opaque, and even in fairly clear regions, the water absorption will change by a factor of 6,  Qearly,
 this will  make  an impact on the path length chosen and therefore the  detection limits of the
 technique.  The effects of water vapor must be determined  for each gas to be measured, and
 operational strategies must be determined before the final configuration is selected. If different
 paths are to be used, the conditions for switching from one to the other must be defined. The
 effects of water vapor may indeed  preclude the  measurement of various compounds at various
 times.
       For short-term, intensive monitoring, the compound selection may have to be tailored to fit
 the conditions found in the field.  For most short-term field operations, the operator will not have
 the luxury of selecting from among many path configurations or determining optimum time periods
 for performing  the measurements.
       One question that has arisen during site installation concerns the appropriate height above
ground level for transmitting the beam.  The possibility exits, when the  surface temperature is
changing, for the beam to wander off the retroreflector.  This variance is caused by a gradient in
the index of refraction of the atmosphere, and the effect seems to be greatest during the twflight
times of the day. If Ihe beam is well collimated and only slightly larger than the retroreflector, ft
                                           580

-------
 can wander enough to significantly diminish the signal strength. This phenomenon has probably
 never been reported because most beams being used are large in comparison to the retroreflector.

 DATA ACQUISITION
       The rate at which the data are collected must be dictated by the expected rate of change
 in the concentration.  Taking data as a single spectrum for more than about 15 min is futile unless
 the sampling time is extended to at least 1 h so that the signal-to-noise ratio can be increased by
 a factor of 2.  In most cases it  is much more appropriate to collect data in 2- to 4-min increments
 and if necessary to subsequently co-add the spectra.  When the plume is small in comparison to the
 oath length, it may move in and  out of the path.  Under these conditions, long sampling times
 actually reduce the signal-to-noise ratio.
       The basic information that is acquired by the remote sensor is the interferogram; the data
  hould  be taken in 2- to 4-min increments and archived  for later processing.   Although 2-min
 S cquisition times indicate the need for a  lot of computer storage, large-volume  disks are now
 available,  as are data compression techniques.
       The primary piece of ancillary data that is required is the vapor pressure of water in the
  tmosphere. It is not satisfactory to record only the relative humidity because it is the total number
 a, water molecules that determines the amount of interference to be expected.

 I AND BACKGROUND
       Converting the data to an absorbance spectrum requires a knowledge of the response of the
 •  trument in  the absence of absorbers. This spectrum is called the IQ spectrum. When open path
 ins     are used, discrete measurements of the compounds of interest in the atmosphere cannot
 SeDbtained, and* some mechanism must therefore be used to acquire an IQ spectrum.  There are
 f  ° ways  to accomplish this:  (1) to take a spectrum with  a path length short enough so that the
  ^  Chance due to the target gases is not measurable, (2) to take a spectrum upwind of the source,
 fruo wait until the target gas concentration goes to zero, and (4) to make a spectrum synthetically.
       When obtaining an I, spectrum by using the first  technique, it is critical to understand that
    detector can become saturated when a short path is used.  For most of the systems available,
  h    ath will  probably be at least about 20 m (one way), but the optimum distance has to be
 *he ^Ljjned for each  instrument.  Technique 2 can be  used  if the upwind side of the source is
 "ete jbje> i,ut the technique  requires a second retroreflector or a wholesale movement of the
 acces  -j^jjuique 3 can only rarely be used at most sites and should not be depended on. A
 SCIlSh tic spectrum (technique 4)  can always be made, but it is very time-consuming.  However,
 syp***   l^tvypot is to be measured quantitatively, this last technique is the only valid one to use.
       The background spectrum is  created by that energy entering the system from the  300*
    kbody background. The field of view of the  telescope generally is larger than the retroreflector,
  At allows  light  from  the surroundings  to enter  the system.  If this light is modulated by the
 ?°  rf  ometer, it produces  a spurious signal that must  be subtracted from the data spectra.  To
 interter    su|,traction, the operator needs only to turn the instrument light source off and record
 perform i

 2 sPe  rj*jje final question is how often these IQ spectra should be recorded. Certainly, whenever
      .  a  change in the water vapor or  carbon dioxide, new !„ spectra must be recorded. Twice
 tb®re      n jn the absence of any changes, is probably  prudent.  Also, the background spectrum
  h  Sid  be  recorded at least twice a day  (daytime/nighttime).


 ^   The need for standardizing FT-IR  field measurements has been established. This paper
        QA/QC considerations that must be addressed in developing a reliable standard procedure
preseflts^.^  ^ JR instrurnents in fie]d studies.
for '"
                                           581

-------
             A TECHNIQUE TO DERIVE  BACKGROUND
          SPECTRA (U FROM SAMPLE SPECTRA  (I) FOR
        OPEN-PATH FTIR  SPECTROSCOPY APPUCATIONS
                      Robert J. Krfcks and Douglas E. Pescatore
                            BLASLAND, BOUCK & LEE
                      RARITAN PLAZA 111, RELDCREST AVENUE
                           EDISON, NEW JERSEY. 08837
                       Robert H. Kagann and Carl L McCautey
                              MDA SCIENTIFIC, INC.
                          3000 NORTHWOODS PARKWAY
                                   SUITE 185
                           NORCROSS, GEORGIA, 30071
      The application of open-path Fourier-transform Infrared (FTIR) spectroscopy in meeting air
measurement needs depends on the creation of a sample absorption spectra, which Is derived
from intensity measurements of both background spectra (IJ and sample spectra (IJ.  Use of la
values that are inappropriate or not representative because of changing environmental conditions
is frequently a concern that must be addressed.  Large errors in the reported open-palh data and
the inability to analyze portions of the collected data set may result from changes in la shape and
contaminant content when collection of appropriate and representative I0 values Is Impractical.
Such limitations to the collection of I0 data may arise ffom logistical constants, such as during
continuous fixed-station monitoring of process operations at an industrial facility.
      This paper presents a procedure that may be used to derive a representative I0 spectrum
from previously collected I spectrum. The use of the approach for continuous process monitoring
and ambient air toxics measurement is investigated.  The results of testing this procedure are
provided and evaluated. Limitations of the technique and possible improvements are discussed.

INTRODUCTION
      A number of methods have been established to obtain background (IJ spectra for open-
path FTIR applications. Synthetic backgrounds have been constructed to follow the genera) shape
of the collection single beam spectra (I).1 The  inability lo properly handle water vapor or other
Interfering species In the regions of analyses (imits the usefulness of this technique in open-path
measurement applications. Standard approaches for obtaining I0 spectra Involve spectra collection
upwind or offwind of the source,2 spectra collection along the measurement path at times when
the target compounds are not present,8 or spectra collection over onfy a short portion of the
measurement  pathway.   These methods are generally satisfactory for producing 10  spectra;
however, for tow-level target compound concentrations or when the time between successive I9
                                     582

-------
 measurements is long, any changes in baseline of the I  spectra can be significant.
       This paper describes a technique which involves automatically generating a background I0
 spectrum during a continuous sequence of measurements. The I0 spectra are generated directly
 from the I spectra in an iterative manner, so that the nm I spectrum of the sequence is paired with
 the I  which was calculated from the previous measurement, n - 1 .  The technique is described in
 detail and  examples of its application to actual  open-path FTIR data are provided. The method
 is tested using synthetic spectra provided from  gas library reference spectra and an open-path
 field spectrum free of contaminants. The impact on minimum detection limit (MDL) improvement
 's discussed, and the present limitations of this  technique, particularly when dealing with below-
 MDL species, are examined.

 METHODOLOGY
       The  procedure described in  this paper to generate I0 spectra from I spectra is referred to
    tne iterative technique, as it involves generation of I0 spectra directly from  I spectra in an
 Iterative manner. This technique requires an initial I0 spectrum obtained in a manner that provides
 the best representation of collection pathlength  and water content. The time between collection
  f an initial I0 and the  start of data collection should be minimized.
       Figure 1 presents a flowchart of the iterative technique for generating I0 spectra. The first
     involves collection or  selection of an  initial  I0 spectrum. The  next step is to obtain a single
    m I spectrum, followed by formation of an absorption spectrum, A,  that is created using the
 •Tal I  spectrum and the first I spectrum.  Next, the concentration analysis on the target gases
 •   erformed.  If  any concentrations are  detected, they are then subtracted from the absorbance
 IS  ctrum.  I is then recreated from the  modified A spectrum,  using the initial I0  spectrum.  The
 sPe atecj'l  spectrum now becomes the I0 for use with the next single beam I spectrum collected,
 "d the process is repeated with each sequential I spectrum collected.
an     The  procedure  for producing a single beam spectrum from an absorbance spectrum and
     n Sjngie beam I0  spectrum was initially verified by using two existing single beams, I, and I2,
*?i  Lire 2} to form an absorbance spectrum, A, 2  (Figure 3). The generated single  beam spectrum
  ?Ftaure 4) was obtained from I2 x 10'A1>2.  I, was then divided into I,  producing a straight line
 I* ^lSum (Figure 5), which requires that the single beam spectra \z and I, be identical.
specu ^e  data  collection and experimentation for this project were carried out using an MDA
  -antjfic Model 282080 open-path FTIR system, consisting of the FTIR unit, a corner-cube based
  t  oreflector, a plane mirror, and a Kontron 386 personal computer. To minimize  electromagnetic
    rference, signal transmission was carried by  fiber optics cable. The  basic software used was
    i ctic Corp. Lab Calc software, with enhancements provided by MDA Scientific and Blasland,
    ek & Lee. The spectral library used for method development and testing was provided through
      Scientific by Infrared Analyses, Inc.  Some additional library spectra were supplied directly
     MDA Scientific and were generated by Blasland, Bouck & Lee. The gases used as part of
      gthod evaluation were supplied by Scott Specialty Gases and analyzed by Scott to 1-2%

                 g|x  jteratjve ^ technique tests were  performed.  Two of the tests involved
          ^ ^ gx  erave                  were  perorme.    wo o te tests involved
      ration of synthetic mixtures in which the target and interferant compound concentrations were
pr°P~   he rernaining tests involved data collected during actual field investigations. For all tests,
    H absorbance file was first analyzed for the components contained using classical least squares
eiSf\  analysis supplied with the open-path  FTIR system software.  Analysis results were
fit    ated using the initial I0 for the set of spectra. The iterative technique for generating I0 spectra
0ene*hen applied, and absorbance files were produced and analyzed  using LSF analysis to
was trw  concentratj0ns and concentration residuals. The concentration residual is equal to three
genera"  tan
-------
       Method  Test  1  involved the  use  of  a  series of mixtures containing  chloroform,
 tetrachloroethylene, and  freon-11 as target compounds, with water and methanol as interferant
 compounds.  The target and interferant compounds were added, through the use of library
 spectra, to typical open-path absorbance spectra formed from two  background single-beam
 spectra containing only normal atmospheric components.4 The initial I0 was one of the clean single
 beam spectra.
       Method Test 2  involved the use of series of mixtures in which benzene, mesitylene, and
 methylene chloride were chosen as target compounds. Water vapor was the interferant, and it was
 additionally added in varying concentrations to each absorbance spectra  in the series randomly
 shifted by 0.5 wavenumbers to simulate water peak location change.
       Method Tests 3, 4, and 5 involved applications of the technique to real spectra collected
 during  projects using  open-path  FTIR  for  data  quality  assessment and  emission rate
 determinations.  Method Tests 3 and 4 used data generated during a project carried out for
 benzene, toluene, ethyl benzene, and xylene (BTEX) emission estimations,  in which n-octane and
 iso-octane were used as  surrogate compounds for Cfl and higher straight and branched aliphatic
 hydrocarbon  concentration  estimation.   Method  Test  3   involved  iso-octane  and  octane
 concentration analyses, and Method Test 4 involved benzene analyses used for quality assurance
 assessment of measurement accuracy.  Method Test 5 used data generated  during a project to
 measure carbon monoxide and methane along a busy roadway in Munich, Germany.
       A final  method  evaluation was  carried out  (Method Test 6)  which dealt with a potential
 limitation of the  I0  generation technique caused by presence of target compounds  below MDL
 which slowly increased in concentration with time.  In this situation, the successively generated I0
 spectra would contain an increasing amount of target compounds and the resultant absorbance
 spectra would not show the presence of the target compounds as they would  be below the MDL
 level.  Method Test 6  was designed  to illustrate this limitation and  to evaluate a  solution by
 incorporation of a "feedback" loop to minimize the problem. The target compound used In this test
was trichloroethene, with  chloroform,  carbon tetrafluoride, and 1,1-dichloroethane present as
 interferant compounds.
      The impact of use of generated I0 spectra on MOLs was studied for three compounds using
 spectra collected during a day of project work at a Superfund site during the fall of 1991.(5> The
 target compounds were analyzed for in their prominent absorbance regions and were not detected.
The  MDLs were estimated based on  two times the concentration residual provided from LSF
analyses.

RESULTS
      Table 1 presents the results from Method Test 1.  The concentrations derived using the
iterative I0 technique showed the feasibility of its use. This test did not show major differences in
the quantification of the target compounds using an iterative I0 and a single initial I0. Analyses of
the iterative I0 absorbance spectra gave slightly better quantification for trichlorethyleneand freon-
 11 and slightly worse quantification for chloroform as compared to the single initial I0 analyses.
However, the analyses of  the absorbance spectra based on only an initial I0 showed some toss of
sensitivity and identification failure (#7  run for freon-11 and #6 run for chloroform), whereas the
iterative I0-derived spectra analyses provided values in both cases. The iterative I0 analyses results
showed significantly lower concentration residuals that reflect better LSF analyses.  For compounds
with  two analyses  regions, the use  of iterative I0  spectra provided much better agreement In
concentration  values between analyses  regions and  reasonable concentration residuals.  The
analyses of the initial I0-derived spectra showed considerable failure in the secondary analyses
regions.
                                          584

-------
       Table 2 presents the results of Method Test 2.  There is a dramatic difference in analyses
 results, as the use of the initial I0 caused the LSF analysis to fail to identify and quantify two of the
 three target compounds, benzene and methylene chloride, in runs #2 through #6, The third target
 compound, mesitylene. was lost at run #4. The iterative I0 technique provided spectra for which
 i op ana|ys'es correctly identified all target compounds in  runs #2 through #4, and identified
 mesitylene and benzene in runs #5 and #6. The quantification of benzene and mesitylene were
  deauate (5.2 - 10.3% error for benzene and 12.2-45.5% error for mesitylene). Methylene chloride
  uantification was much poorer.   Initial poor LSF quantification caused  incorrect compound
   btraction and subsequent carry-over of residual methylene chloride to the next iterative I0.  The
 S   se of the poor methylene chloride quantification was the strong water  influence in the regions
 °  thvlene chloride absorbs.  The shift in wavenumber of the water spectrum, which simulated
 171   st-case absorbance spectra noise levels, caused the LSF analysis to fall.
 w    "      3 present the results of Method Test 3.  The concentration values generated for n-
        and iso-octane using the iterative I0 technique were very similar to the field results for both
     oounds  All iterative I0- resultant concentrations were slightly tower (within 1 % for n-octane and
Cn<& for iso-octane)  than  those provided  using  initial I0  based absorbance  spectra.  The
1°%  ntration residuals decreased by a factor of 2 - 3.5 for the analyses of the iterative I0 based
               presents the results of Method Test 4. Overall improvement in quality assurance
           results were  seen in all  concentration residual  values  and in  two of the three
accura  *  Qn va|ues  The average of the three runs showed an accuracy improvement of about
°°Sf and almost 100% reduction in the concentration residual when using the iterative I0 technique.
189&- aTab)e 5 presents the results of Method Test 5. The ambient atmosphere was measured on
    1 .  walk on the downwind side of Wolfrathauser Strasse, a busy road in Munich, Germany. Two
a  H'pnt species were measured, carbon monoxide and methane. Each species was analyzed first
arn   ina a  background spectrum measured with the retroreflector array set very close to the
^  mrrter/receiver telescope so that the atmospheric path was less than one meter (close-in IJ.
transmit  ana|ySis was performed using the  iterative background generation  procedure.  The
^ S6K « orocedure was restarted in run #5 after the round-trip path length was reduced from 200
iterative P    meters. Therefore, the iterative analysis for both gases in Run #1  and  Run #5 are,
metef cessity identical  to  the  close-in  l? analysis.  However,  in all of the other runs, the
^ "ntration values agreed very well with those from the  close-in I0  analysis.  The  iterative
concen   resu|ted in significant reduction  of the concentration residual.  This comes about
techniq"     background spectrum  of  the (n -  1)* measurement is almost identical to the
{jecause      Spectrum of the  n* measurement, except that the absorptions due to the target
rrieaSeUhave been subtracted out.
gases i»   6 presents the results of Method Test 6. Trichloroethytene (TCE) showed no detection
        al values increased from 0.5 to 2.5 ppm-m.  At 2.5 ppm-m, TCE should be detectable, but
0$ actual       Reraise |0 spectrum used to form the absorbance spectrum contained only 2 ppm-
atthtePfVp   The resultant absorbance  spectra apparently contained only  0.5 ppm-m of the
&  °    nd  which is below the acceptable detection limit of twice the concentration residual value
comP°u!\ ' j^Q reuse of the original background single beam spectrum BK2 (no TCE) with single
(2 PPm"oectrum DL5 resulted in a 2.87 ppm-m value of TCE.  Removal of the TCE and  creation
t>eam spe    modifled DL5-BK2 absorbance spectrum resulted in the absorbance spectrum
of  '" frJ? Msina DL6 providing a reasonable TCE value.
       ° "  re5 j||UStrates the results of the use of a iterative I0 spectra on MDL. The MDL variation
          ver the course of a day is shown for toluene, m-dichlorobenzene, and 1,2-dichloroethane.
         °
                                           585

-------
The use of iterative I0s to form the absorbance spectra resulted in a distinct improvement in MDL
(20-34%) for the compounds, although some individual MDL values are worse than those obtained
when using only a single initial I0 to generate the absorbance spectra.

CONCLUSIONS
       The results of this study indicate that a general improvement in concentration values and
great improvement in concentration residual values can be obtained by use of the iterative I0
technique. The use of synthetic mixtures indicates that interfering compounds and water vapor
variation are accommodated much more easily by using generated I0s.  Complications result in
method application if identified target compounds are not correctly quantified by LSF analyses, and
are carried over  as positive or  negative values in the iterative I0.  The  occurrence of target
compounds below MDL can potentially allow a slow, non-detectable increase in compound values,
but a suitable remedy for this problem is use of  a "feedback" loop by using an earlier iterative I0
and checking for positive compound absorbances above MDL values.
       The application of the iterative I0 technique to actual field data caused some alteration in
concentrations, and significant  improvement in concentration residual.    The demonstrated
improvement  in target  compound accuracy  illustrated by  Method Test  4 suggests that the
concentration changes indicated for field data values are actual improvements in values.
       Finally, as  illustrated by the considerable  concentration residual improvement throughout
this study and by the  results of MDL variation  by use of iterative I0s,  it  is likely that in  most
instances generally lower minimum detection limits can be achieved using the iterative I9 technique.
       Further testing through additional applications to field  data is  necessary before final
acceptance and general use of this technique.

ACKNOWLEDGEMENT
      The authors would like to express their thanks to Dr. Roy Brandon, MDA Scientific, for his
advice and for providing some required reference spectra for this study.

REFERENCES

1.    P.L. Hanst,  "Analyzing  Air  for ppb Concentrations of Trace Gases  Using  Spectral
      Subtraction; bulletin published by Infrared Associates, November 1990.
2.    R.J. Kricks, T.R. Minnlch, D.E. Pescatore, P.J. Solinski, D. Mickunas, L Kalin, O.A. Simpson,
      M. J. Czerntawski, and T.H. Pritchett," Perimeter Monitoring at Upari Landfill Using Open-Patn
      FTIR Spectroscopy: An Overview of Lessons  Learned,1 Presented at the Air & Waste
      Management Association 84th Annual Meeting, Vancouver, B.C., June 1991.
3.    S.E. McLaren and  D.H.  Stedman, "Flux  Measurements Using Simultaneous Long-Path
      Ultraviolet  and  Infrared  Spectroscopy,'  Presented  at the Air &  Waste Management
      Association 83rd Annual Meeting, Pittsburgh, PA, June 1990.
4.    R.J. Kricks, D.E. Pescatore, R.  Lute, and T.H. Pritchett, 'Preparation  and Use of Synthetic
      Mixtures in Assessing Performance of Project-Specific Analysis Methods Software for Open-
      Path FTIR  Spectrometers',  Presented at the  First Annual  Remote Sensing Specialty
      Conference, Houston, Texas, March 1992.
5.     Blasland, Bouck & Lee, Fenceline Air Monitoring Purina Chestnut Br*r h, I, ?achate Area Sol
       Intrusive Activities. Report prepared for USEPA -  Environmental Response Team under
       contract to Roy F. Weston, December 1991.
                                          586

-------
Table I. Method Test 1 Results


#1
If •





#2
7* *-





#3





#4




#5



#6




Run
CLFM


TECE
Freon tl


CLFM


TECE
Freon II


CLFM

TECE
Freon II


CLFM

TECE
Freon II

CLFM

TECE
Freon

CLFM

TECE
Freon II



Reg. 1
Reg, 2
Ave.

Reg. 1
Reg. 2
Ave.
Reg. 1
Reg. 2
Ave.

Reg. 1
Reg. 2
Ave.
Reg. 1
Reg. 2
Ave.

Reg. 1
Reg. 2
Ave.
Reg. 1
Reg. 2
Ave.

Reg. 1
Reg. 2
Ave.
Reg. 1
Reg. 2
Ave.
Reg. 1
Reg. 2
Ave.
Reg. 1
Reg. 2
Ave.
Reg. 1
Reg. 2
Ave.
Initial I0
ppm-m fCR)
16.18 (.81)
13.38 (2.22)
15.85
8.3 (.7)
20.91 (.21)
17.48 (.95)
20.74
25.36 (.84)
22.42 (2.17)
24.97
11. 76 (.67)
17.05 (.2)
12.65 (.79)
16.78
11. 42 (.8)
8.47 (2.12)
11.05
13.21 (.99)
14.15 (.4)
9.6 (1.4)
13.8
7.21 (.76)
4.52 (2.04)
6.88
8.86 (1.67)
9.29 (.75)
Below MDL
9.29
4.13 (.73)
Below MDL
4.13
7.55 (2.63)
6.43(1.21)
Below MDL
6.43
3.12 (.71)
Below MDL
3.12
Below MDL
Below MDL
Below MDL
Below MDL
                                                      Iterative I0
                                                       ppm-m fCRl
                                                         NA
                                                         NA
                                                         NA
                                                         NA
                                                         NA
                                                         NA
                                                         NA
                                                      25.31 (.3)
                                                      24.62 (.08)
                                                        24.67
                                                       10.9(.5)
                                                      16.87 (.25)
                                                      15.92 (.91)
                                                         16.8
                                                      11.18 (.3)
                                                      10.5 (.07)
                                                        10.53
                                                      11.63 (.5)
                                                      13.91 (,25)
                                                      13.77 (.92)
                                                         13.9
                                                       6.8 (.16)
                                                       6.4 (.04)
                                                         6.43
                                                      6.71  (.77)
                                                      9.05  (.38)
                                                      7.62 (1.35)
                                                         8.95
                                                      3.62  (.12)
                                                      3.35  (.03)
                                                         3.36
                                                      5.06(1.03)
                                                       6.14 (.5)
                                                      4.95 (1.8)
                                                         6.05
                                                       2.56 (.1)
                                                       2.36 (0)
                                                         2.36
                                                      4.81  (1.3)
                                                      Below MDL
                                                      Below MDL
                                                      Below MDL
Actual
ppm-m
16.0
 9.0
21.0
25.0
11.0
17.0
11.0
12.0
 14.0
  7.0
  7.0
  9.0
  4.0
  5.0
  6.0
  3.0
  4.0

  0.0
                                            587

-------
Table I.  Method Test 1  Results (cont'd)
         Run
  Initial
pom-m (CR1
#7 CLFM


TECE
Freon II


#8 CLFM


TECE
Freon II


Reg. 1
Reg. 2
Ave.

Reg. 1
Reg. 2
Ave.
Reg. 1
Reg. 2
Ave.

Reg. 1
Reg. 2
Ave.
4.2 (.72)
Below MDL
4.2
9.67 (4.3)
Below MDL
Below MDL
Below MDL
5.3 (.72)
Below MDL
5.3
12.97 (5.22)
9.85 (2.4)
Below MDL
9.85
  Iterative I0
   ppm-m (CR)
  3,68 (.17)
  3.32 (.01)
     3 32
  6.98 (.52)
  3.09 (.25)
   2.48 (.9)
     3.04
  4.75 (.25)
  4.19 (.04)
     4.21
  10.2 (1.03)
   9.61 (.5)
  8.17(1.8)
     9.51
Actual
ppm-m
                                                                              4.0
                                                                              6.0
                                                                              2.6
                                                                              5.0
                                                                              9.0
                                                                              9.0
Table II.  Method Test 2 Results
         Run
  Initial
cpfp-m fCRl
#1 Benz



MESI
MECL


#2 Benz



MESI
MECL


Reg. 1
Reg. 2
Reg. 3
Ave.

Reg. 1
Reg. 2
Ave.
Reg. 1
Reg. 2
Reg. 3
Ave.

Reg. 1
Reg. 2
Ave.
—
55.53 (27.52)
54.00 (21.44)
54.57
26.68
30.27 (9.44)
28.86 (5.52)
29.22
—
—
—
—
31.62(5.94)
—
—
___
  Iterative I0
  ppm-m fCRl
     NA
     NA
     NA
     NA
     NA
     NA
     NA
     NA
 45.26 (4.95)
 45.77 (5.68)

    45.48
 31.61 (3.52)

27.16 (12.29)
    27.16
Actual
DPm-m_
                                                                             57.0
                                                                             30.0
                                                                            30.00
                                                                            48.0
                                                                            36.0
                                                                            34.0
                                         588

-------
Table II.  Method Test 2 Results (cont'd)


                           Initial I0                Iterative I0                Actual
        Run               ppm-m (CR)             ppm-m fCRl             ppm-m
#3 Benz    Reg. 1          —                  36.12 (2.57)
             Reg. 2          —                  36.5 (2.89)
             Reg. 3          —                     —
             Ave.           —                    36.29                  39.0
    MESI                 19.11(7.52)            19.07(1.75)               24.0
    MECL    Reg. 1          —                     —
             Reg. 2          —                  24.0 (6.23)
             Ave.           —                     24.0                   34.0
#4 Benz    Reg. 1          —                  35.63 (2.29)
             Reg. 2          —                  35.42 (2.79)
             Reg. 3          —                     —
             Ave.           —                    35.55                  38.0
    MESI                   —                     6.54                   12.0
    MECL    Reg. 1          —                     —
             Reg. 2          —                  13.9 (6.23)
             Ave.           —                     13.9                   27.0
#5 Benz    Reg. 1          —                  33.19 (2.35)
             Reg. 2          —                  34.23 (2.99)
             Reg. 3          —                     —
             Ave.           —                    33.59                  37.0
    MESI                   —                    11.06                  16.0
    MECL    Reg. 1          —                     —
             Reg. 2          —                     —
             Ave.           —                     —                   14.0
#6 Benz    Reg. 1          —                  34.33 (4.57)
             Reg. 2          —                  33.17 (5.55)
             Reg. 3          —                     —
             Ave.           —                    34.18                  37-0
    MESI                   —                    13.01                  19.0
    MECL    Reg. 1          —                     —
             Reg. 2          —                     —
             Ave.           —                     —                   31.0
                                       589

-------
Table III.   Method Test 3 Results





                           n-Octane                    iso-Octane
Event #
RN 121
RN122
RN 123
RN 124
RN 125
RN 126
RN 127
RN 128
RN 129
Initial \0 (ppm-rn)
Cone. (CR1
18.53 (.66)
1928
17.47
18.63
17.68
19.46
15.74
13.22
11.41
Table IV. Method Test
Targef Cornnound
Benzene -
Benzene -
Benzene -
Average
Run 1
Run 2
Run 3

(.67)
(.64)
(.70)
(69)
(.75)
(.68)
(.56)
(.51)
Iterative I0 (j
Cone.
18.52
19.24
17.40
18.54
17.57
19.33
15.58
13.03
11.18
ppm-m) Initial I0 (ppm-m)
fCRI Cone. (CR1
(.25) 1.66 (.50)
(.20)
(.29)
(.22)
(22)
(.20)
(25)
(22)
(.20)
1.56 (.51)
1.58 (.49)
1.85 (.53)
1.48 (.52)
1.95 (.57)
1.31 (.52)
1.07 (.43)
1.29 (.39)
Iterative I0 (p
Cone. (
1.64
1.52
1.52
1.78
1.39
1.83
1.18
0.93
1.14
pm-m)
CBL
(.19)
(.15)
(.22)
(.17)
(.17)
(.15)
(.19)
(.17)
(.16)
4 Results
Known
Concentration




135
135
135
135
Initial
Cone
082
108.4
136.1
110.9
I0 (Dom-m)
_GB_
30.6
48.6
29.9
36.7
Iterative
Cone
131.1
125.5
145.3
133.4
I0 toom-m)
_£B_
23.3
16.9
15.
18.6
                                          590

-------
Table V.  Method Test 5 Results

Run
1 IMt »^
1
2
3
4

5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
Round-trip
Path Length
fmeters)
200
200
200
200
4f\f\
1UU
100
100
100
100
100
100
100
100
100
100
100
100
100
100
c<
Close-in
Cone.
1.80
2.16
2.21
2.50
Son
.C\i
2.01
2.52
2.27
2.67
3.89
4.02
3.38
2.63
4.3
2.29
2.98
3.35
2.58
4.6
D
I0 (ppm)
.OR.
(.26)
(-26)
(.28)
(.30)
/ AK\
(,4Q)
(.39)
(.53)
(.46)
(.58)
(-90)
(.97)
(.75)
(.52)
(1-0)
(.43)
(.65)
(.77)
(.52)
(1.2)
CC
Iterative I
Cone.
—
2.16
2.21
2.50


2.00
2.52
2.26
2.68
3.93
4.08
3.40
2.62
4.33
2.23
2.94
3.32
2.52
4.59
D
„ toom)
-GB_

(.02)
(.03)
(.03)


(.09)
(.16)
(.09)
(.13)
(.33)
(.09)
(.23)
(.25)
(.51)
(.60)
(.24)
(.13)
(.26)
(.66)
CH<
Close-in^
Cone.
2.551
2.504
2.546
2.580
2£A
.04
2.46
2.49
2.47
2.55
2.64
2.56
2.54
2.54
2.57
2.49
2.61
2.61
2.64
2.97
I
(DDrrrt
CB_
(.97)
(.94)
(.90)
(.80)
/ AT\
(•*')
(.42)
(.39)
(.40)
(.40)
(.45)
(.40)
(.42)
(.40)
(-49)
(.46)
(.42)
(.39)
(.44)
(.56)
CH
Iterative I,
Cone.
™ .
2.505
2.546
2.536

"•"•"•
2.46
2.49
2.47
2.55
2.63
2.56
2.54
2.53
2.61
2.49
2.61
2.61
2.64
2.99
4
, fppnri)
CR

(.56)
(-29)
(.20)


(.14)
(.18)
(.13)
(.17)
(.21)
(.18)
(.16)
(.15)
(.22)
(.34)
(.33)
(.27)
(.33)
(.46)
Table VI.  Method Test 6 Results
         Run
        DL1
        OL2
        DL3
        DL4
        DL5
        DL5
        DL6
Spectrum Used
for Obtaining I.
 BK2
 DL1
 DL2
 DL3
 DL4
 BK2
 DL5
                                          Trjchtofoethvtene toom-ml
Measured
NO
ND
ND
ND
ND
2.87
3.84
Actual
0.5
1.0
1.5
2.0
2.5
2.5
3.0
CCL and 11 OCA present in similar concentrations as interferant compounds.
                                      591

-------
                                              Get Initial
                                          Background = 1(0)
                                            and set n = 1
                                                    	J
                                         Obtain Single Beam
                                           Spectrum, I(n)
                                              Calculate
                                             Absorbance
                                           Spectrum A(n)
                                                JL
                                              Perform
                                            Concentration
                                          Analysis on Target
                                               Gases
                                                i.
                                               If any
                                           concentrations,
                                            subtract from
                                         absorbance spectrum
                                         Recreate I(n) using
Figure 1.  Flowchart of Iterative Technique for Generating I0 Spectra.
                                 592

-------

•< * * • * * « M
    FIGURE 2.   SINGLE-BEAM SPECTRA

                           10 •
CCNERATCO SINCLE-BCAI4 SPECTRUM
                                                                  •-
                                                                   •••-
                                                        FIGURE 5. AWOtBAWCC 5PCCTHUM A(u»
                                                  i.
                                                                                   MB
                                                                              I *•»-!      «4/t«/M

                                                                      DIVISION Or SIWCU-BtAM IiiY Ir

-------
£
                                 HDL Based on Initail Io Toluene
                          A	& MDL Based on Iterative I0 Toluene
                          Q	B MDL Based on Inltall Io U2 Dlchloroethane
                          Q— -B MDL Based on Iterative Io L2 Dichloroeth&ne
                          O   O MDL Based on Inltall Io "  - DlcWorobenzene
                          O	O MDL Based on Iterative lon - Dichlorbenzene
                                                                                                                   14:00     U:30
                                                                        (time)
                                                                   MDL VARIATION  WITH  TIME
FIGURE  6:

-------
   A METHODOLOGY TO DETERMINE MINIMUM DETECTION
       LIMITS FOR SITE-SPECIFIC TARGET COMPOUNDS
             USING OPEN-PATH FTIR  SPECTROSCOPY
                       Douglas E. Pescatore, Robert J. Kricks,
                      Robert L Scotto, and Timothy R. Minnteh
                           BLASLAND, BOUCK & LEE
                     RARITAN PLAZA III, FIELDCREST AVENUE
                          EDISON, NEW JERSEY,  08837
                              Thomas H. Pritchett
                   U.S. ENVIRONMENTAL PROTECTION AGENCY
                       ENVIRONMENTAL RESPONSE TEAM
                             GSA RARITAN DEPOT,
                          EDISON, NEW JERSEY, 08837
ABSTRACT
^"^  Open-path Fourier-transform infrared (FTIR) spectroscopy provides an ideal methodology
   assess downwind community impacts and compliance with preestablished health-based
fenceline action levels during site assessment or cleanup activities at hazardous waste sites. As
n any environmental monitoring application, however, minimum detection limits {MDLs) must be
known  in advance to ensure that nondetects still provide data to achieve the project's
measurement quality objectives (MQOs).  For open-path FTIR spectrometers, MDLs vary with time
and open-path configuration, and may vary significantly.
      This paper presents a methodology for deriving MDLs based on compound and specific
soectral region. The variation of MDLs with pathlength and time are discussed.

INTRODUCTION
      The applicability of generic minimum detection limits (MDLs) developed by the instrument
manufacturer or from  independent research efforts is increasingly being questioned in field
monitoring projects involving open-path Fourier transform infrared (FTIR) spectroscopy. A generic
MDL generally represents a  compound's "best attainable" MDL, as it is usually based on the
 ompound's strongest absorbance region and is generally determined in optimally controlled
                                    595

-------
 conditions. Additionally, such MDL measurements are. in most instances, determined using a
 closed cell or over a single fixed open-path distance.1  However, because instrument sensitivity
 varies  widely with measurement   conditions  and measurement   pathlength, use of more
 representative project- or measurement-specific MDLs is preferred.2
       Although there are many methods to determine MDLs, a standard procedure has not been
 established. The purpose of this paper is not to compare or discuss various methods to determine
 MDLs, but to present simple calculations of spectral noise and compare them to target compound
 absorbance levels to yield conservative  pre-field MDLs.
       The need to derive more representative MDLs stems from their use to determine project
 feasibility in  the planning stages and  to demonstrate  compliance with measurement quality
 objectives for work carried out on site. In order to insure that data quality objectives are obtained
 throughout a project, it is necessary to produce conservative MDL estimates in the pre-field work
 stages.  Because on-site MDLs are used as maximum default  concentrations when non-detects
 occur, these values must be more refined to account for the variability in spectral noise.
       Spectral noise varies during the day due to changes in temperature, atmospheric moisture,
 and other components of the atmosphere. The amount of noise contained in a spectrum is also
 a function  of the availability of background (upwind) spectra. Although coanatyses for water can
 account for a good portion of the noise  caused by water, it will not resolve the noise caused by
 line shape changes in the water vapor absorbance between the I0 and I spectra.  Figure 1
 (Spectrum A) presents a spectrum that illustrates an example of this type of noise. Other types
 of noise are instrument-based, and the  exact origins are hard to define.  These types of noise
 would be virtually impossible to field-correct.  It is  important to note that instrument noise varies
 from day to day and from run to run, and  can affect MDLs dramatically. Figure 1 (Spectrum B and
 Spectrum C) illustrates two examples of  types of instrument-based noise.

 METHODOLOGY
       The determination of MDLs involves evaluation  of compound IR absorbance and the
 associated absorbance spectra noise level.  The determination of compound IR absorbance is
 based on  assessment of  absorbance region, peak magnitude, and peak  area. Absorbance
 spectra noise levels (i.e., noise contained in the  spectra that results from source attribution plus
 background) is determined from the sample spectra (I) and the background spectra (IJ.
       When making a direct comparison of absorbance spectra noise level  (noise absorbance)
 to the signal absorbance (expressed as  the absorbance value  per 1 ppm-m of compound) of a
 irget compound, the MDL value is calculated from:

                        ^ r	noise absoftanoa	„.  ___ _
                       A x  ....                jf i  ppm-m,
                           signal absorttanoa 9 1 ppm-m
 (here K = the acceptable minimum signal-to-noise ratio.
      For this study, K was set at 2, based on the use of 2 times the signaMo-noise to define the
MDL Presented below are methods of estimating noise absorbance and signal absorbance from
sample spectra and library spectra and methods of generating MDL values.
      Three methods (A, B, and C) were developed to evaluate the level of noise, in absorbance
units, over specific regions and to compare the noise levels to library spectra absorbance strengths
over the same regions.
      In methods A and B,  the noise regions used are defined  through peak table software3
selection of the peak edges for the compound of interest.  In method C, the analysis regions to
use for each compound  of interest are defined by the operator/analyst.
                                         596

-------
       Noise absorbance are obtained by calculating the root mean square of the variation of the
 absorbance spectra over the regions defined in each method. The absorbance spectra used are
 free of the compounds being evaluated for MDLs,
       The signal absorbance is expressed as the absorbance value of the library compound
 divided by the library concentration value to yield a per 1 ppm-m value.  In method A, the
 absorbance value of the library compound is the highest value across the region. Methods B and
 C take the average absorbance across the regions defined by these methods. After initial testing
 of these methods, software was developed to run within Lab Calc™ for quick execution of  each
 method.

 RESULTS
       Table 1 provides a comparison of a sample of  results of using these MDL generation
 methods on a typical absorbance spectrum that is free of compounds of interest.
       The calculated concentration and resultant concentration residual (CR) were obtained by
 synthetically adding the compound to the typical absorbance spectrum at the value generated from
 employment of methods A, B, and C, and  analyzing for the compound of interest by least squares
 fit (LSF) analysis. The fit ratio (FR) is determined by the division of the calculated concentration
 by the CR.  The FR should be approximately the same as K.  The CR Is an output of LSF analysis
 and represents the unexplained residual remaining after the LSF algorithm is  applied to the
 spectrum. It can be viewed as the residual "noise" after LSF. Twice the CR will also approximate
 a signal-to-noise ratio of 2 to 1.
       The results indicate the method A procedure produces the lowest MDL values, but in 43%
 of the cases these MDLs were below the FR value of 2. Two cases were in agreement with a FR
 value  of 2, but in one of these cases the concentration calculated by LSF analysis was nearly
 double the input value. One case overstated the MDL, as the FR was significantly better than 2.
       For method B, the calculated MDLs produced were generally larger than procedure A, but
 43% of the MDLs are  still below a FR of 2.
       For method C, the calculated MDLs produced are larger than for method B and are in
 reasonable agreement with the  CR value, except for two cases.  However, 29% of the MDLs
 produced are below a FR of 2, but in these cases the FRs are between 1 and 2.

 CONCLUSIONS
       Although methods A and B proved useful for the stronger absorbing compounds, they were
 not conservative enough for the weaker absorbing compounds.  Method C overestimated MDLs
 ftjr some compounds and generally did well with weak  absorbing compounds.  Over all, these
 methods were not very effective in regions where water peaks were very strong, and In some cases
  diibited nonlinear behavior. The methods were generally conservative where water impacts are
 not  strong and were handled  well by  LSF analyses.  In evaluating  these results, and in
  nnslderation of the relationship of 2 x CR to MDL, the best current method for establishing MDL
 S field data appears to be the use of 2 x CR.
       Upon review of the library water's impact on the LSF analysis, it would seem to be beneficial
   explore the difference between the library water and the data spectrum.  A further refinement
  f these methods could be to attempt to subtract the water out of the data spectrum using library
   ter  references. The residual noise result  from the procedure would then be used in methods
   B  and C procedures to determine MDL values.
A  '  fa compound concentrations approach MDL values, the impact of noise mistakenly fitted
    SF analyses as positive or negative values of the compound become evident.  (Seen in Table
tW  g  us from analyses of known concentrations of compounds).  These LSF analysis "artifact"
 1 is contribute to the uncertainty in actual concentration value at tow compound concentrations.
                                          597

-------
Higher K values and thus a higher signal-to-noise requirement will result in less uncertainty in
reported concentration value and are recommended in determining the quantitation limit for
compounds.
      Although the MDL calculations did not prove to be useful in field applications, they are
useful in approximating MDLs prior to on-site work, as long as the estimate of path length and an
absorbance spectrum free of the compounds of interest and representative of such a pathlength
are available. Methods B and C are useful for providing information on expected MDLs during
project feasibility assessmentsand during project specific analytical method development. Method
A  should not be employed except for very  narrow absorbance peaks  (width less than 5
wavenumbers).

REFERENCES
1.     W.B. Grant,  R.H. Kagann.  and W.A.  McClenny, "Optical Remote Measurement of Toxic
      Gases,'J. Air & Waste Management Assoc., January 1992.
2.     T.R. Minnich, R.J. Kricks, and R.L Scotto, Field Standard Operating Procedure for the Use
      of Open-Path FTIR Spectroscoov at Hazardous Waste Sites. U.S. Environmental Protection
      Agency, Preliminary Draft for Technical Review, March 1992.
3.     Lab Calc. Software:  Galactic Industries Corporation: 1990 licensed software package,
                                         598

-------
                                                  TABLE 1

                        COMPARISON OF 3 METHODS OF MDL GENERATION WITH 2 x CR"
1056-114
1009-1051
2840-3135
740-781
1245-1288
4.08
109.14
13.2
8.61
11.8
5.25
45.25
8.88
8.95
27.41
4.38
40.17
15.29
5.62
26.88
2.15
0.74
2.32
1.30
4.56
7.65
83.25
9.05
16.55
61.79
6.78
78.13
15.46
13.2
61.28
3.32
1.43
2.34
3.06
10.39
12.59
153.62
101.27
13.78
50.68
11.7
148.45
107.56
10.43
50.17
5.71
2.72
16.25
2.42
8.50
                               2xCR          Method A	           Method B               Method C
                   Analysis     For All           Cone. Cal.                Cone. Cal.              Cone. Cal.
Compound           Region      Cases'"*    MDL    Bv LSF   FR      MDL   BvLSF    FR     MDL   By LSF   FR

Benzene            1014-1055    59.6      17.98    19.86   0.67     42.88   44.77    1.5     42.82   44.69    1.50
                   3029-3117    50.98    12.08      ND     —      20.25     ND      —     57.73   36.67    1.44
1.1,1-Trichloroethane
Toluene

Methytene Chloride
Notes:

  ND   = Value not obtained, likely equal to or less than zero.
  (a)    = All concentration values and MDL values are ppm-m
  (b)    = These values are applicable to all methods of MDL generation as LSF analyses would normally be carried out using analysis
          regions shown.
  CR   = concentration residual
  FR    = fit ratio (concyCR)
  LSF   = least squares fit
  MDL  = minimum detection limit

-------
               SPECTRUM A


                  >*y——J^^^y^.
,0
 u
    800
          1OOO

Wavenumbers (cm— 1)
1200
                            Res= 1 cm— 1

-------
          VOC EMISSION RATE ESTIMATION FROM
 FTIR MEASUREMENTS AND  METEOROLOGICAL DATA
                                  Ray E. Carter, Jr.
                                   Dennis D. Lane
                                   Glen A. Marotz
                             Department of Civil Engineering
                                  4002 Learned Hall
                                  University of Kansas
                                 Lawrence, KS  66044

                                   Mark J. Thomas
                                   Jody L. Hudson
                                 U.S.EPA, Region VII
                                   25 Funston Road
                                Kansas City, KS 66115


ABSTRACT
      Two methods of estimating the VOC emission rate from a single point source arc described.
B°ft methods use FTIR measurements and meteorological data as inputs to a form of the Gaussian
a"spersion equation to produce an estimated emission rate. Method 1 uses means of wind speed and
J^id direction for the duration of the test period; Method 2 uses one-minute means of those variables.
 ield testing has  been undertaken at a flat, grass-covered site by the University of Kansas, in
cooperation with Region VII of the U.S.EPA and Kansas State University.  VOC plumes are produced
USU18 a plume generator that allows the emission rate to be accurately varied and controlled, and to be
continuously measured during a test.  Whole-air samples are collected during many of the tests to
Provide supporting data.  Test days are scheduled so that the general  synoptic weather framework
Jttnaitts similar from test  day to test day; the effect of stability is examined by selecting the timing of
^l periods within a given day.  The downwind distance is varied, so that its effect on the performance
?  "* estimation methods can be assessed.  Initial testing is conducted using a single point source;
 owever, laier phases of  the study will focus on simulated and actual area sources, in an attempt to
fir*? aPPIicabil'ty to Superfund sites.  Results from one series of tests show good overall results, with
, ,  *ISnifiamt differences in the performance of the two estimation methods.  For eight releases of
 'M-trichloroethane, correlations between measured emission rates and rates estimated using the two
methods have coefficients of >0.98. Estimations for stability classes C and D show a mean negative
 135 of approximately 30%; estimations for stability classes A and B show only a small bias.
  development of
of that work, KU
      The University of Kansas (KU) has assisted Region VII of the U.S.EPA in the
  VQC monitoring capability for the region during the last several years ». As a part o          ,
J« assisted in the field testing of an open-path Fourier transform infrared (FTIR) spectroscopic method
J:^loP«l by Kansas State University (KSU) and Region VH *.  Results have shown the FTIR method
J> ** a viable one for ambient air VOC measurement. KU, in cooperation with KSU and Region VH,
 *~ undertaken to extend the capabilities of the FTIR technique by using it to estimate VOC emission
*tes from various types of sources>  with emphasis on applicability to Superfund sites.  To accomplish
  s Soal, KU is conducting field tests of techniques that use FTIR measurements and  appropriate
   wal data in  conjunction  with a form of  the Gaussian dispersion equation to  produce an
                                         601

-------
estimation of the emission rate 3.
       The objectives of the study include (1) the development of field protocols to ensure that data
collected will be of appropriate type and quality to perform emission rate estimations, (2) an assessment
of the performance of the estimation methods for both the  single-point-source and area-source cases,
including a determination of statistically appropriate confidence intervals, (3) a determination of the
applicability and relative accuracy of the estimation methods as a function of downwind distance and
atmospheric stability, and (4) a determination of the effect of VOCs being released at different heights
within an area source.

APPROACH
       The study is divided into three phases, which are being performed consecutively over a two-year
period.  The three phases consist of field testing the emission rate estimation methods (1) using only
a single  point source, (2) using multiple point sources to simulate an area source, and (3) at selected
actual VOC area and/or point  sources.
       Two emission rate estimation methods are being evaluated for the single-point-source case in
Phase 1; both methods are based on the premise that integration of the Gaussian dispersion  equation in
the crosswind direction results  in an expression for the emission rate as a function of the path-integrated
concentration 3.  The methods differ in their use of meteorological data: one uses values for wind speed
and wind direction that are averaged over the duration of the test period;  the other employs  one-minute
means of those variables 4. Other methods, or modifications of the above methods, will also be tested
should the results warrant that action.
       During Phase  1, the effective plume height and the measurement height are both approximately
two meters.  With the source and receptors very near ground level, the applicable form of the Gaussian
dispersion equation is as follows:
       C(x,y)  = (Q/Tff^utexpP/^v/a,)1],                           (1)
 where C(x,y)  -  concentration at (x,y), in gm/mj,
           Q  =  emission rate, in gm/sec,
         ffy.ff, =  horizontal and vertical dispersion coefficients, in m,
            u =  mean wind speed, in m/sec, and
          x.y  -  downwind and crosswind distances to receptor, in m.

 Dispersion coefficients (ay and aj were determined from Pasquill-Gifford stability classifications, which
 were estimated from the standard deviation of the horizontal wind direction (DO) J.

 Integrating with respect to y, from y=-e» to y= + <», and rearranging yields

           Q  = [(2x)%/2]CyaIu,                                    (2)

    where C,  = crosswind integrated concentration, in gm/rn2.

 This  method should produce a good estimation of the emission rate, given an accurate value of the
 crosswind path-integrated concentration and the satisfaction of assumptions made in the development
 of the above equations.
       The assumptions used in developing the Gaussian equation are seldom rigorously adhered to in
 field tests. However, various sensitivity analyses show that meeting some assumptions is more critical
 than others.   For example, over short diffusion  times and within small  distances (the first tens of
 meters), the downwind distribution of material  should take the same form as the wind-fluctuation
 distribution, which approximates a Gaussian distribution fairly  closely <
-------
detector.  Because of fluctuating winds, these two conditions are not always met, and in those cases
Equation 2 cannot be accurately applied to the emission rate estimation problem.
       The use of meteorological data to characterize the configuration of the plume during the test
period allows Equation 2 to be used more accurately.  Consider Equation 1 in a rewritten form:
                      Cu/Q = (l/TtyrJ exp[-'A(y/cr,)2]

Summation of these  values for evenly spaced points along the IR path yields a relationship between
path-integrated concentration, wind speed, and  emission rate for a given stability class and network
orientation.  Values for Cu/Q can be calculated under the ideal-case conditions used to derive Equation
2 and summed across the IR path to yield (Cu/Q),. Values can also be calculated using the measured
wind direction data from the test period and summed to yield (CU/Q)M.  The ratio of these two values
can be used as follows:
                                 (Cu/Q)M

where Cy, is the path-integrated concentration that would be observed under the ideal-case conditions
and CyM is the measured path-integrated concentration. Cyl can then be used in Equation 2 to more
accurately estimate the emission rate.
       (Cu/Q)M can be determined either by using a mean wind direction for the entire test period, or
by using one-minute means of wind direction.  In the latter case, one-minute means of wind speed are
also used in Equation 2. These two methods of determining (Cu/Q^ give rise to the two emission rate
estimation methods alluded to in the introductory section.

EXPERIMENTAL METHODS
       The descriptions in the following paragraphs refer  primarily to Phase 1.   Phase 2 will follow
a very similar protocol with the exception  that in Phase 2,  four or five point sources will be arranged
to simulate the emission characteristics of an area source.   The arrangement of these sources and any
modification of the equations used will be based on results from previous studies and on results obtained
in phase 1.  Methodologies for Phase 3 will be developed based on data collected in Phases 1 and 2,
and on inspections of extant VOC area sources by EPA/Region VII personnel.

Study Site
       Tests  are being  conducted  on a  flat, extensive grass-covered  field with dimensions of
approximately 3 km (E-W) by 1 km (N-S) near the University of Kansas-Lawrence.  There  are no major
sources of hydrocarbons, such as transportation routes, etc., within close proximity of the field.  The
field is maintained throughout the growing season and the grass height remains relatively constant.

VOC Generator
       VOC plumes are produced using a VOC generator designed and constructed by the KU Civil
Engineering Department l. Measured emission rates  reported in  this paper  were produced using a
graduated cylinder and a stopwatch at the conclusion of each test. For the tests now being undertaken,
the VOC generator has  been refined  to provide the  following capabilities:   (a) to accurately and
precisely vary and control the emission  rate, and (b) to continuously measure  the rate during the test.
The emission rate will be varied over the range of 20-200 ml/min (liquid flow rate) to ensure that the
estimation methods are valid over a wide range of rates.

Meteorology
       The following meteorological data are collected during each test:    one-minute means and
standard deviations of wind speed (2m) and wind direction (2m) and one-minute means of temperature
S2m) and dew point (2m) are measured.  Barometric pressure is measured and  local sky conditions are
noted.  Favorable  sampling  days  are  chosen based  on  a forecast of relatively  steady winds at
                                            603

-------
approximately 2-5 mps,  and no  frontal  passage  or precipitation.   The  general synoptic weather
framework therefore remains similar from test day to test day. The effect of stability is examined by
selecting the timing of test periods within a given day.

Sampling Protocol
       Meteorological variables are monitored on-site for at least 30 minutes prior to the start of testing.
When it is determined that wind characteristics are favorable and are likely to remain so for at least 1-2
hours,  the best-judged network centerline direction is chosen and the sampling network is laid out.
Pollutant is released for at least 5  minutes prior to  the start of a test, so that a steady-state plume can
be established across the sampling network.  Whole-air samples are opened simultaneously with the
commencement of FTIR spectra collection.  The duration of the tests is 12 minutes.

FTIR Measurements
       FTIR  measurements are conducted by KSU personnel, in cooperation with Region VII, using
their own  instrumentation  and methodology  2.   During the tests  discussed in this paper,  FTIR
measurements were also made by Region II of the U.S.EPA  and by MDA Scientific g.  In order to
assess the applicability of the estimation methods to various downwind distances, the distance from the
VOC source to the center of the FTIR path is varied.  The minimum distance of 50 meters allows a
relatively steady-state plume to develop prior to reaching the FTIR path, while still  providing easily
measured concentrations. It is expected that the maximum distance will be no more than 500 meters,
although this distance  will be dependent on results obtained at  lesser distances.  The FTIR path length
is 100  meters at the shorter downwind distances; it will be adjusted along with downwind distance.

Whole-air Sampling
       Whole-air samples are collected in stainless  steel canisters  along the FTIR path during as many
tests as possible (5-7 samples per test).  Previous work has shown that a 10-20 percent difference can
be expected between whole-air and FTIR concentrations w. Therefore, point concentrations can be used
to provide  an independent assessment of  the estimation methods; they can also  be  used to provide
characterization of the distribution of pollutant within the FTIR path, which may allow refinement and
enhancement of the estimation methods 4.  Sampling and analysis of canister  samples are performed
according to FJ>A Method TO-14, with modifications developed at KU l.

RESULTS AND DISCUSSION
       Table  I  shows measured and estimated VOC emission rates from the Intercomparison Study
conducted by KU  on  June  4-6, 1991.  Estimated  rates were based on the mean of path-integrated
concentrations measured by the three FTIR participants.  Only data for those compounds identified
correctly by all three participants were used.  To provide an emission rate estimation for compounds
not correctly identified and to provide an independent assessment of the estimation methods, estimated
emission rates based on canister-derived path-integrated concentrations are also included in the table.
The emission  rate estimations were also expressed as percentages of the measured values; those values
are summarized in Table II, with results segregated by stability class (A-B vs. C-D).
       Examination of Table I  shows that Method 2 significantly outperformed Method 1 for the data
from Test 2;  the converse is  true for Test 5.  With these two exceptions, there was  no significant
difference in the performance of the two estimation methods for  the data from this series of tests, as
the pairs of estimations agreed  within 10%  in all other cases.
       Because the design of the Intercomparibility  Study did not specifically include emission rate
estimation work, the quantity of data collected and the limited range of emission rates  used for most
compounds preclude extensive  statistical analysis of the data.  However, there were eight releases of
1,1,1-trichloroethane with a fairly wide range of emission rates. For these tests, correlations between
measured and estimated values produced coefficients  of >0.98 for both estimation methods.
                                             604

-------
Table I. Measured vs. Estimated VOC Emission Rates
Te«t
1
2
3
4
5
6
— — — —
7
8
9
10
11
12
13
14
15
16

Sub.
Cliu
A
A
A
A
B
D
C
c
C
D
C
C
D
C
C
c
c
Compound
1,1,1-TCA
1,1,1-TCA
Trichloroethene
Toluene
J.U-TCA
Chlorobenzent
Toluene
1,1,1-TCA
Chlorobenzene
Dichloromethine
Tclnchloroclhene
Die hloro methane
Iioocune
TrichlotoeUune
Toluene
1,1,1-TCA
Chlorobenztne
DicMoro me thine
boocune
booctine
1.1.1-TCA
FreoolB
Dkhloromethine
faoocune
Dichlorotnethine
Tetrachloroeihena
lioocune
t,l,l-TCA
Freonll3
UOOCUM
1.1,1-TCA
PreonJlJ
Dichloromethine
Tetrachloroethene
Trichloroelhena
Emission Rate (
-------
       The data in Table II show that distinctly different results were obtained for different stability
 classes:  for classes A and B, estimated values fell both significantly above and below the measured
 value, with the mean percentage near 100%; for classes C and D, very few estimated rates were above
 the measured rate, and most estimations were between 60% and 80% of the measured value.
       A potential source of error in these estimation methods is the use of dispersion coefficients as
 determined from Pasquill-Gifford stability classifications. It is likely that a more accurate determination
 of ar and a. can be made by relating them directly to the measured deviations of horizontal and vertical
 winds (OQ and at, respectively)7; however, a, was not measured during the tests reported in this paper.
 Tests now  undertaken include the measurement of 
-------
        A  COMPARISON OF VOC CONCENTRATIONS
      ASSESSED BY OPEN-PATH FTIR AND CANISTERS
                                    Glen A. Marotz
                                    Dennis D. Lane
                                  Ray E. Carter, Jr.
                                  University of Kansas
                              Civil Engineering Department
                                   4002 Learned Hall
                                  Lawrence, KS 66045

                                    Mark J. Thomas
                                    Jody L. Hudson
                                  U.S. EPA, Region VII
                                    25 Funston Road
                                 Kansas City,  KS 661 IS
ABSTRACT
      Open-path FTIR spectrometry is currently being used to perform ambient air VOC surveys at
Superfund and other sites.  Although the methodology possesses characteristics that make it attractive
as a near-real-time monitor, its performance has not been compared to reference techniques.  The
University of Kansas and U.S. EPA/Region VII conducted a field experiment intended to assess the
Qualitative and quantitative capabilities of three FTIR Systems by comparing FTIR results with data
from whole-air canisters.   Fifteen  releases constituted  the  experimental set; mixtures of unknown
compounds selected from  a target list  of twenty-seven  were released.   Path-integrated VOC
concentrations along the IR paths  ranged from approximately  30  ppb to 300  ppb.  Halogcnated
compound identification was excellent; performance was not as good, and differed from participant to
uarticipant, in the identification of unsubstituted compounds. Quantification of aliphatic halogenated
compounds resulted in less than a 15%  mean percent difference when compared with canister results.
Statistical testing indicated that all three FTIR instruments produced concentrations that agreed fairly
well with canister values, but also revealed some differences among the three instruments. The pooled
      data showed a larger variance, and correspondingly lower precision, than the canister data.
 PJTRODUCTION
       Commercial Open-path Fourier Transform Infrared Spectrometer (FTIR) systems are viewed by
 many as an important addition to the available instrumentation for monitoring VOCs in ambient air.
 While open-path FTIR technology is increasingly being used, instruments employing the approach are
 •  relatively early stages of development and application.   There is virtually no standardization  in
 fetation or performance, which raises questions about the iniercomparability of data generated by
 different FTTR systems, and its relationship to data produced by extant reference techniques.
       While results from previous studies1-1-1 represent the performance testing of some open-path FTIR
         they  cannot be assumed to represent other FTIR systems, nor do they provide complete
        ' to the questions discussed earlier.  The University of Kansas (KU), in cooperation with the
 rsEnvironmental Protection Agency, Region VII (EPA), was asked to evaluate and document the
 • tercomparability  of ambient air toxics monitoring data generated by multiple open-path FTIR
             . This was achieved by conducting a series of field tests using three different systems.
               were MDA Scientific, Norcross, Georgia; U.S. EPA/Region U, Edison, New Jersey;
 and US EPA/Region VH, Kansas City, Kansas/Kansas State University, Manhattan, Kansas. Collected
                                           607

-------
data were used to evaluate the qualitative and quantitative performance of the participating FTIR systems
relative to data generated from a network of point monitors converted to path-averaged concentrations.

METHODOLOGY

Study Framework
       The study was conducted on a flat, short (average height, 35 cm) grass-covered, closed-access
field in a rural area 5 km west of Lawrence, KS4 5. The experimental design consisted of 15 individual
trials.   During  each trial, one  of five different VOC  mixtures, unknown to the participants, was
released.   Each  mixture  consisted of from  1  to 3  compounds selected from a  list of 27  possible
compounds provided to the participants several months before the study began. Each of the mixtures
was released during three separate experimental runs  for a total of 15 releases.  Two portable stations
were used to collect data on wind  speed/direction, air temperature, dew point temperature, and
barometric pressure at a height of two meters at upwind and downwind locations.

Measurement Protocol
       The three FTIR instruments monitored along parallel paths normal to the projected plume
centerline. Tests were performed  on  three different days. On days 1 and 3, Participant A monitored
along the path nearest the source (47 m downwind); Participant AAA monitored along the path farthest
from the source (53 m downwind). On day 2, those positions were reversed in order to identify any
bias that may have resulted from monitoring position.  Participant AA monitored along the center path
on all three days (50 m downwind).
       Whole-air samples (stainless steel canisters) were collected at nine points along a line parallel
to the FTIR paths,  and centered on a point 48.5 meters from  the VOC source (Figure 1).  Canister
sampling locations were arranged  at 10-meter intervals from 40 meters left to 40  meters right of the
projected plume centerline. Height was 1.7 meters, in order to approximate the sampling height of the
FTIR  instruments.    The  canister  samples  were  analyzed  by GC/FID,  following  cryogenic
preconcentration4. Results from these analyses were used to determine a path-averaged concentration,
using a  recently developed methodology2.

RESULTS AND DISCUSSION

Meteorological Conditions
       Wind directions remained generally easterly, which was the most favorable direction for the test
operations given the orientation of the field site and the fetch conditions upwind.  Directional deviation
during any one test was quite small; wind speeds and speed deviational values were very consistent also.
Stability classes  C and D were more common (10 of 17 tests) than classes  A or B.
                     60
                     50
                     40
20 -
                     10 -
                                          FTIR Path
                          • Canister
                          A A
                          • AA
                          • AAA
                             I
                         k
                            Projected Plume
                              CenterSne
                                              Source
                                              •    I
                         0   10  20   30   40   50   60  70  80   90   100
                                           Meters

                                  Figure 1. Samping Network Layout
                                             608

-------
fTIR and Canister Results
       Path-averaged concentrations reported by the three participants, and path-averaged concentrations
derived from the whole-air  canister samples collected during  the study  are shown  on  Table I.
Qualitative results are summarized on Table II.

Table I.  Path-Averaged Concentrations - Overall Results

1
2
3
4
5
6
7
1
9
10
11
11
13
_.
14
•
16

Number
06041243
06041305
06041344
06041425
06041506
0605115
06051141
06051123
06051144
06051315
06051346
06051401
06051454
06051514
06061001
06061030
06061056
Sun
Tun*
(CM)
12:43
IKW
1:44
1:25
3:06
11:15
11:42
12:43
11:44
1:25
1:46
1:01
2:54
3:14
10:08
1030
10-56

VOCPrwa
ortd*Mifi*d
l.l.l-TrichlOiOcdua*
I.U-TricUaiMhuM
n- Pi MUM
Trichlorathot
TollMM
1.1.1-Trkhlondbui*
Chlorob*nac
Tolutd*
l.l.l-TricManeth*M
ChlorabcOZtM
DkblonnncHUM
UOOCUM
Trkhloroelhcw
TollMtt
l.l.l-TricUonMtMjM
QUorobcouM
DichlomnetKtM
booctutt
l.l.l-TricUonMhuH
FrwulH
Uaoctam
DicUoromriMM
TuncUoroctoa*
l.l-Dichloro(*uw
1,1,1-TricUiMMduM
UCKKIUM
1.1.1-TrkMnniiihini
SS±L



CO A AA
NC
NC
NC
316
96
91
76
34
33
29
230
97
215
107
155
100
u
7*
215
no
43
69
51
130
63
150
65
rat
60
93
76
34
57
46
175
76
330
275
90
150
370
NR
to
131
NR
47
60
195
105
200
140i
295
NR
100
165
105
250.
lOSa
75
70
160
155.
160
15
NR
105*
70
70
100.
55
55
160
to
110
AAA
2*1
99
141
32*
NR
35
116
NR
21
65
225
112
211
123
297
157
109
160
141
131
66
71
77
151
Id
146
to
NR
66
74
77
49
55
51
159
to
33*

115
66
NR
261
5*
45
74
NR
26 1
NR 1
254
103
164
NR
243
1.1
90 1
219
NR
NR
52
" 1
171
NR
194
74
41
NR
57
57
NR
54
41
171
66


                               . Co«c«nHBlin« nfOKti it p«UH
                                              609

-------
Table II.  Summary of Qualitative Results
Compound
l.U-TCA
Trichloroethene
Dichloro methane
Tetrachloroelhene
Freon 1 13
Chlorobenzene
Toluene
Isooctane
False Positives
Number of
Releases
6
3
6
3
3
3
3
3
15
Concentration
Range (ppb)
30-100
250-330
130-230
60-100
40-80
20-80
30-100
30-110

No. Correct Identifications
A AA AAA
6
3
6
3
3
3
0
0*
0
6
3
6
3
3
3
1
6
0
6
3
6
3
3
2
2
0
1
       * - Isooctane identified only as a 'hydrocarbon"

       Some FTIR instruments  have difficulty in identifying unsubstituted aliphatic hydrocarbons*.
Isooctane was released as an unknown, and it presented identification problems.  Participant AAA had
stated prior to  the study that they would be unable to identify such compounds due to the use of an
optical filter which suppressed the IR region used to identify n-hydrocarbons; Participant A was able
to identify isooctane only as a "hydrocarbon."  An unsubstituted aromatic compound, toluene, was
released during the study. Results in this case were also not particularly good; in none of the three tests
in which toluene was released were all three participants able to identify it as "present".  During one
toluene release, Participant AA ran out of liquid nitrogen  for their detector which may have affected
their ability to detect the compound.
       The six halogenated  compounds  shown in  Table II  were released  as unknowns.  These
compounds were present in the IR paths at path-averaged  concentrations ranging from approximately
30 ppb to 300 ppb.  Qualitative results  for these compounds were quite good. Participant AAA was
unable to identify chlorobenzene as present in Test S; with this  exception, all of the halogenated
compounds released were correctly identified by each  of  the participants.  Only one compound was
incorrectly identified as being present (1,2-dichloroethane  by Participant AAA in Test  13).
       Quantitative results were assessed by comparing FTIR to canister  results to determine overall
accuracy and  precision, as expressed in the collective FTIR data set.  Differences in performance
between  the individual instruments, and between the individual instruments and the canister method,
were determined through the use of statistical tests.
       In order to assess the overall accuracy of the FTIR results, FTIR concentrations were expressed
as percentages of canister-derived concentrations for the halogenated compounds only.  The mean and
a of these values for each FTIR system are shown in Figure 2. Examination of the plots reveals a large
positive bias for chlorobenzene in  the  concentration estimates provided by participants A and AA.
Otherwise the overall means for each compound are within  15% of the canister values; the pooled data,
minus chlorobenzene,  have a mean of  100.1%, with a standard deviation  of 20.5%.   These values
indicate no general pattern of bias and good overall agreement between the two methods.
       The overall FTIR precision was assessed by calculating relative standard deviations (RSDs) for
each of the six halogenated compounds released (Table HI). There were only enough canisters available
to collect the three collocated samples necessary to fulfill the QA requirement (Table IV), so precision
statistics could not be generated. However, many collocated whole-air samples were available front the
period 1985-19877. Table III shows RSDs determined  from those studies, and from analyses of audit
samples by three laboratories  in the summer and fall of 1991.
                                              610

-------
         250
       6«

       B 200
          150
          100
ra
c
           50
         • A. Mean
         D A. StDev
         H AA. Mean
         D AA. StDev
         0 AAA. Mean
         EQ AAA. StDev
                                      Hd
                                                          =. r


               111 TCA    TCE   FREON113   PCE
                                                  DCM
CB
                   Figure 2. FTIR Concentrations Expressed as Percentages
                               of the Canister Concentration
Table HI.  FTIR and Whole-Air Canister Variance.
Open-Path FTIR
1991 Intel-comparison
CompoupH std.dev.
1.1. -TCA
TrichloroeUjcne
Dichloromethane
Chlorobenzene
Tetrachloroethene
Freon
Pooled
22.6%
12.8%
9.3%
28.1%
6.8%
12.2%
16.7%


Whole- Air Canisters
(1985-1987)
Compound
1.1,1-TCA
Toluene
Benzene
Isooctane
n-heptane
IsopenUne
n-pentane
n-bexane
Pooled
std.dev.
4.2%
6.1%
2.1%
3.3%
3.7%
1.6%
2.0%
4.8%
3.8%
Whole-Air Audits
Interlab. Comparison
CflWTVPd
1,1.1-TCA
TnchJoroelhene
Dichlororoethane
Chlorobe&Dene
Tetrachloroethene
Toluene
Pooled
std.dcv.
7.6%
10.8%
34.2%
21.0%
26.6%
20.3%
18.7%


Table FV.  Concentrations from Collocated Canisters (June, 1991)
Test
3
9
15
Compound
Trichloroethlene
1,1,1-TCA
Toluene
Chlorobenzene
Isooctane
1.1,1-TCA
Freon 113
Concentration (ppb)
419, 424
151, 150
163, 167
135, 132
130, 136
216, 233
173, 183
                                       611

-------
       The statistics indicate that much greater precision was obtained with the canister technique in
the 1985-87 study than with open-path FTIR methodology, but several factors must be considered before
this statement can  be made for the general case.  The most  important  factor is  that the FTIR
measurements were made by three different instruments, operated by three different teams using three
different Standard Operating Procedures.   Conversely, the  sampling and analysis of the collocated
whole-air samples were always performed by the same group of individuals, using the same equipment,
instrumentation, and operating procedures. In the case of the audit analyses, most concentrations in the
audit samples were at least  one order of magnitude lower than those measured during the field study
 by the three FTIR participants,  which would generally  lead to higher RSDs for the audit analyses but
 it would appear  that the variance seen in  the whole-air method is increased by including results from
 other laboratories.
        A second factor that may have contributed to the FTIR variance results is that the measurements
 were made  at slightly different downwind distances (47, 50, and 53 meters).  A  Gaussian dispersion
 equation predicts a 10-15% decrease in point concentrations over a three-meter increase in distance at
 the ranges  used in this study, and a 5-7% decrease in  path-averaged concentration.   Field tests
 conducted with  whole-air samplers deployed at 40, 43, and 46 meters downwind in  a previous study
 produced point-concentration changes of 3-12% for three-meter increments.  Further analysis of this
 variance component is difficult because, in many cases during the field study, the FTIR system located
 nearest the  source produced the lowest concentration,  but it is reasonable to assume  that a portion of
 the overall variance was caused by differences in monitoring positions.  Given these two contributions,
 the overall precision of the open-path FTIR methodologies used during the study was very good.

 Statistical Comparisons
        The  fifteen blind trials produced twenty-three cases  in which correct identifications of aliphatic
 and aromatic chlorinated compounds were made by all three FTIR participants. Concentration estimates
 for the single aromatic compound, chlorobenzene (Tests 4  and 9), were outliers or extreme  values as
 defined by their position relative to the canister value1 and were removed from the FTIR data sets.  The
 twenty-one  remaining concentration values for each instrument  were considered together in order to
 produce a  sample size  sufficient for subsequent statistical analysis.   The  corresponding canister
 concentration values for the aliphatic chlorinated compounds were assembled into a fourth data set.
        While repeated  trials  on one compound at one concentration likely  would yield  a normal
 distributional pattern, data  sets formed by accumulation of single assessments  of different compounds
 would not be expected  to do so. However, the variance structure of the bias relative to the canister
 value [(FTIR value - Canister Value)/Canister Value]  should approximate a normal distribution; tests
 indicate that this was the  case.  Sample size (21), and the degree of approximation to the normal
 distribution, permit use  of the parametrical t-test and Analysis of Variance.  Non-parametric tests were
 also used for comparative purposes; such tests are distribution-free, robust,  and approach the power of
 parametric  tests if normality, which is not a requirement for use, is a property of the sample.
        Levels of significance for hypothesis testing are often arbitrarily established in studies where no
 prior guidance is available  to suggest that one level or another is  more appropriate10.  PROB-values are
 a better alternative in such cases, because they indicate the probability of making a Type I error.
        Correlations were assessed  for each pair of data sets  (Table V).   The  coefficients indicate
 significant (.001) association between the data set pairs.  Thus, there is a strong linear relationship
 among the FTIR instrument concentration estimates despite different designs and protocols.
        The  correlation results,  however,  do not show whether the FTIR data sets were all drawn from
 the same population;  an Analysis of Variance (ANOVA) was performed under the null hypothesis that
 the three data sets were so drawn.  The F-statistic for  the test was  3.06, and  the PROB-value was
 0.057.  The nonparametric  equivalent of this test (Kruskal-Wallis), produced an H-statistic of 6.298 and
 a PROB-value of 0.042. Results suggest that there is some evidence that the three FTIR data sets are
 not drawn from the same population, but the major contributor to such an outcome is unclear.
                                              612

-------
Table V.  Correlation Coefficients for Non-Standardized Data


A
AA
AAA
Canister
r P
0.973 0.943
0.980 0.909
0.940 0.896
A
r P

0.977 0.955
0.928 0.926
AA
r P


0.944 0.968
       The source of the variation indicated by the ANOVA was determined using the t-test and
         '  Matched-Pair Signed-Rank Test tests performed on each FTIR data set pair, and on each
  	-.^xr  data set  pair (Table VI).  Paired  comparisons of FTIR data  sets indicated  that
concentration values from instruments A and AA were drawn from the same population,  but that
instrument AAA values probably were not. This outcome helps clarify the ANOVA results described
above.  In general, the result was due to somewhat higher concentrations produced by instruments A
"•"* AA compared to those from instrument AAA. However, if the individual FTIR concentrations are
    yed against the canister method, then there was not sufficient statistical evidence for rejection of the
    hypothesis that the paired FTIR/canister data sets were taken from the same population.

Table VI.  Results of Paired Tests on Standardized Data
Pair Tested
A-Canister
AA-Canister
AAA-Canister
AA-A
AAA-A
AAA-AA
t-statistic
1.60
0.49
-1.89
-0.72
-3.08
-2.48
Prob.
0.13
0.63
0.074
0.48
0.0059
0.022
Wilcoxon
Statistic
159.0
153.0
66.0
107.0
41.0
51.0
Prob.
0.135
0,198
0.089
0.644
0.010
0.026
       The overall results of the statistical procedures for the aliphatic chlorinated hydrocarbon
 ass«sinents taken as a group for each instrument indicate (a) a strong linear association among the data
 **& from the three FTIR instruments (Table V); and (b) good agreement between concentration values
 «timated by the FTIR instruments and those obtained from the canister method (Table VI).  However.
 (c) there appeared to be statistically significant differences among the concentration estimates for the
 thr«c FTTR instruments.

 CONCLUSIONS
       The FTIR participants in the intercomparison study demonstrated an excellent ability to identify
 kalogenated compounds.  Performance  in identifying unsubstituted compounds,  both aliphatic and
 *n>matic,  was not as  good  overall,  and performance differed from  participant  to participant.
 Quantitative assessments for  aliphatic halogenated compounds were quite good overall,  FTIR data
 flayed lower precision than that obtained by collocated canisters,  out similar precision to that
 *ained in an interlaboratory whole-air audit study.  Statistical testing indicated some differences in the
      concentration assessments from participant to participant.  Finally, all three FTIR instruments
          concentration estimates that agreed fairly well with canister values.
                                             613

-------
REFERENCES
1.    Spartz, M.L., M.R. Witkowski, J.H. Fateley, R.M.  Hammaker, W.G. Fateley, R.E. Carter,
      M. Thomas, D.D. Lane, G.A. Marotz, BJ. Fairless, T. Holloway, J.L. Hudson, and J. Arcllo,
      "Comparison of Long Path FT-IR Data to Whole Air Canister Data from a Controlled Upwind
      Point Source," Proceedings. EPA/AMWA International Symposium on the Measurement of
      Toxic and Related Air Pollutants, Raleigh, NC, pp. 685 (1990).

2.    Carter, R.E., Jr., M. Thomas, D.D. Lane, J.L. Hudson, and G.A. Marotz, "Use of Wind Data
      to Compare Point-Sample Ambient Air Concentrations with Those Obtained by Open Path FT-
      IR," Proceedings. EPA  International Symposium on Field Screening Methods for Hazardous
      Wastes and Toxic Chemicals.  Las Vegas, NV, pp. 571 (1991).

3.    Russwurm, G.M., R.H. Kagann, O.A. Simpson, W.A. McClenny and W.F. Herget, "Long-path
      FT1R Measurements of Volatile Organic Compounds in an Industrial Setting," J. Air Waste
      Manage. Assoc.. Vol. 41. No. 8, pp. 1062 (1991)

4.    Carter, R.E,  D.D. Lane, G.A.  Marotz, "Long-Path FTIR and Whole-Air Intercomparibility
      Study, June 4-8, 1991," Technical Report, Region VII, U.S. Environmental Protection Agency,
      Kansas City,  KS (1991).

5.    Marotz, G.A., R.E. Carter, D.D. Lane, "Sampling Design  and Protocols Used in a Recent
      Study of Long-Path FTIR and Canister Compound Detection  and Estimation  under Controlled
      Field Conditions," Paper 2.4 in Proceedings. AWMA Specialty Conference on Optical Remote
      Sensing and Applications to Environmental and Industrial Safety Problems. (1992).

6.    Spartz, M.L., M.R. Witkowski, J.H. Fateley, J.M. Jarvis, J.S. White, J.V.  Paukstelis, R.M.
      Hammaker,  W.G.  Fateley, R.E. Carter, Jr., M. Thomas,  D.D. Lane, G.A. Marotz,  B.J.
      Fairless, T. Holloway,  J.L. Hudson, D.F. Gurka, "Evaluation of a Mobile FT-IR System for
      Rapid  Volatile Organic Compound Determination,  Part I:   Preliminary  Qualitative  and
      Quantitative Calibration Results," Journal of Geophysical Research. Vol. 90, No. C5, pp. 8995-
      9005 (1989).

 7.    Carter, RayE. Jr., M.S. Thesis, "Refinement and Field Testing of a Whole-Air Method for the
      Trace-Level Determination of Volatile Organic Compounds," University of Kansas, Department
      of Civil Engineering, Lawrence, KS (1989).

 8.    Schaefer, R.  and  R.  Anderson, MINTTAfi.   Reading, MA:   Addison-Weseley  Publishing
      Company, Inc (1989).

 9.    Ryan,  T.A.,  Jr.,  and  B.L. Joiner.   "Normal probability plots and  tests  for  probability,"
      Technical Report, Statistics Department, Pennsylvania State University.

  10.  Miller, I., Frucnd, J. and R. Johnson, Probability and Statistics For Engineers.   New York:
      Prentice Hall (1990).

DISCLAIMER
      This research project was funded by the U.S. Environmental Protection Agency under Contract
No. 070456NTEX,  The opinions, findings, and conclusions expressed are those of the authors and not
necessarily those of the U.S. Environmental Protection Agency.
                                            614

-------
         FTIR Open Path Monitoring of Fugitive Emissions
                   From a Surface Impoundment
              During a Bioremediatlon Test Program

                           Robert H Kagann
                          MDA Scientific Inc.
                      3000 Northwoods Pkwy #185
                        Norcross Georgia 30071

                           William A Butler
             DuPont Environmental Remediation Services, Inc.
                      Wilmington, Delaware 19809

                           James R Small
                          DuPont Engineering
                        Newark, Delaware 19714
Abstract


      An FTIR Remote Sensor was used to monitor fugitive emissions during a
pilot-scale test to demonstrate an in-situ Bioremediation alternative for sludge
contained within a surface impoundment.  The Bioremediation demonstration
and concurrent air emission monitoring took place In a 520 square meter pilot
cell which was constructed within a surface impoundment. The pilot cell was
equipped with separate submersible mixers and surface aerators. The pilot cell
was monitored along the downwind side by the FTIR sensor during periods of no
activity, mixing only, and mixing combined with aeration.  The measured
concentrations of the volatile and semi-volatile organic compounds emitted
increased markedly when the aeration was started. Concurrent emission
isolation flux chamber measurements indicated similar results.
                                 615

-------
Introduction
       A pilot-scale test of in-situ bioremcdiation of waste sludge was conducted in a pilot
cell within a surface impoundment. It is important from the standpoint of industrial hygiene
that fugitive emissions caused by the remediation activity be closely monitored. The open
path FTIR was investigated as a monitor because its integrated configuration ensures that
the emission plume can be measured for any wind condition.  Conventional point sampling
techniques present a  problem because of die possibility that the  strong  portion of the
emission plume can miss the discrete locations of the samplers and  flow in between them.
The remote nature of the open path measurement allows  measurement over  inaccessible
regions,  such as open water.  Another advantage of the open path FTIR is that the
concentration determinations can be obtained in real-time.  One can immediately obtain
information about any potential  health impact at the  site  during any of the  remediation
activities.

The Open Path FTIR System

       The open path FTTR used in the present program is a prototype  of  the MDA
Model 282000, which is used in a unistatic configuration.  A single transmitter / receiver
telescope transmits an twelve inch diameter beam across the parcel  of atmosphere to be
measured.  A comer-cube retroreflector array, placed out in the field, returns the infrared
beam to  the telescope, at the focus of which  is a liquid nitrogen  cooled MCT detector.
Before transmission, the infrared radiation passes through a Michelson interferometer of a
wishbone design. The wishbone design uses comer-cubes instead of flat mirrors and thus
has the advantage that the alignment of the interferometer components (such as the beam
splitter) never need to be readjusted in the field. The resolution of the interferometer is 1
cm'1.

       The retroreflector array, which is fourteen inches square, can be place farther than
500 meters from the transmitter / receiver telescope. The effective optical path is double
the distance to the retroreflector. This has the effect of doubling the absorbance signal.

The Method  of Determining Concentrations

       Thr chemical concentrations are obtained using the Beer's law relationship that the
absorbance due to a given  chemical species is proportional to the  concentration of the
chemical times the pathlength of the absorbed light through the chemical

                           A(v) = e(v)CLt                               (I)

which states that the concentration of a gas which absorbs  light at the optical frequency,
v. time the pathlength, L, that the light travels through the chemical gas, is proportional to
the absorbance, A(v).  The proportionality constant is the absorption coefficient, C(v),
which is a spectral parameter which solely depends on the particular molecular species that
is absorbing the light  The absorbance is defined by
                                       616

-------
                                                                          (2)

where I(v) is the intensity of the light, at frequency v, after it passes through the absorbing
gas, and Io(v) is the intensity of the light if all conditions woe the same except that the
absorbing gas is not present  The raw spectral data obtained from the open  path FTIR
corresponds to I(v) and is referred to as the single beam spectrum. The fe(v) spectrum is
referred to as the background. The ratio in Eq (2),  I(v) / Io(v), cancels all optical effects,
such  as the blackbody distribution  of the infrared source,  the  scatter property of the
atmosphere, the  transmissivities and  reflectivities of the optics, and the spectral response
of the detector.

       The concentrations of absorbing gases are obtained in the present system using the
multicomponent  classical  least squares, CLS, algorithm  described by  Haaland and
Easterling.1  This algorithm uses the relationship in Eq (1) to obtain the concentration
pathlength product of the absorbing gasses.   The algorithm is capable of handling gas
mixtures in which the absorption features of different components overlap. This feature is
necessary for atmospheric work because water vapor lines overlap much of the infrared
spectrum. The algorithm also has correction terms for linear baseline error.  This is an
important feature for open path measurements because it greatly reduces any  error from
using an Io(v) spectrum which is not  well matched to the I(v) spectrum.

       The algorithm calculates the roncentratioo-pathkngth product of the absorbing
gases. The conccntration-pathlength  product can be used in plume dispersion models to
calculate tmiw*"* fluxes and concentrations at downwind receptors. One rnry divide the
concentration-pathlength  product  by the total round-trip  path  length  of the infrared
radiation to obtain a path-averaged concentration.  If the absorbing gases were uniformly
distributed along the path, the path-averaged concentrations would also be the  actual
concentrations in the beam.

The Measurements

       The first task in making open  path FITR concentration dr
-------
 background measurement was 93 meters which was chosen to match the pathlength used in
 the first configuration for the emission measurements.

       The two configurations used to measure the chemical emissions are also shown in
 Figure 1.  These measurements were made by co-adding 64 sweeps, which takes about two
 minutes.  The measurements were  made using two different configurations both roughly
 parallel to the shore of the  surface  impoundment  The first  configuration used a one-way
 distance of 93 meters and the  second used an 81 meter one-way path.  Figure 2 shows the
 single beams from Run 1 in the top trace, the second trace is the background spectrum, and
 the bottom trace is the resulting absorbance spectrum from which the concentrations were
 determined. The absorption band of halocarbon 12 can be seen in the region from 800 to
 1200 cm-1, and the carbon monoxide band (not analyzed in the present program) can be seen
 at 2150 cm-1.

       Table 1 summarizes the results for the concentration determinations made over a
 four day period. The concentrations are reported in ppb, path-averaged. Each compound
 was analyzed using CLS in several different spectral regions.  The concentrations shown in
 Table 1 are the weighted average of the individual CLS results. The weighting parameters
 used  are  the standard  deviations of the  least-squares  fit propagated to the individual
 concentration determinations.  The numbers in the parentheses are equal to three times the
 standard deviation of the weighted  average,  and are relative to the  last two digits of the
 reported concentration value.  The  weighted average standard deviations were calculated
 from the weighting parameters, which are from the standard deviation of the least-squares fit
 as propagated to the individual concentration determinations.
       An example of a field spectrum is shown in Figure 3. The top trace is from Run 8 in
which 84.1 (3.1) ppb of chlorobenzene and 253.8 (9.1) ppb of o-dichlorobenzene (path-
averaged) was measured. The second trace is the reference  spectrum of chlorobenzene (170
ppm meter) and the bottom trace is the reference of spectrum of o-dichlorobenzene (153
ppm meter).
Discussion

       The first two measurements occurred before the onset of the remediation activities.
Halocarbon 12 was measured during these two runs, with concentrations 9.73 (26), and
12.45 (0.33) ppb, for Runs 1  and 2 respectively. Independent flux chamber measurements
and analysis of the contents of the sludge indicated that the predominant species present in
the pilot cell were chlorobenzene and o-dichlorobenzene and to a lesser extent, halocarbon
113. Halocarbon 12, if present, was a very minor component. The halocarbon 12 measured
during these two runs was determined to originate from an upwind source on the other side
of the surface impoundment.
                                      618

-------
       The concentration determinations made on die first measurement day are  plotted
against the time of the measurement in Figure 4. The mixers n die pikx ceU were turned on
before the first  measurement The aerators were turned on at 1437, and die concentrations
of  both  chlorooenzene and o-dichlorooenzene irh, mril tmmedtaaciy afterwards.  The
concentration of chlorobenzene reached a peak of 89 ppb (paoVaveraged) and leveled off.
Tbe same trend occurred widio-dkhlarobenzene, which reached apeak of  254 ppb and
then leveled off.  A plot of the concentrations, of cnlorobenxene and fMtiffrkyfrfTtre"?.
versus die time of measurement is shown in Figure 5. The aerators  and mixers were on at
the onset of the measurements. When the aerators were switched off for a short period just
before 15:00, the concentrations feU below the detection boat  When the aerators were
switched back on. the concentrations immediately irmtfre*  The same trends can be teen
in die measurements of the third day, which are plotted in figure 6,

       The standard deviation of  the least-squares fit is a good representation  of the
precision of the concentration measurement.2   In the present study die standard deviations
varied from 1 to 11 percent of the  concentration value*.  The matn sources of systematic
error  are: error in the concentration of the gas used  to measure die icfutnct spectrum.
non-linear error in UK baseline of the absorbance spectrum, non-nncarity in  die detector
response, and  Boltzman  temperature effects.   Oo the basis of  various  validation
measurements,1-4-*-6 die total systematic error is estiratrd to range from 5 to 20 percent.
depending on bow close the concentrations are to the mmtmuro detection Icvei
       A measure of the tyww***G CTTOT can be oNiifttxi fry performing a ojuatity assurance
Procedure. This consist of flowing a known quantity of dte tarfet gases through an internal
cell through which the infrared fry" p«T«T  before it transmits through die atmosphere.
This cell  is a part of the MDA FUR Remote Sensor, however,  work  to provide a
quantitative amount of gas goes beyond die scope of the present fcasibiliry study.
Conduit
       The present study was a feasibfliry study.  Tbe results indicate (hat die open path
      would be a valuable  monitoring tool during bioremediaoon activities at surface
impoundments. Quality assurance procedures wen beyond the scope of this ontial study.
In future appiVtrtofti quality «y^"rr procedures wiD be foDowed in order to determine
»e overall accuracy of the concentration i
                                       619

-------
References

1. D. M. Haaland and R. G. Easterling, "Application of New Least-squares Methods for
   the Quantitative Infrared Analysis of Multicomponent Samples," Applied
   Spectroscopy 36,655-673. (1982).
2. R. H. Kagann and O. A. Simpson, "HiK Remote Sensor Data from the EPA Region
   VII FTIR Intcrcomparison Study," AWMA/CMA Conference on Optical Remote
   Sensing and Applications to  Environmental and Industrial Safety Problems,
   Houston TX (April 5 - 8, 1992).
3. R. H. Kagann, R. DeSimone, O. A. Simpson, and W. F.  Herget,  "Remote FTIR
   Measurements of Chemical Emissions," EPA/AWMA International Symposium on
   Measurements of Tone and Related Air Pollutants, Raleigh NC (April 30 - May
   6.1990).
4. G. M. Russwurm, R- H. Kagann, O. A. Simpson, W. A. Mcdenny, and W. F. Herget,
   "Long-path  FTIR measurements of Volatile Organic Compounds in an Industrial
   Setting/ J. Air Waste management Assoc. 4,1062 -1066, (1991).
5. R. E. Carter Jr. D. D. Lane. G. A.  Marotz,  and J. Hudson,   "A Field-based
   Intercomparison  of the Qualitative and Quantitative Performance of  Multiple Open-
   Path FTIR Systems for Measurement of Selected Toxic Air Pollutants," EPA Report,
   Contract No. 0704S6NTEX (1991).
6. R. J, Kricks, R. L. Scotto. T. H. Pritchett, G.  M. Russwurm, R. H. Kagann, D. B.
   Mickunas, "Quality Assurance Issues Concerning the Operation of Open-path FTIR
   Spectrometers,"   AWMA/CMA  Conference on Optical Remote Sensing  and
   Applications to Environmental  and Industrial Safety Problems, Houston TX
   (April 5-8, 1992).
                                    620

-------
Table 1   The Open-path FTIR Concentration Determinations,  AD values arc  path-
          averaged.  The reported concentrations are the weighted average of several
          determinations     made     over     different     absorption     bands.
          The numbers in the parentheses are equal to three times the standard deviation
          of the weighted average.  They originate  from the standard deviation of the
          least-squares fit for each individual determination.
R
u
n

1
2
4
5

7
8
9
10
11
12
13
15
16
17
18
20
21
22
23
24
25
26
?,7
29
30
32
33
34
35
36
37
38
39
40
41
42
43
46
Day

5-20










5-21










5-22
















Time

14:19
14:24
14:35
14:38
14:43
14:48
14:54
14:59
15:04
15:09
15:14
9:22
10:25
11:07
11:13
14:06
14:50
14:55
15:00
15:09
15:15
15:37
8:43
9:16
9:24
9:29
9:45
9:48
9:50
9:53
10:10
10:15
10:20
10:26
11:49
11:54
13:20
13:21
13:32
Path
Length
oneway
(meters)
93










93










81
















CLBZ
(DDb)
13.2(4.4)


32.8 (5.9)
62.7 (3.2)
88.7 (4.7)
84.1 (3.1)
74.4 (3.0)
79.1 (4.6)
72.0 (3.5)
74.3 (2.6)

19.4 (5.9)


44(12)
61(25)
55 (19)

51 (21)
50(14)
63(20)



145 (12)
128 (12)
59(11)
44(11)
38(11)
43 (15)
43 (13)
85(11)
143(12)
196(13)
152 (13)
112(38)

133 (16)
ODCB
(DDb)



90.9 (9.1)
164.5 (9.7)
244.6(8.1)
253.8 (9.1)
234.4 (8.6)
219(11)
225(11)
203.6(5.3)

39 (12)
44(13)
5403)




67(26)
69(19)
137(49)

109 (21)
110(22)
384(22)
394(20)
240(20)
195 (21)
176(20)
115(20)
116(20)
254(20)
383 (21)
532(22)
398(20)
355 (48)

377(26)
Fll
(DDb)
0.95 (12)








3.23 (81)


























13.8 (1.7)


F12
(DDb)
9.73(26)
12.45 (33)







1.88(65)





























F113
(DDb)








4.6(1.8)
5.9 (1.8)
3.12(91)

3.7 (1.2)
3.7 (1.3)
3.4 (1.2)
27.0 (4.9)


8.5 (2.4^


7.0 (2.5)

















                                      621

-------
Table 1
(Continued)
It
D
D

47
48
49
50
SI
54
79
91
92
93
95
96
97
100
101
102
103
105
106
107
108
109
D»7

5-22





5-23
5-24














Time

13:37
14:07
14:12
14:23
14:38
15:10
15:20
10:17
10:21
10:24
10:26
10:31
10:34
10:41
10:46
10:51
10:53
10:58
11:06
11:11
11:17
13:24
Path
Length
oneway
(meters)
81





250
81














CLBZ
(DDb)
150071
115(181
111(175
115(151
131 (121
119(11}

65(20)
64(18)
114(101
113(23)
155(201
173^20)
83 (19)



107 (19)
nS^W)
137 (19)
191(20)
113.6(8.6)
ODCB
(ppb)
409(28)
306(30)
304(29)
318(30)
317,02^
351(29)

212 (38)
212(36)
351(35)
400(44)
475 (42)
190(39)
193 (40)
184(47)


260(36)
446J36L
342(38)
514(37)
189(28)
Fll
(ppb)






















F12
(rob)








4.6(1.1)
6.30(93)












F1U
(ppb)



13.6 (4.4)



10.1 (4.0)
9.0(4.1)












55 (10)
                                622

-------
Surface
Impoundment
Retro
                                          Retro
     Pilot Cell
                                   81 m
                  93 m
                                             93 m

                                  lo Measurement
    North
  Figure 1    The Configuration of the Measurements Made at the Pilot Cell in the
           Surface Impoundment. The position of the retroreflector array is outside
           of this view. The wind was from the south east direction during the
           background measurement and from a southerly direction for most of the
           chemical emission measurements.
                           623

-------
           7OO
                     120O
                                 1 7OO      22OO      27OO
                                 Wov»numt>«r»  (cm—1)
                                                                  32OO
Figure 2  The Single Beam Spectra and the Resulting Absorbanee Spectra From Run  1.
          Top Trace:  The downwind (I) single beam spectrum.  Middle Trace:   The
          background (lo) spectrum.  Bottom Trace: The Absorbanee Spectrum.  The
          absorption bands in the region from 750 to 1200 cnr1 are due to halocarbon
          12.
               Rung
               Chkxobenzene
              o-t>cM
-------
        May  20,  1991    Waste  Water  Site
                                    • Chlorobinzin*
                                    * o-dlclhlorob*nztn»
                                    * F 11
                                    • F 12
                                    * F 113
0.
^
.0
~&
£:

-------
       May  21,  1991  Surface  Impoundment
           200
           175
           150
           125
       *   100
       o
       O
            75
            50
            25
                                     * Chtorob«nz«n«
                                     * o-dlelhlorob*ni«n*
             14.0
              A
M.5
15.0
       A ON
   A  OFF
15.5
   t  Time   (Hour)

     A  ON
Fifurc 5  Plot of Measured Concentrations versus Time During Day 2.  The error ban
        represent three hues the ***ima
-------
       May  22,  1991  Surface  Impoundment
                                        Chlorobtnz»n*
                                        o-dlclhlorob»nz«n«
           800
           500
        a)  30°
       i
        
-------
                                                   May
                                                      1992
AIRBORNE LIDAR MAPPING

OF OZONE CONCENTRATIONS

DURING THE LAKE MICHIGAN

OZONE STUDY


Edward E. Uthe, Program Director
John M. Livingston. Senior Research Meteorologist
Norman B. Nielsen, Senior Research Engineer
Atmospheric Science and Effects Program
Geoscience and Engineering Center
 Prepared for presentation at 1992 EPA/A&WMA Symposium
 on Measurement of Tox'c and Related Air Pollutants
 Durham. North Carolina 4-8 May 1992
 To appear in Proceedings
                              628

-------
             AIRBORNE LIDAR MAPPING OF OZONE
    CONCENTRATIONS DURING THE LAKE MICHIGAN
                               OZONE STUDY*

               Edward E. Uthe, John M. Livingston, and Norman B. Nielsen
                                    SRI International
                                333 Ravenswood Avenue
                                 Menlo Park, California


 ABSTRACT
     An airborne differential absorption Hdar (DIAL) was used during the 1991 Lake Michigan
 Ozone Study (LMOS) to map the vertical distribution of ozone concentrations across Lake Michigan
 downwind of urban and industrial areas of the south lake region. The DIAL, which was designed as a
 compact instrument for installation on a relatively small-sized twin-engine aircraft (ideal for operation
 °n regional air-quality studies), is based on the use of an excimer laser and Raman cell to generate
 multiple-wavelength ultraviolet energy appropriate for remote measurement of tropospheric ozone.
     Collected DIAL backscatter signatures are analyzed in terms of contour analyses of vertical
 ozone concentration distributions across Lake Michigan. During times of southwesterly winds, large-
 scale urban ozone plumes with ozone maxima at elevated altitudes were observed (mostly over the
 lake and eastern shoreline) that increased in concentration during the day. Small-scale elevated ozone
 minima, caused by subsidence of clean air aloft and by chemical destruction of ozone by industrial
 reactive-gas plumes superimposed on the larger-scale urban ozone plumes resulted in very complex
 vertical ozone  distributions.  Other data reveal effect of increased convection over land surfaces (as
 opposed to over water surfaces) and significant variability of ozone vertical distributions over small
 fane intervals that arc difficult to observe without use of remote sensing techniques. DIAL-derived
 ozone concentrations compare favorably with airborne in-situ ozone measurements.
BACKGROUND
     Near-surface ozone concentrations downwind of many urban areas frequently exceed the
national ozone standard established by the U.S. Environmental Protection Agency. One approach to
understand dynamic and chemical processes leading to ozone excellences and to investigate effec-
tiveness of control strategies designed for attainment compliance, as mandated by the 1990 Clean Air
Act Amendments, is to conduct numerical experiments with air-quality photochemical models tailored
and validated to specific regional areas.  Model development and validation for specified locations,
emission inventories, and meteorological conditions requires field observation of ozone concentration
distributions with high spatial and temporal resolutions over regional areas,
     A substantial and successful effort has been made to develop and apply differential absorption
iidar (DIAL) for profiling tropospheric and stratospheric ozone concentrations.  Basically, the DIAL
technique transmits laser energy at two or more closely spaced wavelengths with different absorption
coefficients of a specific gas (e.g., ozone) into the atmosphere and analyzes range-resolved lidar
°aclcscatter signatures in terms of gas-concentration profiles. The technique has been adequately

 "^ conference paper is a condensed version of a paper recently submitted for publication in the Journal of the Air and
 aae Management Association.
                                        629

-------
discussed in the literature1 since its Tint demonstration by Schotland.2 DIAL systems for ozone mea-
surement have been demonstrated based on flash-lamp pumped dye lasers,2-3 laser-pumped dye lasers,
*~7 excimer lasers.8-14 and CC>2 lasers.15 However, these systems were operated from the surface or
large aircraft; systems capable of being operated from small twin-engine aircraft typically used on
regional field studies are needed for mapping ozone concentration distributions required for air-qual-
ity model development and validation applications.

Compact Airborne Ozone DIAL
      Since 1979, SRI International has applied airborne lidar to air quality studies using elastic scat-
tering, fluorescent scattering and DIAL systems operated from a relatively small-sized Queen Air air-
craft. I6"18  Airborne lidar air-quality investigations using small aircraft have also been well demon-
strated by the U.S. Environmental Protection Agency.19-20  SRI International developed a design for
an ultraviolet DIAL (UV-DIAL) suitable  for instillation on the Queen Air based on the use of an
excimer laser and stimulated Raman generation of energy at proper wavelengths for airborne tropo-
spheric ozone measurement as suggested  by Shibata et al.10  This approach is ideal for air-quality
investigations, because of the high spatial resolutions that can be obtained by the relatively high
transmit energies and high pulse rates of excimer lasers. The design accounted for cost and time con-
straints (the system construction began February 1991 for use on a June 1991 field study) in addition
to aircraft limitations on system weight,  size, power and weight distribution. A Questek Model 2050
vp excimer laser operating with KrF (248.5-nm emission wavelength) was modified to operate on its
side with beam exit directed vertically upward through a 3O- x 145-cm enclosed optical table attached
to the laser, as pictured in Figure 1.  The beam was directed through a 1-m Raman cell containing HZ
gas and the Raman wavelength-convened energy transmitted vertically downward from the aircraft
(ihe 248.5-nm residual energy was blocked from transmission).  The DIAL receiver consisted of a l4'
inch telescope and two (EMI 9893B/350) photomultiplicr detectors; the wavelength response of each
receiver channel was determined by dichroic and interference optical filters. The detectors were gawd
off for signal return at short ranges  to prevent detector saturation.  Signal output from each ^fXC^[
was input to 10-bit, 20-MHz (7.5-m range resolution) transient digitizers with internal memories useo
to average a number of backscaner returns before the records were transferred to a MicroVAX II com-
puter that controlled data processing, display and optical disk recording.  An RGB memory/gnP^
module and video scan convener provided for processed data display on a standard TV and recording
on an 8-mm VCR. Other data sources included time and LORAN-C aircraft location.  Details of tne
UV-DIAL and aircraft installation are given by Nielsen et al.21

LMOS Data  Collection
     The Lake Michigan Air Directors  Consortium (LMADQ*  is conducting a major mcasulCJ1J£
and modeling study of ozone concentrations over the Lake Michigan regional area. As part of
Lake Michigan Ozone Study (LMOS). an extensive atmospheric sampling program was condu
from mid-June through early August of 1991.22  The LMADC as a special research study, w
airborne DIAL measurements of two-dimensional ozone-concentration distributions along flignt
extending across Lake Michigan. The LMOS afforded an opportunity to evaluate applications _^
performance  of the compact airborne UV-DIAL.  The  DIAL measurements provide LMOS   ^
potentially  detailed ozone distributions  of much higher spatial and temporal resolution than can
obtained with in-situ sensors.                                                            .-^
      Flight tracks for the five in-situ sampling aircraft used on LMOS were prearranged by obw
FAA flight approval.  Because one objective of the DIAL program was to validate observed o
concentrations, the latitude-longitude flight patterns of the in-situ aircraft were also used by the V ^
aircraft; however, the DIAL aircraft was flown at a constant altitude, typically 1.7 km (5500 ft) a
 *The met of mjnois. Indiana. MktufMi ml Wi
                                            630

-------
the surface.  The DIAL aircraft was based at the Waukegan, Illinois, airport and was flown west-to-
east across the lake along a flight path flown by an aircraft operated by North American Weather
Consultants (NAWC),23 and returned along a flight path farther north flown by an aircraft operated by
the National Atmospheric and Oceanographic Administration (NOAA).^4  Figure 2 presents a
computer-generated plot of a typical DIAL aircraft flight pattern superimposed on an outline of Lake
Michigan. Table I presents a log of times that airborne DIAL ozone data were collected during the
LMOS.

Table L  Airborne Oa-DIAL Data Log.
Date
"~ 06/28/91
07/03/91
07/10/91
07/16/91
07/16/91
07/17/91
07/17/91
07/18/91
07/18/91
07/19/91
07/27/91
07/30/91
07/31/91
Time
1140-1400
1340-1440
1350-1500
1220-1420
1700-1910
1130-1255
1654-1930
1130-1411
1700-1900
1840-1936
1400-1514
1220-1400
1230-1515
Raman
Gas
D2
D2
H2
H2
H2
H2
H2
H2
H2
H2/D2
H2/D2
H2/D2
H2/D2
Remarks
Computer problems; some data
System changes; some data
H2data
Good H2 data
Good H2 data
Clouds on eastern end; computer problem at 1255
Some computer outages
Some computer outages
Some computer outages at end of run
H2/D2 test; some data
System test; some data
System test; some data
DIALJin-situ comparison
      Although the laser is capable of a 50-Hz pulse rate, a 30-Hz rate was used because of aircraft
power limitations.  [A new, low-power data system incorporated since LMOS will allow use of the
50-Hz rate on future studies.]  Range resolved backscattered energy at wavelengths of 277 and 313
nm for H2 Raman gas, 268 and 292 nm for D2 Raman gas, or 277 and 292 nm for a gas mixture were
digitized with a resolution of 7.5 m over a range interval of about 2.9 km so that surface returns were
always present  The digitizer memories were used to average backscatter signatures for 150 laser fir-
ings (5 s), which corresponds to a flight distance of 290 m at the typical aircraft speed of 130 mph.
Output of the averaging memories was displayed on an oscilloscope for real-time monitoring of sys-
tem performance.   All data were recorded  on optical disk for subsequent analysis of ozone
concentrations.

Data-Reduction and Analysis Method
      The DIAL system collected a large volume of data that must be compressed for effective dis-
olay and analysis in terms of ozone concentration distributions.  More than 20 million data points
result for each 1° longitude flight path segment.  The following procedures were applied to generate
two-dimensional cross sections of ozone concentrations depicted as contour analyses:
     .    The flight path was divided into eight approximately equal intervals for each 1° of longi-
         tude, with the objective of evaluating an ozone profile for each interval.
         The 10 recorded DIAL backscatter signature pairs nearest to each location for which an
         ozone profile is desired were averaged. This results in averaging data collected from 1500
         laser firings for evaluation of each ozone profile—a typical aircraft travel distance of
         2.9km.
                                           631

-------
RAMAN CCU.
MM. RECEIVER

                                     SM QUEEN AIR
                                          17 JULY 1981
                                     1651 - 1930 COT  -I
 41 S
                                                  •SO
                          DIAL •trmft fl%M tn
                                  -*1 it i r II HIM
                        632

-------

        DIAL ozone analysis, correcied for wavelength dependence of molecular attenuation and
        backscatter but without aerosol correction, was applied to 150-m thick layers  Values were
        evaluated at 7.5-m altitude increments and a five-point running mean was used to produce
        the final ozone profile.
        The resulting grid of ozone values was input to a contouring algorithm. Figure 3 illustrates
        a grid of ozone values (every other point in the vertical is printed in this example) and the
        resulting computer-generated ozone concentration contours.  Only the contours are retained
        on final presentations and ozone concentrations greater than a given value (typically 80 ppb)
        ne shaded.

                                                   Airborne DIAL Data Examples
                                                        On 10 July, the DIAL aircraft  was
                                                   repetitively flown over the western side of
                                                   Lake Michigan along the southern pan of
                                                   the  flight  pattern  shown  in  Figure 2.
                                                   Surface ozone concentrations on 10 July
                                                   were substantially less than the  120-ppb
                                                   standard.  Figure 4  presents three  ozone
                                                   cross sections as  the aircraft made west-to-
                                                   east traverses  during the  time periods of
                                                   1348-1359  CDT, 1418-1427 CDT.  and
                                                   1446-1456 CDT; these cross sections show
                                                   an elevated wedge of enhanced ozone con-
                                                   centrations of 75 to 90 ppb sloping upward
                                                   from west to east  The well-defined edge of
                                                   the  ozone wedge may be associated with
                                                   daytime convective activity over  land sur-
                                                   faces  and stable  air over water  surfaces.
                                                   These data show consistent ozone patterns
                                                   for  repetitive traverses of the same flight
                                                   path, adding validity to the DIAL observa-
                                                   tions  and  also showing  that significant
                                                   variations of vertical ozone distributions
    occur over short time periods, such as the altitude decrease of the ozone maximum  above the
western shoreline.
     Figure 5 presents  ozone  distributions observed near the western shore of Lake Michigan on 1
  lv 1991 during the time penod 1138-1157  CDT.  This was the second day of a muUiday ozone
   sode in the Lake Michigan Area with southwesterly winds. Clouds Limited the observations east of
e7°W longitude.  A well-oefined ozone plume, centered at an altitude of 500 m, is observed over the
lake surface with its western edge coincident with the lake shoreline. The contour analysts suggests
  it increased convection introduced by surface heating of the land surface may have established the
western edge of the ozone plume and may also have resulted in larger ozone concentrations at higher
altitudes than over the water surface.  The higher-altitude ozone contours near 87°W longitude may be
  result of increased convection associated with cloud distributions that were observed over the east-
ern part of Lake Michigan.
      Figure 6 is a contour analysis of ozone distributions derived from DIAL data collected on 18
 ulv 1991 during the period 1708-1754 CDT  as the DIAL aircraft was flown west-to-east  along the
 outhern  pan of the DIAL flight track. The vertical ozone distributions above the western shore of
Lake Michigan are about 60 ppb and agree with values observed on an earlier flight across the  lake on
18  July.   However, as shown by ozone  concentrations greater than 80  ppb (the shaded areas of
       ,, .  - •  •" '  » '
-  •
Contour «o«ly«4i of
airborne DIAL
1157 CDT, din-tag »
                                           633

-------
               t—LU       '   '   1.  t   Tit   !   t T
        020
        060
     1
        040
              10 JULY 1418-1427 COT

              OZONE VALUES IN ppb
        020
                       --PROFILE LOCATION INDICATOR
                       ;   -           -   ...
        060

                          878
                          LONGITUDE — og the loulbcrB nigbt track.
                               654

-------
 075
 023
 000
  980
       -I	1	1	     	1	
        LMOS 17JULY1901 1138-I1S7CDT
     OZONE VALUES IN ppb
                        /PROFILE LOCATION INDICATOR
                                     LAKE •• | •• LAND

       _4	i  T  i—J-i	J	14—i—t-i
      875
LONGITUDE — « W
                           870
Figure 5.  Contour analysis of ozone distributions derived from
        airborne DIAL observations made on 18 July 1991,1806-
        1848 CDT, during a west-lo-east flight along tbe northern
        night track.
                                                     Figure 6), a large-scale ozone plume has
                                                     developed over Lake  Michigan with the
                                                     highest concentrations  (>110ppb)  at
                                                     altitudes below 300 m. The position of the
                                                     large-scale ozone plume is consistent with
                                                     transport by southwesterly winds of efflu-
                                                     ents from the Chicago area. An interesting
                                                     ozone  minimum (50  ppb)  is  embedded
                                                     within the large-scale  ozone plume at an
                                                     altitude of  650 m.  The ozone minimum
                                                     may  result  from subsidence of clean air
                                                     aloft or from  industrial  plumes rich in
                                                     reactive gases that destroy ozone.  The
                                                     high  concentrations located just west of
                                                     the ozone minimum suggest that the ozone
                                                     minimum results from subsiding air with
                                                     compensating  high concentration (>100
                                                     ppb)  air from lower altitudes  penetrating
                                                     above 500 m.
                                                          A  contour  analysis  of  ozone
                                                     concentrations derived  from data collected
                                                     on 18 July 1991 (1810-1848 CDT) during
                                                     the  return  east-to-west flight on  the
                                                     northern part of the DIAL flight track is
                                                     presented in Figure 7.  Relatively uniform
ozone concentrations are observed west of the 87°W midlake location, with an elevated, 90-ppb ozone
plume at an altitude above 500 m. The ozone concentrations east of 87°W are substantially greater
than those west of 87°W.  The ozone concentrations >80 ppb (shaded area) are probably part of the
Chicago urban ozone plume identified by data collected along the southern flight leg (Figure 6), being
consistent with the southwesterly winds. Ozone concentrations and plume structure agree well with
data collected by the NOAA aircraft.24  An ozone concentration minimum located at 86.5°W and
250 m altitude is embedded in the high ozone concentration urban plume resulting in complex ozone
distributions with concentrations ranging from  50 to 150 ppb over a  relatively short distance. The
ozone minimum is probably a result of an industrial plume of reactive gas destroying ozone. A search
of the in-situ data records from the aircraft operated by North  American Weather Consultants con-
firmed that sharp ozone minima were associated with sharp NOX maxima, indicating the effects of
reactive gas plumes on ozone concentrations.23
      A comparison between  airborne DIAL and airborne in-situ measurements of ozone concentra-
tions was conducted on 31 July 1991.  The DIAL aircraft was flown at  an altitude of 1676 m (5500 ft)
while the  in-situ measurement aircraft was flown along  the same flight track, but alternately at alti-
tudes of 380 and 750 m.  DIAL data records were analyzed in the same manner as for  the contour
analyses, except that ozone profiles were evaluated for 150-shot averages (rather than for 1500-shot
averages) and the ozone values  nearest to the two in-situ aircraft altitudes for each profile were
retained for the data comparison.  An eleven-point running mean was performed on the DIAL values
to simulate 1500-shot averaging used for the ozone contour analyses. The results are shown in Figure
g. The DIAL-observed ozone concentrations are generally within 10 ppb of the in-situ observations
with the DIAL values showing more ozone variability along the horizontal path than the in-situ val-
ues, but not in a random manner,  indicating the validity of the DIAL-obscrved variations. Aerosol
effects resulting in higher DIAL values are minimized by comparing ozone concentrations along hori-
zontal paths, rather than by comparing ozone profiles.
                                          635

-------
   	I   •   •   •   •  *  t i
                     U3MXTUOC-I
Flc*r* *. Coatoor
        •IrbOTMDlAL
        IMt-UUCDT,

 i derived from
i IS July 1991,
I nijhl along the


            s-nvuumreBiVBBm
                                  UUl—f»LAJ«
       t/ttttt.ttltJt.ttt.
   171
                                                   H*
       -
                                        ,31 July 1991.
                          636

-------

OWL. '«•
MS
          »ecr


                                                            CONCI l SHINS
                                                            AND FUTURE PI \Ns
                                                                 A compact airborne DIAL
                                                            designed for UK on relatively
                                                            small twin-engine aircraft appro-
                                                            priate for application to urban
                                                            and regional air-qualm-  r
                                                            fatioos  has been demonstrated
                                                            by making ozone concentration
                                                            distribution measurements dur-
                                                            ing  (be  1991 Lake Michigan
                                                            Ozone Study  Altitude/distance
                                                            ozone  cross section*  made
                                                            across Lake Michigan revealed
                                                            complex vertical ozone distribu-
                                                            tions resulting from large-scale
                                                            urban ozone plumes and wedges
                                                            and  superimposed small-scale
                                                            ozone minima caused by subsi-
                                                            dence of clean air aloft and by
                                                            destruction of ozone by elevated
                                                            industrial reactive gas  plumes
                                                            The DIAL ozone concentration
                                                            observations   made   during
                                                            LMOS typically ranged  from 50
                                                            to  150 ppb. typically  showed
                                                            ozone maxima at  elevated alti-
                                                            tudes  and  larger ozone con-
                                                            centrations  over the  eastern
                                                            shoreline than over the  western
                                                            shoreline  of Lake  Michigan.
                                                            in general agreement with results
                                                            derived   from  in-stiu   air-
                                                            borne measurements.23-24  DIAL
                                                            ozone concentrations  compare
favorably with independent in-iitu measured ozone concentrations, but  aerosol effects on the DIAL
analysis must be considered.25  Although the DIAL ozone concentrations may be biased by  as much
   10 to 20 ppb by unaccounted aerosol effects, ozone distributions depict structure of the  Chicago
  ban plume and expected differences m daytime convection over land and take surfaces and should
 rovide additional information on ozone transport diffusion and transformation processes upon fur-
ther analysis with wind and emission inventory data.
     Two shortcomings were noted with  the airborne ozone-profiling DIAL system, and  possible
means to reduce their effect on ozone measurements are being considered- The photomulnplicr detcc
tors limit the receiver dynamic range to less than three orders of magnitude.  Greater receiver  dynamic
range is needed to extend the ozone measurements over a greater altitude interval. One method is to
use two or more detecton on each wavelength channel in a configuration that provides for detection
of strong signals from short ranges by one detector and detection of weak signals from long ranges by
the other detector.
     KM! '»'
                  *"•
    of airfcorac fV-DI AL <
                              657

-------
     The other problem is atmospheric aerosol effects on ozone measurements. Because of the
slowly varying ozone absorption coefficient with wavelength in  the ultraviolet, a relatively large
wavelength interval is needed between DIAL ozone wavelengths. This can introduce uncertainties in
the ozone evaluations because of wavelength variability in backscatter and attenuation of atmospheric
aerosols.  Browell et al.25  have investigated aerosol effect* on ultraviolet DIAL measurements of
ozone and have shown that correction factors as large as 30 ppb  may be needed in regions where
aerosol scattering changes abruptly.  A longer-wavekngth lidar measurement, such as with a Nd:Yag
laser (1.06 urn), could be used to evaluate an aerosol concentration profile to provide a first-order cor-
rection for aerosol effects on the DIAL ozone measurement. However, a better method may be the
derivation of an aerosol attenuation profile at ultraviolet wavelengths by observing Raman back-
scattering of the excimer laser energy from atmospheric nitrogen.2W7 Because nitrogen is a well-
mixed gas with a known density profile, a Raman nitrogen return can be interpreted in terms of atmo-
spheric attenuation at the Raman wavelength and used to derive UV-DIAL aerosol correction terms-
Because of the relatively high aerosol concentrations downwind of urban and industrial areas, addi-
tional effort is needed to correct the DIAL ozone measurements for these aerosol effects.23 In add1'
lion, use of combined H2 and Di Raman wavelengths will reduce the DIAL wavelength interval and
thus reduce the aerosol effect.2*^9
     The LMOS DIAL ozone distribution measurements indicate that effects of industrial reactive
gas plumes on ozone depletion were  observed.  The value of the DIAL measurements would be
greatly enhanced if the distribution of nitrogen oxides, hydrocarbons, and other chemical species that
affect the  ozone chemistry could be remotely measured in addition to ozone.  Although lidar tech-
niques can be used for this purpose, use of separate systems for each gas  species would probably be
needed, which would require a much larger aircraft than the Queen  Air.  An alternative approach
would use passive radiometnc techniques to measure column-content gas concentrations. We have
purchased a Fourier  transform  infrared (FTIR) emission spectrometer to measure high-resolution
infrared spectra of thermal radiation from which path-integrated gas concentrations can be inferred-
Ozone can also be measured by the FTIR and these measurements may be useful for correcting the
DIAL ozone profiles for the aerosol  effect.  We plan to evaluate the use of coaligned DIAL and FTIR
on future ozone-measurement programs.
     The airborne DIAL measurements made in the Lake Michigan regional area show that complex
ozone concentration distributions can develop in the  vertical and that these distributions can vary
greatly over relatively short time periods.  Observation of the detailed diurnal variability of ozone
concentrations over specific locations will provide important data for development and validation of
air-quality models needed for evaluation of strategies designed to reduce near-surface ozone concen-
trations over regional areas. The DIAL system, used as an upward-viewing, ground-based sensor.
may provide continuous moniioring of vertical ozone distributions of the atmospheric boundary lay**'
and we plan to investigate this capability in the near future.

ACKNOWLEDGMENTS
     The work described here was sponsored by the Lake Michigan Air Directors Consortium.
Conclusions relating to causes of the variations in ozone level are those of the authors and not neces-
sarily those of the Lake Michigan Air Directors Consortium.

REFERENCES
  1  R.T.H Cottis, P.B. Russell, *lJdar measurement of panicles and gases by elastic backscattering
and differential absorption.- in Laser Monitoring of the Atmosphere EJ> Hinkky. ed. (Spriogef-
Verlag. Berlin. 1976). pp. 71-151.                        —r—  .           J
 2. R.M.SchoUand.-Some observations of the vertical profile of wwer vapor by means of * fro00*1'
based optical radar." Proc. 4tk Sy*p  Remote Sensing oft** Exvirotneta (University of Michig*"-
Ann Arbor. 1966). p. 271.
                                           &3S

-------
  -  G  Megic, J.Y. Allain, M.L. Chanin, J.E. Blamont, "Vertical profiles of stratospheric ozone by
     sounding from ground," Nature 270:329 (1977).
 4  A J Gibson, L. Thomas, "Ultraviolet laser sounding of the troposphere and lower stratosphere,"
Nature 256:561 (1975).
 <   S  Sutton, "Differential lidar measurements of ozone in the  lower troposphere," Report
TPRD/L/2967/N85, Central Electricity Research Laboratories, England (1986).
 6  E V. Browell, A.F. Carter, ST. Shipley, R.J. Allen, C.F. Butler, M.N. Mayo, J.H. Siviter, Jr.,
\v M  Hall  "NASA multipurpose airborne DIAL system and measurements of ozone and aerosol
 rofiles," Appl. Opt. 22:522 (1983).
 1  J G Hawley, L.D. Fletcher, G.F. Wallace, "Ground-based ultraviolet differential absorption lidar
mlAL) system and measurements," in  Optical and Laser Remote Sensing, D.K. Killinger and A.
Snordean, eds.(Springer-Verlag, New York, 1983).
 ft  IS  McDermid, D.A. Haner, M.M. Kleiman, T.D. Walsh, M.L. White, "Differential absorption
 •A   systems for tropospheric and stratospheric ozone measurements," Optical Engineering 30:22

*o  T J  McGee, D. Whiteman, R. Ferrarc, J.J. Butler, J.F. Bums, "STROZ LITE: Stratospheric
    ne lidar trailer experiment," Optical Engineering 30:31 (1991).
°    T Shibata, T. Fukuda, T. Narikiyo, and M. Maeda, "Evaluation of the solar-blind effect in ultra-
^ let ozone lidar With Raman lasers," Appl. Opt. 26:2604 (1987).
v*0  G L Megie, G. Ancellet, J. Pelon, "Lidar measurements of ozone vertical profiles," Appl. Opt.
ili-1454 (1985).
^    Q Uchino, M. Tokunaga, M. Maeda, Y. Miyazoe, "Differential absorption lidar measurement of
12' osoheric ozone with excimer-Raman hybrid laser," Opt. Lett. 8:347 (1983).
00  I  Werner K.W. Rothe, H. Walther, "Monitoring of the stratospheric ozone layer by laser radar,"
\3' Ld Physics 832:113 (1983).
     r>  Uchino, I. Tabata, "Mobile lidar for simultaneous measurements of ozone, aerosols and tem-
14~  rure in the stratosphere," Appl. Opt. 30:2005 (1991).
peraturc  ^ ^ Asai, M. Ishizu, T. Aruga, T. Igarashi, "Measurements of the urban ozone vertical
15'file with an airborne COz DIAL,'Mpp/. Opt. 28:931 (1989).
p    F E  Uthe, "Elastic scattering, fluorescent scattering, and differential absorption airborne Hdar
lt'  ivations of atmospheric tracers," Opt. Eng., 30:66 (1991).
ob  E E Uthe, W. Viezee, B.M. Morley, J.K.S. Ching, "Airborne lidar tracking of fluorescent tracers
17  onospheric transport and diffusion studies," Bull. Am. Met. Soc. 66:1255 (1985).
f°r a— p tithe  "Applications of surface based and airborne lidar systems for environmental monitor-
,18' »jAlr Poll. Cont. Assoc. 33:1149 (1983).
in^' r L  McElroy, T.B. Smith, "Vertical pollutant distributions and boundary layer structure observed
l9'  -rborne lidar near the complex Southern California coastline," Atmos. Environ. 20:1555 (1986).
by airw McElroVi -Estimation of pollutant transport and concentration distributions over complex
20.  '• o'f Southern California using airborne lidar," J. Air Pott. Cont. Assoc. 37:1046 (1988).
tClTaw B  Nielsen, E.E. Uthe, J.M. Livingston, E. Scribner, "Compact airborne lidar mapping of lower
21    heric ozone distributions," Proc. Int. Conf.  Lasers '91, (Society  for Optical and Quantum
atm°rSnics, McLean, Virginia, 1991).
^1CC M  Koerber, "An overview of the Lake Michigan ozone study," presented at Air, Water and
22*    Technologies Conference, Detroit, Michigan (11-14 November 1991).
Was**   Gordon, W J. Hauze, "Aircraft and lake vessel special measurements—the Lake Michigan
23'    gjudy 1991  summer field program," Report AQ91-24 submitted to the Lake Michigan  Air
ozone s  t^nsottiumt North American Weather Consultants, Salt Lake City, Utah, 84106 (1991).
                                           639

-------
24. M. Luria, J.F. Boatman, D.L. Wellman. R.L. Gunter, B.A. Waikins, S.W. Wilkison, C.C. Van
Valin. "Lake Michigan ozone study (LMOS):  measurements from an instrumental Aircraft," NOAA
Air Resources Laboratory. Aerosol  Research Section, Boulder, CO, submitted to Atmospheric
Environment,  1991.
25. E.V. Browell, S. Ismail. S.T. Shipley, "Ultraviolet DIAL measurements of O3 profiles in regions
of spatially inhomogcneous aerosols," Appl. Opt. 24:2827 (1985).
26. A. Papayannis, G. Ancelict, J. Pelon. G. Megie, "Multiwavelength lidar for ozone measurements
in the troposphere and lower stratosphere." Appl. Opt. 29:467 (1990).
27. M. Riebcsell. A. Ansmann, C. Wcitkamp. "Raman lidar measurement of the atmospheric aerosol
extinction profile." Optical Remote Sensing of the Atmosphere 1990 (Optical Society of America).
28. W.B. Grant, E.V. Browell. N.S. Higdon. S. Ismail. "Raman shifting of KrF laser radiation for tro-
posphcric ozone measurements." Appl. Opt. 30:2628 (1991).
29. D. Diebel, M. Bristow, R. Zimmcrmann, "Stokes shifted laser lines in KrF-pumped hydrogen:
reduction of beam divergence by addition of helium," Appl. Opt. 30:626 (1991).
                                           640

-------
   APPLICATION OF A FREQUENCY- AGILE LIDAR  SYSTEM
                 FOR ENVIRONMENTAL MONITORING


                      Joseph Leonelli, Lewis Carr, and Leland Fletcher
                                     SRI International
                                  333 Ravenswood Avenue
                                   Menlo Park, California

ABSTRACT
       SRI International has designed, developed, and demonstrated an infrared differential absorption
  .  /jR DIAL) system that can be used for environmental monitoring to detect, identify, and measure
    centrations  of  ambient or  fugitive  emissions  of volatile organic  compounds (VOCs) in  the
       here.  The IR DIAL system uses  a single, frequency-agile, CO,, TEA laser; a 10-in. receiver
            the Dall-Kirkham configuration; a liquid-nitrogen-cooled, HgCdTe, photovoltaic detector,
  Ha personal computer operating system.  The self-contained system is mounted in a small van,
*"   des column-content measurements in ppm-m, and displays time series plots  of VOCs having
sjrdficant spectral activity in the 9 to 11 urn region.
       The  1990 Clean Ak Act Amendments (CAAA) have increased the need for new, ambient,
 •  monitoring techniques capable of real-time data analysis, wide-area surveillance, and multimaterial
^  urement analysis.  Open-path electro-optical remote sensing techniques have developed in recent
me^ where the  measurement of fugitive emissions and toxic gases can be made routinely with
^6  rnercially available or custom-built instruments.1 SRI has demonstrated the ability of a van-mounted,
C0luiwavelength, DIAL system to measure ambient concentrations of ethylene, perchloroethylene, and
multt    ^ a toxjc Disposal Si(e2f and concentration profiles of organophosphorus vapor clouds in a
^"f5 test environment.  Under an internal research and development program supporting environmental
^   ~toting technology, we designed, custom-fabricated, and demonstrated the ability of a compact DIAL
m0fl    using a single,  frequency-agile, CO2, TEA laser to measure concentrations  of VOCs in the
   
-------
copper mirror  For a given voltage, the scanning mirror inn is moved to i specific angle.  slig»">_
changing the pathlength of the cavity and, hence, the wavelength.  Wiih the appropriate placement ot
the grating and scanning mechanism with respect to the User cavity, the entire COj spectrum can be
accessed in a -2 to 2 V range,
       The receiver moduk consists of  a lekscope  and detector with matching  fields of view.  The
detector is a HgCdTe, four-quadrant, photovoltaic, liquid-nitrogen-cooled model with a D* of 2E10. A
focusing lens has been inserted between the telescope and the detector to maximize the return signal
The return signal  from the detector undergoes some preliminary processing by the receiver electrons*
and ii relayed  to the DAPS.  Figure 2 diagrams the DAPS. The DAPS computer is an 80486, 25 M»*
personal computer with a standard PC-AT bus. The AT bus contains interface cards for control  of &11
the DAPS equipment.  Three PC-AT interface cards control the frequency-agile mechanism. The first
card is a 16-bit, parallel. I/O card that sends a digital representation of the galvanometer scanner voltage
to the galvanometer controller. The second card converts a digital code u> an analog trigger pulse wr»c»
is sent to the  DG535 digital delay  generator which, in mm, triggers the external input of the la*r
high-voluge power supply. The third card is  a omer that controls the time delays between setting the
voltage on the galvanometer for each line and triggering the User. The delay between firing the 1**^
and collecting the receive signal is set by the DG535.  This delay can be changed via the IEEE-*sa
interface. The control and collection of  the digitized signal is performed by the Tektronix  RTD7 lOA.
which  is also controlled by  the computer through the IEEE-488 interface.  The DIAL system  is
completely computer-controlled.  The application software is written in Microsoft C 6.0 and excc"^g
on the  MS-DOS operating system. The software links with the subroutine library  drivers for IEEE-*
interface calls, frequency-agile mechanism control, and dispUy.  The software has five components^
setup, data acquisition, storage, processing, and dupUy.  The setup includes a menu-driven waveleng
selection package, RTD710A and DG535 hardware parameter selection, algorithm parameter settings.
and data storage and display options. The data acquisition system is capable of taking data at  ra
to 60 Hz.   Data can  be stored to  separate output files in  its  raw and Kalman-filtered CL vs>
formats.  The  CL data can be dispUyed  on the VGA monitor as time series data.  The compact
system was mounted in a Dodge Ram van as  shown in Figure 3.

DEMONSTRATION*  RESULTS
       We drove the compact DIAL system from California to North Carolina and operated it during
i two-week test program in April 1991. The DIAL system was located approximately 600 m from/.^
line that served as the topographic target for subsequent CL measurements.  The  operating condlU^
were fair with low variable wind speed  and direction, partly sunny skies, and an ambient tempera
of 72°F. We used two Urge, flat, shallow plastic pans as containers from which the ether and me"1*"
could evaporate.  The SF6 was disseminated  from  a gas bonk mounted at the rear-end of a PlClt".£
truck.  We placed the two shallow pans on the ground a few meters in from of the tree line next w
pick-up truck.  The  disseminator and the lidar system operator coordinated disseminations  and oa
collection using a CB radio.  The DIAL system collected aad stored all data.  Data analysis
in  real  time and the  measured vapor cloud concentrations were dispUyed on the operating
monitor. We processed the vapor concentration measurements using a Kalman filler algorithm.
vs. time plots dispUyed the concentration in units of ppm-m. The first test performed was a series ^
two-minute SF6 disseminations.  Figure 4 shows the results for one of these trials.  After this  *e
preliminary trials, we proceeded to disseminate small quantities of mcthanol and ether vapor usi  »
evaporative techniques. We poured approximately  1/2 L of ether into the shallow pans.  Vapori
wa* sluggish due to the moderate temperature and partial cloud cover.  The DIAL system me^.urc
concentration  of ether vapor as it evolved during the 15-minute cruL Figure 5 presents the real-time
analysis for the ether dissemination as a CL  vs time pkx.  The ether was poured onto the pan ''
3*minute mark. At S minutes, the vapor cloud drifted into  the line of site of the DIAL system-   7
DIAL system continued to measure  the  ether concentration  until the pan was dry.  The  pc**'
concentration  of 130 ppm-m was observed 10 minutes into the trial After 15 minutes, the concentration
was essentially down to background levels. We performed additional trials with ether. Figure 6 Prc$cn r
the real-time data analysis of a tnal using mcthanoL  The CL vs time plot shows the dissemination o
methanol at the  2-minute mart.  As with ether, the methanoi wms poured into the pan.  The (***
                                              642

-------
concentration of 200 ppm-m methanol was observed 7 minutes into the trial.  Table I lists the expected
and measured system sensitivity in ppm-m for SF6, ether, and methanol.  The sensitivity estimates are
based on  the magnitude  of difference  in  the  absorption coefficients between  the  absorbed and
nonabsorbed lines; the transmitter power, the system's transceiver detectors, electronics,  and digitizers;
and the computer algorithm's ability to distinguish 2% changes in the  signal return.   Assuming
reasonable values for each of these factors, the sensitivity is defined as the minimum perceptible signal
change directly attributable to the presence of a VOC when the signal-to-noise ratio is one. In general,
however, practical field-application detection limits will be somewhat larger.
_Table I. DIAL System Sensitivity.
Compound
Acetic anhydride
Ammonia
Benzene
Dimethyl(methyl)phosphonate
Ether
Ethyl acetate
Ethylene
Methanol
Perchloroethylene
Sulfur hexafluoride
^Toluene
Predicted Sensitivity
(ppm-m)
65
0.7
75
0.4
45
12
2
3
3
0.1
166
Measured
(ppm-m)
-
-
2502
0.83
25
-
22
10
52
0.1
-
CONCLUSIONS
      The compact DIAL system, using frequency-agile COn TEA laser technology, represents an
optical remote technique for measuring and monitoring the ambient and fugitive emission of VOC and
toxic gases. The prototype DIAL system4 can provide simultaneous real-time measurements of several
VOCs. Work on this system continues. We intend to use our DIAL system in studies at several sites
"> California that have fugitive emission problems and are of interest to the California Air Resources
Board and the Bay Area Air Quality Management District

REFERENCES
J- W.B.  Grant, R,H. Kagann, and W.A. McCtenny, "Optical Remote  Measurement of Toxic Gases,"
     Air & wa«t* Mffmt  *>  p>.  18-30(1992).
2- S.M. Hannon, D.L. McPherrin, L.W. Carr, L.D. Fletcher, and J. Leonelli, "Atmospheric Monitoring
at a Toxic Waste Treatment Facility with a Multiwavelength CO2 Lidar," in Proceedings of the 1991
ALS. EPAfA A WMA international Symposium on Measurement of Toxic and Related Air Pollutants."
Vlp-21, Air & Waste Management Association, Pittsburgh, 1991, pp 679-684.

J J-P. Cameo, K.R. Phelps, J. van der Laan, E.E. Uthe, P.L. Holland,' J.G. Hawley, L.D. Fletcher, R.E.
Warren, N, Nielsen, A. Rosengreen, and E. Murray, Infrared Differential Absorption Lidar for Vapor
SSJSSgon, CRDEC-CR-88039, Chemical Research, Development and Engineering Center, Aberdeen
Proving Ground,  1988.

4- Patent disclosure submitted.
                                           643

-------
                                                Transmitted
                                                  signal.
                  Beam steering optics

                   Output coupler —    $
                  Brewster angle
                        window
                                                                       Telescope
                    Brewster angle ,.
                          window  v,
                                                                       ^ Liquid nitrogen
                                                                      >   cooled HgCdTe
                                                                           detector


                                                                       Receiver
                                                                       electronics
                                                      Receiver electronics
                                                         power supply
                                                                                p92-OOS'flO
                             Figure  1.   Sensor head block diagram.
 Output coupler
             Brewster angle windows
                                                           Voltage-controlled
                                                            galvanometer
                       Laser high-voltage
                         power supply
Transmitted
  signal
                                                                            Digital to galvanometer
                                                                              voltage controller
                  i- A
          !
                    External trigger input
                         DG53S digital delay
                           pulse generator

                                                IBM PC compatible 80486 25 MHz computer with
                                                4 Mbytes of DRAM, two 60 Mbyte hard drives,
                                                backup tape drive, 1.2 Mbyte and 1 44 Mbyte floppy
                                                drives, and VGA display
                                                PC-AT bus to 16 bit parallel interface
                                                       PC-ATbustodiflitaMc-analog converter interface
                                                        PC-AT bus to IEEE-488 interlace
                                                        1 MHz timer and clock module
Received
 signal
--3-ir««***
"•••^i^^-- •
 :...^--'^58
                                 ft**
                                                                         External trigger Input

                                                                          Tektronix HTD710A 100 MHz,
                                                                          10 bit, dual-channel, transient
                                                                               waveform digitizer
                        Telescope
                  Figure 2.   Data acquisition and processing block diagram.
                                                   644

-------
    Figure 3.  Compact DIAL system mounted in the van.
   19
   10
E

&

d
   -s
                 I
            SFe released
SF^off
                      --	
     0   10  20  30  40  50   60   70   80  90  100  110  120  150
                        TIME (seconds)
                                                   p«2.005
-------
        100
        .
        200
        100

                                               i—•—r
                                            Xv,
              Eth»r dissemination
           0    100               400   SOO         700   800
                             TIME (seconds)
Figure 5.  Kalman-filtered CL >v time for ether al a target range of 600 ni.
                             TIME (s^onds)
      Figure 6.   CL vs. time for methanoi at • Urge! range of 600 m.
                                646

-------
 SIGNAL PROCESSING  FOR CHEMICAL MICROSENSORS


                            Nicholas Kyriakopoulos, Tanvir ul Haq
                   Department of Electrical Engineering and Computer Science
                              The George Washington University
                                   Washington, DC 20052
ABSTRACT
       Surface Acoustic Wave (SAW) chemical sensors have been proposed as detectors of chemical
vapors in a variety of field applications such as air quality monitoring, toxic gas detection, etc. The
attractiveness of SAW devices lies in their ruggedness and simplicity of operation.  Most of the research
 ctivities involving the use of SAW devices as chemical sensors have been concentrated in the selection
 f chemical coatings, and in pattern recognition techniques. The focus of the efforts is the discrimination
Liong different chemical compounds.
       A new approach toward the improvement of the selectivity of SAW devices is being presented
.   fjjjg paper. The frequency  shift exhibited by the surface wave when the coating  is  exposed to a
          chemical vapor may be modeled as the response of a dynamic system. In the simplest form
          would be of the first order, and the response could be characterized by the total frequency
Tjft ^d the time constant. Thus, discrimination among different vapors would be based on two, instead
Sf one, parameters. Each chemical could be identified as a vector in a two-dimensional space. Higher
°rder systems would identify individual compounds as vectors in a multi-dimensional space. Preliminary
       based on actual test data indicate that it is possible to model the frequency shift of SAW chemical
       as the response of dynamic systems.
        ff-f w ^p • ~ ^" ~
        Surface Acoustic Wave devices are being investigated for use as chemical vapor sensors, Small
      x jggedness, simplicity of operation, low power consumption, and sensitivity make these devices
 Snoealing as detectors of chemical  vapors in a variety of field applications  such as  air quality
 a^nitoring»  clinical analysis, industrial process control, toxic gas detection, etc.1-2 It has already been
    jjjjghed that it is possible to identify chemical vapors at various concentrations using SAW devices
 65 sensors. Research activities are directed toward improving the sensitivity and selectivity of these
 Svices. A SAW chemical sensor is  essentially a crystal oscillator covered by a coating of sorbent
 material- When exposed to a particular vapor, the frequency of oscillation changes from the quiescent
 Inference frequency. The change in frequency is  a function of the particular vapor, its concentration,
   d the coating material. Thus, the frequency shift and the coating are used as discriminators.
 ^     presently, the research efforts are concentrated in the development of specific coating mat
         _fl__~.:***» a f*wiiiAns*v shift Prtrtvtjcnnnfltno trt o enA/*SfflA ^UA*M. 1^.^.1 __~i	^	..»    «*. .  .*
                                                                                 materials
 eh producing a frequency shift corresponding to a specific chemical and concentration. Detection of
    ical8 is accomplished by constructing arrays of sens
 hefflica18 ia ——"-r	 —  	~	j-  — sensors with different coating materials { Cj,
f  1   n}. The response of the array to a particular vapor at a particular concentration is a set of points
/Af'c> in d* multidimensional space of coating  materials. These points form a pattern.  Pattern
    coition techniques are used to discriminate between different chemicals and concentrations.M
teC°   In this paper we present a new approach for improving the sensitivity and selectivity of SAW
     ical sensors. It is based on the observation that the shift in the frequency of oscillation is a function
 tt*. only of the coating, but also of the exposure time. The first part of the paper contains a short
   - w of the principles of operation of SAW devices. Modeling of the frequency shift as the response
^^fitst order dynamic system is discussed. The time constants of the system are identified and some
°f * rimental results are presented.
                                           647

-------
FUNDAMENTALS OF SAW SENSORS
       A SAW chemical sensor consists of a piezoelectric crystal excited by an RF signal. Typically
these devices operate in the range of 100 MHz - 200 MHz;  devices in the GHz range have also been
constructed.' Placing the crystal in an  oscillator circuit produces a Rayleigh surface wave.5 Figure 1
shows a typical SAW chemical sensor;  Figure 2 is an equivalent circuit  representation of a crystal
oscillator.
                        RF AMP
      RF AMP
                    Mfnpl*
  Figure 1,  An example of SAW Chemical Sensor

           Jttpraud wtt pMUNMfnn WoUfra, H; BtOnu*. Jr.. D.5.:
           Jtrm, N.l.i !• ChaniaJ lanon ipd Microiimnmmiooin
           Otmy.lL E.: Ma; W.I.. Bd*.; ACS Sy
                             Figure 2.  Circuit Model of a Crystal Oscillator
          1MB Scrii* 403:
W«bJnflw.'D.C.. 19I»; p!65.
Coating the surface of the crystal with a sorbent material converts the device into chemical sensor. A
chemical vapor passing over the coating material changes the mass loading of the surface of the crystal
and causes a shift Af in the frequency of oscillation. In Figure 1, there are two adjacent oscillators; one
is coated with the sorbent material while the other is without it. The second oscillator is used to generate
the reference frequency. As the coating is exposed to the vapor, the frequency of oscillation shifts.
Multiplying and filtering the two signals generates the difference signal.
       The piezoelectric quartz crystal oscillator can be represented by the simple equivalent electrical
circuit shown  in Figure 2.  The motional capacitance C represents the mechanical  elasticity of the
vibrating body,  the motional inductance L  is a measure of the vibrating  mass, and the equivalent
resistance R corresponds to the total loss of mechanical energy dissipated to the surrounding medium
and the supporting structures. The shunt capacitance C, is an actual lump capacitance due to the
electrodes on the oscillator and stray capacitance. Analysis of the conditions for oscillation yields an
expression for the total frequency shift given by Equation I.1-2

              A/ - (*i**j) f? f>d                                                          (1)

where Af is the  observed SAW oscillator frequency change, k, and k, are  material constants for the
piezoelectric substrate, fc is the resonant frequency of SAW oscillator, p is  the coating density, and d
is the thickness. The material constants, k, and k, for typical ST-quartz piezoelectric SAW device are -
-8.7X104 and -3.9 xlO*1 mVkg respectively. Typically, Af is in the range of 105 Hz- 10* Hz. The
                                              648

-------
Chan8e in mass and consequently M, is a function of the coating material, the chemical vapor, and the
concentratiort. It should bt noted that frequency shift vn Eq. (1) is not a ftmction of time.

A DYNAMIC MODEL
      Exposure of a SAW sensor to a chemical vapor does not produce an instantaneous change in
        fl  instead, the  frequency shift is a continuous  and  differentiable function of time. Such
        non is to be expected since the change in the mass of the coating  material cannot be a step
        A typical response of a SAW sensor to a chemical vapor is shown in Figure 3.  For this
        the vapor was Toluene, the coating material Fluoropolyol,  the concentration 10,000 mg/m3-
    to ambient temperature 25°C.  Data were collected by exposing the sensor to the vapor until a
   *JTstate freqiiency shift was reached, men drattingoff the vapor sopply nod patgiagtbe coating until
    frequency returned  to  the reference  value; for this particular sensor the process M  repeated
     "tically a few times. Examination of the sorption and desorptum phases reveals that the frequency
      «sus time may be described, at a first approximation, by exponential^fliiictions. ^^j^^jjft
                                              where c:  '       ---«-...     l~  —   ..—*.
          j w»*u% luuvuuil VaU t^ff Wrl-Ulvu *** ***Vt*ie ••»«•»»»• •—• ••—- —                    	    I
        and time, respectively. Steady state is defined as lim Af(c,t) - M(c) as t-*», wi
    frequency shift that would result after the device has been exposed to a concentration c for a
    "sntly long time.                                                          ..   .
      Consider the exponential frequency shift functions shown in Figure 3, corresponding to a given
     '*~lt«n\ c. &f(c,t) can be expressed as a family of exponentials ustoj the time constant l/a as a
       f- TTiere is an infinite number of linearly independent exponentials having final frequency shift
_     ie parameter a coutd be an additional variable for the classification of compounds,  me model
^fc of the following form:

                 f) - A/fc)  (l-O                                                    ®
                            wo  m  m "."• «.'••
                   Time In *«ondi
so
                                                   iooisoa»s»»oa6o«»*s09fla
                                                        Tlm« in Mconda
Typical
                        of SAW Device to a vapor    Figure 4. OiaracteriMtion of the response in terms
                                                         of time constants
       given compound may be characterized by the vector £Af(c),«J. Further examination of iha
       « cU^rvc^eaTSa^           rfctog «>*«     "'''
            time constants. These are designated as Tr and T-t.-,	,         „**-<*..&.* i«,
          apparent that the response of the SAW sensor to a given vapoi may be characterized by
                                            649

-------
 four instead of two parameters, namely, coating material,  rise time, decay  time, and steady state
 frequency shift. In effect, this particular vapor may be represented as an element of a 4-dimensiooal
 instead of a 2-dimensional space. Using a,= l/Tr and ad=l/Td as parameters the two  exponential
 functions may be written as:

                      - 4/to (1-*-*'^                                                    (3)
 Thus, the particular vapor and its concentration may be characterized by the 4-tuple [c, Af(c), a,, aj.
 The parameters ar and at can be identified by using parameter estimation techniques. Measured data
 can be fitted to the model given by Eqs. (3) and (4).
        The most commonly used  system identification techniques assume linear models for simplicity
 of calculations.6'7- Although Eqs.  (3) and (4) are nonlinear in a, and odl they can easily be linearized.
 Taking logarithms we obtain
                  = y.
 and
                                                                                          ft
where y,(t) and y/t) are functions of the measured frequency changes versus time of exposure.
Defining the unknown parameter vector 0T = [a,, aj, Equations (5) and (6) are of the form

              Xfl^) =  4>r(0 fl                                                              0

In practice, since measurements are corrupted by noise, there is a noise component added to Eq. (7).
      The estimation problem may be formulated as follows: Assume that the time response data are
generated by a system having an output described by y(£,t). Using the measured time response data y(t),
find £ such that the predicted time response y(t) is as close to the measured response as possible. Let
the estimation error be defined as:
For discrete time measurements the estimation error is
In terms of the estimated parameter vector g, Eq.(8) becomes:
                                             650

-------
 For least square estimation, a cost function is defined as:*


                        2   '                                                              (9)


 The best estimate 0 is obtained by minimizing J(fi,k) with respect to fl,
 or
                                   "              o                                        (10)
           (10) gives a set of linear algebraic equations in g, namely,

               P & " «                                                                   (11)

 which can be solved for 9.


 MODEL IDENTIFICATION
        The procedure described in the preceding section has been applied to a set of experimental data.
     ,esults are shown in Table I . Figure 3 corresponds to entry number 1 in the Table. For each data
 -cord the steady state frequency shift was calculated by  subtracting the highest  frequency recorded
        the exposure to the vapor from the initial (baseline) frequency. The results indicate that rise and
            °°nstailts can  ** identified from  measurements.  Also, for a given  vapor at a specific
            n different coating materials produce not only different frequency shifts but also rise and
       times.
        Of particular interest is the observation that for all data records, the rise and decay times differ,
   —-times by a considerable amount.  One preliminary conclusion should be that the physical processes
 "! aon*"00 and des°IPtion m not mverses of each °*er, » should be noted that the data used for this
 2 dv were not collected for the purpose of validating the proposed model, but for  other purposes.  For
 ITS reason they were not an ideal set for evaluating the feasibility of this concept. One of the major
 "Joblems  was the fact that the frequency shift had not reached a steady state value; the exposure and
 prr^uig Ptiases were too short ** U can ** seen from Figure *• sbnUar characteristics were exhibited
 ?U*he other data sets.
 10 ^   For these particular data records the exponential models for the sorption and desorpdon phases
   vide reasonably close approximation to the physical process. Figure 5 shows a comparison between
pt° measured frequency shift and the calculated one using the estimated rise and decay times. This plot
tht~!ajonds to item 1 of the Table. Similar correlation between measured and calculated responses'have
       *rfained for the remaining data sets.
       DU»"
                                              651

-------
                 Table 1. Time constants for various vapors and concentrations.
No.

1
2
3
4
5
6
7
SAW Coating

Fluoropolyol
Tenax GC
Tenax GC
Tenax GC
Tenax GC
Tenax GC
Tenax GC
Vapor

Toluene
Toluene
Toluene
Chloroform
Chloroform
Dichloroethane
Dichloroethane
Frequency Shift
Af (Hz)
6,744
8,432
2,732
11,555
27,515
4,016
2,154
Time Constant
I/a Sec.
Rise
39.3
16.7
28.6
62.8
60.7
8.8
15.6
Decay
31.7
31.9
33.2
68.2
18.4
7.3
15.8
Concentration
mg/m3
10,000
40,000
10,000
44,000
175,000
150,000
9,375
                                                                         Original
                                                                         Modeled
                   SO   100   150  200  250  300  350  400   450   500
                                Time in seconds

                 Figure 5. Comparison of the modeled and measured responses.

CONCLUSIONS
      In this paper it has been shown that the variation in time of the frequency shift of SAW chemical
sensors coating information that could be used to improve the selectivity of these devices. Based on the
observation that the frequency  shift is a dynamic as opposed to static, process,  each vapor producing
a frequency shift on a SAW sensor may have as an image unique dynamic system. Increasing the order
of the system would provide a potential tool for improving selectivity.
                                           652

-------
ACKNOWLEDGEMENT
       The authors wish to thank Dr. Hank Wohltjen of Microsensors Systems, Inc. for providing the
data used in this study.

REFERENCES AND BIBLIOGRAPHY

1  H. Wohltjen,  D. Ballantine,Jr.,  "Vapor detection with  surface acoustic wave microsensors", in
Svmposium sponsored by the Division of Analytical Chemistry at the 196th National meeting of the
American Chemical Society, Los Angeles, 1988, pp 157-175,
9  D Ballantine.Jr., H. Wohltjen, N.Jarvis, " Surface acoustic wave devices for chemical analysis",
tjaLjaeilL 61(11):7 (1989).
3S. Rose-Pehrsson, J. Grate, D.  Ballantine, P. Jurs, " Detection  of Hazardous vapors including
mixtures using pattern recognition analysis of responses from surface acoustic devices", Anal. Ghent..
60(24): 11 (1988).
   V) Strouf, Chemical  pattern recognition. J.  Wiley,  1986.
 * —  Dieulesaint, plastic waves in solids:applications to signal prWrfffting, J.  Wiley, 1980.
 ' jj \v". Sorenson, Parameter estimation:principles and problems, M. Dekkar, 1980.
n  G A Bekey. ydentification and system parameter estimation. Pergamon Press, 1983.
 ' gjchard H. Middleton, Digital control & estimation, Prentice-Hall  1990. pp 356-358.
                                            6S3

-------
        OPEN PATH AMBIENT MEASUREMENTS OF POLLUTANTS WITH A DOAS  SYSTEM

Charles p. Conner, Bruce W. Gay Jr., William B. K.arches, and Robert K. Stevens

    U.S. Environmental Protection Agency,  Research Triangle Park, NC 27711


ABSTRACT

      A differential optical absorption •pectrometer (DOAS) made by Ops is AB
(Sweden) has been in operation since August 1991 at the U.S.  EPA in RTP, NC.
The analyzer unit ia located in an environmentally-controlled shelter in the
EPA parking.lot.  Four separate open optical path* have been established,
ranging from 202 to 816 meters.  The 816 meter path crosses a highway while
all the shorter paths are located near parking lots,   semi-continuous
measurements of SOj,  o,, NO, and NO, were made.   The measurement cycle involves
measurements on each path in sequence.   The total of all measurements on all
paths requires approximately 20 minutes to complete,  thus there are three
values for each unique gas-path combination per hour.   These values are
averaged into hourly averages.  Continuously operating Federal Reference
Method (FRM) instruments were also located in the DOAS shelter.  These
instruments were measuring SO,,  O,, NO,  and NO,.   Their  results are  reported as
hourly averages.  Comparison of the long-path DOAS measurements with the FRM
point measurements indicates a high level of correlation.   Considering the
potential problem of comparing a long-path measurement to a point measurement,
the high correlation is encouraging.  The shorter DOAS paths yielded the
highest correlations with the point measurements, as expected.

INTRODUCTION

      The differential optical absorption spectroscopy (DOAS) technique for
measuring gas concentrations was developed in Germany in 19791 .  This
technique involves measuring the gas1 ultraviolet or visible absorption
spectrum in a long air path.  The differential absorption spectrum of the gas
species is derived from the raw spectrum.   The concentration is derived from
the differential absorption spectrum using the Beer-Lambert law with known
differential absorption cross-section data.  This long-path monitoring
technique has been compared to point-measurement techniques in several
studies".   There  is much interest  in the use of this instrument  for  routine
monitoring applications as either a supplement or replacement of point-
measurement instruments.  This study further examines the ability of the DOAS
instrument to provide reliable measurement data for gaseous pollutants.

EXPERIMENTAL

      The commercial DOAS unit made by OPSIS AB  (Sweden) was installed in
August 1991 at the U.S. EPA in Research Triangle Park, NC.  It was placed  in a
portable shelter located in the parking lot behind the EPA Annex building.
The shelter is environmentally controlled with both air-conditioning and
heating for temperature regulation.  The DOAS instrument consists of three
main components! external light sources, receiving telescope, and analyzer
unit.  If only one path was to be monitored, a  fixed receiving telescope would
be used.  In our system, a moveable (rotation and tilt) telescope was selected
because we wanted to monitor multiple paths.  The receiving telescope was
mounted on top of the shelter.  Our receiver Incorporated coaxial light optics
so that retroreflector paths could be used.  We could both illuminate and
observe retroreflectors with this combination transmitter-receiver
("transceiver") unit.  Of course this unit could also observe external light
source paths.  There is a compromise in detection ability with this unit which
limited our ability to measure certain gases.

      Our system was set up with four monitoring paths - two using external
light sources and two with retroref lectors.  Path 1 used a light source placed
on the roof of a building at Research Triangle  Institute - the path length was
                                      654

-------
    meterB.   Path  2  was  a  retroref lector path, having a total path-length of
    meters.   Path  3  used a light source on the EPA Annex roof - 202 meter*
 )ith-length.   This light source used an extended 0V lamp eo that MO and KB,
  uld be measured.  Path 4 was another retroreflector path of 288 metere in
, "oth.   Path 1  crosses  Route 147 (Durham Freeway) while all the other paths
  !| located over local parking lota.  He attempted to measure up to 11 species
*  _.ch  path. The results Cor only four gasee are being reported because of
°n T   ^imitations.   The large number of gases and paths being monitored
•y* ultaa in measurement  cycles of about 18 minutes.  Thus 3 measurements were
r* j to  calculate  the hourly averages which are analysed here.

      EPA Federal  Reference Method analyzers for SO,,  O,, NO and NO, were
   ,-«tlna simultaneously at the shelter during the entire period reported
Op*.7 10/10/91 - 3/31/92 (except ll/l - 11/10 when they were being relocated
h*fn an  Adjacent shelter to the DOAS shelter).  The SO, concentration was
'r°7 red with a  Pulsed Fluorescence SO, Analyzer Model 43A by Thermo Electron
""* trumenta  (TEI).  A 0V Photometric O, Analyzer Model 49 by TEI was used to
Ine      ozone.  The  nitrogen oxides were measured with a chemiluminescence NO-
                 Hodel 42 from TEI.
       The DOAS and FRM data for SO,, O,. NO and NO, were obtained as one-hour
     aaes   The FRM data was continuous except for the  11/1/91 to  11/10/92
*V*Tod  * There are 'occasional gaps in the DOAS data during the  10/10/91 to
""*     1 period.  There are several reasons for these gaps.  Moat  of the gaps
        that several hours were due to maintainance problems; e.g., waiting  for
       . Calls or delivery of parts.  The more frequent but shorter gaps were a
        of the software automatically eliminating data  where the measurement
  'fOJ;iationa resulted in erroneous answers.  Many tines the miscalculation
bjicux   Vh9n light levels were low; e.g., during rain or fog.  The compromise
°ct  .1 arrangement exacerbated this tendency, particularly for the NO
°P   laments.  There were also occasional gaps when diagnostics and other
IDa&0m experiments were being performed off-line.  Since this  is  still
•y   TSereda research (not monitoring) tool, this was  acceptable. Data
c°n*i.bility still averaged over 90%, except for NO which was  especially
*v   %Ible to miscalculation because of marginal light levels.
       Linear regression analyses comparing the DOAS  and  FRM data were
    wormed.  The correlations between DOAS  and FRM data for SO,, O,,  and NO,
p«rr  * caiient when using all available DOAS data.   The  NO data,  however,  were
*****   very poorly correlated.  The measurement uncertainty calculated for  each
often    *t VBiue provides a data quality  measure which  can be used to reject
«"**  based upon empirically-determined criteria.  The elimination of DOAS  NO
d»ta  r,no«e deviation exceeded 3.0 pg/m3 was found to substantially  improve its
d»ta  Vation with the FRM results.  There was no benefit  to filtering the other
corr«A»    yigure 1 shows the correlation, R1,  between the data seta  for SO,,
g*B ° '*. N0^, for each month and each path.  Paths  2 and 4 clearly yield the
Oj» *",! correlations.  This is logical because these were shorter paths and
highe*Ior. point-like in nature (the FRMs  provide point  measurements).  There
h«nc*_onsistently hl9h correlations between the two  disparate monitoring
v*t*  Toues for all paths throughout the six-month period.  Figure 2 show
       o                                                             shows the
    hCr« average concentrations for the gases, for DOAS Path 1 and FRM
0*"*   Lnents.  scatterplots of selected FRM and DOAS data are shown in Figure
    *       3a shows the January 92 so, data where  no problems were observed.
        3b shows the SO, March 92 data.   There  are  clearly many outliers.   When
     5%. Were examined  in detail, all of the circled data were found to occur
~~-     day, March 31st.  Obviously something happened on that day, either DOAS
on °nS data have been corrupted.  Changes to both instrument configurations
of FP^.de on March 30,  so no definitive explanation has been found.  For the
were   ion analysis reported earlier, the March 31st data was removed.
     e*  3a and 3b demonstrate the utility of scatterplots in examining a data
     re"*
                                       6SS

-------
      The NO data varies widely  in quality over time.  Figure 4 shows the
correlations between the DOAS and FRM results for NO.  NO Buffered from the
low light level* which were often present due to the compromise optical
arrangement.  As mentioned earlier, data with deviations greater than 3.0
(ig/tc? were rejected.  In some months this improved the data set tremendously,
e.g. October 91, January 92, and February 92.  The March 92 results, on the
other hand, were very poor in spite of the data filtering.  The light levels
on Path 3 during most of March were very low, due both to poor optical
alignment and a badly deteriorated mirror coating in the light eource.

SUMMARY

      A commercial  DOAS instrument has been in operation at EPA in Research
Triangle Park, NC for more than  six months.  A comparison between the ambient
DOAS measurements and FRM measurements made concurrently, has been presented.
For the criteria pollutants SO,,  O,, and NO, there is excellent correlation
between the measurement techniques.  The DOAS NO measurements vary widely in
quality as a result of sensitivity to low light level* sometimes present
during the six month period.


REFERENCES

1.  U. Platt, D. Perner, and H.  W. Pate, "Simultaneous Measurement of
Atmospheric CH2O, O3, and NO2 by Differential Optical Absorption", J. Oeophys.
ROB. 84: 6329-35 (1979).

2.  R. K. Stevens,  R. J. Drago,  H. T. McLeod, J. B. Bell, R. Hard, Y. Mamane,
and H. Sauren, "Evaluation of a  Differential Optical Absorption Spectrometer
as an Air Quality Monitor", in Proceedings of the 1990 BPA/AHMA International
Symposium on Measurement of Toxic and Related Air Pollutant*. VIP-17, Air C
Haste Management Association, Pittsburgh, 1990, pp 688-694.

3.  T. L. Conner and R. K. Stevens, "Air Quality Monitoring in Atlanta with
the Differential Optical Absorption Spectrometer", in Proceedings of the 84th
Annual Meeting & Exhibition. Air fi Haste Management Association, Pittsburgh,
1991, paper 91-68.9.


This paper has been reviewed in  accordance with the U.S. Environmental
Protection Agency's peer and administrative review policies and approved for
presentation and publication.  Mention of trade names or commercial products
does not constitute endorsement  or recommendation for use.
                                     656

-------
                 DOAS  vs.  FRM Data
                      S02 - All paths
                      N02 - All paths.
            10/91          12/91          2/92
                   11/91          1/92          a/92
                           MonthAear
                       03 - All paths.
            10/91          12/91           2/92
                   11/91          1/02          3/92
                           Uonth/Year
                    Pathi • Path 2 M Path 4
Figure  1.  Correlations between DOAS  and FRM data
                          657

-------
                S02 Monthly Average Concentrations
                      10/91
                           11/91
      12/91
           1/82
       Month/Yetr
                                            2/92
                                                  3/92
                N02 Monthly Average Concentrations
                      10/91
                                            2/92
11/91
                                       1/92
                                  IlonLh/Year
                                                  3/92
                 03  Monthly  Average  Concentrations
                      10/91
                           11/91
      12/91
            1/92
       Month/tear
                                             2/92
                                                  3/92
                                DO/
                                        FRM
Figure 2.  Monthly  average concentrations  measured by DOAS and FRM.
                                 658

-------
a)
               DOAS   vs FRM Scatterplot
                     January 92 S02 Data
              10    20   30   40   50   60   70   80   90
b)
       -10
               DOAS vs  FRM Scatterplot
                      March 92 S02 Data
                    20         40
              10         30         50
                            FRM Data
60
     70
60
      Figure 3.   DOAS vs FRM scatterplots of data (units Mg/m )
                          659

-------
           DOAS  vs.  FRM Data
                  NO - Path 3.
      10/91
       12/91
11/91           1/92
         Month/Year
2/92
                                           3/92
              All data.
                Filtered data.
Figure 4.  Correlations between DOAS and FRM NO data.
                       660

-------
           Session 15
Air Pollution Dispersion Modeling
 S.P.Arya andS.T. Rao,  Chairmen

-------
Multiplying Factors To Convert 1-Hour Maximum Concentration
screening Estimates To Annual Estimates  For Sources
infl"enced By Building Wake Effects
Lewis H.  Nagler+
atmospheric Sciences Modeling Division
National  Oceanic and Atmospheric  Administration
u  s   Department of Commerce
Research  Triangle Park,  NC 27711
INTRODUCTION

    simplify the dispersion modeling process, the Environmental
To-tection Agency (EPA)  has  developed screening models.  These
  reening models use EPA recommended conversion factors for
scllverting one hour concentrations to longer time periods.  However,
Cpa "Guideline" modeling procedures1, do not include a recommended
  ^version factor for converting  1-hour screening model
C     ntrations to averaging  periods beyond 24 hours.  The purpose of
      paper is to derive  conservative screening values for converting
  e hour concentrations  to annual values for sources influenced by
 1  version factor.   Previous  research has evaluated a number of data
c°n  s  -to derive a conservative  1-hour to annual estimate2 ' 3 .  The
barces used in that research were  located  in both simple and complex
3  rain.  The recommended  one hour  to annual conversion  factors
fc  ived from those data  bases range from 0.0252'3 for sources in
d. nle terrain to 0.050^ for  sources in complex terrain.  Building
s    effects were not considered  in that research.
     In the Fall of 1991,  EPA introduced a test version of a revised
   .  strial source Complex Model  (ISC2) .  This version considers
1 •   ctional dependent downwash with both the Huber-Snyder and
dl5;  iman-Schire building  downwash  algorithms.  In the modeling
S  wsis to derive a conservative  1-hour to annual ratio for sources
an     building wake effects  are  important, ISC2 was used.
     e  *•"
       author is on assignment  to Region IV, U.S. Environmental
Protection Agency.
                                 663

-------
APPROACH

Three  U.S.  Heather Service Stations were selected to represent  three
different climatological  regimes.   The stations selected were Tampa,
Florida,  Greenville,  South Carolina and Nashville,  Tennessee.

Several building types  were chosen to  obtain a  wide variation of
building  widths and heights.   Most of  the building dimensions came
from Prevention of Significant Deterioration permit applications.
Only the  building types at either  end  of the spectrum selected, i.e.,
the tallest and shortest  buildings,  were not derived from permit
applications.

The SCREEN  model was  run  for 69 combinations of stack heights and
building  types.   Each combination  was  run in the rural and urban
mode.  For  some sources,  1SC2  calculations were made by allowing the
building  height and width to vary  by direction.   Calculations were
then redone by  holding  either  the  height or  width constant for  all
directions.  The SCREEN results were used to estimate the maximum one
hour concentration on which to base  the one  hour value for the  short
term to long term ratio.   The  receptor of maximum concentration
defined from the SCREEN model  was  used as the basis for selecting the
ISC2 model  receptor field.

Based on  data from the  SCREEN  model, both the ISC short term  (ISCST2)
and the ISC  long term (ISCLT2)  models  were run  for each of the  69
source combinations in  both the rural  and urban mode.   In most  cases,
the downwind receptor selected from  the SCREEN  model also
corresponded to  the annual  maximum downwind  receptor for the  ISC2
model.   Receptor spacing  was generally held  to  100  meters.

The ISCLT2 model was  not  run for all three Weather Service stations.
Since the ISCST2 model  and  initial runs with ISCLT  indicated  that the
Greenville,  South  Carolina  station consistently had the highest
calculated concentrations,  the other two stations were deleted  from
the long term ISC2  analysis.

RESULTS

The calculated ISCST2 and ISCLT2 ratios  were plotted as a function of
building type (supersquat,  squat and tall) versus stack height.
Figures 1-6 are  the plotted data for Greenville  only.   Tables showing
the input data and  the  model calculations  are not included here, but
are available on request.    When the  rural  dispersion coefficients are
used,  the ratio  of  SCREEN to ISCST2  (annual)  and SCREEN to ISCLT2,
shows that for supersquat and  squat building types,  the 0.025 ratio
suggested by previous research  , is  supported by the data  used
here.   A ratio in the area  of  0.075  is  indicated when  these same
input data are used with urban coefficients.  When  the ratio of
SCREEN to both the  ISCST and ISCLT models  were plotted for tall
building type versus stack height,  an even higher ratio was found.
                                  664

-------
For  the tall building types  there  is less difference between results
for  the urban or rural mode  of the model(s).  For these tall type
buildings,  the data indicate a ratio of 0.09 to 0.10.

pictures 7 to 14 are plots  of the linear regression line for all three
 eteorological stations.   Not shown are regression plots for all
Building types combined.   For that situation, the calculated constant
4 a 0.044 for the rural case  and 0.094 for the urban case.  These and
 ther plots and data analyses are  available on request.

CONCLUSION

     d on stack height and  building type, a wide range of one hour to
  nual ratios were found.  These ratios are dependent on whether
3ban or rural dispersion  coefficients were used, as well as on the
  Aiding height and width.   Current EPA 1-hour conversion factors are
   ecj on the use of one value, plus or minus a small range of that
*>a®   f   The ratios now in  use are  meant to be conservative, and were
va:"ccted so one would not  have to  consider differences in input
s lues  such as urban versus rural.  Based on the 1-hour to annual
vaiYoS'found in this study,  a conservative ratio of 0.08 plus or
r?-T..« n.02  is recommended.   The upper range of 0.1 will cover tall
   e  structures and the bottom  limit of 0.06 would still be
*             for squat  and  supersquat structures.
r   is 0 02 is
    e structu
*   scrvative

ACKNOWLEDGMENTS

     author wishes to thank Mr.  John Irwin for his suggestions  and  for
The iding some of the data used in this study.

DISCLAIMER

       -n the research described in this article has been supported by
A    United States Environmental Protection Agency (EPA) ,  it has not
      formally released by EPA and should not at this stage be
  s   4-rried to represent Agency policy.   It is currently undergoing
c°£  rnal review and clearance for technical  merit and policy
^plications.

DEFERENCES

     ruidelines for Air Quality Maintenance Planning and Analysis,
*•   volume 10 (Revised):  Procedures for Evaluating Air Quality Impact
     of New Stationary sources, EPA-450/4-77-001,  October 1977.

     ., c  Environmental Protection Agency, 1989:   Guidance on Metals
2'    nd Hydrogen Chloride Controls for Hazardous  Waste Incinerators,
     Volume IV of the Hazardous Waste Incineration Guidance Series.

     TT-win, John S., 1990:  Memorandum to EPA Regional
3<   ilteorologists on Multiplying Factors to Convert 1-hour Maximum
     concentrations to Annual Average Concentration Estimates.
                                  665

-------
 OUT


 004


 am


 004


 O.OJ


 oe:


 IE1
           I5.000   JIJ7C  13.1JO  13 000
     as

                                                                                                         to
                                                                         or
                                                                rural di»p«r»ian.
                                                                             ratioi for t  buildlngi *• »
OJt


GM


a or
 01

an

OM
                                                            U2


                                                            •01
                                 ism    Htaa
  Figur* 3.  on* hour Scrtwi aod«l  ratulti  to
  annual rscsr ratio* for cupwrcquat tiulldlng*  as
  > function of stack teiglit for both urban and
  rural di»p»r«ion.
           4.  Ona hour Scnmn Bodal nculu to
    annual ISCtT ratio* for sup«r*qiwt buildlngi a
    a function of stack b*ig.\t f— both orban and
    rural diaparsion.
   Flijur* a.  ona hour Scracn aodal  results to
   annual ISCLT ratios for tall  buildings as  a
   function of ttadc h*igbt for  both urban and
   rural dlcpcriion.
            t.  ona kour SCVMB Mdal r«»ults to
     annual ISCST ratios for tall building* as a
     function of stack hslqht for both urban and
     rural dispersion.
                                                    666

-------
                     Q
                     a
             STACK HEIGHT
                                                                STACK HEIGHT
      *•  UHMT n^r.Mlon BtutlyBls  of
      -»»r»u» cmblAMl ISCST «nd ISOT to
             r.ti.0.  for «qu«t bulldingi tot
                                                                             •ad ISCIT to Scr**a
dl»p«r«ioa.
              for
•LI
                      O     g
                     -0	—
                                                             Q
                                                             a
                                                                                  D
                                                                                  a
                                                                          _l	1-
               STACK HEIGHT
                                                                 STACK HCJGHT
                                  of *t»cfc
                     ISCST «ad IICW to 8er**n
            ntioa for *«P«*Iu«t building*
                «CST «nd WCW to Saw.
        ntlo. f«
                                                   for
                                             667

-------
                                                  o
                                                  t-  ••«.
                STACK
                                                                   10     »     *"
                                                                   STACK HEIGHT
       11.  Linear rcgrusian analysis  of *tack
t«lqht  versus c<»l>liwd ISCST »nd ISCIT  to Scr**n
conc«ntr*tlp«riian.
                                                         v«r.u. cnblMd  ISCST
                                                   conc«ntr*tion ratios  for both squat
                                                   building* (or urb«n dispsrsion.
                                                                                       "* scr^" ,
                                                                                               *
                       O
                       a
                 °   °     °x
                 	^8	X
                  STACK HEIGHT
Flou
b*l«
     r* 11.   Lln*«r i«qr*«sioa «ntly«l* at stack
 concentration  ratio* for tall fcuildinjs tor
 rural dlsparslect.
                                                                      STACK HEIGHT
                                                                          MM*
       14.  UnMr rsqr*s*ioo
baight *«r*us costoinsd  ISCST
co«caFitr»tlen ratios tor tall
urban  dispersion.
                                              668

-------
              MULTIZONAL MASS BALANCE MODELING OF BENZENE
                         DISPERSION IN A PRIVATE RESIDENCE

     Azzedinc L»iuarl
     Environmental Information Technology Services, Computer Sciences Corporation, Research Triangle Park, NC
     27709
     Andrew B. Llndslrom
     Human Exposure and Field Research Division, Atmospheric Research and Exposure Assessment Laboratory,
     U.S. Environmental Protection Agency, Research Triangle Park, NC  2771J
     Brian D. Tcmpleman* and John S. Irwin*
     Atmospheric Sciences Modeling Division, Air Resources Laboratory, National Oceanic and Atmospheric
     Administration, Research Triangle Park, NC  27711

ABSTRACT

A residence in Roxboro, NC, was found to have its well-water supply contaminated with benzene (- 300 ug/1) and
other organic compounds.  The residents of the house do not currently drink the water, but they use it for daily
chowers. A study was designed to monitor and model short-term benzene dispersion within the house during and
after a shower.

A multizonal  mass balance  model, CONTAM88, was used to predict  interzonal air flow rates  and  benzene
 oncentration distributions within the house.  The idealization of the building was created using NBSAV1S, a
 reprocessor to CONTAM88. Simulation results showed that the highest concentration occurred in the shower stall.
nurine the shower, the master bathroom concentration was less than half the shower-stall concentration. Benzene
  ncentrations in the master bedroom and other rooms were lower.  Simulated benzene concentration distributions
°howed that benzene from the shower rapidly dispersed in the bouse, and reached equilibrium in all the rooms in
less than 30 minutes after the shower.  These results were supported by SF6 experimental data.

   nzene samples were collected using glass, gas-tight syringes in the shower stall and at various locations in the
h use The average benzene concentration after a 20-minute shower was 978 ng/m3 in the shower stall, 263 ng/m
   the master bathroom, and 70 ng/m3 in the master bedroom.   Simulated  and average measured  benzene
  ncentrations yielded a similar behavioral trend.  It was concluded that multizonal mass balance models may be
      in designing field study monitoring strategies.
jNTRODUCTION

n  nzene has the largest production volume of any chemical that has been causally linked to cancer in humans/1 *
i  's a pollutant thal * $Pread i" lhe environment from sources such as tobacco smoke, automobile refueling, and
• tdustrial waste.*2'3'41 Residential use of benzene-contaminated water may result in significant inhalation, ingestion,
£,d dermal exposures.*51

p—vious investigations have shown that trichloroethylene (TCE) contaminated  water supply may constitute a
 •nificant point source of human exposure for the bather, and a dispersed source for other inhabitants in the home.
pgr highly volatile chemicals, inhalation exposures have the potential to be equal or greater than those associated
  •in direct ingestion of water/6'7' For households using tap water contaminated with TCE, inhalation exposures in
w>        ild be as large as or larger than a conservative  estimate of ingestion exposure.  The assumption thai a
            consumes 2 liters (1) per day of tap water  was considered a  conservative estimate of  ingestion
exposure-*"

      uiaament to the Atmotpheric Rewvch and Expwurc Aueumert Laboratory. U.S. Environmental Protection Agency.
* 01* BMI0W
                                                 669

-------
 In 1985, a residence in Roxboro, NC, was identified as using ground waier contaminated with benzene, xylene, and
 other organic compounds. The benzene contamination has been characterized by measurements of 7 ng/1, 32 M8/L
 and 445 ug/l in 1986, 1989, and 1990, respectively. The homeowners nave continued to reside in the bouse and use
 the water for all their normal purposes except drinking and cooking. In 1991, Che U.S. Environmental Protection
 Agency (EPA) conducted a series of tests to assess shower-related exposures that occur throughout the house during
 and after a single 20-minute shower, to determine the relationship between  various monitoring techniques  and to
 assess the usefulness of multizonal mass balance models during experimental study designs.

 STUDY OBJECTIVES

 The objectives of this study are to (1) investigate the possibility of using multizonal mass balance models to predict
 locations where benzene concentrations are significantly different from background  concentrations in order to
 optimize sampling times and locations during a field study design, and (2) test the model performance in a well-
 defined microenvironment.

 THE MULTIZONAL MASS BALANCE MODEL, CONTAM88

 The multizonal mass balance model used in this investigation is the National Institute of Standards and Technology
 (NIST) model, NBSAVIS/CONTAM88*9) developed for EPA, to simulate transient  contaminant concenlradon
 distribution in buildings. The model is based on the element-assembly approach, which assumes that a building can
 be represented as  a combination of well-mixed zones linked by flow and kinetic elements {contaminant mass
 transport and decay). CONTAM88 solves a set of mass balance and flow equations. The mathematical formulation
 of the contaminant concentration is:

                                      trie?  +   IMI      . ff
 where:  C    = vector containing the discrete concentration values
        [W]  = system mass transport matrix containing flow rate data
        [M]  = system matrix containing mass (volume) data
        G    = system generation vector containing kinetics data.

NBSAVIS is a preprocessor to CONTAM88 that allows the idealization of the building through the generation of
a file that describes the building configuration, including indoor and outdoor contaminant sources.  Data input to
NBSAVIS are controlled by a series of screen-fill subroutines, which allow the user to specify interior and exterior
wall types, interior and exterior doors, windows, open passageways, filters and fans, room descriptions, and HVAC
system descriptions.

RESIDENCE DESCRIPTION AND IDEALIZATION

The private residence, which is located in a rural area in Roxboro. NC, is a single-story house.. The bouse has three
bedrooms, a bathroom, a family room, a laundry room, and an open area that consists of a living room, kitchen, and
dining room (Figure 1). The master bedroom area includes a bathroom with a separate shower  The bouse also has
a full basement, an attic, and a carport. The residents of the house get their water from a nearby well, located south
of the residence.

The NBSAVIS preprocessor was used to build the idealization of the house. The parameters of the bouse that were
measured to  run NBSAVIS are as follows:

          Physical dimensions (including all windows, doors, and other openings),
          HVAC system output, including locations of all vents and the associated air flow rates,
          Contaminant source information (name, molecular weight,  emission rate),
          Source locations (outside or inside, particular rooms of the house), and
          Local meteorological conditions (temperature, wind speed, and wind direction).
                                                 670

-------
 RESULTS AND DISCUSSION

 Air flow rates from all the vents of the HVAC system were measured using an Omega HH-30 vane anemometer;
 the HVAC return flow  rate (Table 1)  was measured using a Sbortridge Instruments  Row Hood.   Constant
 meteorological conditions were assumed, because the duration of the simulations did not exceed 4 hours.  The
 estimated local meteorological conditions were:  2 m/s wind speed, 220° wind direction, and 25 °C temperature.

 In the first stage of the study, a 15-minute shower was simulated-with water temperature of approximately 40 "C,
 at a flow rate of 10 I/minute.  The contaminant, benzene, was modeled as a point source located in the shower stall.
 The most recent benzene-in-water concentration (445 ug/1 measured in the house in 1990) and a 61% transfer
 efficiency of TCE from shower water-to-air (from McKone and Knezovich**) were used to estimate the benzene
 emission rate-45 ug/s. Also, sulfur bexafluohde (SF6) was released in the shower for IS minutes and its dispersion
 was monitored throughout the residence. Syringe samplers were placed in all rooms of the bouse (one sampler per
 room, in a location not exposed to  direct air flow from  the vents) to monitor concentration gradients.

 Each room in the house was considered as one zone, except the master bathroom which was considered as two zones
 because it has a separate shower stall. During the entire testing period, the HVAC system was running (only fan
  n)   The  ceiling fans were also running at their lowest speed to  allow constant contaminant mixing without
 disturbing interzonal air flows. Using the above conditions, benzene dispersion throughout the house during and after
 tlie shower was simulated.

 Simulation results for the first stage of this study showed that the highest benzene concentrations occurred in the
 shower and master bathroom, then in decreasing concentrations, in the master bedroom and hallway.  The living
 mom, dining room, kitchen, and family room had lower concentrations. These results were supported by the SF6
 r°«erimental data (Figure 2). Modeled benzene concentration distributions showed that benzene rapidly dispersed
 f *£e house, and all rooms in the house reached equilibrium within 30 minutes after the  shower (Figures 3a and 3b).
 Therefore, a total sampling time of about 50 minutes may be chosen. After that time,  simulated concentrations of
    jut 50 Mg/m3 were found in the house.
    the second stage of the study, the living room, dining room, kitchen, and family room were considered as one
    U-mixed zone. Furthermore, the total simulation time was 50 minutes. The shower was run for 20 minutes with
 ** bathroom door closed.  After the shower, the shower-stall door was open and the bathroom door was kept closed
 ft 5 minutes to allow for the individual to dry off and get dressed. After that time, the shower-stall and bathroom
       were opened.  The average measured shower water flow rate was about 6.3 1/min, and the average waterborne
         concentration from the pre-sbower head samples was 292 ug/1. Waterbome benzene concentrations from
         shower bead samples and the drain-level samples were measured and used to calculated the water-to-air
         efficiency.  The average calculated benzene transfer efficiency was 88% yielding a benzene emission rate
 n
  f27 5 V&s-  Usin* ** above conditions' k611261* dispersion throughout the house during and after the shower was
            Simulation results of benzene dispersion showed a benzene concentration of 625 ug/m3 in the shower
  rn-
   il afvt a 20-minute shower, 278 MS/rn  in the master bathroom, and 148 pg/m3 in the master bedroom. The rest
  rtoe rooms in the house had concentrations of less than 40 ug/m3.

   ---oe concentration levels were measured during a 3-day, 3-shower period (i.e., 1 shower each day).(10) Glass,
   ctiebt syringe samplers were placed in the shower stall, bathroom, master bedroom, and living room.  The total
*   niing time was 120 minutes.  After 20 minutes, the shower-stall concentration reached an average value of
^g Wm3  (standard deviation, SD, equal to 514 jig/m3), the master bathroom concentration reached 263 ug/m3
  en *&* |ig/m3),  the master bedroom concentration reached 70 ug/m3 (SD * 14 ng/m3),  and the living room
   •ientratfon reached 40 ug/m3 (SD » 16 ug/m3).  Figures 4 and 5 show  the simulated and measured benzene
C°Jioentralions -n ^ sij0wer stail and the master bathroom, respectively.

    .   the  shower, there was significant variability in the data, which may be due to incomplete mixing, dynamic
I?U^1 don in ** benzene-in-water concentration, and experimental errors.  The benzene concentration during the third
va**";  was much higher than during the first two showers. This difference may be due to variability in water flow,
860 ell as sampling inaccuracies  due to incomplete  mixing.   Differences between simulated and measured
as     uatjons may be due to model limitations. For instance, the assumption of a well-mixed zone may be too
     ff"
                                                  671

-------
 simplistic.  Also, the assumptions and parameter estimation used in the idealization of the house may constitute a
 significant source of uncertainty.  Overall, the model did well in predicting the zones of significantly different
 concentrations and the time necessary for the contaminant to reach equilibrium throughout the house.

 CONCLUSIONS

 In the first stage, CONTAM8S was used to plan the study design.  SF6 was used to measure flow rates within the
 house.  Modeled benzene concentrations in the shower were more than twice the master bathroom's concentration
 during  the  shower.  After  the  shower  and opening the shower door, benzene quickly dispersed in the house.
 Concentration equilibrium was reached within 30 minutes. This result suggests that a total sampling period of less
 than 50 minutes would be appropriate for this type of study. Simulation results also showed that the living room,
 dining room, kitchen, and family room have similar concentrations.  Therefore, they were grouped  into one zone.
 The SF6 experimental  analysis yielded similar  results.

 In the  second stage of the study, benzene concentrations were simulated and measured in the shower, master
 bathroom, master bedroom, and living room. The average measured shower benzene concentrations were about 40%
 higher  than  the simulated ones; the simulated master bathroom concentrations were about  6% higher than the
 measured ones, and the simulated master bedroom concentrations were about 100% higher than the average measured
 one.  The simulated concentrations in  the rest of the rooms  were about 20% lower than  the measured ones.
 Therefore, CONTAM88  may only be used  to  simulate broad trends of concentration distribution throughout the
 house.  Using CONTAM88 for the exposure assessment suggested that a 1-hour sampling time should be appropriate
 for a 20-minute shower.  The model also helped in  deciding the rooms in which to  locate the samplers, to monitor
 benzene concentration  distribution.  Simulation results will hopefully help investigators plan field studies and
 minimize the cost of the  studies.

 ACKNOWLEDGEMENTS

 The authors wish lo acknowledge and thank Mark Johnson awl David Proffitt for the air exchange and SF6 data, used during the preliminary stage
 of the study,  The authors also  thank Larry Michael for the benzene data. This work was sponsored by the Indoor Air Research Section, U.S.
 Environmental Protection Agency.

 DISCLAIMER

 This paper has been reviewed  in accordance with the U.S. Environmental Protection Agency's peer »nd administrative review policies and
 approved for presentation and publication. Mention of trade names or commercial products does not constitute endorsement or recommendation
 for use.

 REFERENCES

 1.  EPA. 1984. National emission standards for hazardous air pollutams:Regulalioii of benzene. FBderarRejjister. 49(110):23,478-23,495.
 2.  Fishbcin, L. An overview of environmental and lexicological aspects of aromatic hydrocarbons. I. Benzene.  Sci. Total Environ.. 40, 189-
    218. 1984.
 3.  International Agency for Research  oo Cancer (1ARC). IARC Monograph on the Evaluation of the Carcinogenic Risk of Chemicals and
    Dyestnffs.  Volume 29.  pp. 93-148. Lyon. France. 1982.
 4.  Webster. R.C.. Maibach, H.I., Graenke, L.D,, and Craig, J.C Benzene levels in ambient air and breath of smokers and nonsmokers in nrbu
    and pristine environments.  J^Toxicol. Environ. Health. 1S:567-S73. 1986.
 5.  Shehata. A. T. A multi-route exposure assessment of chemically contaminated drinking water. Toxicology and Industrial Health. 1(4):277-
    298. 1985.
6.  Andelman. i. B., A. Couch, and W. W. Tburston. Inhalation exposures in indoor air to trichloroethyleoe from shower water. Environmental
    Epidemiology, pp. 201-213. 1991.
7.  Andelman. J. B.  Inhalation exposure in the home to volatile organic contaminants of drinking water.  Science Total Enviro., 47:443-460.
    1983.
 8.  McKone, T.E. and J.P. Knezovich.  The transfer of iricMoroethylene CTCE) from a shower to indoor air: experimental measurements and
    their implication. J. Air A Waste Mumt. Asaoc.. 41:832-837.  1991.
9.  Grot, R.A. User's Manual NBSAVIS/CONTAM88.  A user interface for air movement and contaminant dispersal analysis in multizone
    buildings.  National Institute of Standards and Technology, Gaithersburg, MO. 1991.
 10.  Michael. L C  VOC support to the Roiboro, NC, benzene investigation.  Research Triangle Institute.  RTI/4657-07AA)2F. 1991.
                                                      672

-------
s:i^i^irb2n.— •••'"••"•""•
ROOM-**
•i»w
(s1/*--
Mitch«n |l-T7
laundry roam 13.13
Dininf roo»-l
Dining roo«-2

Family roo»-2
.^roo. 1-1
B*droo» 1— «
B«d r oov 2 1
B*throo«
...t.r tMKlrooa-1
voter b^lroo»-a
Master bathro*
Living roam-i
Living roo«-2
BJ»«"«nt
2.TJ
1.9«
I.M
.
1.11
O.tl

4 . ; i
J.OJ

3.0C
3 . S»

H«turn 1 «« !J


* • • • *
—
• — > s —
-
, 	
«r
< *SL ^-—
"~ ^ •
. : 1 *
• •
»w - —4— — trr -
< ^—
* k£ui"c i . ij4, in iiulic oi UK ROXDOTO nouse



i
1 1
.
j::
^
5J*
.
JC » ^ •
-~~,
       2  Measured SFfr concentration distribution
within the  house  During and  after  a


-------
              BENZENE SIMULATED CONCENTRATIONS
                (15 mn »ho»«r. 45 uq/i •mi»»ian rat*)
                        20   25   30
                         Time (mm)
45  50
 Figure  3a.   Simulated   benzene  concentration
 distribution during and after a 15-min, shower, for
 the rooms of highest concentration levels.
                                                            60
                                                            so
                                                          "Si
                                                            40

                                                          130
                                                            20

                                                            10
                        BENZENE SIMULATED CONCENTRATIONS
                          0 5 mid ihowtr. 4J ug/l (million rate)
10   15   20   25   SO   35   40   45  SO
         Tim* (min)
             Figure  3b.    Simulated benzene  concentration
             distribution during and after a 15-min. shower, for
             the rest of the house.
        SIMULATED /MEASURED BENZENE CONCENTRATIONS
               (20 mm srio*er. 27 ug/i tmiision rate)
    1600
  "E 1400
  JNzoo
  I tooo
  o
  1 800
  I MO
  i 400
  N
  J 200
      0
                      20  25  30
                         Time (min)
Figure 4. Simulated (S) and measured (M) benzene
transient concentration in the shower stall, during a
3-day, 3-shower experiment.
                     SIMULATED/MEASURED BENZENE CONCENTRATIONS
                            (20 min •hower, Z7 uq/1 «mi»ion rot*)
                 300
                 450
                 400
                 350
                 300
                 2SO
                 200
                 ISO
                 100
                  so
                   0
                        5   10  IS  20   25   30   35 • 40  4S  M
                                     Tim* (min)
             Figure 5. Simulated (S) and measured (M) benzene
             transient concentration in  the  master  bathroom,
             during a 3-day, 3-shower experiment.
                                                   674

-------
                                 Comparison of Modeled Concentration Profiles
                            Using Site-Specific and Constant-Condition Meteorological
                                      Data for the ISCLT and PAL Models

                                                      by

                                                 John Streicher
                                         Computer Sciences Corporation
                                       Research Triangle Park, NC 27709

                                                      and

                                               Brian Templeman
                                     Atmospheric Sciences Modeling Division
                                           Air Resources Laboratory
                                National Oceanic and Atmospheric Administration
                                       Research Triangle Park, NC 27711

                        • On assignment to the AbnMph«He Research and Exposar* Assessment Laboratory,
                                         U.S. EaTironmeotal Protection Aftncjr
ABSTRACT

         Modeling atmospheric pollutant dispersion from ground-level area sources generally requires site-specific, or at
       •te-representative meteorological data.  Models that predict annual-average concentrations as a  function of radial
leaSt "  and Bzimuthal direction accept data in standard formats such as STability ARray (STAR), or hourly (CD-144)
distance     j^,^ Source Complex - Long Term (ISCLT) model and the Point, Area, Line Source (PAL) model are
forma1-  i»
    example*-
         However, an air quality screening analysis may only require estimates of the annual-average radial maximum
       (rations. Modeled annual-average radial  maximum concentrations (azimuth-independent) are less sensitive to the
conccn  ^ ^eftut jn site-specific meteorological data.  Such a one-dimensional  treatment does not fully utilize, and
variatio       ^ require, the two-dimensional information that is available in conventional meteorological data formats
**     STAR or CD-144.  Is there a single combination of atmospheric stability, wind speed, and frequency of occurrence
50011 **  azimuth-independent "constant-condition" pseudo-meteorological data input) which can provide a useful screening
(i ,e. , an     ^ annual-average radial maximum concentration profiles for ground-level area sources?

         A comparison of modeled annual-average radial maximum concentration profiles, from a small area source, was
            en several constant conditions and  meteorological data from several sites.  Two models were  selected
rnade  be   djfferent modeling approaches, the  ISCLT model (a sector-average Gaussian plume dispersion algorithm), and
fCpteseai *KXJCJ  ^a  fmite-line-source  "point  estimate* Gaussian  plume  dispersion algorithm).   Reasonably  good
the ff^     oj.  jmjuai.average radial  maximum  concentration  profiles from  ground-level area  sources  for  five
   resen a.. $-tes waa simulated using constant conditions; however, the resulting single combination of atmospheric
        '0*    jp^ed, and frequency of occurrence that produced radial maximum concentrations are model dependent.
                                                       675

-------
 INTRODUCTION

         Modeling of atmospheric contaminant dispersion falls into two broad categories: one employing comprehensive
 analytic algorithms and demanding extensive data input; the other employing simplified algorithms and/or default values
 and requiring relatively fewer input data.

         A screening analysis follows the second approach.   The purpose of a screening analysis, in the context of air
 quality regulation, is to eliminate from further comprehensive analysis, those sources  that  pose no significant threat of
 degradation relative to  ambient standards. To  conclude  regulatory compliance  using  simplified  algorithms,  any
 discretionary input should represent a reasonable worst-case or upper-bound estimate.

         Some screening models require that atmospheric dispersion variables be parameterized as constants.  Typical of
 these are models that treat dispersion as a one-dimensional,  source-to-receptor process.  Such models find application in
 the characterization of dispersion from single ground-level area sources. Specifically, parameterizations for stability, wind
 speed, and frequency of occurrence are assigned, with constant values chosen to generate reasonable upper-bound annual-
 average concentrations at receptor locations.  Although the ease and  simplicity of such an approach has obvious appeal  as a
 screening tool, the values of stability, wind speed, and frequency of occurrence input intended  to generate upper-bound
 annual radial maximum concentrations are not established, and may not be valid except in .non-urban environments, over
 non-complex terrain.

 STUDY OBJECTIVE

        The objectives  of this study are to estimate the range of annual-average radial maximum concentrations generated
 by ground-level area sources, using  a diverse group of sites located  throughout the United Slates, and to determine the
 single condition of stability,  wind speed,  and frequency of occurrence that best characterizes (for modeling purposes) the
 midrange,  and the lower and upper bounds of the observed range of such concentrations.   These dispersion "constants"
 may provide a useful tool to aid modelers in screening analyses of ground-level area sources.  The extent to which these
 dispersion 'constants' are model dependent is to be discussed, and the generality of any determination must be qualified
 accordingly.

        The scope of the study encompasses at least 20 meteorological data  sites from a wide range of climates  and
 topographies around  the United States.  Multiple years of meteorological data for selected sites are to be examined to
 determine the range of  year-to-year variation. The determination of the best fitting constant-condition profile for lowet
 bound, central tendency, and upper bound, is determined in part by a regression analysis on the constituent parameters -
 wind speed, stability, and frequency of occurrence.

        Presented here are  preliminary findings based on  the  analysis of data from five sites:  Albany, NY,  1988;
 Amarillo. TX, 1987; Boise, ID,  1988; Peoria, IL, 1987; and Topeka, KS, 1988.

MODEL DESCRIPTION

        In this study, two Gaussian dispersion models are employed: the ISCLT1 and the PAL2.  These models calculate
concentrations  using different  dispersion  algorithms, therefore  it is not expected  that their  respective predicted
concentration profiles will coincide  for a  given  input data set.  However,  both models use the same Pasquill-Gifford
stability categories and dispersion coefficients.

        The ISCLT model calculates atmospheric dispersion concentration profiles using a Gaussian-plume, sector-avenge
algorithm.   The receptor concentration data obtained  from the ISCLT model  represents the average concentration at a
specified distance from the  source in a given sector,  typically  a 22.5 degree arc  corresponding to one of 16 nominal
directions.    Area sources are  modeled  using  a virtual  point-source  algorithm.   Briefly,  (he virtual point  source
corresponding to an area source may be defined as an imaginary point source (of identical source strength), located upwind
from the area source,  such that the extent of its transverse dispersion exactly overlaps the transverse dimension of the area
source.  Meteorological  data  are input into the ISCLT model  in the  STAR format.  STAR data is an array of annual joint
frequencies  for  each stability  class,  wind direction, and  wind  speed  category.    Therefore, specific  hourly site
meteorological data has been lost.

        The PAL model calculates atmospheric dispersion concentration from area sources using a Gaussian-plume, finite-
line-source algorithm. Area sources are internally represented as • series of line sources. Concentrations of atmospheric
pollutants are calculated  at specific receptor locations; no sector average a computed. A climatological version of the PAL
model was developed to  process a year of hourly meteorological data, optionally processing all hours or sampling as few as
                                                      676

-------
1 «» 24 hou», AIL references to PAL in. this study refer to th* climatological version.
       Surface- and upper-air data sets from the  five sites (Albany, NY; Amarillo, TX; Botse,
       KS) were downloaded from the EPA's Office of Air Quality Planning and Standards  ela
      - These data sets were then formatted for inclusion into me 1SCLT and the PAL model input
*** a STAR data set was generated  from (he hourly me.eotological data.   For the PAL «*'
Biological data were required. Default mixing heights were used in the ISCLT amuUUons. Mixmg hetghls compuled
 °m temperature profiles in the upper-air data were used fa the PAL sunuJations.

co™   > Potion of input  data representing constant conditions  of stability ^^^ jS'StlS
^tructioa of single-subilily aid single-wind speed job. frequency Junctions  (STAR format) and houri'*" ^s»||"8
*.  ~    *tie wm'rti.   L                          «• •      ^i* £« i.v« «4«Kil>iv raA^5  riffurc ^ snows coTjcentraiion
         « unique characteristic of anv constant-condition profile is tie aamuty w«»-  *is<"»
       fo' seven Dseud™T  i  • i    ,  , «^nn«  Table 2 lists the PasquiH stability categones as defined by
               r™uao^DCitoroIoClCHl COnstAQl CODQ1UOO«*  1BOT" * wo»a uiw * *^^         •*    **
           td cover, and wind speed.

           '3 shows concentration profiles for the five sites (dotted lines), and three wnstan! MjfU^: f^J*
            &'3/10* (solid Jin«). The concentration profiles generated using E stability provide the best fit with the
           ''to the ISCLT taodtl). These constant conditions prwWe approximate upper bound, central tendency, and
         '• respectively, for the five data sites, as modeled by the ISCLT.
                                               6T1

-------
                                                                                                            A
         Figures 4 and 5 show concentration profiles generated by the PAL model. Maximum annual concentration (gnT*)
 is plotted as a function of radial distance (m) from the source. It is important to remember that inherent within the ISCLT
 model is the concentration averaging within a given sector.  No  averaging is performed in an hourly model like PAL.
 Therefore, one would not be surprised to  find a different set of constant conditions that characterize the upper and lower
 bound of the concentration profiles.

         Figure 4 shows  concentration profiles for the  five sites.   The range  of  concentrations  at  any  distance
 (approximately  a  factor of 4)  is slightly  larger with PAL than with the ISCLT model.  Although both models apply
 Gaussian dispersion coefficients, the sector averaging algorithm of the ISCLT model appears to diminish the distinction
 between individual site profiles.  Although ranking hierarchy is essentially the same as with the ISCLT model, the PAL
 model clearly resolves the concentration profiles from the Boise and Albany sites (the ISCLT model did not), but does not
 clearly resolve profiles from the Peoria and Topeka sites (the ISCLT model did).

         Figure  5  shows concentration profiles for the five sites (dotted lines),  and three constant conditions: D/5/409C,
 D/5/1596, and D/5/556 (solid lines).  Stability D was  chosen because the concentration estimates provide the best fit to the
 site profiles.   These constant conditions provide  approximate upper  bound,  central tendency, and lower  bound,
 respectively, for the five sites, as modeled by PAL.

 CONCLUSIONS

        The constant-condition para me terizat ions  that characterize maximum annual concentration profiles for dispersion
 of volatiles  from ground-level area sources are model dependent.  Based on a preliminary sample of five data sites, the
 annual-average radial maximum concentrations from ground-level area sources range from E/3/10% to  E/3/30% (ISCLT
 model), and  from  D/5/5% to D/5/40& (PAL  model).  An approximate mid-range characterization is E/3/15% (ISCLT
 model) and D/5/15% (PAL model).  The  range of annual-average maximum concentrations at any distance is at least a
 factor of 3 using the ISCLT model; or a factor of 4 using the PAL model.

        The  application of constant-condition meteorological data is limited to a screening analysis of single ground-level
 area sources, in non-urban environments, over non-complex terrain. The limited number  of sites examined in this report
 renders its conclusions as tentative.  The range of year-to-year variation to be found in meteorological data  at any single
 site is  to be investigated in future study.

 ACKNOWLEDGMENTS

 The authors wish to thank Bill Petersen for providing the climatological version of PAL.  The authors also wish to thank
 Alan Huber and John Irwin for their contributions to this effort.

 DISCLAIMER

This paper has been  reviewed in accordance with the U.S. Environmental Protection Agency's peer and administrative
 review policies, for approval for presentation and publication. Mention of trade names or commercial products does not
constitute endorsement or recommendation for use.

REFERENCES

 1. Industrial Source Complex (ISC) Dispersion Model User's Guide.  Second edition.  U.S. Environmental Protection
Agency, EPA-450/4-83-004.
2. User's  Guide  for PAL 2.0:  A Gaussian-Plume Algorithm for Point, Area,  and Line sources.   U.S. Environmental
Protection Agency, EPA-oOO/8-87-009.
3. Office of Air Quality Planning and Standards (OAQPS) Technology Transfer Network (TTN) electronic bulletin board.
Modem (919) 541-5742.  Information (919) 541-5384.
4. Industrial Source Complex (ISC) Dispersion Model User's Guide.  Second Edition (Revised).   U.S. Environmental
Protection Agency, EPA-450/4-88-002a.
                                                     678

-------
                              -oca

        131




 ,

g   t9-»






J
•v.
      •






                        Fifurc 3

-------

       •
I
I

       •
          10-7
                                                     ____ '988
                                                      ___ !968

                               . - .
                                                 •
                                                     1  J 4
                                  Figure 4
                                             ,
                                                BOrSC	1988
                                                -
                                                       __l 987
                                 . JiTiOfiS
                                                •
                                  Figure 5

Table 1. Model Input
                                     Table 2, Stability Catagories
                               680

-------
      ATMOSPHERIC DEPOSITION OF TOXIC METALS TO LAKE
    MICHIGAN: PRELIMINARY ANNUAL MODEL CALCULATIONS


                                    Terry L. Clark*
                                Air Resources Laboratory
                     National Oceanic and Atmospheric Administration
                      Research Triangle Park, North Carolina 27711
 ABSTRACT
        Concern is growing for the environmental water quality of the Great Lakes,  Atmospheric
 deposition of toxic substances is recognized as a major pathway of contaminants to the water
   edium.  To  estimate the annual atmospheric loadings of five  toxic metals - arsenic (As),
   dmium (Cd), chromium (Cr), lead (Pb), and nickel (Ni) — to Lake Michigan,  the Regional
 T  erangian Model of Air Pollution (RELMAP) was applied using a preliminary 1985 airborne
   xics emissions inventory developed by EPA for U.S. and Canadian anthropogenic sources.
 At 3-h intervals this model creates pollutant puffs containing particles with diameters of either
   -  m or 5.0 /*m, transports them across the eastern North American domain, and calculates
     and dry deposition amounts for each unit-degree  cell.  Total direct deposition amounts to
 ^ lake are determined from  these calculated amounts and a land-use inventory that defines the
 liter surface portion of each cell.
        The preliminary model results indicate that Pb deposition, approaching 700,000 kg/yr,
     eds by an  order of magnitude the deposition of the other metals, which range from  18,000
 CX/ T to 58,000 kg/yr.  The relative contribution of dry and  wet depositions  to the total
 ^  cjtjons is  highly dependent on the particle size.  For the smaller particles dry deposition
 ^    ted for  10% or less of  the total deposition versus the nearly 40%  for the larger particles.
         r, the  total deposition to the lake is not nearly as sensitive to particle size.
 ^TRODUCTION
        Atmospheric deposition is a major pathway of toxic substance loadings to the Great
          Using  an  empirical approach, Strachan  and  Eisenreich1 have  estimated that
 L**e ' jmately 95% of tne tota^ loadings of Pb to Lakes Superior, Michigan, and Huron are a
 aPPr.   f atmospheric deposition.  In recognition of the significance of atmospheric deposition,
 re-S|U  III of the 1990 Clean Air Act Amendments requires EPA and NOAA to quantify the annual
 Titf6  heric loadings of numerous specific toxic substances to the Great Lakes, Chesapeake Bay,
 atIChamplain, and other coastal waters.
        As an  initial response to this mandate, the Regional Lagrangian  Model of Air Pollution
          )2 was aPPl'e*' to estimate tne annual 1985 atmospheric deposition of five toxic metals
          ^ ^e CAAA ,ist _ As> cd( Cr  pb? j^ Ni _ to Lake Michigan. In the near future,
        jej wju also be applied to calculate the annual deposition amounts of an additional  15
tflis. msubstances to the entire Great Lakes Basin.

       On assignment to the Atmospheric Research and Exposure  Assessment  Laboratory, U.S. Environmental
*      Protection Agency
                                         681

-------
 MODELING APPROACH
        For these applications, RELMAP uses preliminary EPA estimates of 1985 air emissions
 from North American anthropogenic sources and by wind erosion east of 105° West longitude3.
 (Emissions from other natural sources, such as forest fires and volcanic eruptions, were not
 considered.)   These emission estimates,  based on  the  1985  National  Acid Precipitation
 Assessment Program (NAPAP) volatile organic carbon-(VOC) and paniculate matter inventories
 for both point and area sources4, were aggregated to unit-degree cells within the model domain
 (Figure 1). Neither particle size distributions nor seasonal emission factors were included in the
 initial EPA toxics inventory.
        The model also uses a 20-km land-use inventory*, climatological monthly mean mixing
 heights', as well as 12-h wind and 1-h precipitation measurements for the entire year of 1985
 to transport pollutant puffs of uniform-diameter particles  across its four-layer eastern  North
 American domain and calculate both wet and dry depositions to land and water surfaces within
 each unit-degree cell. The  model assumes (1) spatially homogeneous maximum  mixing heights
 (i.e., the mixing heights over the lake and land surfaces are  identical); (2) thorough vertical
 mixing in the daytime and  no vertical  mixing at night; (3)  uniform horizontal dispersion (i.e.,
 no dependence on atmospheric stability); and (4) either 0.5 /*m or 5.0 ftm particle diameters
 (i.e., for each model simulation the particle diameters were identical).   This was a reasonable
 range of particle sizes in regions removed from significant local sources).
        Dry deposition is calculated by the product of the 3-hour-mean surface-layer air concen-
 trations and a seasonally dependent deposition velocity based on particle diameter,  as well as
 atmospheric stability and land-use characterizations within each unil-degree cell.  The depth of
 the surface layer changes diumally from a daytime maximum of 700 m to 1500 m to a nighttime
 minimum  of  30  m  to 50  m, depending on  the season.  The dry  deposition velocities are
 consistent with size-dependent rates appearing in the literature, 0.2 cm/s to 2.0 cm/s \
        Wet deposition of the  toxic metals is calculated by  the product of a washout ratio and
 hourly precipitation amounts raised to the 0.622 power.  Precipitation amounts and occurrences
 are characterized by frequency distributions  for each 3-h period and for each unit-degree cell*.
 The  model  avoids   using  cell-averaged precipitation  amounts, which  strongly  tends to
 overestimate the precipitation occurrences,  and to a lesser extent, the precipitation amounts.
 Total direct deposition to Lake Michigan is then determined by spatially integrating the dry and
 wet depositions across only the water surface within each cell.
       Temporally varying emissions, chemical reactions, changes in particle diameters, phase
 changes, particle resuspension, indirect deposition from land and vegetative surfaces, and land-
 water differences  in meteorological  parameters were not addressed   by  this initial  model
 application. Therefore, these model results are preliminary. Future applications should address
 these issues.

MODEL CALCULATIONS  OF ATMOSPHERIC DEPOSITION
      The  annual  deposition amounts  of any pollutant to  Lake Michigan depend on the
proximity of sources, the emission  rates,  meteorological  factors, and atmospheric removal
efficiency. Since the emissions rate of Pb was an order of magnitude greater that the rates for
the other  four  toxic  metals, its annual  deposition  to  Lake Michigan  was also an order of
magnitude greater, as Table I and Figures 2 and 3 demonstrate.  Pb deposition, approaching
700,000 kg/yr, dominated the total deposition of the  remaining  metals, which ranged  from
18,000 kg/yr to 58,000 kg/yr.
                                          682

-------
       Table I also shows that the relative contribution of dry deposition to total deposition is
 highly dependent on the modelled particle diameter.  For smaller particle sizes (i.e., 0.5 ftm)
 dry deposition accounted for 10% or less of the total deposition.  On the  other hand, dry
 deposition of  the larger particles  (i.e., 5.0  pm), accounted for nearly 40% of the total
 deposition.  The difference in the relative contributions  is a result of the greater deposition
 velocities for the larger particles.                                         .   ,_ _ ,   .
       However, the total deposition for the two particle sizes differs by less than 20% for As
 a"3QO km east  of Lake Michigan), whereas for the
 other meals, souroes ^ concentrated in both southern Ontario and the Milwaukee-Clncago-
 °ary corrider (along the southwest shore).                           .
  L    Thus, if one is interested in  only the ipJBu deposition lo vhe tanja lake  partite size
 characterizations may not be necessary. However, if one is interested in either icjaj deposition
 to subsections of the lake or source-receptor relationships, particle size characterizations would
 te needed, since the deposition velocities (1) are dependent on particle sizes and (2) will delate
 tne atmospheric transport scale.

 COMPARISON OF MODEL CALCULATIONS WITH INDEPENDENT ESTIMATES
       An alternate method  of estimating atmospheric deposition of toxic  metals  to  Lake
 Mi<%an is empirical    Strachan and Eisenreich* also estimated the  annual atmospheric
 deposition of Pb and other toxic substances, to Lake Michigan, as well as the other four lakes
 ]n the Great Lakes Basin    Their estimates  were based or,  typical  values for the annual
 Precipitation amount, particle washout rate,  dry deposition  velocity, and air  concentration in
 remote areas.  From this mass balance exercise, they estimated an annual Pb deposition rate of
 543,000 kg/yr, anptoxim^elv 20% low* than the RELMAP Pb calculation.  The greater model
 calculation is not surprising since the modeling approach accounts for the emission contributions
 fro* the  densely  populated  industrialized  areas adjacent to the lake,  while thei empirical
 approach, by  virtue of  using air concentrations typical in areas far removed  from  these
 stgnificant source areas, virtually ignores the urban contributions.

 CONCLUSIONS                                                        .,_,    -.     t
 .  .    *ELMAP,  a simple atmospheric model parameterizing the transport »dI deposition of
 <°*'c substances, has calculated the annual atmospheric deposition of five toxic metals to  Lake
Jfthfcm.  Two majorcon  lusions resulted from this  study.  First, it has been shown that
f hough partis to controls the relative contributions  of wet and dry depositions to the total
Deposition for La^ Micni     total ^ly integrated deposition itself is largely ;"*ns£ve to
f^'de size.  This may not be the case for the other lakes, since the enussujn Pa ^™ ?^
 ° each lake are quite different.   However, in determining  source-receptor retaUonsmps and
     ort scales, particle size distributions are essential. Secondly, deposition eshma^s based
       on air concentration data in remote regions are  likely underestimatmg Lake Michigan
     tions, since the empirical approach does not account for the effects of the emissions m the
     and industrialized areas along the southwest shoreline.
                                          6S3

-------
ACKNOWLEDGEMENTS
       This modeling effort is supported in part by the EPA Great Lakes National Program
Office, the Air and Radiation  Division of EPA Region V, and the EPA Office of Air Quality
Planning and Standards. The  author expresses his appreciation of the effort of George Mapp,
Computer Sciences Corporation, in applying the model and analyzing the results.

DISCLAIMER
       This paper has been reviewed in accordance with the U.S. Environmental Protection
Agency's peer and administrative review policies and approved for publication. Mention of any
trade names or commercial products does not constitute endorsement or recommendation for use.

REFERENCES

1      W. Strachan and S. Eisenreich, Mass Balancing of Toxic Chemicals in the Great Lakesi
       The Role of Atmospheric Deposition, Appendix I from the Workshop on the Estimation
       of Atmospheric Loadings of Toxic Chemicals  to the Great Lakes  Basin, Windsor,
       Ontario, 1988, 113 p.

2      B. Eder, D. Coventry, T.  Clark, and C. Bellinger, RELMAP: a Regional Lagrangian
       Model of Air Pollution User's Guide. EPA/600/8-86/013, U.S. Environmental Protection
       Agency, Research Triangle Park, 1986.

3      W. Benjey and D. Coventry, "Geographical distributions and source type  analysis of
       toxic metal emissions", in Proceedings of the  1992 U.S.  EPA/A&WMA International
       Symposium  on Measurement of Toxic and Related Air Pollutants. Session 23, Air &
       Waste Management Association, Pittsburgh, 1992.

4      M. Saeger,  J. Langstaff, R. Walters, et al., The 1985 NAPAP Emissions Inventory
       (Version 2V Development of the Annual Data and Modelers' Tapes. EPA-600/7-89-012a,
       U.S. Environmental Protection Agency, Research Triangle Park, 1989.

5      S. Page, National Land Use and Land Coverage Inventory. Lockheed Engineering and
       Management Services Co.,  Inc., Remote Sensing Laboratory, Las  Vegas, 1980.

6      G. Holzworth, Mixing Heights. Wind Speeds, and Potential for Urban Air Pollution
      Throughout  the Contiguous United States.  AP-101,  U.S. Environmental  Protection
       Agency, Research Triangle Park, 1972.

7     C. Davidson and Y.  Wu,  "Dry deposition of trace elements", In Control and Fate of
      Atmospheric Trace Metals. J.M. Pacyna and B. Ottar, Eds., 1989, pp 147-202.

8     O. Bullock, "The effect of sub-grid-scale rainfall analysis on sulfate wet deposition
      estimates in the Regional Lagrangian Model of Air Pollution (RELMAP)", in Preprints
      of the Seventh Joint Conference on Applications of Air  Pollution Meteorology  with
      AWMA. American Meteorological Society, Boston, 1991, pp 81-84.
                                        684

-------
 Table I.  RELMAP calculations of the 1985 atmospheric deposition (kg/yr) of toxic metals to
 Lake Michigan for two different particle diameters.
Pollutant
Arsenic
Cadmium
Chromium
Lead
Nickel
Particle
Size
0.5
5.0
0.5
5.0
0.5
5.0
0.5
5.0
0.5
5.0
Dry
Deposition
5,870 (10.0%)
19,033 (39.2%)
2,053 (10.0%)
7,179(39.2%)
2,908 ( 8.7%)
13,129(37.1%)
62,456(9.1%)
254,201 (37.7%)
2,483 (8.3%)
9,539 (35.9%)
Wet
Deposition
52,552 (90.0%)
29,484 (60.8%)
18,575 (90.0%)
11,122(60.8%)
30,678 (91.3%)
22,275 (62.9%)
627,306(90.9%)
420,818 (62.3%)
27,489 (91.7%)
17.069(64.1%)
Total
58,422
48,517
20,628
18,301
33,586
35,404
689,762
675,019
29,972
26,608

Figure 1.  T*16 unit-degree configuration and model domain of RELMAP.
                                         685

-------
                    ANNUAL DEPOSITION TO LAKE MICHIGAN
              700
              600
              500
              400 -
              200
              100 -
                                                 0.5 Micron Particles
                                CD         CR          Nl
                                    TOXIC METAL
                              DRY     BS2I WET    777A TOTAL
                                                                  PB
Figure 2.   The RELMAP-calculated annual depositions of five toxic metals to Lake Michigan
        for 0.5 pm particles.

                    ANNUAL DEPOSITION TO LAKE MICHIGAN
             700
             600 -
             500 -
             400 -
             -300 -
             200
             100 -
                                                   5.0 Micron Particles
AS
                                CD         CR          Nl
                                    TOXIC METAL
                              DRY     ggg WET    V77*  TOTAL
                                                                  PB
    re 3.   The RELMAP-calculated annual depositions of five toxic metals to Lake Michigan
        for 5.0 fim particles.
                                      686

-------
                        WIND TUNNEL MODELING

                 FOR EVALUATING THE DISPERSION

                           OF TOXIC CHEMICALS
                              Ronald L. Petersen, Pn.D., CCM
                                           and
                                    Chester E. Wisner
                                Cermak Pcterka Petersen, Inc.
                                  1415 Blue Spruce Drive
                                  Fort Collins, CO 80524
 INTBODUCTION
       Many of the most significant releases of air toxics occur in complex air flows. Examples include
  fineries,  chemical  manufacturing plants, and research laboratories,   Gases  released in  these
  nvironments are transported through the buildings, towers, tanks, and other structures associated with
 GU  facility. Both the transport and the dispersion of pollutant plumes are affected to a major extent by
 he presence of these obstacles to the flow.  Numerical models1-2 are frequently utilized to estimate the
    centrations Downwind of the release.  However, these models do not accurately account for the effect
 Cf the structures and hence produce inaccurate estimates of the pollutant concentrations.
 °     To  obtain more accurate estimates, physical modeling in a wind tunnel can be utilized. To the
 oecialist in atmospheric modeling, wind tunnel modeling is in effect "an analog computer and, compared
 *-fh digital computers (numerical models), it has the advantages of near-infinitesimal resolution and
 near-infinite memory3." The basic equations of motion are solved by simulating the flow at a reduced
  ale ^d measuring the desired quantity (concentration).   Alternatively, the layman  can consider the
 Vjnd tunnel model  to be an accurately scaled version of the processes in the real atmosphere. To utilize
 Jhis technique, a scale model of the facility of interest is constructed and placed in a boundary-layer wind
 ninnel. Then, a variety of release scenarios are simulated and the resulting concentrations measured at
  looted downwind locations.
 SC     This paper  discusses the validity of physical modeling, the method for conducting a  physical
       modeling study, and two  examples  of applications  of physical modeling for  estimating
              due  to releases of toxic chemicals.
VALJPITY OF WIND TUNNEL MODELING
       The validity of wind tunnel modeling for simulating atmospheric flows and stack gas dispersion
    received much recent attention.  With the promulgation of the EPA "good engineering practice"
    P) stack height "Sy1^0"' wind-tunnel modeling has been required to determine the GEP stack
    ht ft* many facilities4-  As P811 of a GEP stack heiiht evaluation, the wind-tunnel modeler is
    .^ to verify the performance of  the boundary layer wind tunnel  used  by performing an
^U ospheric dispersion comparability test." For this test, wind profile and dispersion measurements are
"at*?  j£ me wind tunnel without the presence  of structures.  A flat, uniform,  grassland type surface
r*>8hness is simulated  and the wind profiles and dispersion  characteristics are compared with those
"ffyuisf
                                           687

-------
 typically observed in the atmosphere.  Petersen5 showed that the wind tunnel dispersion characteristics
 compared well with those reported for flat homogeneous terrain.
        The real test of the validity of any model is a direct comparison with field observations.  A
 selection of the comparative studies which have been reported on will be cited here to give the reader
 the sense of these results.  Meroney6 compared wind tunnel simulations of 7 different field experiments
 which included 26 separate releases of dense gas. He found that the wind-tunnel modeled clouds were
 very similar in appearance and spread, traveled at the same rate, and had similar concentrations as those
 observed in the  field experiments.   Peak concentrations were generally  within  a factor of 2  of
 observations,  which is impressive considering the inherent variability  of the atmospheric  dispersion
 process. In another study, Thuillier and Mancuse7 demonstrated agreement within roughly 25% between
 wind tunnel predictions and field tracer study results for a study of neutrally buoyant plumes at the Los
 Angeles International Airport. Another study reported by Petersen8 (see Figure  1) shows the level  of
 agreement between model results and field measurements which is possible in a carefully  conducted
 study.  The figure shows a cross section through the plume for a case of stable onshore flow.  Other
 field and wind tunnel comparisons are discussed by Petersen  and Ratcliff*1'0 wherein good agreement
 between the field and the wind tunnel was found.

 SETTING  UP THE WIND TUNNEL MODEL

 Modeling Operating Requirements
       In order to obtain an accurate simulation of the boundary-layer winds and stack gas dispersion,
 certain  scaling parameters in  the wind-tunnel model are matched to those in the "real world."  The
 similarity requirements can  be obtained from  dimensional  arguments derived from  the  equations
 governing fluid motion. A detailed discussion on these requirements is given in the EPA fluid modeling
 guideline3 and will not be repeated here.  The method for converting model concentrations to full scale
 concentrations is also discussed in Snyder3.
       The  concentrations determined from wind tunnel experiments are generally representative of
 1 hour average concentrations in the real atmosphere and are  appropriate for comparison to the Short
 Term Exposure Limits (STEL) or Ceiling Limits (CEIL) published by the  American Conference of
 Industrial and  Governmental Hygienists (ACGIH).  Concentrations for averaging times of up to 1 day
 (for comparison with Time Weighted Average (TWA) limits) can be estimated using time scaling factors
 recommended  by EPA if wind, stability and emission parameters are constant throughout the  averaging
 period.  Annual average concentrations (for use in cancer risk assessments or comparison with ambient
 air quality standards) can be estimated using the  following equation:
                                           N 0
where F(N,Q) is the annual frequency of winds from the direction 8 for a wind speed category N, and
     is the concentration at receptor i for wind direction 6 and wind speed category N.
Scale Models and Wind Tunnel Setup
       For the wind-tunnel modeling evaluation, a scale model of the facility is constructed at the largest
scale  possible.  The  model is placed  in a boundary-layer wind tunnel, and surface roughness and
boundary-layer augmentation devices are installed upwind and downwind of the model so that wind and
turbulence profiles can be generated that are representative of those that would be observed in the
atmosphere.
                                             688

-------
     For each test, a simulant gas mixture is released with a relative density and flow matching that
of the desired full-scale release. The gas mixtures consist of a tracer component (methane, ethane or
propane) and carrier gas (helium, nitrogen, air, argon, CO2 or SF6) in appropriate proportions to obtain
the desired initial plume or cloud density. The concentration of the tracer component is then detected
using a gas analyzer.   Concentration measurements are typically obtained using a gas chromatograph
(F1GC) and a syringe sampling system or direct feed gas sampling system.  With the syringe sampling
system, concentrations can be sampled at up to 50 locations at the same time,  assuring measurement
consistency.  A single component hot-wire sensor is used to monitor the wind speed in the tunnel during
testing. Flow rates are monitored using either a mass flow meter or rotameter

TYPICAL APPLICATIONS OF WIND TUNNEL MODELING
     This section discusses two examples of wind tunnel modeling. The applications  involve:   1) an
assessment of the concentration at building air intakes due to accidental releases from laboratory fume
hood exhausts; and 2) an  evaluation of HF concentrations downwind of a refinery complex due to an
accidental release.

Concentrations at Air Intakes Due to Fume Hood Exhaust
     A research facility was planning to construct a new laboratory building designated PC-1 at their
site which includes several existing laboratory and office buildings. A site plan is shown in Figure 2.
Since the facility handles chemicals that are toxic or odoriferous, it is possible a storage container could
break and the resulting fumes could exit stacks on the roof through the fume hood exhaust system. The
primary objective of this evaluation was to determine the best locations for the air intake plenums and
exhaust stacks on the new building taking into account emissions from the new stacks as well existing
stacks.
     Preliminary visual tests were conducted in the wind tunnel using a smoke tracer released from
the buildings under consideration.  The tests were conducted to qualitatively assess the best locations
for exhausts and air intakes on PC-1.  Based on the visualization, the following three exhaust/air intake
options were specified for further evaluation:  Option 1 — stacks located on  the north end. and  air
intakes located on the north and northeast sides (see Figure 1);  Option 2 — stacks located on the south
end and air intakes on the south side; and Option 3 — stacks located on the north and south ends and
air intakes on the north and south ends.
     The criteria for selecting the  best option was based on  the following considerations.  First, the
air intakes on  PC-1  should be located to minimize  the concentrations  (for a  1 g/s  release of any
chemical) due to emissions from existing and PC-1 exhausts.   Second, the stacks on PC-1 should be
located to minimize concentrations at existing and PC-1 air intakes.
     Table 1 shows the  maximum measured concentrations at PC-1 air intakes  for each of the options
above due to emissions from existing exhaust vents.  At the far right side of the table, the average and
maximum concentration due to all existing exhausts is tabulated. Table  1  clearly shows that Option 2
air intake locations have the lowest average and maximum concentration due to all existing exhausts.
These air intakes are located on the south side of PC-1 and are generally the air intakes that are farthest
from most of the existing exhaust vents.  Air intakes in the roof soffit or on the second floor appear
equally effective.
     Table 2 summarizes the maximum concentrations at PC-1 air intakes due to emissions from PC-1
exhausts. The table shows that the  best option with respect to the lowest concentrations  at PC-1  air
intakes is Option 1 followed closely by Option 2.  Table 2  also shows that the concentrations due to
PC-1 exhaust at PC-1 air intakes are significantly  lower than the concentrations contributed by existing
exhausts (see Table 1). This suggests that some flexibility in locating exhaust stacks on PC-1 is allowed.
     The results presented in Tables 1 and 2 were also used to assess the potential for concentrations
to exceed health (or odor) limits for a selected set of accidental release scenarios. Based on the wind
                                            689

-------
  tunnel study, Option 2 was selected for locating stacks and air intakes for this facility. The results were
  also used to inform staff of the potential for odors if containers of certain materials are spilled in a
  laboratory.

  Determination of HF Concentrations Downwind of a Refinery Complex
        Initial HF concentration estimates for a refinery were obtained using the SLAB numerical model1
  with a surface  roughness length input of 1 cm.  The 1 cm roughness was used in the simulations with
  the SLAB model to account for model  bias towards under-prediction.  This bias was observed when
  SLAB results were compared to field data.  Reducing the surface roughness used in the model eliminated
  this bias.  Thus, guided by field comparison data and engineering judgment, a pseudo roughness value
  was  selected for the refinery application  that would  assure  SLAB  predictions were reasonably
  conservative. Since the concentration estimates using SLAB do not accurately account for the effect of
  structures and varying surface roughness associated with a refinery, wind tunnel simulations of selected
  spill scenarios  were conducted.  The wind-tunnel predicted concentrations were  used to assess the
  validity of SLAB model results.
       A 1:300 scale model of the  refinery  was constructed and placed in the wind tunnel. Three
 different HF spill scenarios (with emission rates of  3, 10 and 130 kg/s) were simulated for D and F
 stability with wind  speeds of 3.5 and 6 m/s.  No attempt to replicate the refinery's heat release was
 made. Figure 3 shows the wind tunnel and SLAB predicted ccnterline concentrations versus downwind
 distance for the 3 kg/s release, a 3.5  m/s wind speed and D stability.  The figure shows that  the wind-
 tunnel predicted concentrations arc significantly less than the SLAB model predictions near the release
 with the expected trend for the wind-tunnel and SLAB model estimates to converge at some distance
 beyond 3 km.
       Also shown in the figure is an emergency planning guideline value (EPG) of 50 ppm.  The EPO
 is the maximum airborne concentration below which it is believed that nearly all individuals could be
 exposed for up to 1 hour without experiencing or developing life-threatening health effects. The figure
 shows that for a 3 kg/s release, the EPG level  will extend out to 2 km based on the wind tunnel results
 and out to 5 km based on the SLAB model.  Hence, the wind-tunnel model demonstrated that evacuation
 zones would be significantly smaller  than predicted by the SLAB model.

 CONCLUDING REMARKS
       Physical modeling  using boundary layer wind tunnels represents a valuable technology for
 accurately estimating concentrations  due to airborne releases of toxic  compounds in complex flow
 regimes.

 REFERENCES
 1.     D.N. Blewitt, J.F. Yohn, and D.L. Ermak, "An Evaluation  of SLAB and DEGADIS Heavy Gas
 Dispersion Models Using the  HF Spill Test Data,"  presented  at the AIChE sponsored International
 Conference on Vapor Cloud Modeling. Cambridge, MA, November 2-4, 1987.

 2.     U.S. Environmental Protection Agency (EPA), "Guideline On Air Quality Models (Revised),"
Office of Air Quality, Planning and Standards  Research, Triangle  Park, NC, EPA-450/2-78-027R, July
 1986.

3.     W.H. Snyder, "Guideline for Fluid Modeling of Atmospheric Diffusion," USEPA, Environmental
Sciences Research Laboratory, Office of Research and Development, Research Triangle Park, NC, Report
No. EPA600/8-81-009, 1981.
                                            690

-------
4     J  Halitsky. R.L.  Petersen.  S.D.  Taylor, ind R.B. Lantz, "Nearby Terrain  Effects in •  Good
Engineering  Practice  Stack  Height Demonstration."  79th Annual Meeting of Air Pollution Control
Association,  Minneapolis, MN. June 22-27. 1986.

5.     R.L.  Petersen. "Dispersion  Comparability of the  Wind Tunnel  and Atmosphere for Aditbalic
Boundary  Layers  with Uniform Roughness." presented  at Fifth U.S.  National Conference  on  Wind
Engineering. Texas Tech University, Lubbock, TX, November 6-8. 1985.

tv     R.N.  Meroncy. 'Guideline for Fluid Modeling of Liquefied Natural Gas Cloud Dispersion," Vol.
I and Vol. II: Instruction Guide and Technical Support Document." Gas Research Institute Report No.
GRI 86/0102.1 and 86/0102.2, Gas Research Institute, May 1986.

      R.H.  Thuillier, and R.M.  Mancuse. 'Building  Effects on  Effluent Dispersion from Roof Vents
at Nuclear Power Plants,  final report  to Electric Power Research Institute by SRI International,  EPRI
Report No. NP-1380,  1980.

      R.L.  Petersen, 'Wind  Tunnel Investigation on  the  Effect of Platform-Type  Structures on
Dispersion of Effluents from Short Stacks." JAPCA. Vol 36. No. 12. December  1986.


-------


*
Jp -

' -Kl'i.1*1 *'
S2£
' v_.
Figure 2.      Plan view of a laboratory site modeled in the wind tunnel showing exhaust locations.
                                                          « 3.5

                        5 '«>
                                                  ' 300
                                                        2000

                                                        (m)
                                                                 4000    1C4
Figure 3.      Wind tunnel and SLAB predicted HF concentrations  versus downwind distance for a
              3 kg/s release. 3.5 m/s wind speed, D stability and various simulated wind directions.


-------
'able 1,       Summary of concentrations (1 g/s enrissioiv rate) al PC-1 air intakes — emissions from
               existing building exhausts.
	 •^OBSESS
Receptor
Inuke IDKo.
kwrtoiii
Maximum Cancenuuua [toe «e
25-EF4
25-EF2
80-COO
80-BSK
10-F7
35-EFI
60-EF1
Indicated Extant!

20-EP17
20-HE92
OtgAn1)
20-INC
30-HE3

20-HE14
60-EF5
Aw
•ma
Mix
  Option 1
            40,43     74.9   87.1    B0.4  106.7347.1   109.6   S4.4   l«.6   2214  J94.1  «5.5   265.1  421.3 21 W 485.3
           31,41.41   IOS.8  11J.6    812   a.6 M5.1   137.9   14.J   20L9   279.1  lSa«  »*6    79,1  119,4 152.1355.1
   Rocf'S
             39      42J   44j    27.9   33.8  80,0  14ft9    7.1    97.9   115,0  112.4   933    71.9  103.3 74.6140.9
                    51.6   45.4    30J   36.8 113.4  167,5    7.4   114.6   115.1  125.6  141.1    85.1    127 89.3167.3
    '•* * 825.26,43    74.9   87.1    61.8    81.3 347.1   109.6   J4.4   194.6   228.4  294.1   4B&6   265.1  4223 208.3 48«
           31.39,42   105,8  103.7    38.4    35.7 355.1   140.9   14.1   202.9   258.5  \6U  224.6    83.1  119.4143.4355.1
          •^u	  	                                    . 	      	^^—^^•^^^^^^•••••••••i^^^^^^^^^^^^^^^^M
Tablc 2-       Summary  of maximum  concentrations  (1 g/s emission  rate)  at PC-1 air intakes
               emissions  from PC-1 exhausts.
            Description
   Locations
                                                                           Maximum Concentration
             Option 1
             Option 2
             Options
2nd fl-N and E
 Roof-N and E

    2nd fl-S
    Roof-S

2nd n-N and S
 Roof-N and S
 4.5
 4.4.

 13.0
 8.4

92.9
95.1
                                                   693

-------
    DEPOSITION  MODELING  OF  CHLORINATED  DIOXINS
                                              AND FURANS
                                     Matthew B .G. Pllklngton and Stephen G. Zetnba
                             Cambridge Environmental Inc., 56 Charles St. Cambridge, MA 02141

 ABSTRACT
    Chlorinated dioxins and furans have different properties which influence their deposition to soil. Typically, dioxin and furan
 deposition rates are calculated using characteristics of tetrschlorodibenzo-^-dioxin (TCDD) as representative of ihe family of congeners
 even though TCDD frequently constitutes a small component. Vapor and particle phases are rarely distinguished, and some
 assessments fail to consider both wet and dry deposition. A method  is developed for calculating total deposition considering these
 factors, using measured ratios of each congener in vapor and particle phases.  Wet deposition is modeled using congener-specific wash
 out ratio* measured in rainfall.  Dry deposition is estimated as the sum of particle and vapor deposition.  The CARB procedure is used
 to calculate particle depositions, while vapor deposition rales are estimated from empirical measurements of representative organic
 compounds. Average dry deposition velocities for congeners arc weighted by relative proportions present in vapor and particle phases.
 The sum of wet and dry deposition fluxes is converted to TCDD toxic equivalents (for use in risk assessments) by weighting congener-
 specific estimates by  toxic equivalency factors. The calculated dry deposition velocity for TCDD is shown to depend on the particle
 size range, assuming dioxins and furms are attached to panicle surfaces.

 INTRODUCTION
    Chlorinated dkixins and fuians have been shown to be extremely toxic and carcinogenic in rodents7.  Although ihe debate
 continues over their potential  to adversely affect human health, current methodologies to estimate human toxicity from animal studies
 suggest that dioxins and furans will continue to be pollutants of concern to human health.  Like many other hydrophobic compounds,
 dioxins and furans tend to accumulate in  the fatty tissues of animals.  As such, the most significant exposure routes are typically
 estimated to be those associated with bioaccurmiLaiion within the food chain.  Risk assessments of emission sources of dioxins and
 furans attempt to trace compounds such as dioxin from their point of origin through all compartments of the environment Given the
 dearth of empirical data, the fate and transport of chemicals such, as dioxins and furans relies on modeling.  Since media such as soil,
 plants, and water serve as the major  vehicles of exposure to both animals and humans,  most critical models for ambient sources are
 those that estimate the rates of deposition of dioxins and furans from the air.  This paper addresses  techniques for modeling deposition
 of dioxins and furans.  The estimates presented herein were part of an exposure assessment of the emissions from a utility boilei
 designed to bum scrap plastics and other  materials. Similar to other detailed deposition studies, both vapor and particle-bound phases
 of dioxins and furans were differentiated. In addition, both wet (via pieciptation) and dry (via settling and adsorption to surfaces)
 depositions were examined. For the latter component, the manner in  which the  particle  size distribution is treated has important
 implications in the assessment of overall deposition of dioxins and furans.

 EMISSION RATES  OF DIOXINS AND FURANS FROM AN INDUSTRIAL COMBUSTOR
    We performed an exposure assessment at a facility in the eastern  U.S. that was burning waste plastics from an industrial process to
 generate electricity. The plant burned 13  tons of waste plastics a day in a batch fed process.  The pollution controls consisted of a wet
 venruri separator and  a packed bed with scrub water flowing counter-current to the exhaust. The combuslor was situated on a hill and
 the stack height of the facility was 18 m.  The surrounding area consisted of pasture, woodland, and urban areas.  Emissions of
 chlorinated dioxins and fiaans were estimated from slack testing of all letta- through ocla-chlorinated congeners/isomers.  Averaged
 results from three test periods are presented in Table 1. In general, more highly chlorinated congeners were found in greater
 abundance, and suck-gas concennationa of furans were greater lhan those of dioxins.  We converted these data to TCDD equivalents
 using I-TEF/89 toxic equivalency factors'. The emission rate of TCDD equivalents (summed over all dioxin and furan congeners) was
 estimated to be 96 ng s~'.
Tablet  Results of Industrial bofler emlsrion testing (average of 3 tests)
~'  '   ~                 I—TEF*   VBiaeLon ]
                                                ng •"'
2,3,7,8-TCDD
 other TCOOi
1,2,3,7,8-PCDD
 other PCDDs
1,2,3,4,7,9 Hex* CDD
1,2,3,6,7,3 Hex* CDC
1,2,3,7,8,5 H«x» CDD
 other Hexa CDDs
1,2,3,4,6,7,8 Hepta  CDD
 other Kept a CDDs
0«a-CDD
1
0
0.5
0
0.1
0.1
0.1
0
0.01
0
0.001
2.27
31.45
ii.se
84.51
l.M
14.52
26.86
123.97
103.64
115.81
237,02
2.27
0.00
5.79
0.00
1.00
1.45
2.69
0.00
1.04
0.00
0.24
                                                           Tima
2,3,7,8-TCDF
 other TCDFa
1,2.3,1,8-PCDF
2,3,4,7,8-PCDF
 other PCDFj
1,2,3,4,7,6  Hexa  CDF
1,2,1,6,7,8  H»*  CDF
2,3,4,6,7,1  Hexa  CDF
1,2,3,7,8,9  Hexa  CDF
 other Max*  CDFi
1,2,3,4,6,7,8  Hepta CDF
1,2,3,4,7,8,9  Hepta CDF
 other Hepta CDFs
Octa-CDF
                                                                                    X-TW*
0.3
0
0>05
0,5
0
0.1
0,1
0.1
0.1
0
0.01
0.01
0
0.001
CHiuian

KUI
51.09
343. SI
41.53
56.7
180.41
187.54
1.04.89
106.01
5.31
594.18
429.18
50.29
278.01
336.42
rate a ng m'
TCDD
•qvlva.
5.11
0.00
2.08
28.35
0.00
18.75
10.49
10.80
0.53
0.00
4.29
0.50
0.00
0.34
                                                        694

-------
Air Dbpmlon Modetlng and Particle Sire Distribution
    Air ooncentrations of TCDD equivalent* were modeled using ihe Industrial Source Complex Short nd Long Term (ISCST and
ISCLT) models, Weadter diu were obtained from a nearby sirport located 10 miles north of Ihe facifily. The maximum modeled av
"•Kentration (at a receptor heighi of 1 m above flic ground) off-site of ihe fscfliry property was found to be 21 HT" g TCDD
'qtivalents m-'.  The distribution of the various d»»tn and farm congeners (not shown) was assumed to be proportional K> the
dwnbution of emission raut (T«ble 1).
    The particle size distribution of ihe stack gas was determined using a cascade tmptdof. The measured particle sue distribution is
tinted in Table 2. These data exhibit » bg-lineH relationship between a particle size and the cumulative mass of panicles that b
~~  "  than that pvtick tize; this phenomena it expected for the range of particto djimeters tested The sk^pe of *• correlation
        !°U  nltBK* ft •MlWj^lt tftMSffttUffA.
««Ctt*«d ^ relttive proportions of PCDOPCDFs that ue found on parried .to and « the v^w oh^ al saibto IBnpenWTO^
•*eie ratXM tie given in Ttble 3, and «* used to diianguiih dry deposition of both pmicte-bmind and vapor f«tw of PCDDfPCDFs.
    We aimme that dioum and funm may deposit via three mean*: dry deposition of particles, dry deposition of vapon, and wet
fepMition of particles,* The general form of the equation used to estimate the mass deposition r*tt D (mass per unit •ret per oral
"•w) * the product of the unbieM concentration c* (mass per volume) and the deposition velocity v, (length per tone):

                                                      D'W                                             *^W

"* foltowinj sections esonute deposirion velodoej for each of ihe Aree mechtniimi.
                    Particles.  I^partxk-boniidPCDD/rKn^oneorttiefbrniationroecha^
   «urface of fly ash particles'. In addition, as the emission stream of hot gues and fly ajh cools, POXVPCDF vapor condewei on
   nrfaces of particles of many tizes. Therefore, we treat particle-bound dioxini u bein| distributed evenly over pMtJcJe' svfsce*
          iwnraedtobe^erioJ  The cancenmtion of TCDO on psrticlet of given size is therefore detenained by weighting the
                      were estimated using procedure* published by the California Air Resources Bostd (CARB) for the
            rates of aerosol emissions from stationary sources1 *.  A putick of a Dankulaf size win scale, m the absence of
ptecV«*itii». with a dry depot ition rate D^ (mass pe» unit trea per unil lime) estinuted by:
* % is a weighted deposition (or *«nling) velocity of the panicle. In the CARB procedure, the deposition velocity depends on
 meteorological conditions (wind *peed. atmospheric stability, «nd tempennw). local ttrrnn. and particle characteristics such n
**1"1 »»                                                                           
-------
  TCDD-carrying particulars as a group is then the sum of individual deposition velocities of each particle siz«
                                                                      VF
                                                                                                                   Eqn,{3)
 where A^ is the total area of the particles present of a specific size. The ratio of the area to the volume of a sphere of diameter 4 is
 6/d, and so the total area of a group of panicles, all of diameter d, and total combined man (Mf) is:
                                                                ,  6
                                                                                        Eqn.(4)
 where p is the density of the particle. M, is the amount of mass for that range, for example panicle size of 0.42 urn has a m«M
 assigned to it of 24.5% of the total mass of the collected particles. This is obviously an overestimate, as there are panicles mat must
 be smaller than  0.42 urn. There is also a similar problem in assigning a panicle representative diameter to the larger end of the scale.
 Particles greater than 11  urn in diameter account for 33.6 % of the mass. An upper end was chosen of 30 pm based on measurements
 at the Hempstead Resource Recovery Facility on Long Island, NY1. The weighted dry deposition velocity was estimated to be 0.24 cm
 s~' using the particle distribution in Table 1 and the deposition velocities estimated by the CARB procedure.

    Dry Deposition of Vapors.  The CARB procedure can model deposition velocities  for particles in the region of 10"* to 10* pm,
 whereas a TCDD molecule is of the order 10~J pm in diameter.  Various problems arise when modeling vapor deposition that the
 CARB procedure does not address.  At the molecular level the shapes of dioxins deviate from a spherical form,  and will be
 approximately cylindrical.  Deposition velocities for I, and SO, have been studied  extensively, but the values measured are so widely
 scattered that they cannot be predicted with confidence'. Sehmel published a review of measured vapor deposition velocities that
 includes some hydiophobic compounds that have molecular weights reasonably similar to TCDD. The closest is methyl iodide'
 (molecular weight 166), which has a deposition velocity onto grass of 0.03 cm «'". Though the molecular weights differ, at very small
 molecular diameters (less than 0.1 pm), gravitational settling velocities are  small compared to deposition velocities. Mass transfer at
 the air-ground interface is controlled by Brownian diffusion if the solubility of the gas in water is low, as is the case for both methyl
 iodide and dioxins/furans. Therefore, we assume a dry deposition velocity (x^^,,) of 0.03 cm s"' for dioxins/furans.
    Table 3       Parameters used to estimate deposition
                                  IB        Jhaaunfc en
                                 phen in   partial••
                                            in
                                            TCDD aquin.
 2,3,7,8-TCDD
 other  TCDD3
 1,2,3,7,8-PCDD
 other  PCDDs
 112,3,4,7,8  Hex CDO
 1,2,3,6,7,8  Hex CDD
 1,2,3,7,8,9  Hex CDD
 other  Hex CDD*
 1,2,3,4,6,7,8  Hep CDD
 other  Hep CDD»
 Octj-CDD
 2,3,7,8-TCDF
 other  TCDFa
 1,2,3,7,8-PCDF
 2,3,4,7.8-PCDF
 other  PCDFs
 1,2,3,4,7,8  Hex CDF
 1,2,3,6,7,8  Hex CDF
 2,3,4,6,7,8  Hex CDF
 1,2,3,7,8,9  Hex CDF
 other  Hex CDF«
 1,2,3,4,6,7,8  Hep CDF
 1,2,3,4,7,8,9  Hep CDF
 other  Hep CDFs
0«»-CDF
4.7871
0.0000
11.0975
0.0000
1.3328
1.9440
3.5866
0,0000
0.4387
0.0000
0.0906
10.6446
0.0000
4.0576
55.4351
0.0000
28.2100
15.8102
16.2467
0.8011
0.0000
1.3629
0.1539
0.0000
0.1499
0.0000
o.oooo
1.0364
0.0000
0.7549
1.1012
2.0316
0.0000
1,7195
0.0000
0.4039
0.0000
0.0000
0.2639
3.6055
0.0000
10.891
6.1040
6.2725
0.3093
0.0000
7.9100
0.9933
0.0000
0.5534
                                   rnotiou of e*ch ii	
                                   preeant  in either Taper
                                   or pertlale pbeee «t
                                   •pproxiaafcelv
vtpor
1.0000
1.0000
0.9146
0.9146
0.6384
0.6384
0.6384
0.6384
0.2033
0.2033
0.1832
1.0000
1.0000
0.9389
0.9389
0.9389
0.7215
0.7215
0.7215
0.7215
0.7215
0.1470
0.1470
0.1470
0.2132
•utlol*
0.0000
0.0000
0.0854
0.0854
0.3616
0.3616
0.3616
0.3616
0.7967
0.7967
0.8168
o.oooo
0.0000
0.0611
0.0611
0.0611
0.2785
O.J785
0.2785
0.2785
0.2785
0.8530
0.8530
0.8530
0.786*
                                            N*eh Out tatie
                                            
-------
 an<^               R is the average rainfall per unit time.

     The wet deposition velocity depends on ratios of the different congeners present in the emission stream.  These ratios can be
 calculated from the emission data in Table 1.  The wet deposition velocity was calculated using the annual rainfall of 1.25 m yr-'. for
 the local area taken from the US Statistical Abstracts".  Since PCDD/PCDFs have very low solubilities in water, we have assumed that
 on]y the paniculate phase of the PCDD/PCDFs are washed out of the plume. Using equation (5) and these data, we obtain a value of
 0.13 cm s'1 forv4w/r

     _A Summary of Deposition of TCDD  Equivalents.  The sum total of deposition of TCDD equivalents was estimated to be 2.3 x
 10"" g m~V.  Figure 1 presents a distribution distinguished by the three mechanisms of deposition and the chlorination of the
 PCDD/PCDF congeners.  As is obvious, furans contribute more to the deposition of TCDD equivalents than do dioxins.  Also, dry
 deposition processes (the sum of vapor and particles) contribute more than wet deposition;  the processes of dry particle, dry vapor,
 and wet particle depositions account for 45, 20, and 35%. respectively, of the total deposition estimate.

 A Discussion of the Particle Size Distribution and Dry Deposition Velocity
     The particle size distribution directly affects the deposition velocity.  Widely differing results can be obtained for the average
 particle deposition velocity by: (1) assuming the relationship between logjparticle size range) and log,0(cumulative mass fraction) is
 linear and (2) aggregating the mass of very small and  large particles at lower and upper cutoff points of particle size.  The dry panicle
 deposition velocity of 0.24 cm »~' was calculated using a cutoff at 0.42 urn for the lower end of the panicle size distribution. Figure 2
 js a plot of the sensitivity of the averaged deposition velocity to the choice of the lower particle size cutoff.  For each point, the lower
 particle size cutoff is  assumed to be the particle size plotted on the z-axis, and the value of average deposition velocity plotted on the
 ,-axis is calculated by assuming that aU of the mass of panicles smaller than the cutoff value is aggregated at the cutoff value.  As
 could be anticipated, the curve generally follows the shape of the dry panicle deposition curves. Starting with values at the right end
 of the graph, adding the effects of smaller panicles (by moving the cutoff point to the left) initially decreases the average
 deposition. Very small particles, however, have deposition velocities much higher would be predicted by gravitational settling,  and the
 deposition velocities of very small particles actually increase as particle size decreases. Consequently, as cutoff points decrease below
 0 1  urn. the average deposition velocity increases.
     This phenomena has important consequences for estimating average deposition velocities  from measured particle size distributions.
 Since these distributions frequently have empirical cutoff points of the order of 0.1 urn, estimations of average deposition velocity that
   negate all small particles at the lower cutoff point may seriously underestimate average deposition velocity.
     fl,e sensitivity  of the dry deposition rate to the particle size distribution is both critical and problematic.  As shown in Figure 2,
 the  total rate of dry deposition may  be largely  strongly dependent on  the distribution of dioxins and furans on small particles.
 Unfortunately, however, conventional analytical techniques provide no information on the frequency of these small particles.  Some
 hysical intuition of the likely characteristics of small  particles is appropriate. Empirical observations provide a cumulative measure of
 the I  mass of dioxins and furans thai are contained on all particles below a given size. Assuming spherical particles of radius r, the
 mass frequency fjr) can be expected to be proportional  to the number density gjrf* and the particle mass, which  is proportional  to
 j jjvided by the total integrated mass of panicles:
                                                                                                                      Eqn. (6)
Furthermore, cumulative mass fractions $„ such as those presented in Table 2 can be expressed mathematically as integrals of the mass
frequency fjr)-
                                                                g
                                                       *m(r) ~ fy,,(r)dr                                             Eqn. (7)


whet* R is the particle radius below which the cumulative mass is contained  As discussed previously, the log-linear nature of the
    irical $ m(f) °' Table 2 is well-represented by a power law:

                                                         4>,,(r)«ar'                                                Eqn. (8)
    i  i
    *fhe number density gjr) is expressed as the probability that the radius of a particle in the distribution of all panicles will lie be
    -en • value r and r + dr. where dr is an iniinitesimally small increment.
                                                              697

-------
 which, combining the above equations, implies that:

                                          /_(r)-r*-'       and       «.(r) - r*"

 Given a "best-fit" value of 0.3 for the coefficient Jt, the empirical profile of Table 2 suggests that the number density of particles will
 vary inversely with particle radius (to a power of 3.7).  This represents a diverging condition in which the number of particles can be
 expected to be very  large as the panicle size becomes small.  In fact, as the particle size approaches zero, the number density of
 particles would be infinite.  As discussed previously, however, physical limits preclude the extrapolation of the distribution to zero
 particle size.  The importance of small particles, especially those smaller than can be measured by conventional analytical techniques,
 is emphasized — the particle size distribution suggests that there will be many more small panicles than large particles. Thus, to the
 extent that surface weighting emphasizes the importance of small particles, it is not surprising that the  average deposition velocities
 shown in Figure 2 are strongly dependent on the assumed presence of small panicles.

 CONCLUSIONS
     Our estimates of dioxin and  furan deposition suggest that 65% of total deposition is due to dry processes and 35% is due to wet
 deposition of particles.  Since these calculations were performed at the location of  the maximum modeled ground-level air
 concentration, these proportions  could be different closer to the source wherein wet deposition scavenging of the plume can be
 expected to be more important  The results of dry deposition modeling indicate that the deposition of particles is more important thin
 the deposition of vapors.  Given the importance of dry panicle deposition, the estimation of the dry deposition velocity of particles is
 of critical importance and may depend strongly on the frequency of small particles, the distribution of which are not ascertained by
 current analytical techniques. Consequently, we suggest that future research be devoted to characterizing the distribution of the small
 particles that can greatly influence deposition velocity.

 REFERENCES

 1. California Air Resource Board, Deposition rate calculations for air toxics source assessments. Air quality modeling section,
 technical support division. 1987.

 2. B.E. Crocs,  SEHMEL - FORTRAN 77 program, a program that calculates dry deposition using Sehmel's curves. Air Resources
 Board. Sacramento, California, 1986.

 3. CS], Draft environmental impact report (EOEA No. 7781) for the East Brideewaier integrated waste disposal system. 1990.1:6-
 136.

 4. B.D. Eitzer, and RA. Hites, "Concentrations of dioxins and dibenzofurans in the atmosphere".  Int. J. Environ. Anal Ghent.
 27:215-230 (1986).

 5. U.S.EPA. Interim procedures  for estimating risks associated with exposures to mixtures of chlorinated dibenzo-p-dioxins and
 dibenzofurans (CDPs and CDFs) and 1989  update.  EPA/62S/3-89/D16, 1989.   "~

 6. R.V. Hoffman, GA. Eiceman, Y. Long, M.C. Collins, and M. Lu, "Mechanism of chlorination of aromatic compounds adsorbed on
 the surface of fly ash from municipal incinerators", ESAT 24(11):1635-1641 (1990).

 7. R.J.  Kociba, D.G. Keyes, J.E. Bower et ah,  "Results of a two-year chronic toxicity an oncogenicity study of 2,3,7,8-
 tetiachlorodibenzo-p-dioxin in rats". Toxicol. Appl. Pharmacol. 46(2):279-303 (1978).

8. G.A. Sehmel, and W.H. Hodgson, Model for predicting dry deposition of particles and gases to environmental surfaces. PNL-SA-
6721, Battelle Pacific Northwest  Laboratories, Richland. Washington. 1978.

9. GA. Sehmel. "Attnos. Environ. 14:983-1011 (1980).

 10.  US Department of Commerce, bureau of the census, Statistical Abstracts of the United States. (108th edition), Washington, DC,
 1987.
                                                           698

-------
                         Contribution by
                            of TCDD TEFs, by congener'class
          I.''
D - Dtoxin
F- Furan
Number. Number of Cl
            !
    'in    0.8-
    ? - 0.6-



    <3    0.4-



          0,2-
                      4-0    5-D    6-D    7-D    8-D    4-F     5-F    6-F    7-F    8-F
                                               Congener class
                     • Wet (panicle) Bl Dry (particle) ^ Dry (vapor)

Figure 1 Contribution by congener to deposition of TCDD TEFs, by congener class.
          0.01
                                          Particle Size Range
                                  Deposition Velocity, Surface Weighted
                 0.10                       1.00
                 Particle size range, to 56 micrometers
                                                                                           10.00
   Figure 2
Average deposition velocity vs. lower cutoff particle size
                                         699

-------
 Further Development of an Interactive Air Transport Model for Superfund Site Applications

 Kevin T. Stroupe
 Pacific Environmental Services, Inc.
 3708 Mayfair Street, Suite 202
 Durham, NC 27707

 Jawad S. Touma
 Office of Air Quality Planning and Standards
 U.S. Environmental Protection Agency.
 Research Triangle Park, NC 27711


 For Presentation at the International Symposium, Measurement of Toxic and Related Air Pollutants, Co-
 Sponsored by Atmospheric Research and Exposure Assessment Laboratory (USEPA) and the Air & Waste
 Management Association, May, 1992, Durham, NC.

 ABSTRACT
        TSCREEN is an IBM PC computer program that provides, by use of interactive menus and data entry
 screens, simplified screening methods for determining maximum short-term ambient air quality impact from
 various  well-deniied releases of toxic air pollutants from Superfund sites and other sources. Recently,
 TSCREEN was revised to include an additional scenario, estimation of ambient air quality impact on elevated
 receptors and complex terrain, more extensive on-line help, and new interactive menus and data screens.
 TSCREEN implements the methods outlined in an EPA workbook of screening techniques  for toxic air
 releases using a logical problem solving approach.  An extensive help system, text editing, and graphical
 display capabilities are also provided to guide the user throughout the program. The purpose of this paper
 is to describe the changes and to present an example in which TSCREEN would be used.

 INTRODUCTION
       Air quality dispersion modeling analysis is important when evaluating the impacts from various
 alternatives for clean up activities at Superfund sites.  This analysis is  frequently required  for planning
 purposes to determine compliance with ambient standards prior to actual clean up and must depend on
 estimated emissions and ambient concentrations rather than on measurements.  TSCREEN, a model for
 screening toxic air pollutant concentrations has been developed as a tool  for this purpose based on release
 scenarios and methods  described in a workbook (EPA, 1988). TSCREEN is an IBM PC-based interactive
 system that allows the user to select an emission rate and the appropriate screening level dispersion modtl
 for each scenario in a logical problem solving approach.

       TSCREEN consists of a front-end control program with many interactive menus and data entry
 screens.  As much information as is logically and legibly possible is assembled onto unique data entry
 screens.  All requests for input  are written in clear text. Extensive help screens are provided to minimize
numeric data entry errors, and default values are provided for some parameters. The user is able to return
 to previous screens and edit data previously entered.  A chemical look-up database and an on-line calculator
 are  also available.  Once the nature of the release is determined, the user must specify the emission rate.
For some scenarios, extensive references to EPA methods are provided, while for others, a specific method
for calculating the emission rate is given. Density checks for the release are performed to determine which
 dispersion model is selected. Data necessary to execute  that particular model is then requested in a logical
format.  Once the model is executed, the concentrations are  calculated and then tabulated in a clear and
legible manner, and an easy to read graph of concentration versus distance is provided. The printed text
 and graphical output can be sent to a variety of printers and plotters through built-in software; minimum
user interface is required.
                                              700

-------
        Maximum short-term ground level concentrations in TSCREEN are based on three current EPA
 screening models (SCREEN, RVD, and PUFF)  that are embedded in the TSCREEN model.  SCREEN is a
 Gaussian dispersion model applicable to continuous releases of participate matter and non-reactive, non-
 dense gases that are emitted from point, area, and flared sources. The SCREEN model implements many
 of the single source short-term procedures contained in the EPA revised screening procedures document
 (Erode, 1988). This includes providing estimated maximum ground-level concentrations and distances to
 the  maximum based on a pre-selected range of meteorological  conditions. In addition, SCREEN has the
 option of incorporating the effects of building downwash. The RVD model (EPA, 1989) provides short-term
 arnbient concentration estimates for screening pollutant sources emitting denser-than-air gases and aerosols
 through vertically-directed releases. The model is based on empirical equations derived from wind  tunnel
 tests and estimates the maximum ground level concentration at plume touchdown at up to 30 downwind
 receptor locations.  The PUFF model (Petersen, 1982) is used where the release time is finite but smaller
 than the travel time (i.e., an instantaneous release). This model is based on the instantaneous Gaussian puff
 equation and is applicable for neutrally buoyant non-reactive releases.

        TSCREEN is programmed in FoxPro™, a software development system, to eliminate several of the
  omplexities in the previous version.  The new TSCREEN (version 2) also includes  an additional scenario
 for air strippers (used in Superfund site remediation applications), a new ability to estimate ambient air
  uality impact on receptors on elevated or complex terrain, and new expanded on-1  ine help. The purpose
  f this paper is to describe the new changes and to present an example in which TSCREEN would be used.

 TSCREEN DESIGN
        In  designing TSCREEN,  attention was  given  to  ease  of use  and low development  costs.
   nlementing the front-end control program was a key element in the design of TSCREEN. The nature of
  front-end program is such that it must be able to execute a number of diverse external programs, i.e.,
dispersion models which are left intact.  Since  these external programs may require large amounts of
*****      .   £J__fc ....J nv«vA*>am mtieF minimJ9A fHa amrtitnf f\f mA-mst***? it- H«A«  Gnj&M^I **f ,•»***«.****** •• H!MH
  ernory, the front-end program must minimize the amount of memory it uses. Speed of execution is also
m'tical in gaining user acceptance. Finally, TSCREEN contains an extensive chemical database library to
h lo provide the variables needed for some of the calculations, A database program is the logical choice for
such an application.

        The front-end program in TSCREEN was written in the FoxPro™ programming language, a superset
  f th« dBASE language family suitable for PCs running MS-DOS™.  The primary purpose of a  dBASE
JanKUaS* is database manipulation, but it can also be used for general purpose programming. The reasons
ft using thi» system are: 1) a user interface which facilitates the debugging process, and as a result, reduces
 he  development cost; 2) pull-down menus and windows which require minimal programming effort to
   ate' 3) built-in functions for database manipulation, and as a result, much less code is required to create
*h   chemical database in TSCREEN; 4) memory management capabilities that allow TSCREEN to run on
   chin«* with less random access memory (RAM) than was possible for the earlier version of TSCREEN that
013  primarily written in BASIC;  and 5) the ability to release most of the TSCREEN front-end program from
Wniory before it executes the dispersion models.  The main disadvantage of this system is the size of the
JjJ   that a user needs to run a system. The system is distributed with two run-time libraries. These are files
 K f contain the implementation of functions that are called by the program. One of these libraries is over
  no kilobyte* (K) and the other is close to 1 megabyte (MB).  Since TSCREEN is distributed through the
  rRAM bulletin board, the executable file and the libraries are still large and are costly for the long distance
          line user to download.
        This example traces the modeling of a release event from the selection of the appropriate scenario
    .   interpretation of model results.  In this example, chlorine gas is released from the vapor space of a
t0   tirized tank through a 2.8 cm diameter hole while being removed from the Superfund site. First, the
pfe5  rio applicable to this type of release is selected from the initial menus shown in Figure 1. This example
Jcenan     continuous gaseous release from a pressurized vessel.  If the user selects the Help key, TSCREEN
      rovide a graphical depiction of each of the scenarios listed to assist the user in the selection process.
                                              701

-------
                                   Figure 1.  Scenario Selection Menu*
                File
                            thltill  Fern"of fteleaae
                              jlate  Hitter Relta
                                                Chemical Database    Quit
                                     GII«XM Ret eaW Type
                                                            Workbook Scenario
                     Flared Stack EnUelona                       - 4,4
                     Stacki. Venti, Conventional Point Source*      - 4.1.2.4.6
                     EiiilHiiiSfsM£lS^i^iSiS™                        I?*JT?"
                     Hut tTple "Fugl tYve'Sourcet*
                     Land Treatment FacfUtlet
                     Hunlelpil  SoUd V»te Land Fills
                     Pettlclde/HerWcide Application*
                     Discharge* fro* Equipment Openings
               HeLp    /Scroll Vertiul Kenua     <«->/<-*>Scroll Horizontal Htnu
               /Lttter»Select Menu I ten   Ex(t Current Menu  <*  (
                                               702

-------
                            Figure 2. Emission Rate Input*
         	Gastou* leak* from Tank*, Pipes,  R«lttf Valve*  • Scenario 4.5
          SOURCE PARAMETERS - Page 1  of 3
          Enttr • unique title for this d»t«'§ model run:
                             Vapor Ventfng OUcharge Rate ->  1259.933 g/s
             Ratio of Specific Heat at Constant Pressure to
              Specific Heat at Conetant Temperature (Cp/Cv) •>
                         Exhaust Gat Molecular Weight (Hw) •>
                                   Releaae Pressure (Pt) ->
                                    Anblent Pretaure (P) ->
                                 Storage Tenperature (Ta) ->
                            Dfaneter at Retea»e Point  ->
          FLOU CHARACTERISTIC
                                      Flow CharacterUtfc •>  Critical
Calculate vapor pressure of chlorine :

                      lnPv  •  InPj  +
where Pv is vapor pressure at T( (atm), Tj, is boiling temperature (10, Pj is vapor pressure at
normal boiling point at atmospheric pressure, lnP1-0, and AL^p is latent heat of vaporization at
boiling point (cal/g-mole).

If the vapor pressure is greater than the release or storage pressure, then TSCREEN cautions the
user that this may be a two-phase release (i.e., aerosols maybe formed upon depressurization) which
might be modeled more appropriately with another scenario.  In this example, the vapor pressure
(5.0 atm] is less than the release pressure (6.8 atm) therefore this is not a two-phase release. See
Figure 3 below.

                             Figure 3. Vapor Pressure Inputs
               Gateous leaks froa Tanks, Pipes, Relief Valve* • Scenario 4.5
          SOURCE PARAMETERS -  Pag* 2 of 3
          VAPOR PRESSURE
                                        Vapor Pressure -> 5.063951  at*
            Letent  Heat of Vaporization at  Boiling Point  -> *8MH cal/g-anle
                              Boiling Point Tenperature  ->
Determine if the release is passive or dense (see Figure 4). First, a buoyancy check is performed as
follows.  If:                        T        T
                                     *   a    '
                                        *  283  '
then the release buoyancy is positive.  However, if the buoyancy is negative then a Richardson
number check is used to determine if the release is passive or dense. If the Richardson number &
30, then the release is dense, and TSCREEN selects  the RVD model.  Otherwise, the release is
passive and the SCREEN model is selected.
                                         703

-------
 6.       Determine the volume release rate (V) (m3/s):
                                     V  -    5   .0224

 7.       Calculate Richardson number (Ri):
                               Ri
2722
                                             28.9  T.
                                                       -   1
                         U3  D
        where D is diameter at release point (m), and U is wind speed (m/s).

        In this example V = .058 (m3/s) and Ri = 8270.  Since the release is dense, TSCREEN selects the
        RVD model.
                                        Figure 4.  Density Checks


                 	 Gaseous Leaks from Tanks, Pipes, Relief Valves - Scenario 4.5
                  SOURCE PARAMETERS - Paga 3 of 3
                  BUOYANCY  CHECK
                                                Buoyancy -> Negative
                                 Ambient Temperature  (Ta) -> j£$ **?
                  RICHARDSON NUMBER CHECK
                                       Richardson Munfcer -> 8270
                                                                   (Dense)
        After the scenario input section, TSCREEN proceeds to the model input section where data for the
particular dispersion model is entered.  Figure 5 shows the input needed to run the RVD model. The user
should calculate the exhaust gas exit velocity using the following equation for input to TSCREEN:

                                                          11
                                      exit velocity  «   -
                                      Figures.  RVD Model Input!

                      Ga*eou* Leeks frost Tanks,  Pipes,  Relief Valves - Scenario 4.5
                 Based on user input, RVD Model has been selected.
                 RVD MODEL INPUTS - Page 1 of 3
                 RELEASE PARAMETERS
                                   Release Height above Ground •>
                                     Exhaust Gas Exit Velocity ->
                 POLLUTANT INFORMATION
                                 Pollutant Concentration (vol) ->
                                    Pollutant Molecular Weight •>
                 TIME
                                       Duration of the Release ->
                     Desired Averaging Tine for the Calculation
                                            of Concentrations •>
                                                                        •in
                                                704

-------
       The RVD model output is extensive. It begins with a listing of model inputs and identifies the
maximum concentration, the distance, and  the meteorological conditions associated with the maximum
concentration. The next output section lists the concentration at each of the distances along with the
meteorological conditions.  For this example, maximum offsite concentration is  1.36E+07 jig/n? at 122.4
m downwind.

SUMMARY
       TSCREEN is an interactive model for estimating ambient pollutant concentrations for a variety of
release scenarios from Superfund sites and other sources of toxic air pollutants.  This computer program
implements the procedures developed in a document entitled "A Workbook Of Screening Techniques for
Assessing Impacts of Toxic Air Pollutants,* (EPA, 1988) and should be  used in conjunction with this
workbook. TSCREEN has a front-end control program that also provides, by use of interactive menus and
data entry screens, the same steps as the workbook. An extensive help system is provided to guide the user
in selecting the appropriate scenario and associated  screening dispersion model.  Text editing, graphical
display capabilities, a chemical database and a calculator are also provided. The revised version of TSCREEN
includes an additional scenario and on-line help. TSCREEN can be downloaded by registered users on the
EPA's Technology Transfer  Network, SCRAM Bulletin Board System (EPA, 1991).

REFERENCES
Brode, R.W., 1988. Screening Procedures for Estimating the Air Quality Impact of Stationary Sources fDraft
f«r Public Comment). EPA-450/4-88-010. U.S.Environmental Protection Agency, Research Triangle Park, NC,
      PB 89-159396).
Environmental Protection Agency, 1988. A Workbook of Screening Techniques for Assessing Impacts of Toxic
Air Pollutants.  EPA-450/4-88-009.  U.S. Environmental Protection Agency, Research Triangle Park, NC,
(NTIS PB 89-134349).

Environmental Protection Agency, 1989. User's Guide for RVD2.0- A Relief Value Discharge Screening Model.
EPA-450/4-88-024. U.S. Environmental Protection Agency, Research Triangle Park, NC 27711, (NTIS PB 89-
151070).

Environmental Protection Agency, 1991. Technology Transfer Network (TTN) User's Manual. EPA-450/4-91-
020. Office of Air Quality Planning and Standards, Research Triangle Park, NC, (NTIS PB 91-234583).

Petersen, W., 1982. Estimating Concentrations Downwind from an Instantaneous Puff Release. EPA 600/3-
82-078.  U.S. Environmental Protection Agency, Research Triangle Park, NC 27711, (NTIS PB 82-261959).

Touma, J.S., and K.T. Stroupe, 1991.  TSCREEN:  A Personal Computer System for Screening Toxic Air
pollutant Impacts.  Proceedings, International Conference and Workshop on Modeling and Mitigating the
Consequences of Accidental Releases of Hazardous Materials, May 6-10, 1991, New Orleans, LA, pp. 723-734.
                                              705

-------
              rti.gpf.Tsi. on pmraaeteTS bjL SJLft t.Tflffer OIL

                         by

M.P.Singh*; P.Afiarwal; S.Higan; Selva Kunar; T.S.Panwar; Anita Gulati



 *  Centre  for  Atmospheric Sciences,  IIT-Delhi,  Hew Delhi-110016.




 Method0Ingv   :  The  procedure employed for tracer  test   for  SFg
 includes  the continuous steady release of a  measured  volume  or
 SF* a passive tracer through a calibrated gas flow meter. The low
 volume samplers were arranged all around the  source or in an  arc
 depending  on the  wind  speed and  direction.  Air  samples  are
 collected  and  analysed by electron capture detector  using  Gas
 ehromatograph.
           The  meteorological  data  is  obtained  from  foldable
 meteorological  tower  at the site and 30m  meteorological  tower
 installed at IIT.

 Poldable meteorological tower at. 1.25m gives data of:
 l)wind speed, direction and wind gust,
 2)radiation measurements
 3)air temperature & humidity
 4)pressure & surface temperature

 30iq meteorological toner has instruments at Q. levels:
 l)wind speed & direction
 2>air temperature  & humidity
 3)turbulence measurments
 4)soil temperature

 Present.   Mflrk  :  (1>A set  of 16  runs were taken in  the  month  of
 Feburary  under different stability conditions at sports ground at
 IIT.  The  circular  arcs  were at a distance of 50m,  100m & 150m.

 (2)A similar type  of diffusion experiment was performed in  April
 at DLF Qutab Enclave and the distance of  the last  arc  was 500m.

 (3 Subsequently  diffusion  experiments  were  performed  in  the
 months of July,  Sept.,  Oct.  at IIT and DLF Qutab Enclave.

 Results:
       Meteorological  data  and  sampling  layout  of   diffusion
 experiment at IIT is summarized in Table-I.  The concentration  of
 SFg  obtained after analysis of bags is summarised  in  Table-II.
 The  SFg concentration data was used for plotting of contours  at
 fixed downwind distances Fig.-l.
       Sigma-y  was calculated by applying contour,  trajectory  &
 sigma-theta  methods  and  after comparison  with  PG  curves  the
 descending series were:
      observed/contour/trajectory/sigma-theta/sigma-y/PG curves
                                  706

-------
(l)The  enhanced horizontal difusion is attributed mainly to  the
variability of wind direction or meandering during low wind speed
directions.
(2)In  near  calm conditions the plume  segments  become  puddles
lying  in  some areas of the grid and  these  prolonged  episodes
result in  localised area of high concentration.
(S)Average  night time concentration were higher by 50-1002  over
day time concentration.
(4)The trajectory method reveals that all the runs have wave like
distribution.
  TABLE-1
               METEOROLOGICAL DATA AND SAMPLING LAYOUT

                 Q£ DIFFUSION EXPERIMENT AT UJ DELHI
"" "" "" 1
RUN! DATE
MS* '
NO* »
f
t
4


, -13.2.9
1
1
t
t
2 J13.2.91
< 4
3 '13-2.91
4
4 J13.2.91
i
• 14 2.91
£ i
•
6 J19.2.91
4
7 119.2.91
1
6 '19.2.91
4
9 -19.2.91
« and
•20.2.91
4
0 '20.2.91
1
, -21.2.91
4

2 J 2 1 • •
' •> 91
3 3*1 "••
1

* A t ^
* t
' ? 91
15 ;2i-^-
,. h-'-3'
« 4
EMISSIONIRELEASE; RELEASE
RATE ; POINT J TIME
(cc/min); I (1ST)
> i
i i
< i
so ICENTER ; 1100
; ; OF
3 113.2.91
4 1
• 1
50 ICENTER ; TO
i i
so ICENTER ; 0430
J OF
50 JCENTER ', 14.2.91
i <

50 JCENTER J
1 1
1 |
30 ICENTER 10930-1030
I 4
1 4
30 ICENTER 11215-1315
4 1
4 1
50 ISHIFTEDJ1615-1715
i i
c i
30 J CENTER 12330-0030
i i
4 1
1 1
1 1
1 1
30 JCENTER 10330-0430
< i

so ICENTER 10930-1030
• i

50 J SHIFTED! 1145-1245
I 1
50 JSHIFTEOI1245-1315
i 1
I 1
30 ICENTER ;ieoo-i9oo
t t
t t
20 ICENTER 12300-0000
* *
i «
30 ICENTER :033Q-04QO
f •*
; ;
COLLECTION;WINO
TIME ISPEEO
(I^T) ,[fn/G)
4


1200-12301 1.6
I
4
1
1
4
1630-16001 1-6
1
4
1900-18301 2.1
k
2330-0030 i 0.4
1
I
0400-04301 0.4
1
1
1000-10301 2.7
t
1245- 1315! 2.5
i
1645-17151 2.1
1
1
0000-003OI 0.3
1
1
I
1
1
0400-04301 1 .0

1000-1020; 1 .4

1215-12451 1 -7
i
1245-13151 1 .0
c

1830-1900! 0.8
1
1
2330-OOCOI 0.5
i
0400-04301 0.4
I

WIND
DIRECTION
(dec)



274-347



355-017

273-303
331-021

312-316


260-306

246-213

285-317

283-330



284-333

284-357

271-359

324-063


316-328


260

309-53

STABILITY
(P-G)



B



e

C
E

E


C

B

B

F



F

a

B

&


c


E

E
                               707

-------
CONCENTRATION  QF. SULPHUR HEXAFLUQRIDE AJ DIFFERENT  SAMPLING EOINT




                               DURING



                      EjCPEfllHENT AJ HT. DELHI
IELH
4

























1
RUN-5
(PPT)
11000
22000
21000
21000
1S50
2100
1260
29000

1450
2700
13000
4100
700
293
527

35OO

334

2900

2400
8000

RUN-6
(PPJ)
50
1 101
115
222
357
40
28
200

119
176
205
36
7
9
20

26

24

438

82
99
	 	
RUN -7
(PPT)
31
248
190
9
7
17
20
29

6
2B8
38
27
10
10
19

22

20

143

72
0
. 	 --
RUN-*
(PPT)
385
304
11fl
4
6
S
1282
622
53

201
61
5
5
5
345
7

5

83

42

3
                                       TOR

-------
QE SULPHUR HEXAFLUORIDE A!  njFFERENT SAMEUNG PQINI
                DURING




       EXPERIMENT £! 117.  EE.ktil
^^^^
SAMPLING
POINT
i
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
^-—

RUN-9
(PPT)
433
15
2131
8934
70
24
41
21
149
4113
6172
1336
0
18
72
0
636
2226
2636
3910

RUN- 10
(PPT)
1068
76CO
60
40
59
48
57
88
643
2252
87
100
87
73
53
68
62
507
44
71

RUN-1
(PPT)
15
372
616
5
13
10
6
12
141
56
162
10
109
11
45
13
19
23
171
171

RUN- 12
(PPT)
58
96
49
106
175
395
759
203
5
28
27
14
10
11
1 OO
6
e
14
13
50

RUN- 13
(PPT)
42
30
48
141
55
206
1060
61
10
12
25
13

61
215
5
5
8
14
65

RUN- 14
(PPT)
3167
,4179
2270
8
4
2
2
&.
1386
3385
7324
523
574
3
6
14
285
963
282
41

RUN- 15
(PPT)
89
9394
13784
12862
404
44
15
33
117
9097
14643
6614
2242
21
28
75
44
9542
159
689

RUN- 16
(PPT)
7917
3095
3950
5317
16267
5027
3805
4177
2438
2034
1819
618
319
2688
2507
834
2715
953
933
705
                        709

-------

-------
           Session 16
Measurement Methods Development
     Philip Hopke, Chairman

-------
  METHOD DEVELOPMENT FOR THE ANALYSIS OF VINYL CHLORIDE IN
                       GASEOUS AND PVC RESIN SAMPLES
                             M. Tardif, £. Dowdall, C. H. Chiu

                       River Road Environmental Technology Centre
                   Technology Development Branch, Environment Canada
                                    3439 River Road
                                Ottawa, Ontario K1A-OH3
       Vinyl Chloride is a proven health hazard producing both carcinogenic and toxicological
       necessitating regulated control of environmental emissions. Industrial production of vinyl
   londe along with its main application, the production of PVC (polyvinyl chloride), are the main
sources of environmental discharge. A technique to monitor the release of this substance at these
industrial sites is essential.
       When Canadian vinyl chloride regulations first came into effect, chromatographic analysis
  as performed using packed column technology. Due to changes in technology, the need to update
 he standard reference method, to allow for use of most recent technologies was recognized.
       The paper will deal with the application of fused silica capillary columns for the separation
   d determination of vinyl chloride in gaseous and resin samples. The analysis of resin samples is
  erformed by headspace technique using a  commercially available system equipped with an
P toinatic turntable and interfaced to a capillary column.

INTRODUCTION
       The following method development work was undertaken to update the current standard
  ference method for the determination of vinyl chloride emission levels from vinyl chloride and
oolwinyl chloride production plants.
       Sources of emission at VC production plants consist of gaseous effluent from stack emissions
   A process vents. Sources  of VC emissions from PVC manufacturing plants are as follows: 1)
^ cess vents, 2) reactor vessel openings and 3) PVC resin - Residual monomer remains entrapped
Pr  he resin at various concentration levels dependent upon the processing stage. There is a need
Jfl monitor emission levels of VC from the PVC resin downstream from the stripper since venting
£* m this point  on is directed to  the atmosphere. These sources are tested annually to verify
     oliance with CEPA vinyl chloride emission regulations.
c010? changes in industrial processes in the manufacture of PVC incurred changes in emission
    Is of vinyl chloride. Notably, one of the major changes in the industrial production of PVC is
 h  creator porosity of the polymer produced in today's resins as compared to those produced when
 h   methodology was first introduced. This particular change in characteristic promotes faster
  i ase of the entrapped monomer from the polymeric beads when in contact with  air, and
  h  auently, residual VC concentrations are lower. This in turn necessitates procedural changes
Sample preparation and handling to minimize exposure of the resin to air so that reproducible
in sa^gJTients may be taken that are representative of the industrial process conditions.
&eas  ^g original methodology calls  for the chromatographic analysis of vinyl chloride using
      j column technology for analyte separation. With the advent of capillary column technology
P  ' h offers greater flexibility and faster analysis time the need to update the reference method
                                          713

-------
to Include these columns became apparent For the purpose of this study the following capillary
columns were evaluated, Al2Oj/KCt PLOT, PoraPLOT Q and DB-624 column. All are designeo
for the analysis of light hydrocarbons,                                                  .
      Vinyl Chloride in gaseous samples (Tedlar bags) is determined by direct analysis of tn
gaseous phase by gas chromatography coupled to an FID detector. Residual VC monomer in resi
slurry  is determined using an indirect method (beadspace analysis technique). This technique is
based on the equilibrium reached between the gaseous and solid phase in a closed system.

EXPERIMENTAL
Apparatus
       Gas Chromatofraph. An HP 5890 SeriesII Gas chromatograph equipped with an
detector  and controlled by the  HP  Vectra/OS Chemstation was used for sample analysis.
following columns were evaluated Al2Oj/KCl PLOT (0.53mmID x 25M), PoraPLOT Q (0^3mmUj
x 25M), DB-624 (0.53mmID x 30M, 3 micron film). The carrier gas used was Helium U-H'P Jjjp
Nitrogen U.H.P  as carrier makeup gas. Hydrogen rero and Air zero were used for  the M
flame.
       Headspace AnalyKr. The Tekmar 7000 beadspace analyzer was evaluated, which has an
internal heated platen which can accommodate 12 sequential vial positions with a 50 posit»°
carrousel autosampler providing unattended sample processing. This instrument also has a patefltc
mixing feature which was evaluated to determine if reduced equilibration time was feasible. Samp
vials of 22 mL volume  size were used with aluminum caps and Teflon-lined butyl rubber sea*
Headspace sample loop sizes used  were O.lmL,  0.5mL and l.OmL, Operating  Conditions: TB
internal platen for sample equilibration was set at 90°Q the sampling valve and  transfer line was
set at 100°C

Calibration
       Gas standards of Vinyl chloride in nitrogen U.H.P @ the following concentrations in PP
(mol/mol) were used from 1) Matheson Gas Products @ 1.15 ± 52%, 533 i 2% & I480-ttf^
and 2) Supelco (NBS certified jf2%): 0.991, 10.01, 49.97. 100.4 , 1020.    Various sampling J°°P
sizes were used. O.lmL, 0.5 mL and l.OmL.

Sample preparation
       The resin sluny was suction filtered through a buchncr funnel fitted with a Whatman pap<
filter. The filtering process is continued only as long as a steady stream of water is exiting from tn
funnel. Any excessive filtering will incur losses of VC monomer.                          ,0
       After filtration the resin wet cake is quickly transferred to a plastic bag and twisted shut
preclude air. A 1  to 10  mL disposable syringe, tips removed, is used to transfer an  aliquot of^esin
(0.1 to 2.0 g) from the  bag to a weighed sample viaL The sample vial is  then quickly closed,fL
crimped Teflon lined butyl rubber seals are used The sample bag is opened  only enough to auo*
 insertion of the syringe and is quickly reseated afterwards. The use of a syringe allows for a,m° f
 reproducible sample size as well as minimising exposure of resin to the air. The concentration
 residual monomer in PVC resin is determined on a dry weight basis.

 RESULTS AND DISCUSSION
 Headspace Analysis
       Three different PVC resin slurries (Resin 1, Resin 2 & Resin 3) were evaluated in this>study.
 The equilibration time required for each resin type was established Resin 1  achieved equ^P^
 after 30 minutes (Figure 1) whereas the Resin 2 required a nominal 10 minutes before equi"
 was reached (Figure 2). Resin 3 achieved equilibrium after 45 minutes (Figure  3).
                                           714

-------
   70

   60
 o 30
  10

   0
           Figui* I. EqullbfJrton Tims of Rstln 1 Using H«Ml»pa» Amjyiw (Yth
                                & Without bBxIno Feature
  MMng
                                           Temp.- 90 C
                                            AI203/KCI
                                       TlflM <«*)
                                                                                90
             Rsurs 2.  Equlllbrrion Tims of Ftealn 2 U«lrvB H«ad»paw Analyiw
              *       H      vVWi t Without Mixing F»*ta«
  20
V 15
C

C 10
o
n
c  5
                                                                        Miring
                                                           No Mixing
                                                 B.- 90C
                                              PoraPUOT 0
                    10
                       15              20


                          Tlma (mil.)
                                                                                 30
           Rgur.3.
                                                                   fWtth
  20
V 1S
C

c 10
a
n
«  S
  Mining
A1203/KCJ
     90 C
                                         Na Miring
                                       PomPtOTQ
                                       Temp.. « C
                 10
                              20
                                          30
                                                                    SO
                                       TTnw
                                     715

-------
       To evaluate the mixing feature of the headspace analyzer, samples were re-analyzed under
 various  mixing time  conditions. The mixing  feature   provided a  significant difference in
 equilibration time resins 1 and 3. The equilibration time for the Resin 3 resin was lowered by a
 factor of two using this feature (figure 3). Also it greatly improved equilibration time for Resin 1,
 which was achieved within minutes (figure 1).
       This  mixing feature  provides  reduced analysis time  for  individual samples therefore
 increasing sample turnaround time in theory. For analyses of large batches of samples, however,
 this could in fact be the time limiting factor since mixing is done one sample at a time whereas up
 to 12 samples may be equilibrating simultaneously at any given moment.
       This demonstrates that reducing equilibration time is not necessarily a time saving feature.
 The  main advantages of this feature is the quicker turnaround time obtained when only a few
 samples are to be analyzed and  in  the  reduction of thermal  exposure of the sample thus
 maintaining thermal degradation of the analyte to a minimum.

 System Stability
       Variation in response for the analysis of vinyl chloride standards over a one month period
 on the Al2O3/Ka PLOT column using headspace analysis was below 10% RSD for all standards
 used. The greatest variation in response was observed for the 1 ppm VC level (9.9% RSD) as well
 as the 1480 ppm VC  standard (9% RSD). VC  standard response variation observed using the
 PoraPLOT Q column was slightly lower with a %RSD in the range of 6 - 8% for the 1480 ppm VC
 standard, 3.1% for the 10.04 ppm VC standard,  2.6% for the 533 ppm VC standard and in the
 range of 4 - 7.2% for the 1 ppm VC standard. Both columns exhibited the greatest  variation in
 response at both extremes of concentration in their evaluated linearity ranges.
       VC standards analyzed from Tedlar bags showed much better reproducibility. This is
 expected due to the direct nature of the analysis. The relative standard deviation was below 2%
 for both the53.3 and the 1480 ppm standard and below 5% for the 1 ppm level standard. This mode
 of analysis was more subject to contamination from sample carry-over and  required close
 monitoring by way of blank analyses. The stability of the VC gaseous standards in Tedlar bags was
 determined and repeat injections of a 1 ppm standard was found to be reproducible over the course
 of 48 hours. Due to the nature of the sample collection media and the analyte of interest, losses
 due to leaks or permeation through the bag &/or fittings is of concern and therefore long standing
 stability  is not expected.
       Samples that were analyzed under established equilibrium conditions were very reproducible
 over a period of several months with a RSD of 10%. This figure is representative of the procedure
 as a whole, from sample preparation to instrumental analysis. Within any given day reproducibility
 achieved is below 6% RSD.
       The greatest  factor  influencing accuracy  is the sample  preparation step. Sampling was
 modified from the original reference method to  minimize exposure of the  resin to air. Even so,
 filtration time and the speed at which sample aliquots are transferred to the vials are difficult
 procedural steps to control. There are other inherent discrepancies affecting the accuracy such as
 the procedure used for the preparation of the calibration standards.

      Stability of Resin Slurry.   Interestingly enough, no noticeable degradation or outgassing
was observed in stock resin slurry solutions. All slurry resins were shipped and stored in plastic
containers. Initial analyses were carried out within 48 hours of sampling. Samples were then stored
in the dark in a ventilated refrigerator at 5°C. Subsequent analyses over the course of several
months produced results equivalent to original monomer concentrations. The overall variation
observed was comparable to the variation observed on a daily basis. All slurry resins exhibited this
long standing stability.
                                          716

-------
Column Evaluation
     Chromatograms of slurry samples analyzed on the Alpa/KCL (figure 4) column exhibited
j! sfagle major peak. On the PoraPLOT Q (figure 5) column a second analyte eluted (RT=2.21min)
™ Prior to the VC peak (RT=2.67min) with a peak intensity dependent upon resin type. For
Resin 1 this peak was very close in magnitude to the VC peak. Although this contaminant peak was
   observed for the analysis of resins on the AljO^/KCL column residual VCM concentrations on
    columns were comparable. Therefore isolation of the VC peak  is achieved. The polarity
    ences of the column coating materials may explain these results. The same chromatographic
Pattern was observed using the DB-624 column as for the PoraPLOT Q column for Resin 1 using
a W (50°Q isothermal GC oven temperature,  VCM eluted at approximately 1.5 minutes. The
    sample analyzed on the DB-624 column using a greater oven temperature (100°C) did not
      VC from this neighboring peak. The DB-624 column provides a lesser degree of resolving
     than the PLOT columns. Traces of impurities present in the standard calibration gases were
Jf^ Well resolved from VC on this column. Optimally sub-ambient temperatures would be required
      use of this column for this particular application.
     Resin 1 was found to have the highest loading in both residual VCM and other residual
         ns.  All  three columns were found to be linear in the 1 - 1480 ppm range with
        ts of variation exceeding 0.9995.
     Jktectlfln Limit. The detection limit was found to vary  depending upon the analysis
         used. The detection limit of VC on the A^Oj/KCL column was found to be 0.015 ppm
         ple loop size) and 0.15 ppm using a sample loop of 0.1 mL. The detection limit on the
         Q column was found to be in the vicinity of 0.05 ppm (0 5 mL loop size). In comparison
 .  the detection limit achieved using packed columns,  the use of wide bore capillary columns
        sensitivity by a factor of 10 using an equivalent sample loop size.

     Attention  Times  Reproducibllitv.  Standards  analyzed  on  the   A12O3/KC1  column
    nstrated greater shifts in retention times than the other two columns evaluated. The variation
 j, r*tention time for a given day could range from 0.4 to 25% RSD. For the DB-624 column and
  *• PoraPLOT Q column this variation was < 0.4% RSD. Both the PoraPLOT Q and the DB-624
       are tolerant of water whereas alumina's adsorbency is greatly affected by moisture.
 ty_ ,   Samples and standards were injected in duplicate as a minimum. The system was calibrated
 ofj  ¥ u&ing 3 or 4 point calibration curve and calibration was monitored on a daily basis by way
          standard injections (typically 53Jppm) before and after each  set of samples. Blank
        consisting of nitrogen  U.H.P were run on a daily basis to monitor for any possible
          interferences and cross-contamhiation.

          of NBS certified gas standards and Matheson gas standards
          referenoe method,  for standardization purposes, requires  that all VC  calibration
         used be certified traceable to NBS. Since most VC and PVC  production plants use
         VC standards on a routine basis, these were compared to NBS  traceable standards to
         if these were equivalent and could be included in the updated version of the reference
           Matneson VC standard at the 1.15 ppm level did not agree within its given tolerances,
        necessitating re-calibration using a standard  traceable to NBS.
    lftodified methodology for the preparation of slurry resin samples provided good overall
                                         717

-------
precision. All three resins possessed different characteristics as demonstrated by their variation in
equilibrium times. PVC resin equilibrium time was reduced using the headspace analyzer's mixing
feature but not consistently from one resin type to another. Both of the PLOT columns evaluated
were found to possess the necessary characteristics for potential replacement of packed columns
in the determination of Vinyl Chloride in gaseous and PVC resin samples.

REFERENCES

1. Standard Reference  Method for  Source Testing and Measurement of Emissions of
Chloride from Vinyl Chloride and Polyvinyl Chloride Manufacturing, Report EPS l-AP-77-1, Air
Pollution Control Directorate, June 1979.

2. H. Hachenburg & A. Schmidt, "Gas Chromatographic Headspace Analysis". Heyden & Sons Ltd,
1977.

3. N. Onda, A. Shinohara, H. Ishi'i & A, Sato, "Characteristics of Isobaric Headspace Extraction and
Applications to Multicomponant Systems", J. High Res. Chrom.. 46, May 1991.

4. Dennison et Al.,"Headspace Sampling and Gas-Solid Chromatographic Determination and
Confirmation of.<, 1 ppb Vinyl Chloride Residues in Polyvinyl Chloride Food Packaging",JLA5Sfl&
Chem.. Vol.61, No.4, 1978.
                                       2.0e5
                                       t.BcS'
                                       1.6eS
                                       1.4e5
                                       1.2eS
                                       l.OeS
                                               6.0*4
1.2e5-

1.0e5

8.0e4

6.0e4
        2.0e4
                                                         Resin 1
                                                         AI203KCI
                                                                                VC
                       3
                    §.  JV
                           VC
                   Time (min.)
Ft{«re 4 CkrvmmUmru* of kocfagMcc i
«mAI203/KCIcDlwwi.
                                    ..
                              Time (min.)
                                                      B
            Figure 5 Chrometogram of headspace analysis of Resin 1 on the
            PoraPLOT Q Column.
                                           718

-------
SAMPLING AND MEASUREMENT OF PHENOL AND METHYLPHENOLS (CRESOLS)  IN
D             AIR BY HPLC USING A MODIFIED METHOD TO-8
                         Steven A. Bratton
                      State of North Carolina
                     DEHNR-Air Quality Section
                        4403 Reedy creek Rd.
                            Raleigh, NC
ABSTRACT
     This paper addresses results of the development of a
        d Method TO-8 whose two objectives were: (1) to achieve
        resolution of phenol and cresol compounds in the shortest
 nssible  run  times; and  (2) to develop a sampling technique for
 rtncentrating ambient air samples for analysis of phenol and
 vesols.  The  analytical  method consists of HPLC analysis using
 «rt-capped, reverse phase, C,ft column technology (Waters Delta
en? c     3.9mm x  15 cm,  100 *?. This methodology is used to
j nro^i separation, reduce retention times, and increase the
  nsitivity of the existing Method TO-8. The paper will present
6 lidation data of the analytical method showing reproducibility

a    The  modified sampling technique allows for long-term
          in order to  achieve  lower MDLs than allowed by the TO-8
          sampling. The modified technique utilizes C.. Sep-Pak
    inger sam.                                  ..
   -ivatization,  and analysis  of  the  phenols  as phenolltes.
   lidation information of  the sampling  technique will also be
presented.


jHTRODOCTION

      The analysis of phenol and  cresols as outlined in  Method
    o1 leaves the analyst with two distinct problems not addressed
    the method.  The first  problem is the lack of  resolution  and
    aration between the compounds of  interest.   The separation of
St!  phenol peak from the cresols may be adequate  for  single
   •mound analysis but should be  improved for quantitation of
c   nles containing both phenol and cresols.   The  reproducibility
ed£ linearity data can be  improved upon by achieving  baseline
an» i,|tion between the analytes.  The separation  of m/p-cresol
r& « o-cresol, as shown in Figure 1, is virtually nonexistent.
£r*ration of this kind makes reproducible data extremely
se?flcult to accomplish.  The improved separation is  shown in

Fi9ur^he'second problem that exists in Method TO-8 is the
    hility to accomplish long term sampling by the use of midget
ina7«rrers.  Phenol and cresols are generally found in very low
imp*"9
                                719

-------
concentrations in air samples and require a method for
concentrating the sample for analysis.  The objective of this
portion of the work was to accomplish a method of long-Jterm
sampling ambient air concentrations.

SAMPLING

     The modified sampling method utilizes C.fl Sep-Pak Plus
cartridges,  (Waters chromatography, Milford, HA) activated with
5ml of acetonitrile.  A coating of 10ml of IN NaOH is then
applied and dried under a nitrogen purge for fifteen minutes.
The cartridges are refrigerated until use.  The phenol and
methylphenols react with the NaOH to form phenolates.
     The sampling can be carried out using the same pump systems
required for Method TO-14 by adapting the intake of the pump to
fit the cartridges.  The cartridges are returned to the lab and
the sample eluted from the Sep-Pak with 4ml of acetonitrile.
Depending on the concentrations in the sample a white precipitac
may form which will require filtering through a 0.45 micron
membrane filter prior to analysis,  once the sample is prepared
the analysis will be carried out according to the analysis
protocol described in the Analytical Method portion of this
paper.                                                         en
     The validation of the sampling data was compiled using sev
injections of seven separately prepared cartridges.  Mimic
samples were prepared to represent a concentration, in the 4ml
eluent, of 12.5 ng/ul .  The reproducibility results for standard
deviation and coefficient of variation for each of the analytes
was as shown below:
AMALYTE                          etl-1
Phenol                          78.74                  1.01
m&p-Cresol                     131.25                  0.79
o-Cresol                        69.39                  0.76
ANALYTICAL METHOD

Instrumentation

     A Waters HPLC was utilized for the analysis consisting of
600E multisolvent delivery system  and controller,  a  490        
-------
      Buffers  or  Mobil  Phases
      Buffer A =  Acetonitrile             Buffer  B  =  0.1M Acetate
          Buffer B consists  of  0.1M sodium acetate  buffer made  by
          dissolving  13.6  grams of  sodium  acetate trihydrate  and
          5.8 ml of glacial  acetic  acid in 1  liter  of HPLC  grade
          water and adjusting the pH to 4.5 with  glacial acetic
          acid.  The  buffer  should  be filtered through a 0.45
          micron filter  prior to  analysis.  Buffers should  be
          prepared fresh daily for  routine analysis.

          An  isocratic run is used  with a  flow of 1.0 ral/min
          consisting  of  30%  buffer  A and 70%  buffer B.

      Detector Program

      Time         Detector/Channel       Wavelength        AUFS
      initial             uv/l                274  nm         0.500

     Column

     Data  was compiled using a  Waters Delta Pak C.& silica  based
     column.  The  dimensions are  3.9mm x 15cm, 100  A, with  a  5
     micron spherical packing.  The sequential bonding and
     end-capping process developed  for this column  enable    _
     separation of difficult compounds with high  resolution.

VALIDATION RESULTS

     ReDroducibiltty

     A standard containing 25 ng/ul of each phenol, meta, para,
     and ortho  cresols was prepared.  Seven replicate injections
     were  performed and  the  results are summarized  in Table I.

          Table I.  Reproducibillty for phenol and  cresols  at 25
                   ng/ul concentration.

     PHENOL
     Peak  Areas                Mean          «n-l           cv%

     1685,  1685,  1672
     1682,  1670                1679          6.05           0.36
     1679,  1682
                               721

-------
m&p-CRESOL
Peak Areas
                         Mean
3180, 3171,
3159, 3161
3190, 3193
            3185
                         3177
13.63
0.429
0-CRESOL
Peak Areas
                         Mean
1740, 1760, 1749
1730, 1735
1771, 1760
                         1749
15.07
0.862
     Since the acceptable internal limit for CV% is 2.5%,
this clearly shows the excellent reproducibility of this
method.  The baseline separation achieved in this method has
reduced the CV% to an acceptable value.  The use of the
sequential bonding and end capped column technology, along
with the change in the pH of the acetate buffer, are the
primary changes in Method TO-8 that enhance the separation
and resolution.
     The linearity study was performed on three varying
concentrations.  Each concentration represented
approximately 50% of the previously injected standard.
These concentrations were 6.25 ng/ul, 12.5 ng/ul, and
25 ng/ul.  Each standard was injected in triplicate and a
total of nine points were used in the calculations.  The
linearity results are summarized in Table II.

     Table II.  Linearity Study

PHENOL
Standard Concentration
                                          Peak Areas
25.00 ng/ul
12.50 ng/ul
 6.25 ng/ul

 Plot concentration vs. peak area
 Slope =  .01478   intercept =  .21039
                                           1682, 1679,  1670
                                           825, 835, 832
                                           409, 405, 413
                                        Correlation =  .99997
                            722

-------
     n&p-CRESOLS


     Standard Concentration                    Peak Areas

     25.00 ng/ul                               3194, 3190, 3161
     12.50 ng/ul                               1584, 1575, 1575
      6.25 ng/ul                                782, 781, 790

     Plot concentration vs. peak area
     Slope = .00781    Intercept = .13811    correlation = .99995



     O-CRESOL


     Standard concentration                    Peak Areas

     25.00 ng/ul                               1761, 1771, 1735
     12.50 ng/ul                                879, 857, 862
      6.25 ng/ul                                428, 428, 427

     Plot concentration vs. peak area
     Slope = .01410    Intercept = .24739    Correlation = .99982



     The  linearity is proven to be excellent,  as exhibited by the
in£mation values being greater than .995,  the acceptable
 nternai  limit for HPLC methods.
,     The  newly developed sample technique will,  along with the
f'Ptoved  method,  help analysts in the monitoring of manufacturing
th*   ties  that Produce phenolic resins.   The emissions from
ev* e facilities  are generally in the ppt range, and have been
Pat  mely difficult to detect in the past.   The  use of the Sep
 «* cartridges is more efficient for field studies. Their use
lm^eaees the  Potential of sample loss that exists with midget
ace  9era-   The increased resolution will allow  for a more
em*   te  and quantitative analysis of phenol and cresol
 '"
    william  T.  winberry,  Jr.,  Norraa T.  Murphy,  R.M.  Riggan,
     Methoa  TO-8:  Determination of Phenol  and Methylphenols
    (Cresols)  in Ambient  Air using High Performance  Liquid
    Chromatography,"  in Hf*-h"rts for Determination of Toxic
    Organic  ronipfrundfl in  Alri  Noyes Data corporation. Park Ridge,
        Jersey,  199-220.
    Waters  Columns  Technical  Literature,  The  Delta Pah Care
    Ufie^ Manual,  Waters  Chromatography Division,  1.
                              723

-------
 pi (JURE 1

IMJKT-
  1 ' «
  I
                                                                 11.30
     f^mniE  2

          ItUttt  H/1 ft/91  Ui37!«»   91UHEU 1(1 Bill I
     nt \ US  .3
                                                        4.52
                                                            ;	  |1
nmn <
        t  ft
        tu nill t
                                   724

-------
     APPUCATION OF SOLID PHASE EXTRACTION
             TO THE  DNPH IMPINGER METHOD
                FOR CARBONYL COMPOUNDS
                                   Kochy Fung
                                   AtmAA. inc.
                            21354 Nordhoff St., Suite 113
                               Chatsworth, CA91311
.           and other cartxxiyl compounds in various sources are routinely measured using an
r^Qer method with acidified 2,4-dinitrophenylhydrazine (DNPH) reagent The method requires extensive
"*vent extraction to recover the derivatives for analysis by high performance liquid chromatography.
2?'° Phase extraction using C-18 Sep-Pak was tried and compared with the normal method on a set of
ie! ^ples from difference sources. The results between the two extraction techniques were comparable
JT ^aldehyde and acetone, but not for acetaldehyde, propanal. and methytethyl ketone. Explanations
"* via discrepancies will need further investigation.
         method was developed as a sensitive and specffle method for formaldehyde and other
        with the capability of measuring at the ppb levels of these compounds typically found In
      * 
-------
EXPERIMENTAL METHODS


DNPH impinger samples collected from various combustion sources according to GARB Method 430 were
analyzed using the solvent extraction technique as described by that method.  An  aliquot of these
samples were  then extracted using SPE  and  analyzed  likewise, with high performance liquj°
chromatography.  In order to provide a valid comparison, sample solutions that contained visits
precipitates were excluded from the experiment,  as the ability to take a representative sample aliqu°*
would be in question. C18 Sep-Pak cartridges were used for conducting the SPE. The procedure f0"0*?!
closely to the manufacturer's recommendations. A vacuum manifold with a flow controller to control tn
flow rate was used to facilitate the SPE  process. The rate at which the sample passed through tn?
cartridge was adjusted to about 10 ml per minute. The cartridge was first conditioned by flushing wftri
ml of acetonitrile, then with the same amount of deionized water. Air was allowed to draw through tn
cartridge briefly to remove the excess liquid, followed by a 3-ml aliquot of the sample, and 2 ml
deionized water. After  the excess  water was suctioned off, the cartridge was eluted with 3 rnl
acetonitrile. The eluant was  added with a known  amount of an  internal standard, n-hexanal-DNPn
(hydrazone), as a volume marker and analyzed as usual by reverse phase HPLC.


RESULTS AND DISCUSSION

The separation of the hydrazone derivatives by HPLC allows specific determination of individualcartx^
species present In the sample. An example of a typical chromatogram is given in Figure  1 snowir^.!jg
separation of C1-C7 carbonyls. For the present study, we evaluated five compounds: fontialdehyo<
acetaldehyde, acetone, propanal, and methylethyl ketone, which were the components r
samples. A total of 26 samples were separately extracted using the two techniques and analyzed
batch. Eight samples showed negligible amounts of the higher carbonyls. Thus there were more
points for formaldehyde In the comparison.

The results of the comparison are plotted and shown In Figure 2A-E. For formaldehyde and acetone, tn
were good agreements with the two techniques. The slopes of the regression line were near unity-&r_
correlation coefficients were 0.98 and 0.94  respectively. The highest point for formaldehyde
Figure 2A was excluded from the regression because the capacity of the cartridge  might"
exceeded with that sample.  The analytical precision, as determined from replicate ana
± 2.6% at the 4 ug HCHO/sample level. The difference due to the extraction technique was '•
significant (3s) in 7 of the 26 pairs of data However, the differences were under 10 pen
For acetone, all except 5 pairs of data showed differences of less than 6 per cent from the i
those 5 pairs showed large differences ranging from approximately 9 to 35 per cent in favor <
regression line also showed a positive intercept of 1.93. The reasons for these large |
are not  apparent.

As Figure 2B, D & E showed, there were large scatter In the data set for acetaldehyde, propanal ^^^
In all these cases, SPE yielded significantly lower values. Much of the scatter might have been due~ 0ut
low levels of acetaldehyde and propanal present in the sample on account of the analytical varlabi "V
MEK was present at sufficientfy high levels in the samples that analytical precision should not
factor in the scatter observed. It is possible that the strong acidity of the DNPH medium ml0]L
caused degradation of the SPE medium such that recovery of the compounds were affected °
elution with acetonitrile. Since Sep-Pak contains only about 10 per cent carbon loading, it is less
to attack by strong acids than other C18 cartridges with higher carbon loading. Testing with c
of higher carbon loading should be useful in determining if the SPE medium was a factor In the
observed. Further research work will be needed to determine if the results were due to a negative
for SPE, a positive artifact for solvent extraction, or a combination of both, on the extraction of can*"
                                            726

-------
CONCLUSIONS

SPE technique gave mixed results on the extraction of carbonyl hydrazones from acidic DNPH sampling
solution. The technique appeared to work for formaldehyde and acetone in the range of concentrations
encountered, but failed badly for acetakJehyde, propanal and MEK. The reasons for these differences In
Performance within the same class of compounds are unclear.


REFERENCES

1-      K.  Fung  and D.  Grosjean  •Determination  of Nanogram Amounts of Carbonyls as  2,4-
       Dlnitrophenylhydrazones by High-Performance Liquid Chromatography* Anal. Chem 53:168-171
       (1981).

2-      California Air Resources Board Stationary Source Test Methods: Method 430 - •Determination of
       Formaldehyde and Acetaldehyde in Emissions from Stationary Sources' Revision, 1991

&      W.T, Winberry, Jr., N.T. Murphy and R.M. Riggin, Method TO5 In Compendium of Methods for the
       Deterrpinatlon of Toxic Organic Compounds In Ambient Air. EPA-600-4-84-041, U.S. Environmental
       Protection Agency, Research Triangle Park, 1988.

4-      Methods Manual for Compliance with the BIF Regulations EPA-530-SW-91-010, PB-91-120-006
       Dec. 1990.
                                          727

-------
                                     co  'IX'
                                     ,-.-,  r-c-
                                        CO--
                             r
Figure 1: HPLC Separation of £4^ir*rophenyihyaVazones of C1-C7 Carbonyls: formaldehyde

acetakJenyde (2), acetone (3), acrotein (4), propanal (5), butanal (6), methyletriyl ketone (7), benzai

(8). cyctooexanooe (9). pentanal (10), and hexanal {11).
                                              721

-------
    55
§  50
'€  45-
£J  40-
S  35-
    30-
    25
£  20-
S  15-
1  1Gl
     IT)
                           R-0.88O3
      0  5 10152025303540455055
             Solvent Extraction
                                                     10  20  30  40  50  60  70
                                                       Solvent Extraction
    o
    |
    a
     1
   0.9-
   0.8-
   0.7-
   0>6
   0.5
   0.4-
   0.3-
   0.2-
   0.1
                                                10
       .10.20.30.40.50.60.70.80.9 1
             Solvent Extraction
o
                                                 6
                                                      4  6   8  10 12  14 16  18
                                                        Solvent Extraction
          0.3 0.4 0.5 0.6 0.7 0.8 0.9  1
                 Solvent Extraction
figure 2: Comparison of Solid Phase Extraction to Solvent Extraction Techniques on Five Carbonyl
Hydrazones: Formaldehyde (A), Acetaldehyde (B), Propanal (C), Acetone (D), and Methylethyl Ketone (E).
Graphs report ug/sample determined by the two techniques.
                                        729

-------
     IMMUNO-BASED METHODOLOGY FOR  USE IN AIR
                BORNE PARTICULATE MONITORING


                                       Bruce Higgle
                             Acurex Environmental Corporation
                                   4915 Prospectus Drive
                                    Durham, NC 27713

ABSTRACT
       This paper serves as a general introduction to the use of immuno-based methods in air monitoflj>S
management. Immuno-based collection and detection systems for organic compounds allow for rapi
inexpensive analysis with high specificity and sensitivity and with a minimum of sample preparation til"
and expense. Because these systems are reagent specific, data collection does not require a high lev**
of sophistication as is required for GC/MC analysis. In addition, the costs incurred using immuno-bas
methods are usually anywhere from 1/10 to 1/100 the cost of GC/MS.  Methods have been prove
successful in analyzing for pesticides and hazardous materials in soil and aqueous matrices at the PP
range.  For air-borne paniculate monitoring, available method formats include immuno affinity c°   hie'
enzyme linked immuno-sorbent assays (ELISAs), and biosensors.  Success in developing an accept*
immuno-based method depends upon  both  the chemical and physical properties of the ana^^rtetfy
question, the type and specificity of the antibody, and the method format. Antibody specificity can vary
greatly and depends upon hapten design and conjugation.   Method format requirements are dep< '**   *
upon collection and measurement specifications.  Sophisticated immuno affinity columns can be u
as passive air-borne paniculate collection systems while ELISAs and biosensors can be used to v^A
quantify amounts of analyte. While immuno-based methods are compound or class specific, their
of use and cost efficiency offer monitoring agencies a new dimension in investigative capabilities-

INTRODUCTION                                                                      „
       A number of pesticides, which are potential candidates and some of which have already
analyzed by immuno-based methods, are listed as hazardous air pollutants to be regulated under S66
1 12 of the new Clean Air Act.  These include the fungicide captan, the herbicides 2,4-D, chloram ^
and trifluralin, the insecticides carbaryl, chlordane, pemachlorophenol (PCP), parathion,  propoxuT'  ^
methoxychlor and the plant growth regulator, maleic anhydride.  In addition, other compounds    .
regulated  include  dibenzofurans,  dioxins  (including   2,3,7 ,8-tetrachlorodibenzo-p-dioxin)
polychlorinated biphenyls, all of which are potential pesticide manufacturing by-products. The
of this discussion is  to introduce the  subject of immuno-based methods to  those air and
management analytical chemists who  require  more flexibility  in  their  analytical program8'
flexibility for analyzing pesticide residues in soil and water samples using immuno-based
already been demonstrated.

REVIEW
       Immuno-based methods are reagent specific. The reagent is the antibody. The ant**>°~^
either polyclonal or monoclonal.  Depending upon the hapten used for initiating antibody P1
antibody can be either very specific (low cross-reactivity) and very sensitive (low ppb  rang*) ^
specific (high cross-reactivity) and not sensitive (low ppm range). A hapten is a small mo^c~~}'et. A
daltons) that cannot by itself induce an  immulogical response but can be recognized by  ant*(    th»*
hapten is usually a modification of a compound or analyte such as a pesticide (example:
can be covalently attached to a protein.  The protein-hapten conjugate after inoculation proo
immunological response, which results in a series of antibodies that recognize the analyte. °° '
                                           730

-------
^a'body refers to a mixture of antibodies. Monoclonal antibody is a single identical strain of antibodies.
^c combination of a sound hapten design, successful conjugation, and the right selection of antibodies
    determine whether or not adequate antibody are achieved. If the hapten design is not a sound one,
    there will be either poor selectivity between the  analyte and related compounds (high cross-
    vity) or no response at all.  If the hapten design is a sound one, success will usually depend upon
sfkcting the most responsive antibody. As with any other analytical method, it is important that quality
Checks and standards be placed on the antibody that is used for analytical purposes.  This quality check
j^olves not only the complete characterization of the antibody but also knowing how the  hapten was
^signed.  This understanding of the basics allows the analyst  to know the  potential strengths and
weaknesses of the assay.
      The following  are some general rules for determining the degree of difficulty in  developing
^muno-based methods for target compounds6.  Methods are generally less difficult and as a result less
^Pensive to develop  for compounds that are (1)  hydrophilic, (2) large molecular weight (mw), (3)
          stable, (4)  nonvolatile, and (5) man  made. Methods are generally more difficult and as a
            more expensive to  develop  for compounds  that are (1) lipophilic,  (2) small  mw, (3)
        „ unstable, and (4)  natural occurring. Examples of pesticides  that are  of less  difficult to
     „  methods for  include amurine2*4'12, diclofop-methyl13, permethrin and bioallethrin14*16, and
QQrflurazon10. An example of a pesticide that would be difficult to produce a method for is trifluralin1l.
      Immuno-based method formats include ELISA,  radioimmunoassays (RIAs), biosensors, and
polity columns (technically not an  assay).  ELISAs are routinely used in the medical and diagnostic
kids for determining  the presence of hormones, viruses, and microorganisms.  ELISAs are also  used
* analyzing chemical contaminants such as pesticides and hazardous waste materials in environmental
 ^ples.   ELISAs measurements are  made by enzymatic  activity   which  can  be measured
^trophotometrically. The two types of ELISA currently used for determining pesticide residues are
?J*ct and indirect5. Direct ELISAs involve attaching antibody directly to a stationary base, such as
J^ystyrene, and using an enzyme-linked  hapten.  Indirect ELISA involve attaching a hapten-camer
      conjugate to a stationary base and adding antibody and secondary enzyme-linked antibody. RIAs
        >lly used by medical personnel to determine levels of naturally occurring compounds such as
        ;  the major draw back is that the method requires radioisotopes,  such as I251,14C, and 3H.
         of pesticides that have been analyzed using RIAs include aldrin and dieldrin7 and 2,4-D5.
   _  sors are micro-electronic devices that employ biological agents such as antibodies as  the sensing
^signal-transducing elements8.  Typically a sensory surface is coated with antibodies that bind to an
k yte» which causes a change in  the electrical  properties of the sensor. Northrup  et al? describe the
« Velopment  and characterization  of a fiber optic  immuno-biosensor.  Westinghouse Bio-Analytical
J^tenis has developed a biosensor using a sensor plate technique1. Affinity columns are not methods
^ measure compounds but are instead trapping devices that can be used to collect a compound or class
  compounds for either clean-up  or sample preparation purposes. Affinity columns can be used in
        m with chromatography analysis such  as GC or HPLC or with ELISA. The affinity column
        has been used in conjunction with ELISA for monitoring PCP in air samples3.
      The advantages of using immuno-based methods are  that they are relatively inexpensive  as
        to GC analysis, rapid (matter of minutes), easy to operate (less training time as compared to
        spec), require less sample preparation than GC analysis, very sensitive (ppb levels - comparable
        greater than 50, HPLC and GC required from 96 to 960 minutes per sample while ELISA
        0.2 minutes  per  sample,  and HPLC  and GC had sensitivity limits of  10  and 50  ppb,
          , while ELISA had a range of 1.0 to 40 ppb. ELISA was shown to be very comparable to
       analysis for atrazine15.
                                            731

-------
      While immuno-based methods are compound specific, the antibody can be cross-reactive to
similar structured compounds. When antibody are cross-reactive, then the methods will not be able to
distinguish between the analyte and similar structured compounds. Examples of this include norflurazon
specific antibody that was 48.4% cross-reactive with the metabolite desmethyl norflurazon10 and atra»nc
specific antibody  that was 87% cross-reactive with the herbicide prdpazine4.
      Because immuno-based methods can be portable and can analyze numerous samples in short on*6
periods, methods, such as ELISAs, can  be used for large scale screening purposes.   Experience na
shown that these  methods will occasionally produce false positives but rarely if ever  false negative••
In addition immuno-based affinity columns can give analytical chemists the flexibility to rapidly iso*8
analytes by either filtering out impurities or trapping the analyte prior to GC or HPLC analysis.

CONCLUSIONS                                                                    .  ^
      Immuno-based methods have been shown to have rapid turn-around times, to be sensitive in
ppb range, and to be cost effective for analyzing organic compounds, such as pesticides and hazardo
waste type materials  in environmental soil and water samples.  Immuno-based methods are st
be used for monitoring air samples for various contaminants.  Many of the pesticides that are
hazardous air pollutants to be regulated under Section 112 of the new Clean Air Act have
analyzed by immuno-based methods and commercial ELISA kits are being marketed for these.
research must be  done with this technology because of the  inherent flexibility that it  offers to *°
monitoring management program.  Because the potential benefits involved, it is only a matter of B
before immuno-based methods are used in a regulatory fashion for air monitoring programs.
1. Immunoassav Diagnostics for Plant Diseases and Pesticide Residues. Agrow World Agrocnem
REFERENCES AND BIBLIOGRAPHY
1. Immunoassav Diagnostics for Plant Pis
News, George Street Publications Ltd, Surrey, UK, 1988, pp 53-56.

2. RJ. Bushway, B. Perkins, S.A. Savage, S J. Lekousi and B.S. Ferguson, "Determination of
residues in water and soil by enzyme immunoassay," Bull. Enviom. Contam. Toxicol.40:647-

3. A. Drinkwine, S. Spurlin, J. Van  Emon and V. Lopez-Avila,  "Immuno-based personal cXP?*fl8j
monitors."in Field Screening Methods for Hazardous Wastes and Toxic Chemicals." Second Intern**
Symposium, Las Vegas, 1991, pp 449-459.

4. B. Dunbar, B. Riggle and G. Niswender, "Development of enzyme immunoassay for the detec
triazine herbicides," J. Aerie. Food Chem.38(21:433-437a990).

5. J.C. Hall, RJ.A. Deschamps and M.R. McDermott, "Immunoassays to detect and quantitate
in the environment," Weed Tech.4:226-234(1990).

6. B.D. Hammock, SJ. Gee, R.O. Harrison,  F. Jung, M.H. Goodrow, Q.X. Li, A.D. Lucas, A.
K.M.S. Sundaram, "Immunochemical  Technology for Environmental Analysis," in
Methods for Environmental  Analysis. J.M. VanEmon and R.O. Mumma, Eds. American
Society, Washington, DC, 1990, pp 112-139.

7. J.J. Langone and H. Van Vunakis, "Radioimmunoassay for dieldrin and aldrin," R^«, ComffliilU—
Pathol. Pharmacol.lO:163-17in97SX
                                                                              ,., 16(198®'
8. C.R. Lowe, "An introduction to the concepts and technology of biosensors," THnsensorii^'1
                                           732

-------
 • M.A. Northrup, L.H. Stanker, M. Vanderlann and B.E. Watkins, "Development and characterization
of a fiber optic immuno-biosensor," in Spectroscoov of Inorganic Bioacrivators Theory and Applications
^Qbemisti^  Phygifisf Biology, and Medicine: T. Theophanides,  Ed. Kluwer Academic  Publishers,
Dordrecht, The Netherlands, 1989, pp 229-241.

 °- B, Higgle and B. Dunbar, "Development of enzyme immunoassay for the detection of the herbicide
n°rfhirazon,"  J. Aerie. Food Chem.38n(»: 1922-1925(1990).

 ]• B. Higgle, "Development of a preliminary enzyme-linked immunosorbent assay for the herbicide
^ralin," Bull.  Environ. Contam. ToxicoL46:404-409a991).

 2- J.M. Schlaeppi, W. Foy and K. Ramsteiner, "Hydroxyatrazine and atrazine determination in soil and
 ater by enzyme-linked immunosorbent assay using specific monoclonal antibodies," J. Aerie. Food
ie*JSSU37:1532-1538(1989).

.  • ^- Schwalbe, E. Dorn and K.  Beyermann, "Enzyme immunoassay and fluoroimmunoassay for the
^icide diclofop-methyl," J. Aerie. Food Chem.32:734-74ia984).

j/* L-H. Stanker, C. Bigee, J. Van Emon, B. Watkins, R.H. Jensen, C. Morris and M.  Vanderlaan, "An
  mui»oassay for pyrethroids: detection of permethrin in meat," J. Aerie. Food Chem.37:834-839f 19891

  • E.M. Thurman, M. Meyer, M. Pomes, C.A. Perry and A.P. Schwab, "Enzyme-linked immunosorbent
.  Say compared with gas cnromatography/mass spectrometry for the determination of triazine herbicides
* *ater," AjisLChenL62(18):2043-2048(1990).

r V^-0- Wing, B.D. Hammock and D.A. Wuster, "Development of and S-bioallethrin specific antibody,"
*t^ai£^FoodChemt26:1328-1333(1978).
                                           733

-------
          The Determination of Sub Part-per-Billion Levels
                  of Volatile Organic Compounds in Air
          by Pre-concentration from Small Sample Volumes
                        Norman A. Kirshen and Elizabeth B. Almasi

                            Varian Chromatography Systems
                                  2700 Mitchell Drive
                             Walnut Creek, California 94598
INTRODUCTION
    The determination of basic air pollutants in ambient air is of paramount importance as
legislative acts, such as the 1990 amendments to the Clean Air Act (CAA) of the United States, take
effect. Federal, state and local actions will ultimately reduce emissions from industrial and mobile
sources to meet the requirements of the CAA. The analytical techniques which are used to ensure
that allowed emissions are not exceeded must provide sensitive and definitive measurements of
volatile organic compounds (VOCs) in ambient air at the sub parts per billion volume/volume (ppb)
level.

    The United States was quick to initiate experimental guidelines for VOC analysis in air. The
resulting EPA method TO-14,1"5 is the most commonly used method for VOC analysis worldwide and
therefore it has been used as a guideline for the following study.

    Method TO-14 describes the analysis in ambient air of 41 VOCs, ranging in boiling point from
-29 to 215°C (Table 1). It covers a concentration range from 0.2 to 20 ppb, specifies sample
enrichment (400 mL) on glass beads at -160°C, thermal desorption, separation on a capillary coluiBfli
and detection with a mass spectrometric detector. The first draft of the Contract Laboratory Progr*01
(CLP) method6 was published in February 1991. The samples to be analyzed by the CLP method ar«
from known or suspected hazardous waste sites, therefore the concentration range is from 2 to
100 ppb, higher than required for ambient air monitoring.

    Previous work with TO-14 systems based on GC detectors7 has confirmed that volumes of
approximately 400 mL are required to obtain sensitivities of 0.2 ppb. The same requirements aPP'v.
to quadrupole mass spectrometers. Because of the very high sensitivity of the ion-trap MS, relative1/
small air volumes (60 mL) are required to obtain these or lower detection levels. An integrated
air/soil gas analysis system based on an GC/Ion-Trap MS has been investigated and is described
here. This system has a built-in cryogenic trap, internal standard gas sampling valve loop, sixteen
sample automation and is controlled from the GC/MS workstation. The linearity, precision, and
method detection levels obtainable with this system when using small volumes are reported. In
addition, examples of the quantitative and qualitative analysis of ambient air samples are shown.
                                        734

-------
EXPERIMENTAL


System Description
    The schematic of the GC/Ion-trap MS system is shown in Figure 1. The built-in trapping and
Preconcentrating device, the Variable Temperature Adsorption Trap (VTAT, Figure 2) is capable of
trapping and preconcentating VOCs from air on glass beads at -160°C or on an adsorbent such as
"arbosieve™/Carbotrap™ at ambient temperatures. In the present study only the subambient mode
was used.

                         Sample 1.... Sample 10
         Surrogate
         Standard
   Row Controller
    Carrier Gas
                                Sample
                             Selector Valve
                                                 Auxiliary
                                                 Gai
                               MurUport
                               Switching
                                VtUVM
                                 Saturn QC/MS
H
VariaUe Temperature
  Adsorption Trap
                             I          I
                            Vent or Vacuum

               Figure L   Schematic of a GC/Ion-trap MS System for VOCs.
       Cryotgrap:  2 in. glass beads
                 in stainless steel, 1/8 in.
                                                        Insulation
                                                        Heater Block
             Figure 2.   The variable temperature absorption trap (VTAT).
                                          735

-------
Instrumentation and Conditions

    Cryogenic concentrator:
          •   Variable Temperature Adsorption Trap (VTAT), 5 em of 60/80 mesh
             silanized glass beads
          •   Two automated valves, 4- and 10-poit; capable of sample and internal
             standard (I.S.) introduction
          •   Electronic mass flow controller, 0-100 mL/min, with readout box
          •   Vacuum pump (metal diaphragm)

    Pneumatics:
          Air sample flow rate:    20 mL/min
          Column flow rate:      1 mL/min He
          Auxiliary flow rate:     20 mL/min He

    Temperatures:
          VTAT:      -160°C for 4 min, 180°C/min to 120°C, hold
          Valves:     160'C
          Column:    -50°C for 6 min, 8°C/min to 160°C, hold

    Columns:
          DB-1 (J&W), 60m x 0.32 mm I.D., 1 Jim film or
          DB-624 (J&W), 60m x 0.32 mm I.D., 1.8 yon film

    Ion-trap MS (Varian Saturn II):
          Scan Range: 47-260 u
          Scan Rate:  0.8 sec/scan (3 (iscan/analytical scan)
          RF storage Level: 210 DAC Steps; background Mass: 45 u
          Segment Breaks: 70/78/150; Tune factors: 120/70/100/70
          Automatic Gain Control (AGC) Target: 20000
          Emission Current: 30 uA (Optimized parameters might vary instrument to instrument;

    Standard:
          Alphagaz TO-14 standard, 41 component, 2 ppm

Procedure                                                                           •
    In Method TO-14 a critical part of the analysis is the preconcentration step. In the first stage 01
this enrichment process the sample (generally VOCs present in low or sub ppb concentrations) i»
flushed through the lines with a flow set by the electronic mass flow controller, while the loop
(0.25 mL) is filled by the internal standard (if required). After the initial column and VTAT
temperatures are equilibrated, the air sample and internal standard are directed to the -160*0
VTAT and the VOCs are deposited onto the glass beads.

    The duration of this "trapping" time can be varied and the volume of the analyzed sample
changed accordingly. The sample flow during this step, usually 20 mL/min is held constant by the
mass flow controller. In this study the trapping time was 3 minutes resulting in a 60 mL sampled
volume. After the sample VOCs are deposited, the residual air is removed from the VTAT by the
auxiliary flow. Then the VTAT is heated to 120°C and the analytes are backflushed to the caputa**
column where they are focussed, separated, and detected. Later the VTAT is cooled down in
preparation for the next analysis.
    The main difference between I	«.	..	
in the TO-14 method is the sample size. The method specifies a sample volume of 400 mL. This
                                          736

-------
volume of air can introduce a significant amount of water that might either plug the VTAT or
capillary column. Elimination of this residual water is possible with a semipermeable membrane
dryer such as a Nafion™ dryer. The removal of water with this type of dryer results in the loss of any
^ace polar organics that might be in the sample. The sensitivity of the GC/Ion-trap MS allows trace
jevel VOC detection by preconcentrating only 60 mL of sample. This small sample reduces the
mterference of water and eliminates the need for a Nafion dryer.
    The linearity, precision, and method detection limits (MDL) were examined and real samples
Were analyzed. Before analysis, blank runs were performed. Very often even good quality
j^mpressed air has impurities. The Reconstructed Total Ion Current chromatogram (RTICC) of a
Wank and the accompanying data file is shown in Figure 3. Only trace VOCs of approximately
°-2 ppb or less were found.
    The standard and samples were introduced to the system from stainless steel SUMMA®
Polished canisters. The standard used was a 41 component, 2 ppm VOC mixture (Alphagaz) diluted
with air to the desired concentrations. RTICCs of 2 ppb and 0.25 ppb v/v standards are shown in
'/Bures 4 and 5. Gaussian peak shapes are exhibited by all the compounds including the "gases" (the
BU most volatile compounds) as shown by their mass chromatograms in the Figure 4 insert For the
Jactitation of the gases a peak smoothing algorithm was used, allowing precise quantitation of
"^se components even at low concentrations.
    The precision and MDL were determined by multiple injections of a 60 mL, 0.1 ppb standard.
 ^ndard deviations of the single ion areas were calculated for nine runs and were between 2-9%, the
8verage of the 41 compounds being 5%, Table 1.
            •u: rit s/N i
                MAM of
              4 Ich loroJ If l
                            tltfB
              CMorohnuM
              Tolum
              Allylchlorlte
              BlahlariMvthii
              TFlohlorarii
              Cu-kairUirwhlarlte
              o-Xylm
              Trlchlornrthm*
              l.l,2-trlcMor«-l,2,2-
              Tctneh lororth«i»
              Styrww
              l,l-Bldilan»tlivl«
              1.1.1-TrlcMoi  ~
              1.1.2-ti-1 eh 1 orerthaiMi
              1.3.5-TrlMtlwlUnon
              •91
                                 rit S/H
  997
  978
  969
  957
  953
  928
  913
  898
  883
  876
  869
  867
  833
  819
  889
  880
  884
  718
  784
  692
  698
  682
  661
  64G
  636
                                         R TIM
25:88
12:51
38:45
38:85
28:82
28:38
28:43
19:25
24:32
31:28
26:85
21!B9
38:32
29:18

28:27
24:31
28:18
23:85
32:44
                                                n
                                                SI
                                                    bio ftwt(A>
,185

,KB,
.116
,183
                                                         .133
,111
,878
          t
          T
          1
          1
          t
          T
                                                                       Column
                                                                       Bleed
                    600
                   8:00
 1200
16:00
         1800
         24:00
         2400
         32:00
           Figure 3.   RTICC and result file of a blank (pure air sampled) run.
      NF indicates target compounds not found (below minimum spectral fit value).
                                            737

-------
         Table 1  Quantitation Ions, Retention Times, %RSD and Method Detection Limits
                               for Analytes in Method TO-14.
Compound
Dichlorodifluoromethane
Chloromethane
l,2-Dichloro-l,l,2,2-tetrafluoroeihane
Vinyl Chloride
Bromomethane
Chloroethane
•Tricblorofluoromethane
1,1-Dichloroethylene
Dichloromethane
l,l,2-Trichloro-l,2,2-trifluoroethane
1,1-Dichloroethane
c-l,2-Dichloroethene
Chloroform
1,2-Dichloroethane
1, 1, 1-Trichloroethane
Benzene
Carbon Tetrachloride
1,2-Dichloropropane
Trichloroethene
c-l,3-Dichloropropene
t-l,3-Dichloropropene
1,1,2-Trichloroe thane
Toluene
1,2-Dibromoethane
Tetrachloroethene
Chlorobenzene
Ethylbenzene
m,p-Xylene
Styrene
1,1,2,2-Tetrachloroethane
o-Xylene
4-Ethyltoluene
1,3,5-Trimethylbenzene
Benzyl chloride
1,2,4-Trimethylbenzene
m-Dichlorobenzene
p-Dichlorobenzene
o-Dichlorobenzene
1,2,4-Trichlorobenzene
Hexachlorobutadiene
Quan
Ion
85
50
85
62
94
49
101
61
49
101
63
61
83
62
97
78
117
63
130
75
75
97
91
107
166
112
91
91
104
83
91
105
105
91
105
146
146
146
180
225
RT*
(min)
13:05
14:11
15:11
15:30
16:56
17:36
19:23
20:25
20:42
21:07
22:10
23:08
23:28
24:14
24:30
24:59
25:08
25:50
26:05
26:59
27:32
27:43
28:03
28:47
29:19
30:06
30:33
30:47
31:12
31:19
31:21
33:02
33:09
33:15
33:45
33:58
34:05
34:37
37:56
39:11
%RSD**
(area)
3.8
8.5
3.5
6.0
4.7
9.0
3.2
5.6
3.9
3.8
4.8
4.4
3.7
4.1
4.6
3.4
3.4
2.9
3.8
4.7
5.7
3.9
2.4
2.9
3.5
3.8
4.6
2.9
6.2
4.7
6.0
7.0
8.9
10.1
10.3
3.2
4.3
4.8
9.3
8.0
MDL
(ppb)
0.01
0.03
0.01
0.02
0.01
0.03
0.01
0.02
0.01
0.01
0.01
0.01
0.01
0.01
0.01
0.01
0.01
0.01
0.01
0.01
0.02
0.01
0.01
0.01
0.01
0.01
0.01
0.01
0.02
0.01
0.02
0.02
0.02
0.03
0.03
0.01
0.01
0.01
0.03
0.03
*RT includes the concentration step also, column DB-1
**%RSD calculated from area responses of 9 replicate runs.
                                         738

-------
TOT-
A



/NCClaFa
j\ CH3<

^CClPjCClF
="A
y\CH2CClH
_ /\ 	 '
^\ /\,, A-> 	 A,,,
                                                             M
    8=88

Figure 4.
                            12BB
                            16:80
                              1888
                              24:88
2488
32:88
3888
48:08
                     RTICC of 41VOC compounds, 60 mL, 2 ppb
                   and mass chromatogram of the gases.
   TOT

il
1
1





.1
w»r
Lf



                   120B          1888          2488
     8:80          16:88         24:88          32:08         48:88

         Figure 6.  RTICC of 41 VOC compounds, 60 mL, 0,25 ppb v/v
                                    739

-------
     The MDL was calculated from integrated areas of single quantitation ions (nine replicate runs)
 with the following formula:

                    MDL=sxt

 where s is the standard deviation of the replicate analyses and t is the student's t value appropriate
 for a 99% confidence level and a standard deviation estimate with n-1 degrees of freedom. The
 calculated MDLs were between 0.01-0.03 ppb.

     linearities of the quantitation ion responses versus concentration for the 41 components were
 examined over the range required in the method, 0.1 to 20 ppb v/v, and were found to be very good.
 Representative linearity plots are shown in Figures 6a and 6b.

     In addition to identifying and quantitating target components in a sample it is often necessary
 to identify and estimate the quantities of non-target analytes. For example, dibromochloromethane,
 a non-target analyte is identified and its concentration estimated at 2 ppb in Figure 7a.

 INTERFERENCES
     In ambient air some components are present at much higher concentrations than the VOCs. The
 two most significant components which are concentrated together with the VOCs from the air are
 water (mentioned above) and 002. The reduced sample volumes used here suppress the problems
 caused by these components. For example, to represent a very humid sample, an air sample was
 collected just above the surface of a 60°C water bath. At this temperature the vapor pressure of
 water is 0.2 atmospheres. The chromatogram and results shown in Figures 7a and 7b indicate that
 the preconcentration process was not affected by the high level of moisture.

     Carbon dioxide which is also present in air at high concentrations can be eliminated as an
 interference by choosing the scanning range from 47 to 250 u and setting the background mass at
 45 u. Then C02 (44 u) is not stored or detected by the Saturn mass spectrometer and the detection of
 the early eluting VOCs is enhanced.

 APPLICATIONS
     Two sample applications are shown using the same conditions. The first sample shows a
 chromatogram and the resulting report from ambient air collected in Walnut Creek, California on a
 rainy day in rush hour traffic (Figures 8a and 8b). The aromatics which are the major components of
 exhaust gas emissions found under these conditions are evident The second sample was collected at
 an industrial  site to screen for several polar organics. The RTICC and the mass chromatograms at 31
 and 45, characteristic mass ions used to quantitate methanol and ethanol, respectively are  shown in
 Figure 9.

 CONCLUSIONS
    An integrated air/soil gas analysis system based on a GC/Ion-trap MS has been investigated and
 applied to the analysis of VOCs following EPA Method TO-14. The very high sensitivity of the
 ion-trap MS allows the use of relatively small air volumes (60 mL) to obtain both qualitative
 confirmation (full scan spectra) and quantitative determination of sub ppb levels of VOCS. MDLs of
 0.01-0.03 ppb  have been calculated from multiple runs at 0.1 ppb.

    Since water interference is minimized using this small air volume, the use of Nafion dryers has
been eliminated allowing the determination of polar u well as non polar organic compounds.
                                          740

-------
      Area of Sanpla) iw (AMwttt cf Stnpl* Injected)
"W.
          5.888         1B.MM        15.888        28.888




        Figure 6a.   Linearity of Bromomethmie, 0.1-20 ppb.






oT Sanplo) v» CAMMint of Sanplo  Injocted)
                                                        I.H*  i.in  i^iii' 'sitti' 'iiiiii' 'l
                   G.eea        le.eae        ts.aae        2e.eee



              Figure 6b.   Linearity of lA4-Trimethylbenzene, 0.1-20 ppb.
                                          741

-------
    TOT
                 1B6-
                                 AM-
                                                   Sample
                                                 -
                                                   Library
                                  4^
     40    60    66   168   128   148    168   180

ForwU: C.H.CI.Br2
               COa
               (In this analysis the muss range
               was 35-250 u, therefore, COj
               was detected)
                                                    S-2PPB
        H
      18:48
  1200
  16:06
 1600
21:28
                                              2000
24BB
32:00
2B8B
37:28
Figure 7a.   RTICC of 60 mL air sample collected above the surface of a 60°C water bath
        dibromochloromethane, a non-target analyte is identified (fit 903/1000),
                           estimated concentration 2 ppb.
    Sorted via:  C*lc AnountCA)  *
C.1
23
15
36
2
16
33
34
39
9
31
29
27
35
28
7
71
•M
5
13
18
1
26
32
25
24
22
14
KOMB of Oonpound
Toluene
1 , 1 , 1 TP Ich 1 oroeth*ne
Bonxy Ichlorldo
Oi loroMrtlwirai
BMMM0
1.3.5-Trl—thylbertH.n.
1 .2 ,4-fr 1 no thy lbenx*ne
1 12 »4— TP Ich toroberaEene
D leti lorcwethane
o-Xylone
Styrano
E t hy 1 heracene
ir-D IcJi loroberoen*
n,p-Xy lane
IT 1 ch 1 orof 1 uor*o*« thine

Broncmethtne
Chloroform
l,1.2-Tplchl€iro-l,2,2-
41chlorodlf luorunelhin
CA 1 OPO bensene
4-Ethyitoluene
^1 • « * l,«w
TwtFACli loravwiene
EDB
1 . 1 ,2-Tr Ich loro*t}i*ne
1 . 2-D i ch 1 oroeth&ne
rit SXM
962
B2S
949
821
963
987
989
937
941
985
998
963
939
987
994
7V6
964
971
979
937
877
98S
764
858
784
636
R Tine
Z7:S5
24:26
33:51
13:S9
24:54
33:39
33:39
3?:St
20:48
31: 15
31:86
38:2?
33:53
31-15
19:21
27:26
16:53
23:26
21:66
12:S7
29:59
33:19
29=27
28:40
27:19
24:10
He
UB
BU
W
BB
W
W
w
BB
BU
BU
BB
UB
BU
BU
BU
uu
BB
BU
BB
BB
BB
BU
BB
BU
BB
BU
Calc tat(A)
5.220
1.661
6.793
8.655
8.605
6.593
8.587
6.510
0.499
6.456
0.362
0.347
0.364
0.252
0.248
0.243
8.217
6.194
6.165
8.149
0.143
0.143
0.133
• .879
0.071
0.043
Unite
PPB/V
PPB/V
PFB/V
PPB/U
PPB/V
PPBXV
PPBA»
PPBXU
PPB/V
ppB/U
PPB^I
PPB^U
PPBXU
PPB/V
PPB/V
PPB/U
PPBXU
PPB^
PPB/V
PPBXV
PPBA*
PPBXU
PPBA»
PPB/V
PPB^U
PPB^I
          Figure 7b.  Quantitation Report of the Sample Shown in Figure 7a.
                                         742

-------
TOT
           78

5


a

LJ
BENZENE

95
128 152 ZZ2
     -I "  r
          1588
          20:15
                                                   91
                                               SB
                                                       0-XYLENE
                                                          165  223
Z1BB
28:21
24BB
32:24
27BB
36:27
  Figure 8a.   RTICC of 60 mL air sample collected in Walnut Creek, California
                       on a rainy day in heavy traffic.
Cal
23
28
31
33
32
27
16
36
29
25
34
22
14
Ha.no of Compound
Toluene
w,p-Xylene
o-Xylene
1 j 3 , S-Tr 1 MO thy 1 benzene
4-Ethyl toluene
Ethy 1 benzene
Benzene
Benzyl chloride
Styrene
Tetrach loroethene
1 j 2 , 4-Tr inethy 1 benzene
1 1 1 j 2-Tr 1 eh 1 or oethane
1 , 2-D 1 ch 1 oroe thane
Fit S/N
993
995
989
994
995
993
978
890
729
913
995
787
758
R Tine
27:24
38: 18
30:46
33:14
32:26
29:57
24:20
33:51
38:46
28:42
33:57
28:03
24:20
Me
UB
W
BU
BB
W
UB
BB
W
MM
MM
MM
MM
mi
Calc AnttAJ
5.927
3.105
2. 257
2.151
1.584
1.455
0.981
0.689
0.356
8. 280
0.222
0.175
8.152
Units
PPB/U
PPB/U
PPB/U
PPB/U
PPB/U
PPB/U
PPB/U
PPB/U
PPB/U
PPB/U
PPB/U
PPB/U
PPB/U
      Figure 8b.   Quantitation Report of the Sample Shown to Figure 8a.
                                    743

-------
      SSX
     TOT
    B.31*
       U
                    HETHMKM.
                  12M
                                             24:
21M
2S M
       Figure B.   RTICC aad characteristic tons for methanol and ethanol from a
                     60 mL air sample collected at an industrial site.
                Courtesy of Air Toxics, Ltd., Rancho Cordova, California.

REFERENCES
1.  Compendium Method TO-14, The Determination of Volatile Organic Compounds (VOCs) in
   Ambient Air Using SUMMA Passivated Canister Sampling and Gas Chromatography Analysis.
   US. Environmental Protection Agency. Research Triangle Park, North Carolina 27711, May
   1988.

2.  K.D. Oliver. J.D. Pleil, and WA. McClenny. Sample Integrity of Trace Level Volatile Organic
   Compounds in Ambient Air Stored in SUMMA Polished Canisters. Atmospheric Environ.
   20:1403,1986.

3  M W Holdren and D L Smith. Stability of Volatile Organic Compounds While Stored in
   SUMMA Polished Steel Canisters. Final Report, EPA Contract No. 68-O2-4127, Research
   Triangle Park, North Carolina, 1983.
4.  W A. McClenny. J.D. Pleil. J W Holdren, and R.N. u_*_,.	, -,-—
   Preconcentrition and Gas Chromatograph D^ermin«tkm rfVolatfl. Orfank Compounds. Anal.
   Chero 56^2947,1964.

5.  W A McClenny. et, •!., Canister-based Method for Monitoring Tone VOCi in Ambient Air, J. Air
   Waste Management Association, 41. No. 10.1306.1991.

6  Analytical Method for the Determination of Volatile Organic Compounds (VOCs) in Air Collected
   in Canisters and Analysed by Gas Chrematagraphy/ Mass Soectrometry (GC/MS). Exhibit D,
   Chapter 1, Part LA. Contract Laboratory Program, February 1991.

7  Eliiabeth Almasi and Norman Kirshen, The Anatysia of Volatile Organic Compounds in Air,
   Variable Volume System, Varian GC Application Notes 19 and 33,1969 and 1990, respectively.
                                          744

-------
  PERFORMANCE ASSESSMENT OF THE PORTABLE AND
    LIGHTWEIGHT LOZ-3 CHEMILUMINESCENCE TYPE
                          OZONE MONITOR


              LesII A. Topnam, Gervase L Mackay, and Harold L Schiff
                           Unisearch Associates Inc.
                            222 Snidercroft Road
                      Concord, Ontario  Canada L4K1B5


ABSTRACT
      The model LOZ-3 ozone monitor is described. An internal battery makes the
monitor portable and therefore ideal for studies of indoor air quality, measurements from
aircraft, and other mobile platforms where power may be limited. Ozone is measured by
u*ing its chemfluminescence with the dye Eosin Y. In comparison with ethylene based
ozone detectors, the LOZ-3 has better sensitivity and does not require a bulky and
Jlfinificam interferences in polluted air (presumably due to organic compounds that absorb
Performance assessment u preparation Kir EPA equivalence method approval testing and
*o is similar to EPA test procedures. Similar data for ethylene based detector and a
Photometric detector is described.
lne**ures ozone concentrations via the chemfluminescences of Eosin in solution. This
Portable unit demonstrates excellent performance characteristics when compared to other
p°ne monitors. Fast response, good precision and no interferents, as described by the EPA
Interference Equivalent test requirements, are Just a few of the instruments performance
Spabflitics. Comparisons with thel>asibi 1008 Ozone Analyzer1 and Ethylene
Mlenifluminescent Ozone Monitor* are made.


DESCRIPTION OF THE INSTRUMENT
u.    A schematic of the LOZ instrument is shown in Fig. 1. This analyzer draws 1.5
{ripAain. of sample air into the unit and across a fabric wick that is continuously flushed
V?* * specialty formulated solution containing Eosin. A red sensitive photomuftipUer tube
,"** the light signal from the chemfluminescence at the liquid/air interface. The Eosin
•option returns to the reservoir to be recirculated for approximately one month.
fa    The computer controlled analyzer operates on line or battery power. The battery is
.r*111*! and powers the unit for 4 hours between re-charging. Corrections for temperature
       isure are performed by the computer. The analyzer is configured for automatic
       ' f periodically drawing the sample air through an ozone scrubber. The zero signal
        1 can then be electronically subtracted if the user so desires.
                                    745

-------
INSTRUMENT PERFORMANCE ASSESSMENT

Response
      LOZ response is very fast. The lag time is determined from a strip chart running at
high speed. The elapsed time between the introduction of 400 ppbv of ozone and the first
observable (two times the noise level) response is the lag time which is 2 seconds for the
LOZ. The rise time of 3 seconds is also determined from a strip chart but as the elapsed
time between the first observable response and 95% of a 400 ppb signal. The fall time of
the LOZ is 2 seconds. This is defined as the elapsed time between the first observable
decrease in a 400 ppb signal and 20 ppb.  The Dasibi 1008 reports a response time of 50
seconds for 99% of the final value. The EPA test results for the Ethylene Monitor are; 6-12
sec. lag time, 48-72 sec. for rise time, and 78-120 sec. for fall time. It is clear from these
figures that the LOZ is a significantly faster responding analyzer than either of these two
popular ozone monitors. Fig. 2 shows a comparison of the LOZ and the Dasibi 1008
responses to the introduction of 400 ppbv of ozone.

Noise
      The LOZ signal noise is reported at 0 ppbv ozone and 382 ppbv ozone which is
approximately 80% of the upper range limit (URL) of 500 ppbv. The unit samples a steady
source of ozone from an UV lamp type generator that is also monitored by our Dasibi 1008.
Signal averages are taken every 2 minutes for a total of 25 points, then the standard
deviation is calculated to be 0.05 ppbv for 80% URL. Zero air is supplied from a cylinder
and the same calculation is applied. This results in a standard deviation of 0.04 ppbv for 0%
URL. The Dasibi Analyzer reports a general value for noise as 1 ppb and a stability of +/- 2
ppb at 500 ppb. EPA tests report a noise range of 0 -1 ppb for 0% URL and 1 - 3 ppb for
80% URL tor the Ethylene Monitor.  The LOZ signal noise at zero ozone compares very
well and both are well within the EPA standard of 5 ppb.

Precision
      Six repeated measurements taken at 100 ppbv and 400 ppbv of ozone are expressed
as one standard deviation about the mean for each ozone level. At 100 ppbv or 20% URL
the precision is 0.80 ppb and 1.87 ppb at 400 ppb or 80% URL. Precision for the Dasibi
1008 is listed as 2-1 ppb. The EPA test results for the Ethylene  Monitor report 0-1 ppb at
20% URL and 1-6 ppb at 80% URL.

Calibration Curve
      The Eosin solution is sensitive and consistent in its response to ozone. The solution
is linear in it response up to approximately 200 ppb of ozone. From 200 ppbv to 500 ppbv
the response begins to drop. However, the solution maintains it calibration curve over a
period of one month, which is the maintenance interval for changing the Eosin solution.
This is illustrated in Fig. 3 where the LOZ was compared to the calibrated Dasibi 1008 and
the 1:1 line is added.

Temperature Effects
      Temperature changes after the sensitivity of the Eosin solution. As with most
reactions increases in temperature causes increases in sensitivity. The effect is linear and
the LOZ's computer is programmed to make the necessary corrections. Fig. 4 shows the
uncorrected signal changes with respect to temperature. The linear regression line has been
added to the plot and has a slope of 10 ppby°C. When the program correction is active the
signal changes only 5% over the temperature range 10°C - 41°C.

Interferences
      The Luminox Ozone Analyzer signal is not affected by most common air pollutants;
NO, NO2, HNO3, H2O2, NH3, H2CO. Investigation with SO2 revealed an interference
                                      746

-------
dependent upon the age of the solution. Fig. 5 shows the changing effect of SOj on the
Eojsin solution. The interference is large when the solution is first placed in the unit but
Quickly diminishes approximating an exponential type of relationship with time. The EPA
Interference Equivalent limit is +/- 20 ppb at 80 ppbv of ozone and 300 ppb of SC*2 or 25 %
as shown in Fig. 5. This limit is reached within 3 days of the solution's initial use in the
instrument Storage of the Eosin solution over a 3 month period did not lessen the initial
Positive interference.
      A ore-treatment technique developed in the Unisearch laboratory reduces the initial
effect and brings the Eosin solution response to SO? within the EPA guide lines.  An
increased reservoir volume insures compliance to EPA standards for one month.  CO2 also
causes a positive interference of 37% at 80 ppb of ozone and 750 ppb of CO^ The pre-
treatment technique reduced this interference to a 0% change in signal

CONCLUSION
      The LOZ analyzer demonstrates excellent performance characteristics when
compared to EPA equivalent method requirements and other ozone monitors. It has
several advantages. The compact size and internal battery power option allow the unit to be
used in many applications. No large cylinders are required and the exhaust is non-polluting.
The fast response time is ideal for aircraft measurements. The Eosin solution pro-treatment
technique eliminates all known interferences.  Computer control makes operation simple
and the one month maintenance interval reduces overhead time.

REFERENCES
        sihi
      slphia, 1990.
B Analyzer Operating and Service Manual. Dasibi Environmental
                                               iirementby
                                                .terials,
              Test Method for Ozone in. the Atmosphere: Continuous Mi
                          D 1 5149 1- 90, American Society for Testing and
                    MEASURE AOOE
                                                         REACTION CELL
                                                  •b>olut«
                                         flltar    pr«»ura
                                                   ••nsor
               •Ir pump

            •xhousl
              Pimiihtiij aghM
                                      747

-------
               500
               400
               300
               200
               100
              -100
                                                        400
                                     Tim* (••condi)

                                   LOZ   +  Doilbi 1006
Figure 2.     Comparison of the response times of the LOZ and Dasibi 1008 to the
introduction and removal of 400 ppb.
               500
               400 -
               300 -
         N     200 •
               100 -
                        +  r«b 34  o  F«t> 28  A  Mor 2   «  Mor 6
               D  F*t> 12
Figure 3.     LOZ calibration curves for a one month period as compared to a calibrated
Dasibi 1008.
                                         748

-------
                uo
                660
                «40
                920
                MO
                SCO
                960
                940
                520
                900
                410
                4(0
                440
                420
                400
                340
                3M
                340
                320
                     10    14    IB     22     2«    •»
                                    Timpiratur* (Ctteiui)
                                                        34
                                                              31
                                                                    4i
                        D  LOZ  +  LOZ
                                         DotrOl
                                                  linigi ngrntton
Jpwe 4.     Temperature Effect on the uncorrected LOZ signal is 10 ppb/°C The LOZ Is
Itt°(nunmed to correct tills temperature dependence.
               100*
                9H
                8M
                THI
                40*

                "*
                jox
                IOX
                 0%
               -IM
               -20X
               -3CW
-   D
                    H-F.D
                            • tt-f*,
                                     20-r»b
                                              J4-F«fc
                                                      2»-f+
                                                               04-Hor
                                          OATt
                    a  [S02] - 900 PPSV   * [SCO] • 1*1 PPBV  	 29* ERROR BW»
      5.     SO2 Interference over* one month period which is
   ""ft pre-treatment
                                               eUmtnated by
                                         749

-------
  Measurements of NOy, NOx, and NO2 using a new Converter-Sequencer

                        and sensitive LuminoxR Detection
          John W. Drammond, Paul B. Shepson*, Gervase L Mackay, and Harold L Schiff

                        Unisearch Associates, Inc, 222 Snidercroft Rd.

                                Concord, Ontario L4K IBS

                "York University, Department of Chemistry, Downsview, Ontario.

ABSTRACT
      A commercial instrument for measuring NCk NOx, and NOy is described, where NOy ** NO +
NO2 +  HNOs + HC^NOz + 2 * N2O5 + PAN + alkyl nitrates +  nitrate on aerosols + ... .
Measurements of NOy are important because the sum is a conserved quantity that varies only with the
sources  and sinks of its component  species  and  not on fast or complex chemistry.  Potential
applications for NOy measurements are listed.  In one application, NOy would constitute a pollution
index taking into account both the source for  NOy (possibly NO from automobiles), and the sinks
(possibly dry and wet deposition of HNO3). In another application, the amount of smog (ozone +
PAN) within a moving urban air mass can be predicted from earlier measurements for the NO/
content in the source region. NOy is strongly coupled to ozone production/destruction chemistry. The
fast sensitive measure of NOy provides a method for detection of explosives.
      The NOy converter in the model LNC-3M converter/sequencer consists of a hot stainless steel
tubeppcrated at 400 °C At this temperature, two otherwise difficult to measure NOy species, namely
HNOj a"d*soPr°pyl nitrate, have been  shown to convert at efficiencies approaching 100%.  The
resulting NOx (NOx - NO + NO^ is then measured by using a QOj converter upstream of an LMA-
3 Luminox1* NO2 analyzer.  In  addition to the NOy converter, the LNC-3M converter/sequencer
23jT? number of improvements that remove residual interferences against NO, from 03 and
KAN. Die problem of non-linearities at  small (<2.0 ppbV) NO, mixing ratios is solved by a small
standard addition of NO2 to the sample stream.
 INTRODUCTION
      The use of the sensitive chemfluminescence between NO, and a solution containing luminol has
 been used as a basis for detection of NO, for over ten years'. The commercial model LMA-3 NOi
 analyzer has been marketed since 1985>. Because the luminol/NO2 chemfluminescence is about one
 thousand tones stronger than NO/O, chemfluminescence, small, portable instruments can achieve
 detection limits and response times significant^ better than the larger instruments that measure NO
 using NO/O3.  As was the history of NO instruments, the Luminoi* detector is now being used for
 other purposes other than straight forward measurement of NO* We list a few of the applications for
 the Lummox* technique:  1)  A miniature NO, sonde> (model NO,SON)  makes vertical profile
 measurements for NO; in both the dean and dirty troposphere as well as the stratosphere. 2)  The
 computer based modelLPA-4 PAN anaryzer* uses a buflt-in NO, detector to analyze effluent from a
 GC, thereby insuring fast and interference free measurements for PAN. (NO, and NOx can also be
 measured). 3)  The  model LNC-3 converter/sequencer' is used with the LMA-3 to enable the
 measurement  of NOx (- NO2 + NO) as well as providing automatic NOj and zero readings. The
 LMA-3 has also been used to measure the photolysis rate coefficients for several alkyl nitrates1, and in
 a GC mode to  detect NO fluxes from soils*.
      In this oaper we concentrate on the measurement of NOy using the converter/sequencer, model
 LNC-3M.  NOy, sometimes called "odd nitrogen" consists of the sum of several atmospheric nitrogen
 containing species. (NOy = NO + NO, + HNO, + H&NO, + 2 * N2O5  + PAN + alkyl nitrates +
 nitrate on aerosols + ...). Note that NX), NHj, Nj, and HCN are usually not included in NOy.
      NOy is  a conserved quantity. The amount of NOy in a given air mass is dependent only on
sources and sinks of its component species, and not on interconversion chemistry taking place. Thus,
NOy is a measure of the amount of nitrogen containing "pollution11, independent of the air mass's age.
 In a given air mass, automobile exhaust (containing NO) may be the primary source of the NOy, while
                                         750

-------
 C| D n i>4 _i
'nodelst,?^ deP°si«ion of HNO3 could be the primary sink.  NOy can be used as a tool in chemical
»»e of raf;Qles t° study the fate of the various species or even to assign the source of an air mass. The
air m J   of the target chemical to NOy can be used to account for entrapment of cleaner air as the
*as causel??'  For example> the ratio of CO to NOy can be used to determine whether the pollution
     ,,* <| &y a power plant or automobile exhaust7.                            .
recOfini7^,0lmP0rtance of the coupling of nitrogen chemistry with ozone production has Jong been
         '  to Backround air  the  measurement of NOy, especially m the stratospheric polar
   et n               oy.  n poue    ,
*o>0g ral larnoum of NOy contained in the present air can be used as a predictor for the amount of
^tfoitenf S? and PAN) that will be formed during the day as the air mass moves to the suburban
     j?1 we city'*.
^es X?* fi™1 application for NOy measurement is for explosives monitoring. For example, land
             ication for NOy measurement is for explosives monitoring. For example, land
  -muung dynamite could be located  by their nitrate vapors.  The discrimination against
  N°* can be achieved by time modulating the position of the inlet tube or by using two parallel
°£ Qualitative tests have already been tarried out for TNT and EGDN, and nitroglycerine.
 I Tn0^?land fi11 sites, hazardous vapors could be monitored, and hot spots located
 until now, two techniques have been used to measure NOy, both use the chemiluminescent NO
 I A° Monitor the effluent of a converter. The first method uses a molybdenum converter (see
 ' D«*ereon») and the second uses a gold converter first reported by Bolhnger et a£ ffd further
      Fahey et al»  The gold converter requires the addition of high punty CO in order to
      J Surface art™*   It eihrtiiM h/» tvnflflted aeain that  the "NO? CO
                                              LI tD 14.*** wviMinw*.* *•**• *"O^  r ^^  f
****£'*?P surface active."it should be repeated  again that the "NO2" converter used on most
'WffiS No^NOx monitors is typically molybdenum, and that the converter measurement does pot
*Sffevbut No* Plus severalof the NOy species as well.  It should be stressed, however, that to
^Pleli   7* ^ractly, the converter should be mounted outdoors at the sample inlet to avow tne
     «jrie losses of the NOy species f such as HNO*) which are sticky.
** a NcS^M uses the Lumincar* LMA-3 as the NO2 detector. The thermodpamic processes
only SS^Pj converter aVe enSgetically less demanding than for NOy/NO.  Simple pyrolvsis is the
F^fiffS? 'tep  to generate th?NoTfrom most species of NOy  In the case of flic' NO «toa*j
^esV**6 sample air (or perhaps generated in smaU quantities from pyrolysis of one of the NOy
    "Ait must be  converted to NO,. This is accomplished by using CrOj*.
  ji^Ws vear we win extend thesi NOy measurement capabilities by introducing a general purpose
  S^ detector for nitrate-containing compounds.  Each may be separated and identified by using
  32*** for the effluent fromatfaHopdaiy GO. The principal advantages for usrng a nitrogen
         rtnr ,•-.*_T7 _i\?  „. r_^V__*!_ -f-»*^« ™»,nirp Afie>.rtnr fP.CD) are 11 the resulting
              <= euent  om aaH opuy     .
            r instead of the morl^mnJon electron capture detector (Edft are  1) & resultuig
            is an order of maimitude simpler since chlorinated compounds are rejected in tfte
                                                                ce the deector does not
                        imituue simDicr suite u.uuii»«inju wuui^» —»»—. —- —j	— —  -
                        Such faster throughput is achievable since the debtor does  not
to. t	.uiu^pnenc oxygen or to water vapor.  3)  Because of the LuminoxR sensitivity, no
lcei»tration device is required.
        maHc diagram of the LNC-3M converter/sequencer.  There are four flow paths that are
        the solenoid valves. The waste air purge system serves to continuously flush the unused
        to insure that a fresh sample is always available.
                                         751

-------
 INSTRUMENTATION

 toeetheT'Sth^^MA^?118 H^ *?ed? Wu ret Carried But using a model LNC-3M converter/sequencer
 refced  wi?h  adShLS,  ™,-  ** ^ LuminOX  techn^e, NO, contained in the sample gas *
 cnemnumTnescence of   , i  ^S?1"18  lummo1  on the  surface  <*  a  wetted  wick.  A strong
            * r «  »*. wdvcicngtn centered around 425 nm K vieu/^H Vn/  T \yf A "7 ^-^A                     '**-» J^LU ia vicwcu uy d  ujiULvjuiuivJuiJi-'i- **
 in Sch.ff et aK                 ' mtercompanson of NO2 by tunable diode laser spectroscopy is given


 Description of the LNC-3M








  ed for^.Kh^tS? converter func^ns well between 5 and 60% relative humidity.  If dry air is being
 nSJi £    I  u°n Pu,rP°ses» humidity from the waste air purge system (unused sample inlet) will be
  iaea through the  shell drier. Valves VI, V2, and V3 are laree Teflon valves that rrmtrol the flow ot
 the sample air to the LMA-3.

       tsteeel°n^Cti0n  ^^ ^ c?riverter is  shown in  figure 2.  It consists of a folded coaxal
            V^ ^  ' an  is.mtfnded to be mounted vertically outdoors on the sampling tower.  1
           I °? th^ ^?rtf is  thennostated to 400 ±0.5 °C.  Like  the LNC-3M sequencer unit, t
                 1 VDC, thereby insuring safe operation even in remote locations? The short id®
    J cm long) is internally lined with Teflon.
       The NOx converter is located in the indoor sequencer unit.  The NO to NO7  converter, ftj

    surements1Vaffo,fand fUIther devel°Ped bv Wer»del", has been incorporated to enable accurate
     itrf       kcorporated into the LNC-3M that effectively remove a3J residual
hneanties and interferences previously associated with the basic chemilumifiescent technique:
s(re££ wruTeVaSf^^^                wWch removes >99% * the ozone frol, the sample
2)  The  normal zeroing scrubber supplied with the LNC-3M

       m      0ptlonaUy' a zeroin8 scrubber that effectivejy
                                                                    removes
                                                                                         .
                                                                                         1S
 ! ^ °TWM?^P?rea!i0n SyStem ? r N°2 Provides a standard ad*tion of approximately 2 ppb V NO2
 3 the LMA-3 thereby insuring that the LMA-3 remains in its linear ranee  The LNC-3M's zero
sequence provides the necessary reference zero for the sample air.

Laboratory testing.
upwardo avoid
                                                             allow efficient excellent
                                                       °n the Sam     mast.  A fan
                                           752

-------
         bubbling its effluent through standard KOH ^»ti°* ¥?n°°^Sf *e Tj^SLSSj
   meter.  Commercial ACS grade isopropyl nitrate was diluted 1:10 in dodecane. A thennostated
   *ion tube ^^plo^to^upp? a ttfte stream of calibration gas to ^.^Nmg£JJ
    oped that the moh-bVlenum converter would have ^PP^ ^^^ y^^Sf^S
Educed by the technique, but the Luminox^method gave much ^SSSfSS nSFSSm and




of the LNC-3M, and the third wai a hot quartz tube operated at temperatures up to 700 "C.

  ISCUSSIOV




repeated here, but with special emphasis on the NQy conversion efficiency tests.
tfcB


  * N°*
                                   of
^^^^^^^^&^
nSf*"** "* Cla°<»°*»* A- °Ps ? "PT "S^cw £T££?daun£fod tliat>97%


•iXljf ej  *    «"xj»w\i usi tsUl 4 bv LirfW vj ••**•—*»  - -
sa^gjnal. fe the tests, below, this correction has been


  r°tog scrubber

»«te^^2M?^^
SSL??** *a« paVses nea7h7lOO% of PAN is used. Since the interference appears fa


foJJ^QS) during the summer of 1990. The scrubbers must be replaced weekly instead of twice yearly
  "« standard scrubber.
       ?**" » «»d that chemically oxidizes >99% of O, while passing >90%of 1^ fa Ae
        J-NC-3M, the scrubber is buflt in uptream of the NfePf^ea?°^S;flte?!SS 21
        J?88 fa independent of the NOj m&ng ratio, the LMA-3 should be calibrated with the
        une. No further corrections are necessary.                 .«i «-M .mdfM« tew

             ^a^ia^J^^
                                  753

-------
 scrubber for time periods shorter than 5 minutes, transients in the ozone/luminol kinetics can cause an
 apparent reduction in the NO2 mixing ratios reported by the LMA-3.  The ozone scrubber is required
 in the LNC-3M since ozone is removed in both the NOy converter and the zeroing scrubber. Without
 the scrubber, ozone induced transients in the LMA-3 are cause undesirable artifacts as the modes are
 sequenced.

 NOy conversion efficiency tests.
       Each day that tests were run, two LMA-3 NO2 analyzers, together with their sequencers, were
 calibrated and zeroed by using the  NC>2 calibration supplied by the permeation tube and the known
 flow of zero air (21.1 ppbv).  Since both  LMA-3s were used  as detectors  downstream of the
 sequencers, the normal automatic sampling sequencing program was used during the calibrations and
 testing. This removed any artifact that could  have been attributed  to mode switching or time delays.
 Two parallel  instruments were always run from the sampling manifold in order to give an immediate
 indication of drift or mixing  problems.  Three  NOy converters (400 °C  stainless steel, 400 °C
 molybdenum, and 700 °C quartz) were tested, two at a time. The  branching ratios of NO and NO2
 were also determined as a function of temperature for each converter by placing the NOy converter
 upstream of the sequencer for NOx.
       The NO/NO? conversion efficiencies were verified weekly by supplying known mixing ratios of
 NO  (typically 35 ppbV) to the sampling manifold.  98% of the known NO mixing ratio was recovered
 as NO>2. The  loss of NO in the various NOy converters was always less than 1%.
       A number of tests were made using flow streams of isopropyl  nitrate in the three converters as a
 function of temperature. A comparison between the gold converter and a molybdenum converter have
 already been  carried out10 using n-propyl  nitrate instead of isopropyl nitrate.  In those tests, the gold
 converter (at 300 °C) converted 76% of the reference flow (gold converter at 725 °C) while the
 molybdenum  converter (400 °C) converted 68%. In our tests, using quartz at 700 °C as  a reference,
 60% of the isopropyl nitrate was converted by molybdenum at 399 SC. We were able to  increase the
 conversion efficiency to 83% by continuously adding 0.022% H<> to the sample air.  This process is
 analogous to adding a small stream of CO to  a gold converter.  The LNC-3M, with its stainless steel
 converter operated at 400 °C, gave a conversion efficiency of 97%, as compared to the reference.

 CONCLUSION
       The LNC-3M converter/sequencer is  described.  In conjunction with the LMA-3, the first
 commercial NOy detector is now available. It allows state of the art monitoring of NO2, NOx, and
 NOy, and without the need for either hazardous high purity CO or the necessity of daily regeneration
 of a  molybdenum converter.  The above modes for the unit were  tested for NO2, NO,  HNOi, and
 isopropyl nitrate.  The instrument demonstrated nearly 100% conversion for all four species. In the
 case of the alklyl nitrate, the conversion efficiency was much better than for both gold (literature
 values) and molybdenum converters (by actual comparison).
       A number of features are included in  the LNC-3M to the  alleviate the shortcomings of the
 LMA-3 NO2 analyzer. A small amount of NO2 is added to the sample stream to insure that the LMA-
 3 is operated in its linear region.  An ozone  scrubber is included to remove that last 1% of ozone
 interference.  A special zero scrubber is available that removes PAN  interference for  sampling in
 polluted environments where PAN could constitute an interference.
      A generalized nitrate detector is currently being developed. It will be used in conjunction with a
 state of the art capillary GC to enable a nitrogen specific detection of compounds in complex samples.

ACKNOWLEDGEMENTS
      We thank the Canadian National Research Council for their support through their Industrial
 Research Assistance Program.  We  are extremely grateful for the technical assistance provided by J-
 Zhang and Liz Sahsuvaroglu in carrying out the calibration and conversion efficiency testing for the
instruments.

REFERENCES
 1.  Maeda, Y., Aoki, K., and Munemori, M.,  Chemiluminescence Method for the Determination of
Nitrogen Dioxide, Anal. Chem., 52,307-311, (1980).
2.  Schiff H.I., G.I. Mackay, C. Castledine, G.W. Harris, and Q. Tran, "Atmospheric Measurements of
Nitrogen  Dioxide with a Sensitive Luminol Instrument", Water  Air, and Sou Pollution, 30,105-114,
 J.7OU*
                                           754

-------
       !nf> J.W., LA. Topham, G.I. Mackay, H.I. Schiff, "Use of chemiluminescence techniques
          eight, highly sensitive instruments fprmeasuring^NOj, NO^and O3 , Measurements
                  Schiff, Editor,'
(««"**iS^%Z^^%%^-«^rO^K«, 94Tl4^-14Kl,
  "avid
7< Parrish'rf I?1 ^eastirements of NO fluxes from sofls.    _- „ .   . M .M-aTu«« mrm™rfA>
S&ffS^tSSSiE % SiiSS&JftSSSMSSS SS°St

^^k^S^?-^a^^K^^BT^|
                                        n ik  n:sil«i "A Amiinrl.Rniten
                                        RA.'Ridley, "A
                                        . Res, 92,14710-1
                                                  mind-Based
                                                   1987.
           upuspnenc ozo

1?«»v"' *-K- iJickerson, Ci. Hubier, w.i. L««.C, ^\" p t  I ID!-^ n w nandrutL
^^^5^^.^^"^^-J?SS^d
* ' FaheT?? n of NO, N& NOy measurement methods", J. Geophys. Res., 92,14710-723, ISW7.
^^•s^»ss^F^^^^»tta"^^™
           &fes-JH £>>H stedman, and CA. Cantrell, "Luminol-Based Nitrogen Dioxide Detector",

     '»d'j.W., C Castledine  J. Green, R. Denno, G.L Mackay, and H.L Schiff, "New
     • for use in  Acid Deposition Networks", M^njtftnng Methods ^3gSB,ffriBP
      A^TM STP 1052, E.W.L?aelinsld, Jr, American Society for Testing and Materials, FnU.


             Sw-^wsa-p^c^gg&gSSS&^BE
                              D.W. Fahey, P.C Murphy, C Hoyermale, V.A.
  ta^rVP"00^ G.L Mackay, and ILL Schiff, "Intercomparison of NOz  Measurement
  1 ^ J'GeoPhys. Res. 95,3579-3/97,1990.
                           755

-------
              A FIELD PORTABLE GC ANALYZER FOR ON-SITE
                       ANALYSIS OF  ODORANT LEVELS

                                    Robert C. Mitchntr
                                 General Sales Manager
                                      Scintm Ltd.
                                 Toronto, Ontario, Canada
                                        L4K1B5


ABSTRACT
   In response to the requirements of the natural gas industry for an improved method of odorani
analysis. Scirmen has developed a field portable  GC analyser for on-site analysis of odorants
commonly used in the odonzanon of natural gas. The instrument, the OVD-229, utilizes g*s
chromatography combined with an advanced Ekctro-chemical Cell (ECC) for accurate on-site analysis
of sulphides and mertaptans. Detection level* of benet than 5 ppb are possible with the OVD-229.
   The analyzer has been specifically designed for use in  nigged field environments by utility
technicians. The OVD-229 operates from an internal 12 volt DC supply and does not require the use
of any special or external compressed gases.  The  unit is equipped with a ribbon type printer for
on-sitc printout and data archival.
   Sensor design and results of field testing by  various utilities and environmental companies within
Canada and the United States art presented.
                                          756

-------
that if?011 Cation within most areas of North America for the odorization of natural gas requires
J? £ £as * detectable by its odour at a concentration of 20% of the lower l^t of cornbusdbi ity.
in SL010"?3" "" ™»F • "^ ~"jT"
                            J^UV'H ' *»•••*«» •-»	
              ,vj Wuii~i«ai» «v located within a sir
              Un^taiiied by a separate heatmgccm^lauiciu^ ^

                                                               electrical
         the signal from the ECC is first amplified by a P°tCTtio™f *' f  e       are
      .        . Table 1 depicts the typical retention nmes for the nine
      have an elution time of less than 5 minutes.
                                 757

-------
 Figure 1.   Sample Flow Schematic of the OVD-229
             •   CM *•> 10 00

             &  •* O O W


             •   o CM u> r.
                «n « 
-------
Detector  Description
    [he prime criteria in the design of the Electro-chemical Cell was that it be capable of measuring the
 ^Phur and mercaptan compounds with sufficient sensitivity within a natural gas matrix.  Secondary
    ^derations included, low power consumption, ease of operation, no requirement for special gases,
    pliability. The detector is illustrated in Figure 3.
    Basically  the detector consists of a reference and counter electrode  sandwiched between  two
   "-permeable membranes. The membranes separate the electrolyte, in this case water, from the
Corking electrode which is  exposed  to the gas stream.  Using H2S as an example, the reaction
   •esses between the working electrode, the counter electrode and the gas stream can be expressed as
  ren m equations i) and ii).
          i)  H2S + 4H2O = $04= + 10H+ + 8e~

          ii)  1/2O2 + 2H++ 2e- =  H2°
                                                        Working Electrode

                                                        Counter Electrode
of tv
o tv    semi-permeable membranes act as a proton source for the counter electrode. The bias voltage
    e working electrode (relative to the reference electrode) is chosen such that the reactions shown
 »ove will proceed and the oxidation of hydrocarbons is prevented.  In this manner the detector is
rfvTur? Only to sulphur and mercaptan compounds and is not affected by the presence of methane and
on ,K8her order hydrocarbons present in natural gas.  Table 2 illustrates the effect of the bias voltage
  fie response of the detector.
                           ample Inltt
                                                 L*lr light UMkct

                                                   ortlna Electrode
                                                    •melble Membrine

                                                 Reference/Counter
                                                 lEIectrodri
                                                  'trrncihlf Membrene

                                                  'ermeeble Support

                                                 £leclroljte Heferrolr
   Figure 3.  Schematic of the Electro-chemical  Cell
   Table 2.  Typical Response Characteristics of the  ECC
         Odorant    Bias Volt - 350mV
                    nAmps/ppm

         H2S            214
         MM            202
         EM             116
         DMS            97
         IPM            139
         TBM            92
         MES            120
         NPM           107
         THT            112
                                        Bias Volt - 450mV
                                        nAmps/ppm

                                             302
                                             336
                                             239
                                             224
                                             300
                                             208
                                             240
                                             231
                                             160
Estimated LDL
at 450 mV (ppb)

      1.6
      1.5
     2.1
     2.2
      1.7
     2.4
     2.1
     2.2
     3.1
         Lower  Detection Limit (LDL) is  based on  a Signal to Noise Ratio of 3:1
                                           759

-------
Operating Features                                                                .   .
   Since the OVD-229 was designed for routine field use by utility technicians unskilled in tnc
operation of a GC, the operating software had to incorporate a number of special features for automatic
operation. In addition to the usual microprocessor controlled fault monitors, such as low battery etc.,
automatic calibration and peak shifting  features have been implemented. In normal operation the
technician is required to perform a field  audit procedure prior to each sample analysis.  The audit is
performed using  a single odorant standard, usually from a compressed gas cylinder, which is
automatically controlled via the software. The utility technician is required to input the gas type and
concentration following which the unit automatically injects the standard and proceeds to self adjust
itself to the existing environmental conditions.
   The results from the field audit are used to automatically correct for any changes in the detector
response as well as for any changes in the elution time of the odorants. Since ambient air is used as
the carrier it is common to find a shift in the elution time of the odorants due to changes in the arnbient
temperature of the air. If the calibration factors fall outside of preset levels, the operator is given a
warning and requested to repeat the field audit procedure.
   Although  specifically engineered for use by non-technical utility personnel, the OVD-229 has been
designed with the flexibility for use in more unstructured environments.  By gaining access to tne
second level operating program via a special password, the knowledgeable operator can modify any
number of system parameters for individual applications. Software control features include, detect°
and column temperatures, sampling time, selection of peak height or area, as well as modifying tn
widths and positions of the odorant search windows.  For continuous operation the operator can
specify the duration and period for automatic unattended operation. Additionally, through relative y
minor hardware changes, the operator may change the size of the sample  injection loop, the W
voltage of the detector and complete replacement of the column for alternative applications.         .
   Data output can be specified as tabular or graphic only, both, or no hardcopy printout if the data
to be downloaded to a data logger or PC.

FIELD  EXPERIENCE                                                            .    .  ,
   Since its introduction to the market in June of  1991, some 40 OVD-229 units have been instatica
worldwide for application within the natural gas community.  Although subject to the usual '
pains' of any  new product, the OVD-229 has been generally accepted by this  community as a
quantitative,  field portable odorant analyser. The unit has been found to meet or exceed all oi
design specifications as illustrated in Table 3.

    Table 3.  Specifications of the OVD-229

    Accuracy                  Better than 10% of reading
    Reproducibility             Better than 5%
    Detection Limits            Minimum - 5 ppb
                              Maximum - SOppm
                              Nominal - 50 ppb to 5 ppm
    Operating Temperature      -5 to 45 °C
    Battery life                 6 hours at 20 °C

    In addition to applications in the natural gas community, the OVD-229 has limited experience ^
 alternative markets including the propane, petrochemical, landfill, and pulp and paper industries.
 these applications the unit has been used for ambient air analysis of other reduced sulphur wnaPv:_e
 such  as dimethyl disulphide and carbon disulphide with sensitivities  in  the  low ppb  ran5s[
 Additionally we have internally evaluated the performance of the OVD for other reduced cornpoun
 Results of these evaluations are discussed in the following section.
                                             760

-------
FUTURE  APPLICATIONS
   Through selection of the proper bias voltage of the ECC, the OVD-229 can be configured to detect
a wide variety of reduced species including cyanides, metals, azides and phosphorous compounds. At
present we have conducted limited studies on some of these compounds, the results of which are
presented following.
Sulphur Compounds
   In general the OVD-229 has proven to be an excellent analyser for the detection of a wide variety of
reduced sulphur compounds with sensitivities in the low to sub ppb range.  Applications include
ambient air analysis for the petrochemical, pulp and paper, propane, and landfill  communities.
Additional markets include the rubber industry and the agricultural community which produce a variety
of complex sulphur species such as Diazinon and MBTS.
   To better meet the demands for these industries, Scintrex has been working on the development of
a pre-concentrator for use with the OVD which will enable the detection limits to be increased by a
factor of 10 to 100. Additionally, we are experimenting with selective chemical filters which allow for
selective removal of certain species from the air stream thereby eliminating potential interferences.

Metals
   Metals such as arsenic, mercury, selenium,tellurium, and antimony are also detectable by the OVD.
To date we have examined the capabilities of the unit with respect to mercury and have found detection
levels for mercury in air of better than 0.5 ppb.  It should be noted that these measurements were
achieved with the basic unit and results may be significantly improved for  an optimised system.
Similar detection limits are anticipated for the other metals.

Amines, Azides and  Phosphorous Compounds
   At this time  we have not performed any quantitative work on these compounds, however,
theoretical estimates predict sensitivities in the low ppb range.

CONCLUSIONS                                                    .
   The OVD-229 was designed for application within the natural gas community as a field portable
roercaptan and sulphide detector.  Based upon our field experience with the unit and that of our
customer base, the OVD-229 meets all of the performance requirements for this application.
   The versatile software and hardware design of the unit enable the unit to be utilized as a general
Purpose  field analyser with applications across many disciplines.  In-house evaluations have
demonstrated that the unit is capable of quantitative determination of a variety of reduced compounds
including metals and cyanides. Theoretical calculations predict that the analyser will also be capable of
low ppb detection levels for amines, azides, and phosphorous compounds.     .
.  The OVD-229 has  potential applications as a field portable analyser within the agriculture,
industrial, and environmental fields.
                                           761

-------
  LOW LEVEL MONITORING OF HALOMETHANES, SATURATED
 AND UNSATURATED HALOGENATED HYDROCARBONS IN AIR
          A. Linenberg, and David 8.  Robinson, Sentex
Systems, Inc. 553 Broad Avenue,  Ridgefield, NJ   07657


ABSTRACT

     Detection of low levels of  C1-C3 chlorinated
hydrocarbons recently became an  important  issue  due to
government regulations considering these compounds as
toxics.  Presently, gas chromatcgraphy techniques using a
combination of Kall/Photoionization Detectors is used to
detect these compounds, together with other toxic
hydrocarbons.  This technique, however, was found to be
satisfactory but complicated, especially when on-site
analysis is required using a portable instrumentation.  A
modified Argon lonization Detector allows  the detection of
these compounds easily and reliably,  both  in the laboratory
and on-site, using portable instrumentation.

INTRODUCTION

     Since the introduction of regulations for monitoring
and control of volatile chlorinated hydrocarbons (among
other compounds), in water, soil and  air,  techniques have
been developed for this purpose.  Gas chromatography was
mainly selected as the technique of choice to perform the
separation and analysis of volatile organic compounds.  Gas
chromatography provides high resolution, so that a sample
containing several different compounds can be analyzed for
individual components.  Gas chromatography also  provides
identifications and quantifications of required  compounds.
However, the main advantage of gas chromatography is in the
sensitivity of its detectors, which allow  the detection of
compounds down to the ppb levels and  below.  In  general,
volatile hydrocarbons, including some chlorinated
hydrocarbons, can be easily detected  to low ppb  levels.
However, there is difficulty in  reaching these low detection
levels with chloromethanes and chloroethanes.

The compounds of interest are primarily chlorinated
derivatives of methane and ethane. Typical compounds are
listed  in Table 1.

     The compounds listed  in Table 1 can be present  in
 locations where contaminated water, soil,  or  air may be
 found.  Yet,  these locations do not contain the  above
 chlorinated hydrocarbons exclusively, but include other
                             762

-------
contaminants  such  as  oil  traces  (BTEX) or various  solvents
such as MTBE, Acetone,  and MEK,  as well as other chlorinated
hydrocarbons.

     There are  different  detectors used in gas
chroaatography  for the  analysis  of different compounds.
They are the  flame ionization detector (FID],
Photoionization detector  (PID),  Hall detector and  electron
        detector (BCD).
     ElajBe loniaation Pataotor.
 .    The FID, although  the most popular in gas
chroma tography, may  not be suitable for the analysis of all
compounds due to two reasons:           .
     A,  In some cases,  its sensitivity is not sufficient to
aetect the compounds at required levels.
     B.  The detector response to compounds with low or no
hydrogen content (carbon tetrachloride) is poor.

     Photoionigation Pet actor.                          _
     The PID is sensitive in detecting a large variety of
compounds,  its operation is based on the ionization of the
organic molecules using a UV energy source. , «»*. "^W »
Primarily 10.6 eV, can  ionize all organic molecules of which
the ionization potential is below that level.  Oil
^taminat ions, solvents and some chlorinated hydrocarbons
can be successfully  detected by this detector.  However,
since the ionization potentials of chlor omethanes and
chloroethanes are above  this level (up to 11.4 eV) , the
Rector's response  to those compounds is very 1 imite d-  The
sensitivity of the PID to these compounds is low, and the
J^D's response may differ by two or three orders of
??9nitude when compared  to its response to <*;her
hydrocarbons (i.e.   same response for 1 ppm of benzene and
several hundred ppm  of chloroform).
     TheHalletctor is a             .t=a.s
    all chlorinated hydrocarbons.  The disadvjuit=g«s of

         Sslr. Ire,u«.tly «™»r,t regarding difficulty In
re                            ..           not
resPond to other hydrocarbons.

     £J«Ptr9n CUPtVr* Ptt+qtor^.   h^iocarbons,  but has the
     The BCD is sensitive only to haiocarcons,
     ving limitations:                   areatly vary with
    *lB  Its «^nse to halocarbons may ^great  y^ rclatively
    type of the compound.  The detector wij           s
     response to chloromethane (ppm leve IB) ,  w
     8ive res      to carbon tetrachloriae IPP
     2.  It responds only to halocarbons.
                             763

-------
      The detector of choice for use in environmental
 analysis should have the following requirements:
      1.   Sensitive to both chlorohydrocarbons  and other
 hydrocarbons.
      2.   Relative uniform response to  all  compounds.
      3.   Easy operation and installation in  both  laboratory
 and portable gas chromatographs.


      A combination of the PID/Hall Detector  is frequently
 used to obtain the detection requirement.  The PID,  having a
 typical ionization energy of up to 10.6 eV,  can ionize  all
 compounds having an ionization  potential below this  level.
 This includes  most of the volatile organic compounds such as
 benzene,  toluene,  xylenes,  trichloroethylene,  and
 tetrachloroethylene.   These compounds  are  analyzed with high
 sensitivity and accuracy.   However,  chlor©methanes and
 chloroethanes  have ionization potentials above 10.6  eV,
 therefore the  PID can only detect  those compounds with
 limited  efficiency,  not complying  with the sensitivity
 requirement.   To compensate for this limitation,  the  Hall
 Detector  will  detect all the "missing" compounds,  as  well as
 indicate  which compounds detected  by the PID were
 halogenated.   This combination  is  somewhat cumbersome,  and
 while its performance is satisfactory  in the laboratory,  its
 use  in the field is  limited.

      Araon loniaation Detector.
      The  Argon Ionization  Detector  is  operating on the
 principle of excitation of  the  Argon atoms using  a Beta
 radiation source such as Tritium:

 Ar -* Ar*

      The  meta-stable  Argon  has  the  energy  of 11.7  eV.  When
 colliding with organic molecules,  it creates the  following:

 Ar*  +  R-H •* R- H+  +  e-  + Ar

 (Where R-H is  an organic molecule)
 Meaning,  the ionization of  the  organic compounds.

 Since  the  ionization  energy derived  from the Argon is 11.7
 eV,  it ionizes all compounds having an ionization potential
 below  this  level,  including chloromethanes  and
 chloroethanes, of which the ionization potential can vary up
 to 11.4 eV.  The detector is rugged, simple to operated, and
does not require frequent cleaning.  It can be used in both
 laboratory  and portable gas chroroatographs.  Due to its high
energy, its response  to different compounds is relatively
uniform and does not  vary within orders of  magnitude.  The
detector therefore detects a wide variety of hydrocarbons,
as well as  chloromethanes and chloroethanes.   The  results
are similar to those  obtained from the combination of the
                             764

-------
PlD/Hall Detector,  yet AID results can be obtained in the
laboratory and on-site using a portable gas chromatograph,
with considerably less complications.

Experimental

      A Scentograph Gas Chromatograph (Sentex Systems, Inc.)
using a Micro Argon lonization Detector was used for the
experiments.  The chroroatography performed used a 30 meter
Restck 0.53mm x 0.3 nun coated VOCOL Column.  Samples were
injected directly using  a sampling loop assembly, or
collected on a preconcentrator/trap directly from the air or
using a purge and trap procedure.  The purpose of the
experiments were as follows:
      To demonstrate the  ability of the Micro Argon
lonization Detector (MAID) to detect various chlorinated
hydrocarbons,  as well as other hydrocarbons with an
acceptable response factor.
      To demonstrate the  response of the MAID for water
samples using the purge  and trap technique, for the
determination of low level chlorinated hydrocarbons.

Results and Discussion

      Figure 1 shows analysis of various hydrocarbons in air.
These hydrocarbons have  a variety of ionization potentials,
ranging from 8.5 eV to 11.3 ev.
      Figure 2 shows analysis results of various chlorinated
hydrocarbons,  sampled from air, at low concentration levels.
 1    Figure 3 shows analysis of various volatile chlorinated
hydrocarbons,  carried out by a purge and trap technique.
      All results indicated a uniform response of the MAID
toward hydrocarbons, especially the halomethane and
haloethane compounds.  In addition, the sensitivity obtained
for  the analysis prove that the MAID is a sensitive detector
for  analysis of halomethanes and haloethanes, both in air
and  particularly in water.
     The MAID was  found to be a useful detector for the
Analysis of  hydrocarbons, especially halomethanes and
haloethanes,  as well as other hydrocarbons,  it successfully
£an replace  the combination of PID/Hall Detectors and
orovide a  simple,  reliable and sensitive solution for both
laboratory and field analysis for the determination of those
compounds  in air,  soil and particularly water.
                             765

-------
                     METHANE DERIVATIVES

                      Methylene Chloride
                          Chloroform
                     Carbon Tetrachloride
                      ETHANE  DERIVATIVES

                         Chloroethane
                      1,1-Dichloroethane
                      1,2-Dichloroethane
                    1,1,1-Trichloroethane
                    1,1,2-Trichloroethane
Table 1.  List  of typical methane and  ethane  derivatives.
                           766

-------
                                                  2
                                                  3
                                                  4
                                                  5
                                                      tnpA.
               Loot,
[hlorotorn
Benzene
Carbon tet
Toluene
p-Xylene
o-Xyiene
30
40
40
30
40
60
B'x 1/8' 1 SP-1000, Col. Tenp.:60°[    Col,  Pressure 22 psig
                     Figure 1.  Analysis of Hydrocarbons
                               of different lonization Potentials.

-------
                                           col; 30n x 0,53nn VDCQL
                                           tenp: 50'C
                                           det: AID; trap; TENEX
2
3
4
5
6
7
                                                           1,1 GCE
                                                           tl,2D[E
                                                           1,1 HA
                                                           cl,?DCE
                                                           ICE
                                                           PCE
2.5 ppbv
1,5 ppbv
2.0 ppbv
2.0 ppbv
1.5 ppbv
].5 ppbv
1.5 ppbv
I   I   1   I   I   I   I   I   I   I   I
                              Figure 2,  Low level  analysis  of
                                          Chlorinated  Hydrocarbons of
                                          different  lonization  Potentials.

-------
               tenp; fft
               det: AID; trap; corbosieve
I
2
3
4
5
6
7
8
1,1 DCE
tl,2DCE
1,1 DCA
cl,2DCE
1,1,1 1CA
1,2 DCA
TCE
PCE
2.5 ppbv
1.5 ppbv
2.0 ppbv
2.0 ppbv
1.5 ppbv
1.5 ppbv
1.5 ppbv
1.5 ppbv
Figure 3.  Purge  and Trap Analysis  of
           Low Level Chlorinated Hydrocarbons
           with different lonization Potentials.

-------
      SIMULTANEOUS EN-PLUME AND EN-STACK SAMPLING FOR
      ANALYSIS OF A DETACHED PLUME AT A CEMENT PLANT
 Larry Edwards, Ph. D.                     Lee W. Cover
 Eric Winegar, Ph. D.                       Kaiser Cement Corporation
 Radian Corporation                        24001 Stevens Creek Boulevard
 10389 Old Placerville Road                  Cupertino, CA 96014
 Sacramento, CA 95827
           A paniculate, detached plume  forms from time to time about 50 feet above the
 stacks on a baghouse discharging exhaust gas from a conventional cement kiln. The physical
 arrangement of the facility allowed for sampling the plume in the formation zone. Simultaneous
 in-stack and in-plume sampling was conducted to determine the composition of the stack gases
 both when the detached plume was and was not forming.  During a formation period, the
 concentration of paniculate matter in the  plume nearly tripled,  and  the new material was
 ammonium sulfate. The only increase of note in the stack gas composition when the plume was
 forming was a 50% increase in ammonia. It appears that the formation mechanism involved the
 increased  ammonia raising the pH of  transient water droplets, and at the higher pH, the
 dissolved  SO2  (sulfite)  is much more quickly oxidized to sulfate.  Upon evaporation, fine
 ammonium sulfate particles form.

 Introduction

           The Kaiser Cement (Kaiser) plant in Cupertino, California, has had an intermittent
 plume associated with its baghouse outlets; the origin and nature  of this plume were largely
 unknown.  The plume appears unpredictably, may last for a few seconds to a few hours, and
 then vanishes for periods of minutes to days.  The plume appears to consist of a fine, whitish
 material that is especially noticeable when looking into the  sum.  It definitely in not a steam
 condensation plume. When it is present, there is no visible plume coming out of the baghouse
 stacks; rather, it forms 25-50 feet above the  stacks. The facility is located in a canyon, and the
 local wind currents are very complex, variable, and tend to swirl,  often fumigating the plume
 back down upon the roof of the baghouse.  Therefore, the formation dynamics of the visible
 plume cannot be unambiguously determined by observation.

           It is known that the limestone blended into the kiln feed contains some ammonia or
 ammonium compounds.   Sulfur dioxide, and possibly some sulfur trioxide, are also present in
 the exhaust gases.  Based  on a review of the literature and  experience  with other similar
 situations,  candidate materials for the detached plume include ammonium sulfite [(NHi)2SOj],
 ammonium sulfate [(NH4)2S04], ammonium chloride [NH4C1], sulfuric acid mist [H2SCv2HjO],
and calcium sulfate [CaSOJ. One operating  condition that seems to have some influence on the
 frequency of formation of the detached plume is when the kiln exhaust gases are used to dry the
                                        770

-------
 feed.  When gases are passed through the ball mill where the raw limestone is ground, the plume
 is less visible (or absent) than when the ball mill is bypassed.

            Kaiser contracted with Radian Corporation (Radian) to study this problem. There
 were three questions to be answered:

            •    What is the paniculate matter forming in the detached plume?
            •    What is the nature of the plume formation dynamics?
            •    What is the source of the components forming the plume?

            The physical configuration of the plant allowed for in-plume sampling.  Towers
 existed at both ends of the baghouse, and the stacks were relatively short.  A cable was rigged
 over the baghouse, directly through the region where the plume formed. Open face filters were
 then used to collect paniculate material as it was forming. On one day, four one-hour tests were
 conducted, and during the fourth test, the detached plume was present.

 Characterization of the Facility

            The pyroprocessing line consists of an Allis-Chalmers dual string, four stage
 preheater,  precalciner with a 250 ft. by 16 ft. kiln rated at 5,000 tons of clinkers per day.  The
 raw meal is introduced into the tower exit gas stream and takes about 20 seconds to flow through
 the four stages of the tower before entering the kiln. The feed reaches approximately 800°C and
 is 90% calcined with secondary firing. Recuperated oxygenated air from the grate cooler is used
 for combustion air in the precalciner.

           The exhaust gases exit the tower at approximately 400°C. Before entering the 32-
 compartment dust collector (baghouse), the gases are conditioned with water sprays to 140*C.
 \Vhen the raw grinding mills are operating, a portion of the exhaust gases are diverted through
 the mills to remove moisture from  the raw materials and to air sweep the mills.  These gases
 are  reunited with  the remaining exhaust gases prior  to  the baghouse  and  venting to the
 atmosphere.  Water usage for gas conditioning is based on the baghouse inlet temperature and
 is contingent upon whether the raw mills are operating.


 Sample Design and Testing

           A number of simultaneous in-plume and in-stack measurements were carried out to
determine the composition of the in-plume material and the composition of the in-stack gases and
paniculate material; see Table 1.   Fortunately, sets of samples were collected both when no
ljume was apparent and when a detached plume was forming.  The in-stack gases were sampled
through a  filter to exclude  any paniculate material.   EPA Method  17 sampling was also
conducted to collect paniculate matter in stack, primarily to provide a basis for comparison of
the in-stack and in-plume paniculate material by scanning electron microscopy.
                                          771

-------
 TABLE 1. SUMMARY OF THE TEST DESIGN
          Test Description
             Questions to be Answered
  Exhaust gases in the baghouse
  stacks were tested for ammonia
  and acid gases (impinger
  methods).
    What types of ions (e.g., chloride, sulfate,
    sulfite, nitrate, ammonia) and at what concentra-
    tions are present in the baghouse off gases?
    How do they differ during plume formation?
    Which ions are most implicated?
  The sulfuric acid mist [SOj (g)
  or H2SO4 (1)] in the baghouse
  stack was measured (by
  controlled condensation
  method).
•   Is sulfuric acid mist the source of the detached
    plume?
*   Does the ratio of SO2 (g) to SO3 (g) change
    during a plume incident?
  Samples of the in-stack particu-
  late material were collected
  (Method 17) and looked at with
  anSEM.
    What is the nature of the in-stack paniculate
    material?
    How similar or different is in-stack the
    paniculate material to the in-plume paniculate
    material?
  In-plume paniculate material
  was captured on filters and
  analyzed for elemental content
  (XRF), ionic content (leaching
  and 1C), crystal structures
  (XRD), morphology (SEM), and
  for TOC.
    What is the increase in in-plume paniculate
    material concentration during an plume formation
    incident?
    What is the nature of the in-plume material and
    how does it compare to the in-stack paniculate
    material?
    Does the composition of the in-plume material
    change during an incident?
           Each of these one-to-two-hour tests were run in duplicate under each of the two plant
operating conditions (i.e., with and without drying in the ball mill). During the first three tests,
there was only a slight wisp of visible plume;  during test #4, a clearly visible detached plume
formed shortly after the testing started and persisted for over an hour.  During the fourth test,
the feed was not being dried by the kiln gases.

Results of Testing

           The results of the in-stack gas composition sampling are given in Table 2.  Recall
that a visible plume formed only during test #4.  The only significant difference in the five
reported stack gases was a 50% increase in the ammonia concentration (and a minor increase
in chloride).  Both SO2and SO, showed  some variability in tests #3 and #4, but the changes
could not be correlated with the formation of  the plume. The SOj was higher when the kiln
gases were not being used to dry the feed. In stack moisture during tests #1 and #1 was 9.1%;
during tests #3 and #4, moisture was  10.5%.
                                         772

-------
            The results of the in-plume testing are summarized in Table 3. The total mass was
 seen to increase by a factor of 2.3. All other components also increase, but the most dramatic
 increases were seen in sulfate (approximately a 10-fold increase) and ammonium (approximately
 a 12-fold increase).  Between the two ions, 89% of the total mass can be accounted for. On all
 four runs, calcium was the predominant metallic element, but it increased only nominally on the
 fourth run (i.e., 252, 259, 224, 303 jtg/m3, respectively). The total elemental mass, assuming
 all the sulfur was  present as sulfate, accounted for approximately 1 10% of the total filter mass;
 thus, some of the sulfur may have been present as sulfite since the analytical method could not
 distinguish sulfite from sulfate.  However, bias and differences in the three analytical methods
 fi e-, gravimetric, ion chromatography, x-ray fluorescence)  could also account  for the ten
 percent difference.

            Scanning electron photomicrographs of the in-plume filters showed that the fourth
 run paniculate material  was in much greater abundance and consisted of a great many small
 narticles (
-------
TABLE 2. COMPOSITION OF UN-STACK GASES DURING THE FOUR TESTS
Sample Time
9:30-10:30
10:45-11:45
2:15-3:15
3:30-4:30
Ball Mill
Healing
On
On
Off
Off
NH3
(mg/m3)
17.5
17.8
17.6
27.2
SO2
(mg/m3)
82.78
90.65
117.20
87.32
SO3
(mg/m3)
4.59
4.20
7.29
7.61
cr
(mg/m3)
1.18
<0.5
1.54
1.93
NOj-
(mg/ra3)
0.99
<0.5
<0.5
<0.5
Note:
Moisture content of exhaust gases was 9.1 % during tests
#] and #2, and 10.5% during tests # 3 and #4.
TABLE 3.  COMPOSITION OF THE IN-PLUME MATERIAL CAPTURED ON FILTERS

Sample Time
8:02-10:00
10:45-12:45
1:10-3:10
3:55-5:58

Ball Milt
Heating
On
On
Off
Off
Total
Mass
fog/m3)
1,190
1,190
1,230
2,830
Total
NH/
Gtg/m3)
54.7
24.7
88.8
694.4
Total
so4-
Gtg/m3)
150.4
93.6
347.5
1,825.4
Total
Cl"
(Mg/m3)
61.5
77.7
65.6
142.9
Total
NCV
Gig/m3)
2.9
2.8
5.8
7.1

-------
            The only in-stack substance present in sufficient amounts to account for the observed
 in-plume increase was SO2.  Therefore,  either the formation rate of ammonium  sulfite was
 dramatically increased (for unknown reasons) and the sulfite oxidized  to sulfate during leaching
 and analysis (a distinct possibility), or there was a vastly increased rate of oxidation of SQ, to
 SO} when the plume was injected into the atmosphere.  The latter hypothesis assumes that
 ammonium sulfate formed rapidly if SO3 was present.

            There is some support for the sulfite-to-sulfate mechanism.  In a 1980 paper by
 Dellinger, et al., they report a pseudo-catalytic oxidation of SOj to SO3 in cement kiln plumes;
 the pseudo-catalyst was ammonia.1  The mechanism they proposed involved aqueous chemistry
 in which the sulfite ion in water droplets was rapidly oxidized to sulfate in neutral and basic
 solutions, but only slowly oxidized in acidic solutions. The ammonia acted as a pseudo catalyst
 by absorbing  into the water droplets, raising the pH and allowing for the oxidation to  occur.
 Upon evaporation, ammonium sulfate crystals would result.

            In the present study, there was little visual evidence for water droplet formation in
 any of the tests; the plume appeared to be fine paniculate matter and was persistent. In tests
 #l-#3,  there was virtually  no  visible detached plume.   Of course,  transitory  water droplet
 formation and evaporation cannot be ruled out.  The moisture content of the stack gases was
 9.1 % when the kiln gases were used to heat the feed (i.e., tests  #1  and #2) and 10.5% when the
 lain gases were not diverted (tests #3 and #4).  The lower water in the exhaust gases when they
 were used for preheating was due  to their lower temperature  upon leaving the ball mill;  the
 lower temperature required less water for conditioning (cooling) before entering the baghouse.

            Thus, the only viable mechanism that may account for the increased detached plume
 formation  is that  the  50%  increase in ammonia,  and perhaps a small increase in moisture
content, allowed for neutral to basic water droplets (basic due to absorption of ammonia) to form
a second or two after contact with the atmosphere.  In these non-acidic droplets, sulfite ion was
rapidly  absorbed and oxidized to sulfate with no change in pH.  Upon evaporation,  ammonium
sulfate crystals were formed.  If either the moisture was low or the amount of ammonia was
below the pseudo-catalytic threshold, this process would not have occurred, and the ammonia
and SO2 would have been dispersed into the atmosphere as gases (i.e., tests #l-#3).  In test #4,
jjje increase in ammonia was just enough to initiate the pseudo-catalytic aqueous-phase oxidation
Of sulfite to sulfate with the subsequent formation of fine ammonium sulfate particles.

References

 1) B. Dellinger,  G.  Grotecloss, and  C.R. Fortune, "Sulfur  Dioxide Oxidation  and  Plume
Formation at Cement Kilns," Environ. Sci. & Teph., 14(10): 1244(1980).
                                           775

-------
               Session 17
         Lead in the Environment
Sharon Harper and Laurie Schuda, Chairmen

-------
              EVALUATION OF A FILTER COMPOSITING PROCEDURE
          FOR POSSIBLE INCORPORATION IN THE FEDERAL REFERENCE
                                 METHOD FOR LEAD

             W. A. Loscke, S. L. Harper, L. J. Pranger, K. A. Rehme, and
                                     J. C. Suggs

               Atmospheric Research and Exposure Assessment Laboratory
                         U. S. Environmental Protection Agency
                          Research Triangle Park, N. C. 27711
       The U. S. EPA is considering revisions to the National Ambient Air Quality Standards
 ^ associated air quality surveillance and reporting requirements for lead.  Under the proposed
 ^visions, everyday sampling would  be required around point sources of lead. To reduce the
       of the increased analytical burden  associated with the everyday sampling schedule,
 ^positing of multiple filter samples for quantitation by the lead reference method would be
 Permitted, The laboratory evaluation of a procedure to physically composite portions from three
 to eight filter samples is discussed.  Composites were prepared by punching pairs of circles
 ranging from 3/4 to 15/16 inches diameter from each filter sample. Total filter area extracted
 Pcf composite was approximately 7 square inches. Extractions were performed using a Nitric
 Acid/Hydrochloric Acid mixture with quantitation by  Inductively Coupled Plasma - Optical
 omission Spectrometry (ICP-OES).  Results of the study indicate toat composite lead values do
 not appear to be significantly different than values obtained from single strip averages, even for
 ^       samples produced from individual filter samples with widely divergent lead values.
       The U. S. Environmental Protection Agency has completed its review of the air quality
 "teria for lead. It is anticipated that the Agency will propose several technical revisions to the
National Ambient  Air  Quality Standards' and ambient air quality surveillance and reporting
**L«irements2 for lead.  Under the proposed regulations, the current primary and secondary lead
rjndard of 1,5 ^g/ms,  maximum arithmetic mean averaged over a calendar quarter, would be
^wed to  0.75 ^tg/m3,  monthly average, not to be exceeded more than once in three calendar
years.  The monitoring focus would shift from transportation oriented sources to point sources.
Continuous (everyday)  24 hour sampling around these sources would be required instead of
f^pling every six days as is done at present.  This additional sampling would substantially
U)Crease both the economic and analytical burden of the responsible monitoring organization.
                                        779

-------
       One way to reduce this burden would be to physically composite filter samples for
 analysis rather than analyzing individual filter strips as is the customary practice. Although the
 current Federal Reference Method (FRM) for lead permits compositing, monitoring agencies are
 required to develop their own compositing procedures, conduct special tests to demonstrate
 adequacy of performance, and  obtain formal EPA approval.   It is  anticipated  that most
 monitoring agencies will favor the use of compositing. Under the current regulations, there
 would be much duplication of effort, a plethora of compositing procedures, and an increased
 administrative workload for EPA,

       Consequently it was decided to develop and test a compositing procedure which, if
 successful, could be directly incorporated  into the FRM  for  lead.  The objectives of this
 investigation were (1) to  develop a compositing procedure that would minimize the laboratory
 analytical burden, (2) to determine if average lead concentrations derived from analyses of filter
 composites are statistically equivalent to corresponding averages derived from individual strip
 analyses, and (3) to estimate the allowable range of individual lead concentration values that will
 produce an acceptable composite value.

 APPROACH

       A compositing procedure was developed based on punching pairs of circles from the
 individual filters comprising the composite.  The number of pairs and the diameter of the metal
 arch punch was determined by the number of filters in the composite.  The total filter area of
 the composite sample was approximately 7 in2. A single 1  in. x 8 in. strip was also cut from
 each filter for mathematical compositing.

       Filter samples for the study were obtained from two Hi-Vol TSP samplers operated for
 fifteen days near a lead point source. The 30 filter samples were randomly ordered to simulate
 30 consecutive days (1 month) of 24-hour sampling.  Composite samples were produced using
 filter circles from 3, 6, 7 or 8 filter samples.

       An  ultrasonic extraction procedure  followed by ICP-OES quantitation was used  to
 determine the lead content of the composite samples and single strips. This  method is routinely
 used for metal analyses in our laboratory, and has been designated as an equivalent method for
 lead.3

       The analytical results were processed into data pairs.  One pair member was the analyzed
 lead value for a given composite.   The other pair member was obtained  by mathematically
 averaging the single strip lead values of the filters comprising that composite. Linear regression
 analysis was used to examine the level of agreement between results obtained with the labor
intensive single strip method and the chemical compositing procedure.

EXPERIMENTAL METHODS

       In order to prepare the composite samples it was necessary to modify  or rework the filter
cutting template developed previously.1 Exposed filters were always folded soiled side inward
when  removed  from the  sampler.  Folded dimensions were 4  in. by 10  in.   The modified
                                         780

-------
 template allowed two 1.25 in. by 4 in. strips to be cut from the right hand end of the Alter. The
 first strip contained the border and was discarded.  Transverse  cuts were  made at 1.25 in.
 intervals, measured from the fold, in the second strip by rotating it 90" in the template. The
 resultant doubled squares, soiled sides inward, were used to produce the required pairs of filter
 circles.  The number of circles and the diameter  of the arch punch used for cutting  varied
 depending on the number of filters in the composite, as  shown in  Table I.  Single 1 in. x 8 in.
 strips were  also  cut from each  filter  for  individual  analysis  and  eventual mathematical
 compositing.

       A total of 33 physically composited samples were prepared  by sequential grouping of the
 30 randomly ordered filters.   Ten 3-fi!ter composites were prepared in duplicate to estimate
 Precision.  A single set of five 6-fiIter composites was prepared.   Two 7-filter composites and
 two 8-filter composites were prepared in duplicate to obtain a second estimate of precision.

       Extractions were carried out by placing the composite or single strip samples in 50 mL
 PQlysulfone centrifuge tubes (Nalge No. 31 15-0050)  and covering the filter sections with 12 mL
 °f an acid mixture that was 1 .04 M HNQj and 2.23 M HC1.  The tubes were capped loosely and
 ultntsomcated  for 50 min. at 95'C,  After cooling,  28 mL D.I. H20 was added to each  tube.
 The tubes were recapped, shaken, and centrifuged for 25 min. at 2500 ipm. The extracts were
 decanted to clean bottles for analysis.

       AH samples  were analyzed  on an Instruments S.A. Model JY-70 Plus simultaneous
 sequential TCP spectrometer   Lead data were obtained by  the sequential module reading the
 '20-35 nm lead line.  Repeated analyses of the zero standard fixed the instrumental detection
 limit at 2.2 fig/sample. QC check solutions were analyzed periodically during the project. A
 "•-
                    .
"•Mti-element solution containing 20 jtg/mL of lead showed an average recovery of 99.0%.
Another multi-element solution with lead at the 5 /*g/mL level recovered 102.796  on average.
^ikewise, SRM 3172 used at 4.0 ng/mL of lead yielded a mean recovery of 102.596. It was
included that the instrument was operating in control while data were being collected.
      Regression analyses were performed on paired sets of data which were defined by the
"Umber of individuals in a composite.  The results are shown in Table H and demonstrate strong
Relationships between single strip averages and corresponding composites.  Correlations (R) were
u-»8 or better in all three cases. Intercets could not be statistically differentiated from zero and
ft * _   —r- ^^^-TTV^II aui£iv auij/ avwt«£V4 «uiu w**»«*|'^—»-"-e	j	
u-»8 or better in all three cases. Intercepts could not be statistically differentiated from zero and
«0j>es were equivalent to 1.0 in all cases.  Therefore, it was concluded that single strip averages
    composites were equivalent for all comparisons.

t.     All data were processed in terms of & of lead per 7 in1, of sample.  The equivalent of
£e current standard of 1.5 ug/m3 is 333.3 /xg/7 ina.  The monthly average of the 30 individual
fi«er samples was  323.0 ug/7 in1, which indicates that the lead source was emitung slightly
*low the current standard. At this level, the expected margin of enor in a monthly average
«f individual filters is minimal at  ± 1.696 predicted by the 3-filter composites  ±  4.396
Predicted by the 6-filter composites  and ± 2.996 predicted by the 7/8-filter composites.
                                         781

-------
       The relative standard deviation (RSD) of the duplicate analyses of  the ten 3-filter
composites was ± 3.3%.  The RSD for the four 7/8-filter composite duplicates was ±2.1%.
This small error affected the estimates of the slope and correlation coefficients (R) by less than
0.1%. It was judged that the reproducibility of the compositing procedure was acceptable.

       A successful compositing  procedure must be able to  accommodate individual filter
samples  with widely differing lead values, while providing a measured value close to  the
mathematical average of the individual samples. Table III presents results for two of the 3-filter
composites. In the first example, the individual lead values were widely divergent with values
at the extremes, yet the mean of the individuals and the composite results agreed very well
(within 3%).  In the second example, the individual lead values were more evenly distributed.
The relative percent difference (RPD) between the mean of the individual lead values and  the
composite results was within 3.5%.  There were four other composites in which the range of
the individual lead values exceeded 500 /ig/7 in1.

CONCLUSIONS

       No problems were encountered in preparing composites for this study.  The procedure
is relatively simple and easy to apply. The compositing procedure appears to be acceptable  for
use. Likewise, the extraction of the composited circles and analysis of the extracts was straight
forward and no unusual behavior was observed.  The excellent agreement between duplicates
signifies that the compositing process is highly reproducible.

       Regression analysis of single strip means and composite values resulted in  slope and
intercept values statistically indistinguishable from unity and zero, respectively, and very high
R2  values.   This indicates that  the composite values are  statistically  equivalent  to  the
corresponding single strip means.  Moreover, this remained true even when the individual lead
values varied  over a wide concentration range.

       It is recommended  that the compositing procedure be given  serious consideration  for
incorporation  in the FRM for lead.

REFERENCES

1.  Code of Federal Regulations, Title 40, Chapter I, Part 50.

2.  Code of Federal Regulations, Tittle 40, Chapter I, Part 58.

3.  Federal Register, Vol. 45., No. 46, pp.  14648-9.

DISCLAIMER

       The information in this document has been  funded wholly or in part by the U.S.
Environmental Protection Agency.  It has been subjected to Agency review and approved  for
publication.  Mention of trade names or commercial products does not constitute endorsement
or recommendation for use.
                                         782

-------
|l!b|e I. A sample coraoositinfi plan using from three to eight individual filters
Number
of
Filters
3
4
5
6
7
. 	 8
Number
of
Circles/
Filter
4
4
2
2
2
2
Total
Number
of
Circles
12
16
10
12
14
16
™^«M»B- •—•"••^™
Diameter
of
Punch
(in)
7/8
3M
15/16
7/8
13/16
3/4
.^— —•—••«-
Total
Area
(in7)
7,216
7.069
6,903
7.216
7.259
7.069
•MMM =- — ^^••^
IL Egression estimates for averages (Y) versus composites (X) based on Y =* A + BX
                                   7*3

-------
Table III. Comparison of the means of individual strips with composite values for two
          3-filter composites (units art jig/sample)
Sample
3/08-1 (Fri)
3/03-2 (Sun)
3/01-2 (Fri)
MEAN
RANGE
2/18-2 (Thu)
3/01-1 (Fri)
3/04-2 (Mon)
MEAN
RANGE
Individuals
66.40
8.82
1185.00
420.07
1176.18
746.10
1167.10
201.80
704.96
965.20
Composites
407.901
427.70'
417.80

728. 801
729.60*
729.20

   Duplicate analysis
                                           7S4

-------
 ENGINEERING STUDY TO  EXPLORE IMPROVEMENTS IN
                     VACUUM DUST COLLECTION


                Benjamin S. Lim, Joseph J. Breen, and John Schwemberger
                    U.S. EPA Office of Pollution Prevention and Toxics
                         401 M Street, Washington, DC  20460

                         Paul C. Constant and Karin M. Bauer
                              Midwest Research Institute
                   425 Volker Boulevard,  Kansas City, MO 64110-2299


ABSTRACT

 .     A preliminary laboratory investigation was undertaken to determine the limitations of the
 "« collector previously used on a national survey and on the pilot study of the Comprehensive
 oaternent Performance Study (CAPS), and  to obtain information on the critical design
Pararneters of a vacuum dust collector.  Two dust collectors were designed.  One is a
Aerification of the original blue nozzle dust collector with an in-line cassette used on the two
Devious studies as the unit and the second design, a cyclone dust collector, which operates on
 e Principle based upon centrifugal and gravitational forces.
      Each design was tested to estimate its overall efficiency in collecting dust in the size
 nge of 1 Mm to 2jooo nm from concrete, linoleum, wood floor, carpet, and windowsill.  The
a * n°z*le gave a mean collection efficiency of 17.7% for all surfaces; the in-line dust collection
  87.3% for alt surfaces; and the cyclone dust collector a 95.8% for all surfaces.

INTRODUCTION

a,     EpA's Office of Pollution Prevention and Toxics  (OPPT) is currently conducting a study
hou  me ^D Demonstration houses to assess the performance of the abatements after the
 ou
m  Ses .have been re-occupied.  The performance of the abatements will be addressed by
stud  -ril18 the levck of Jead in dusl and soiL  To PrePare for this study' EPA conducted a Pilot
as  y ln Denver, Colorado in 1991.  One of the objectives of the pilot study was to test and
obseSS the performance of the sampling and analysis protocols.  In this study, field personnel
•nad   d thc dust coljection device used on HUD's National Survey had limitations, namely,
be ^quate collection efficiency and versatility. The explanation for the lack of complaints may
is i    t0 the def"irtion of dust for that survey. The dust of interest was loose, surface dust that
Riatan-Sfcrable from hand to mouth,  however, for the pilot study, dust was defined as all
  ier>al on the  surface within the designated  area from which a sample was to be collected.
orm-  *" exPtoatory investigation was undertaken to (1) determine the capabilities of the
 «»nal dust collector with blue nozzle used on HUD's National Survey, (2) identify the critical
tiJ rf615 needed ^ be considered in the modification of the blue nozzle dust collector or in
       n °f a vacuum dust collector that could be used in EPA's CAPS, and (3) fabricate the
        blue nozzle or design and fabricate a new dust collector.
                                        785

-------
 DUST COLLECTOR DESIGN

       The dust collector that uses the blue nozzle is shown in Figure 1.  This collector has
 three major units:  the nozzle, the vacuum pump, and the filter cassette, which collects the dust.
 Tubing interconnects the three major components, and a vacuum gauge is connected to the
 pump to provide a means to monitor the vacuum. Two additional dust collectors were
 designed. These new designs are shown in Figures 3 and 5. Figure 3 is a schematic drawing of
 a vacuum-driven dust collector that has a 37-mm cassette with a preloaded, 0.8-/im, cellulose-
 ester membrane as an modification of the blue nozzle dust collector.  Figure 5 is a schematic of
 a vacuum-driven cyclone separator dust collector.  This dust collector has the same type filter
 cassette as the in-line dust collector.  It is located at the bottom of the cyclone collector.  Since
 the filter is not actually required, the filter cassette can be replaced by some other appropriate
 collection unit.
       The newly designed dust collector must meet the following performance and operational
 requirements:
       1.  Ability to collect a sample of dust particulates, 1  pm to 2,000 /*m in size, from 1 sq ft
 area in 2 min or less;
       2.  Overall average dust collection efficiency of eighty-five percent (85%) or more for
 carpets, wood floors,  linoleum covered floors, concrete, and windowsills and window channels;
 and
       3.  Low cost, lightweight, portable, easy to use, 110-vac powered, and capable of
 collecting up to 2 g of dust.

 TEST OF DESIGN PROTOTYPES

       The in-line dust collector operates on  the principle of impaction. The air enters the
 nozzle and flows through the filter cassette.  The paniculate matter in the air stream impacts
 onto the filter in the cassette, and the air is discharged from the outlet of the  cassette.  The
 pore size of the filter is the determining factor for the size of particles discharged  from the
 outlet of the cassette. The particles  are submicron in size-the size of paniculate matter that
 most likely remains airborne.
       The cyclone collector operates on a different principle from that of the in-line dust
 collector, which is an  impactor. The dust enters the sampler body tangentiaily at a relatively
 high velocity and proceeds in a rotary direction.  The air within the body forms a vortex, travels
 up, and is discharged  through the top of the sampler case.  This air is discharged at a relatively
 low velocity.  The dust moves downward within the collector's body and is discharged at the
 lower end of the cone into a  collector container. The forces that separate the dust from the
 discharging air are centrifugal and gravitational.  This separation is possible because the air
velocity is reduced considerably after it enters the body of the cyclone, thus allowing the forces
 to separate the particles from the air stream. Some very fine paniculate matter is discharged
from the device.  It is believed these fine particulates are submicron in size. The amount of the
fine paniculate discharged is  a function of the amount picked up and the design of the cyclone
collector.
       The cyclone dust collector is made of PVC pipe and pipe fittings. The  cassette is located
in the cassette holder plug, which screws into the bottom of the cyclone sampler case. The
sampler case is a pipe reducer with an end cap attached to the 4-1/2-in. portion. The nozzle is
a short length of 1-in. PCV pipe connected to the inlet of the cyclone sampler case via a 90
degree elbow. The discharge unit is  a 1-1/2-in. coupler inserted into a machined hole at the top
of the cyclone sampler case (4-1/2-in. end cap). A 1-in. reducer is placed into the discharge end
                                           786

-------
 °f the coupler )o accommodate a 1-in. short piece of pipe.  A 110-vac, 60-Hz, 2 amp,
 commercially available vacuum source is connected to the cyclone discharge end via the
 appropriate size pipe and fittings.

 EXPERIMENTAL DESIGN

       Three factors were considered in the experimental design for the laboratory test to
 estimate the  collection efficiency of the dust collectors:
       One blue nozzle, two in-line collectors, and two cyclones for a total of five dust collectors
 *ere tested.
       Three types of composite materials covering the range of 1 to 2,000 ^m were sampled:
 J-ornposJte d (particles of size <250 Mm plus paint chips), Composite Q (particles of size 5250
 bl« <2,000 Mm plus  paint chips), and Composite Cj (<2,000 pm plus paint chips).
       Five types of surface were used: Wood floor, Linoleum, Concrete, Carpet, and
 wmdowsill.
       A full  factorial design requiring 5x3x5 = 75 unique runs was selected.  Two replicates of
 ^a<* combination were performed  so that some measure of the reproducibility of the dust
 Election procedure  could be estimated.  Thus a total of 150 runs followed wilh  two exceptions:
 Ol»e additional run made on the in-line dust collector and one made on the cyclone dust
 Collector.  The former as needed because of incorrect sampling and the latter was to verify
 P£«orrnance  of cyclone on a concrete surface that provides a collection efficiency of over 100%-
 1J»e runs were scrambled so (hat the two prototypes of each  design were not run consecutively
 nroughout the test.  This was done to eliminate any operator bias in trying to improve the
          : technique wilh repeated runs.

EXECUTION OF TEST

t.     Five principal steps were taken in performing the test:  (1) weighing the cassettes before
|n«y were used to collect dust, (2) applying dust to a surface, (3) collecting the dust from a
 urface, (4) weighing the dust sample, and (5) recording data.
f     The dust was prepared by measuring out 0.9-g aliquot of the dust composite to be used
 °r toe run and added to these paint chips to bring the aliquot to approximately 1 g.  The filter
r^ssette was placed into the dust collector and the aliquot of dust was applied to the 1-sq ft
 "scribed area of the surface (wood floor, linoleum, concrete, and carpet). Dust samples were
  kefi from a defined 1-sq ft area of the surface in overlapping passes, starting from top left
    'mo to the right returning to the left less than one nozzle diameter below. This was
       "* until the right bottom corner was reached.  The process was repeated starting at the
          L. _  j
         	corner going upward.
off   ^ter the dus1 was co"ected wiln the cyclone dust collector and the ax. power was turned
  *. the dust collector operator applied warm, moist air to the interior of the device by mouth
  owing via a short length of tube into the end of the nozzle.  At the same time, the operator
dia1*3 the  outsi
-------
TEST RESULTS
      A total of 152 runs were performed. These included two replicate runs for each of the
75 unique combinations plus two additional runs.  For each run, the collection efficiency (%)
was calculated as:

      Efficiency (%)  •

      Carpet fibers were vacuumed into the cassettes during some carpet runs.  In these cases,
after a cassette was weighed with dust and the accompanying carpet fibers, the fibers were
removed by hand and the cassette was reweighed. An adjusted efficiency was calculated based
on thai reduced weight. Both unadjusted and adjusted efficiency results are shown in Figures 2,
4, and 6 for these runs.
      The absolute and relative variations due to replication for the three  types of dust
collectors are:
Absolute and relative (%) replication errors
Collector type
Blue nozzle
In-line
Cyclone
Without adjustment
2.75
3.93
2.93
15.3%
4.5%
13%
With adjustment
2.61
3.94
125
14.8%
4.5%
2.4%
INTERPRETATION OF STATISTICAL RESULTS

       Blue nozzle dust collector: among the three dust collectors tested, the blue nozzle shows
the greatest variability in collection efficiency when applied to a variety of surfaces and dust
composite types.  It does not achieve the minimum required 85% collection efficiency,
regardless of the surface and size of dust composite panicle sizes.  This is shown by the fact that
the lower 95% confidence  limit to the mean  efficiency is below 85% in all test cases.
       In-line dust collector: the in-line dust collector's efficiency varies significantly between
carpet and all other surfaces, including the windowsill. This holds true for all dust particle sizes.
It docs not achieve the minimum required 85% collection efficiency on carpet, regardless of
dust composite panicle sizes.   However, for all smooth surfaces and the windowsill, the in-line
dust collector achieves a high average efficiency of 94.5%, regardless of dust particle sizes, thus
significantly exceeding the required minimum of 85%.
       Cyclone dust collector:  overall, the cyclone dust collector's performance slightly exceeds
that of the in-line  dust collector. Except for small-sized panicles on carpet, the efficiency of the
cyclone dust collector significantly exceeds the required minimum of 85%. Excluding carpet, the
smallest  lower 95% confidence limit to the mean is 94.0%.  For  small particles, the cyclone dust
collector's mean efficiency of 78.2% does not meet the required minimum of 85% on carpet.

CONCLUSIONS

       The principal conclusions are:  (1) the blue nozzle dust collector is not suitable for the
CAPS because of  its tow dust  collection efficiency, (2) the in-line dust collector is not adequate
for the CAPS because of low rate of surface coverage due to the small nozzle inlet opening;
(3) the cyclone dust  collector is suitable for CAPS.
                                            788

-------
                                                 TjraonTtWng
                                                         Ptt-UpNout*
37-mm G«Hi»n UC£F
           G»»l Vioium Pt*n>
      Figure 1 .  Schematic of dust collector used In pilot study.
      WNozztt
Figure 3. Schematic of MRl-designed vacuum dust collector No, 1.
  110
  TOO
   H
£">
£ n
Jeo
in
c SO
o
I 40
O 30
                                                                                                                                      85%
                                   Clip* AdfraUd
                                                                                                                                  .—
                                                                                                             C2                    C3
                                                                                       + General*    » Unoteum    * Wtodomil   - Wood Floor

                                                                                     Figure 2. Blue nozzle dust collector efficiency.
                              110
                              ! JL
                               u

                               70
                               M

                              *<-•
                               m
                              ...
                               H
                                                                                      Cl
                                                                                                                                     85%
                                                                                                            C2
                                                                                                                                C3
                                                   Conposila Typ«
                                   + Concida    o  LJnoteum    A  WhdowsJU  • Wood Floor
                                                                                       Figure 4. In-line dust collector efficiency.

-------
Figure 5. Schematic of MRI-designed vacuum dust collector No. 2.
                                                                         110
                                                                         too
                                                                        *  >»
                                                                          .
                                                                          .

                                                                            K C*


                                                                                                                    Cl
                                                                             Figure 6.  Cyclone dust collector efficiency.

-------
                       The Development and Validation of a Reliable
                           Household Dust Surface Wipe Sample

 C. Weisel1, P. Yang2, T. Wainman1, J. Adgate1, D. Burns' and P. Lioy1
 1  Department of  Environmental  and  Community  Medicine,  UMDNJ-RWJMS  and the
 Environmental and Occupation Health Science Institute, Piscataway, NJ
 1 Department of Environmental Sciences, Rutgers, New Brunswick, NJ

 Introduction
       Household dust containing lead is a source of lead exposure to infants, toddlers and
 children when the dust is: transferred to their hands and subsequently the hands are placed in the
 mouth, deposited onto food during preparation or resuspended into the air and inhaled.  Thus,
 a  simple reliable method to collect household dust is an essential part of any attempt to assess
 the lead exposure within a home.  Optimally the amount of  lead per mass of dust should be
 reported in addition  to  the lead amount  per  surface area.   The CLEARS  (Childhood Lead
 Exposure and Reduction Study) is evaluating the efficacy of an intensive cleaning regiment of
 households in reducing the  lead exposure and the subsequent blood lead levels in infants and
 toddlers.  To assess the lead exposure from dust, a wipe sampler that had been previously used
 to collect household  dust samples for chromium analysis is being tested for its use for lead
 collection.  This sampler is designed to be easy to use, operator independent and can provide a
 quantification of mass of dust per unit area, the amount of lead per gram of dust, and the amount
 of lead per area for a number of different hard (i.e. non-carpeted) surfaces. This paper describes
 the collection efficiency and reproducibility of this sampler to determine the amount of dust per
 unit area.

 Wipe Sampler
       The dust sampler consists of a template with a fixed-sized opening and a movable plate
 onto which a 37mm filter is placed.  The bottom of the template has a non-skid surface.  The
 filter is placed on a self-adhesive replaceable  silicon disk mounted to the movable plate, that
 provides sufficient friction to move the filter across the surface being sampled.  The handle rests
 on and is  slid across the template  so that the same  pressure is  always applied  to  the filter
 independent upon the operator. The filter is wetted  with  distilled water to increase the dust
 collection efficiency.   The first filter is moved five times across the template from one end of
 the template to 20 mm from the opposite end of the template, since a portion of the  dust is
 pushed along the edge of the filter.  The next filter is wetted with distilled water and is placed
 at the opposite edge of the template from where the first filter was started on top of any dust left
 from the first filter and moved five  times across the template.  A third filter is used to dry the
 surface and to collect any residual dust. Based on a series of five sequential filter wipes, it was
 found that 3 filter wipes collect 93% of the dust, assuming that all dust is collected by the fifth
 wipe (Figure 1).

 Collection Efficiency
       The efficiency of collection was tested using a cardboard chamber to uniformly deposit
 dust on a surface.  Cardboard  is used to minimize the static charge.  Static charge attracts
particles and could result in an uneven dispersion of the dust. The amount of dust deposited was
 determined  by weighing filters that  were placed on the  base of  the chamber prior  to the
                                           791

-------
introduction of the dust into the chamber. Several areas of the bottom plate were wiped and the
amount collected compared to the total deposited.  A collection efficiency based on twenty
samples were 95±8.4% (Figure 2).

Field Sample Comparisons
      The collection reproducibility was also evaluated from the collection of paired samples
at field sites. The result of side by side samples are shown in figure (3). The slope of the linear
regression was 1.0T±..05 and the RJ was 0.89. These samples were collected from different
surfaces,  rooms and floor types. The amount of dust spanned two orders of magnitude with no
bias observed over the entire range. The paired sample data was also analyzed to determine if
any surface type  or location biased the  data.   The mean concentrations collected  in different
rooms (figure 4),  location within a room (figure 5) and floor surface type for two seasons (figure
6) showed no differences between the sample pairs.  The difference between seasons for the
wood  floor  samples is  a function of die sample size  being only three and should not be
extrapolated  to imply a seasonal effect. A statistical test for difference in the means among the
different sets of samples collected (i.e.  fall vs summer, window sill vs floor) indicate that a
statistical difference at me 0.05 level only existed for the floor to window sill for the summer
(Table  1), and no difference in the paired samples was evident in either season.  The probable
reason for a  difference between the window sill and the floor is that a floor is cleaned more
frequently than a window sill, which has greater historic deposition.  This statistically significant
difference was not identified in the fall. One po&nble reason was the same location on the
window sill was sampled during the summer and fall and therefore die amount of dust present
to the fill was only what was deposited in the previous few months.

Conclusions
      In conclusion the dust sampler developed collected >90% of the dust that was present,
side by side samples collected equivalent amounts  and it is easy to use. Studies are currently in
progress to validate that collection efficiency and reproducibility for lead collection on both a per
gram of dust and per cm1 basis.
                                   FIGURE 1

          Cumulative   Percent  Collected

               (assuming 100%  for five  wipes)
      120
          Total Percent Coll«cMd (%)
         0L
          1
                              Sequence Number
                                       2

                                  S«rt*« 6
                                        792

-------
                  FIGURE 2
       Percent  Recovery of Wipe
          Samples in  Chamber
 120


 100


 80


 60


 40


 20
   Percent Recovery (%)
*   *    *  *
* *
             *   *   * *
                Mean Value 95.2%
                 Std Dev 8.4%
   1 23456  7  8  9 10 11 12 13 H 15 16 17 18 19 20
                Sample Number
                  FIGURE 3
        Duplicate Field Samples
        Mass per Sample (mg)
200 r
160 -
100
  Amount (mg)
           50        100        150
                Amount (mg)
                                 200
                   793

-------
                 FIGURE 4
        Duplicate Samples from
         Different Rooms (mg)
  Mass Collected (mg)
400
350
300
250
200
150
100
              i,
         -        -   *
                        	  	    oth»r
                   Room
250

200

150

100

 SO
                 FIGURE 5
        Duplicate Samples from
        Different Surfaces (mg)
  Mass Collected (mg)
    window-till     »helf      frig-top      other
               Surface Type
                     794

-------
                  FIGURE 6
       Duplicate  Samples from
       Different Surfaces (mg)
Mass  Collected (mg)
   ceramic
      Summer 1
linoleum      metal
  Surface Type

HE Summer 2   I -J Fall 1
                                   Fall 2
                    TABLE 1
       Statistical Test for Differences
   Comparison of

 Summer Duplicates

   Fall Duplicates

  Summer Floor to
    Summer Sill
       t-test    prop   significant
                      at .05?
       0.629    .532      no
    Fall Floor to
      Fall Sill

FF to FS Difference
       1.208    .232
       -3.38    .001
SF to SS Difference    -.183   .856
       -1.50    .138
       -.272    .787
no
Yes
                        no
no
no
                      795

-------
    QUALITY ASSURANCE CONSIDERATIONS IN THE ANALYSIS FOR LEAD
       IN  URBAN DUST  BY ENERGY DISPERSIVE X-RAY FLUORESCENCE

                        Harold A. Vincent
                    Quality Assurance Division
                U.S.  Environmental Protection Agency
           Environmental Monitoring Systems Laboratory
                           Las Vegas, NV

                          Dawn M.  Boyer
     Environmental Monitoring Research & Development Program
             Lockheed Engineering & Sciences Company
                           Las Vegas, NV

 INTRODUCTION
     Quality assurance and control for the analysis of lead in
 many materials are hampered by the lack of reference materials
 which  can be used properly for calibration and control purposes.
 This is especially true for the analysis of dusts.  The focus in
 this study was on the determination of lead in household dusts by
 X-ray  fluorescence analysis (XRF) and the kind of quality control
 and calibration that could be used.
     The  physical and chemical characteristics of dusts vary
 widely with location, type of house structure, household inter-
 ior, ventilation, occupant habits, home egress types, and the
 local exterior environment.  Efforts to describe the apportion-
 ment of lead occurrence to specific sample constituents in
 household dust have been attempted by Hunt, et al.(l) using
 scanning electron raicrosope (SEM) and XRF techniques.  This kind
 of information is desirable and helpful but is expensive to
 acquire.
     The National Institute of Science and Technology (NIST) has
 produced standard reference materials (SRMs) containing lead.
 The Research Triangle Institute (RTI) is currently collecting and
 producing bulk amounts of  dusts to be evaluated for applications
 as reference materials.  These efforts will yield materials
 helping  to overcome difficulties encountered due to the differ-
 ences in dusts alluded to  above.
     Appropriate standard  dusts were not available at the begin-
 ning of the EPA's Urban Soil Lead Demonstration Project (USLADP)
 so some site related dust  reference samples were produced to fill
that need.  These were used as double blind audit samples per the
quality assurance plan for the project.  For that project it was
necessary to find whether  soil reference samples could be used
 for calibration of X-ray instruments to be used for dust analy-
 sis.
     Most XRF methods are  comparative and require calibration
using materials similar to those to be analyzed.   Differences in
density, particle size and composition between reference and
unknown samples are correctable if enough information can be
obtained during the analysis.   XRF instrument systems without
 sophistication may lack the capability for proper correction and
thus make the presence of  standards similar to unknowns even more
 important.
                                  7%

-------
     This work focused on the use of analyzed soil samples for
calibration of XRF instrumentation and validation of lead values
obtained from the XRF analyses of unknown and audit dust samples.
Since XRF techniques measure total lead content, comparison can
be made to values obtained with inductively coupled plasma (ICP)
and atomic absorption spectroscopy (AAS) methods, provided those
methods allow for measurement of the total lead content of the
     Household dust samples collected for quality assurance uses
in the USLADP were studied along with various soil reference
samples used for the same project.  The soils and dusts were
collected  in homes and yards in the three cities involved with
the USLADP.  The collected materials were composited to bulk
samples which were the treated and made into the reference
samples described in this work.
     The  six  Dust  samples, which had been prepared for use in the
     P  program, were analyzed by ICP or AAS after dissolution in
hot nitric  acid.   The determinations of lead were also made on
the six samples by X-ray fluorescence analysis using soil refer-
ence standards for calibration of that instrumentation.  The dust
samples had been sieved to pass through 60 mesh screens but were
oredominant in finer grained material.
     The  six  soils used for calibration, known as the Rufus
Chaney  (RC) standards, had been pulverized to pass 60 mesh,
homogenized,  and analyzed by ICP or AAS depending on the concen-
t-ration level of lead.  For XRF determinations, these calibration
 tandards were packed as loose powders in 31mm diameter sample
holders in  amounts to exceed 2 grams for each holder.
     A  study  subsequent to this work (1) showed that a minimum
 ample  size of 0.9 grams is required for infinite thickness when
Ssing silver  excitation and with the instrument configuration
     for  this work. This relationship is illustrated in Figure  1.
                                         1518 nig/kg Pb
               JOOOO -i
                             SAMPLE MASS (G)
        Figure 1.  Infinite thickness for XRF determina-
        tion of lead in dusts.
                                797

-------
      All samples were analyzed in a Kevex DELTA 770 Analyst model
 X-ray fluorescence spectrometer using the silver K-lines from a
 silver secondary target as the excitation.  The analysis involved
 measuring the intensity of the lead L-beta fluorescent line at
 12.62 kev and the intensity of the Compton scatter from the
 silver excitation at approximately 21 kev.
      XRF calibration was done by plotting the ratio of the Pb L3
 line to silver scatter intensities versus the chemical analysis
 values for the RC soil calibration standards.  Laboratory control
 standards at 440 and 17993 mg Pb/kg,  respectively,  along with
 NIST #1648 Urban Particulate,  were used to provide a reasonable-
 ness check on the values and traceability to standard reference
 materials.  The results of the XRF determinations for Pb are
 shown in table I.

                              TABLE I

            METHODS CQMPARTfifW FOR LEAD DETERMINATIONS

      Sample      Type        Pb by XRF        Pb bv ICP/AAS
                               (mg/kg)            (mg/kg)

      BALOl       Dust         78                 58
      CIN02       Dust        252                279
      BAL02       Dust        330                285
      BAL03       Dust       1480               1518
      CIN01       Dust       2433               2275
      BOS01       Dust      17015              20000

      Cincilow     Soil       303                325
      Baltlow      Soil       640                665
      Balthigh     Soil       923                996
      Bostlow      Soil       3132               3358
      Bostmid      Soil       6090               6428

RESULTS
     An energy dispersive X-ray  fluorescence  (EDXRF)  spectrum for
the dust sample BALOl is presented  in  Figure  2.  showing  the two
major L-lines available for  use  in the lead determination and the
silver Compton scatter line  at approximately  21  kev,  which is
used  for the intensity ratio calculation.  This  dust  sample was
determined by XRF to  contain 78  mg Pb/kg.  There are  no  apparent
spectral line interferences.
     The inset in Figure 2 shows an enlarged  picture  of  the
energy range containing the  Pb La and  L6 peaks.   The  peak to
background ratio, apparent in this inset graph,  indicates that
the determination is  well above  the detection limit for  lead in
this kind of sample.
     Figure 3 shows spectra  for  three  samples with  varying lead
content.  The most intense lead  lines  are  for sample  dust,  BOS01,
which was determined  by ICP  measurements to contain 20,000 mg/kg
lead and by XRF to have 17015 mg/kg lead.
                                798

-------
      4
    s

  >• trt
                  -    ;;
             ^^~         _*..

                                 *• *o  rt M  n
                        J>
rigur* a   tOXXF >p*ctnai for A du«t with low
           l*v«l l««d content.

                         •01
  «o «»       •*          ?«

rigur* 3.  BOXRF »p»ctra  for thr** du«t».

-------
     Figure 4 shows a plot of  the values  for X-ray fluorescence
analysis of lead in the RC standards  versus chemical values for
the samples up to 4000 mg/kg lead.  The solid line drawn is a
linear regression line for that  relationship.  Symbols for the
dust samples on the plot  show  that  the fit of XRF-derived values
are as good or better than for soil audit samples.
                       XRf analysis for soi Is and dusts
                         tn RC soi i Stas  ca i tt^at ion
                       versus AAS/ICP analysis
                           JUJQIT SOUS  * CXSTS  * OC SOIL STANDARDS
        rigur* 4.  X-ray versus chemistry; regression line
        fit.
DISCOSSIOM
     Comparison of spectra for the dust sample with spectra for
soils used  in  this study did not show the presence of any ele-
ments nor any  unusual  concentrations that would likely interfere
with the use of soils  for calibration. No sample density  or
particle size  measurements were made.
     The Pb Lfi line at 12.61 Xev was chosen for use over the Pb
La  line at  1O.54 kev because of the higher X-ray penetration
depth for sampling of  the more energetic line. Possible spectral
interferences  for the  10.54 kev line by the presence of arsenic
 in  any  samples were avoided by this choice.
                                 800

-------
     The data  for both soils and dusts  indicate a  close  fit of
 XRF values  to  chemical values that the  origin  of the  material  is
 n°t a significant variable.   The samples  can be considered site-
 typical so  that  site-specific references  are not required  for
 this project.
     The lack  of agreement of the XRF value for the dust sample
 with the highest lead  versus the ICP value is  similar to that
 observed for soil  samples with similarly  high  lead content.  The
 non-Linearity  of XRF analysis for higher  concentrations may be
 attributed  to  sample absorption of X-rays or instrumental  charac-
 teristics at high count rates.   This can  be accounted for  with
 the use of  calibration curves.   Most of our interest  for the
 Present work lies  in the 0-4000 mg/kg concentration range.
     All x-ray work in this  study was done using an EDXRF  detec-
 ^°r-  XRF is a more inclusive term than EDXRF  and  is  used  more
 frequently  throughout  this paper because  the findings should be
 similar for wave-length and  other XRF techniques.

 CONCLUSIONS
     Analyses  of dusts by XRF for Pb in the 0-4000 mg/kg range
 showed good agreement  with chemical analyses.  Use of soil
 *eference standards for calibration of  the X-ray analyzer was
 prS?d t0 be pr°Per when aPPlied  to analyses of dusts  in this

     Apparent  self absorption of the sample or of lead in the
 staple occurs  at higher concentrations  for both dusts and soils
 aM causes  the response to be non-linear at some concentration
    — 20,000  mg/kg.

                          BIBLIOGRAPHY

   Hunt,  A., Johnson,  D.L.,  Thornton,  I.,  "Descriptive Apportion-
   "• of Lead in  Housedust by  Automated SEM",  Water. Air and Soil
            Vol 57/58,  pp€9-77  (1991).

 ?! Boyer,  D.M.,,  Hillrnan, D.C. , Vincent,  H.A.,  "Minimum Sample
 ^ze for the Analysis  of Lead in Urban Dust by Energy Dispersive
 A-ray Fluorescence", Pittcon"92. New Orleans,LA, March 9, 1992.

                              NOTICE

Although the research described  in this article has been funded
 wnfMi.. jor  in partj fay the United states Environmental Protection
        through Contract Number  68-CO-0049 to the Lockheed Engi-
      .  and Sciences Company, it has not been subjected to Agency
    ew.  Therefore it does not necessarily reflect the views of
    Agency and no official endorsement should be inferred.
                               801

-------
       Session 18
Ambient Air Measurements
 Dennis Lane, Chairman

-------
                     A  REVIEW  OF

              SE>ECIA1?ED   NMOO   DATA.
                          Keith Baugues
                    Emission Inventory Branch
           Office of Air Quality  Planning  and  Standards
                             U.S.  EPA
              Research Triangle park,  North  Carolina
ABSTRACT
     Samples of  ambient  nonmethane  organic  compounds (NMOC)  were
collected  in canisters in  numerous  cities between 1984 and 1988.
Many of these  samples were analyzed to determine individual  NMOC
peaks.   This  paper focuses  on an analysis of  this  data  set.
Several statistics have been computed including:  the average carbon
number, the average molecular weight and the split factors used in
the Carbon Bond  4  chemical mechanism for photochemical modeling.
in  addition,  the  relative abundance  of  major  peaks  and  trends
observed in the data are discussed.

INTRODUCTION

     During the  summers  of 1984  through 1988, morning (6-9 a.m.)
measurements of  ambient  nonmethane  organic  compounds (NMOC)  were
collected  at numerous  cities across the  United States.   Samples
were taken on weekdays, typically from June through September.  A
subset of  these samples were analyzed using gas chromatography to
determine  the relative abundance of  individual hydrocarbons.  This
paper focuses on an analysis  of  this data set.   Discussions will
cover only those NMOC sites which  have  been designated as urban
sites.  Since  the  number of samples analyzed varied from city to
city and  year  'to  year,  the reader  is cautioned  to  question any
results based  upon small  sample sizes.   Results for  all urban
sites,  regardless of   sample   size,   have  been  included  for
completeness.   A  small  percentage  of  each  sample was  listed as
unidentified.   This small fraction has  been  excluded  from the
analyses described in this paper.

AVERAGE CARBON NUMBER

     A carbon  number  is  the average number  of  carbon atoms  in a
typical  hydrocarbon molecule.    This  value is  of  interest to
researchers.  Average carbon numbers for the 66 city/years ranged
from 4.4 to 6.9 with a median level of 5.0.  Fifty percent of the
_ity average values fell between 4.8 and 5.2.   Individual values
are shown  in Table I.
                              SOS

-------
 AVERAGE  MOLECULAR WEIGHT

      The average molecular weights  for the 66 city/years  ranged
 from 60.8 to 85.9 with a median level of 67.8.   Fifty  percent  of
 the   city averages  fell  between  65.7 and  70.0.    Values for
 individual city/years  are listed in  Table  I.

 CARBON BOND 4  SPLITS

      Emissions of  nonmethane organic  compounds  are  treated  as
 various  classes  of compounds within  chemical mechanisms.   The
 Empirical Kinetic Modeling Approach (EKMA) utilizes the Carbon Bond
 4  mechanism.   Table I shows the  percentage  of  emissions  within
 various   chemical   classes.    The  abbreviations  represent the
 following:

 PAR   - paraffins          ETH  -  ethylene        OLE - olefins
 ALD2  - higher  aldehydes   FORM -  formaldehyde    TOL - toluene
 XYL   - xylene             ISOP -  isoprene        MR  - nonreactive

      The overall  average at the  bottom  of   Table  I  is  being
 considered as  a new default value  for use with  EKMA.

 REACTIVITY

      The California Air  Resources Board (CARB)  has  developed a
 method of estimating reactivity based upon modeling analyses using
 a detailed chemical mechanism.1'3  The values computed in this paper
 are  based upon the maximum   incremental reactivity (MIR)  scales
 developed for  CARB.  The values shown  in  Table I, under  average
 reactivity,  reflect the  maximum  amount  of  ozone  formed given the
 amount of VOC and the reactivity  of the VOC for each city.   The MIR
 scales were developed for low  NMOC/NOx ratios.  The values computed
 using  the MIR scale estimate  reactivity  based on two components  of
 NMOC.  The first  is the  amount  of NMOC, while the second is the
 reactivity  of  the individual compounds.   The  average  reactivity
 values range from  456  to 2377 with a city  median of 1013.   Fifty
 percent  of the  values fall between 772 and 1400.
     In  order  to  determine the  impact  of the  speciation alone I
 have developed a term called  standardized reactivity.  This is the
 reactivity computed  using the MIR  scales,  but  standardized  to  an
 NMOC  level  of  l ppraC.    The standardized reactivity values  range
 from  1219  to 1780 with  a median of 1530.   Fifty percent of the
values fall  between 1450 and  1600.   Ninety percent of the values
 fall between 1350  and  1700.   Therefore, much of the variation  in
 reactivity  from city to  city is due to the amount of NMOC, not
 necessarily a different composition of NMOC.
     The reactivity values for individual days within a city also
 show a large range.  Table II displays reactivity values for each
of the days  sampled in 1985 in Dallas,  Texas.   Also shown is the
 amount of reactivity from paraffins, olefins, aromatics and  other
compounds.  There  is more than a  factor  of five difference between
                               806

-------
 the rainiaum and maximum reactivity values.  In this case, nearly
 all of the difference appears to be due to a lower amount of voc on
 the minimum day.   The standardized reactivity values do not show
 this  wide  distribution.    The range in  standardized  reactivity
       is between  1327  and  1782.
PREVALENT COMPOUNDS

     Table in illustrates the top 12 compounds found within urban
samples presented here.  These  12 compounds make up fifty percent
of  the  mass on a ppbC basis.  The  most prevalent compounds are
isopentane, followed by n-butane and toluene.


TRENDS

     Data from  two  sites were  analyzed:  Dallas,  Texas (5 years ,
i9B4-i9fc7) and Fort Wortn, Texas t* years, 19&4-19S7>.   The average
concentration  of the  top  12  compounds,  discussed above,  were
analyzed  UBing Daniel's  Test  to  determine  if any trends  were
Present at  the 95%  confidence level.   In Dallas  the following
trends  were observed:  isopentane,  m  &  p xylene  and n-pentane
(downward) and acetylene (upward).  The trends in Fort  Worth were:
Propane, ethane and acetylene (downward).

INCLUSIONS

     The typical hydrocarbon compound in an urban area has a carbon
juptber of 5.0,  a molecular weight of 67.8 and a reactivity value or
Jbe  maximum incremental reactivity  scale  of  1013.   Reactivity
values computed using the MIR scale show a wide range from city to
city and from day to day at a given  site.  When these  values are
standardized to renove the  influence of  the  amount of NMOC,  the
Jange is  decreased  significantly.   The  most prevalent compounds
found were  isopentane, n-butane and toluene*   Data at two sites
^dicate downward  trends in  a  few  compounds,  but there  was  no
a9reement in which compounds were decreasing between the two sites.
 Barter,  W.P.L.,  "Development  of  Ozone Reactivity  Scales  for
v°latiie Organic Compounds"t EPA-600/3-91-050  (August 1991}

 *^t Resources Board,  "Proposed Reactivity Adjustment Factors for
ffansitional Low-Emission Vehicles - Technical Support Document",
La*ifornia Air Resources Board  (September 27, 1991)
                               807

-------
                                                         TABLE I

                                   Various Statistics  for Aibient VOCs frci Urban Sites
                          No.      Avg  Avg                                                        Average       Standardized
City/State          year  Sables  C Ho. Ml    PAR   m   OLE   ALD2  POM  TOL   XYL   ISOP  XR    Reactivity    Reactivity

                                          64.8  0.535  0.027 0.042 0.050 0.025 0.105 0.107
                                          71.4  0.562  0.037 0.036 0.054 0.022 0.112 0.123
                                          66.8  0.540  0.040 0.027 0,056 0.020 0.112 0.130
                                          70.1  0.573  0.021 0.028 0.054 0.020 0.099 0.137
                                          85.5  0.541  0.013 0.019 0.056 0.021 0.166 0.152
                                          66.1  0.532  D.D33 0.031 0.057 0.021 0.119 0.127
                                          61.2  0.582  0.033 0.028 0.049 0.021 0.081 0.088
                                          62.4  0.656  0.010 0.026 0.059 0.020 0.062 0.064
                                          67.2  0.702  0.009 0.026 0.071 0.020 0.063 0.066
                                          84.4  0.640  0.014 0.024 0.053 0.020 0.089 0.124
                                          65.3  0.510  0.046 0.032 0.059 0.021 0.120 0.138
                                          73.3  0.543  0.014 0.022 0.051 0.021 0.1(2 0.132
                                         69.5  0.510 0.034 0.020 0.039 0.020 0.152 0.152
                                         68.5  0,542  0.033 0.027 0.061 0.020 0.128 0.124
                                         70.9 0.556 0.035 0.026 0.053 0.021 0.132 0.118
                                         67.8  0.579  0.024 0.026 0.050 0.020 0.109 0.115
                                         69.1 0.568 0.035 0.027 0.052 0.021 0.118 0.117
                                         71.4 0.599 0.028 0.027 0.048 0.021 0.098 0.113
                                         79.3 0.600 0.014 0.038 0.045 0.023 0.134 0.114
                                         64.7 0.548 0.034 0.024 0.048 0.022 0.102 0.123
                                         63.6 0.557 0.027 0.025 0.045 0.021 0.1D1 0.111
                                         70.0 0.559 0.028 0.029 0.054 0.023 0.113 0.118
                                         67.2 0.567 0.031 0.027 0.051 0.021 0.101 0.113
                                         65.6 0.537 0.034 0.021 0.058 0.020 0.120 0.117
                                        65.9 0.558 0.020 0.024 0.048 0.021 0.112 0.126
                                        64.8 0.556 0.039 0.026 0.053 0.021 0.093 0.120
                                        64.0 0.580 0.033 0.025 0.057 0.021 0.092 0.098
                                        64.4 0.557 0.019 0.054 0.045 0.021 0.095 0.114
                                        64.3 0.559 0.018 0.067 0.043  0.022 0.091 0.100
                                        66.4 0.568 0.034 0.033 0.054 0.023 0.098 0.104
                                        66.1 0.560 0.035 0.039 0.057  0.022 0.096 0.109
                                        67.2 0.561 0.033 0.025 0.057 0.021 0.107 0.121
                                        69.7 0.631 0.012 0.025 0.072  0.020 0.067 0.098
                                        66.2 0.555 0.037 0.027 0.068  D.020 0.100 0.115
                                        69.8 0.555 0.038 0.033 0.049  0.024 0.115 0.114
                                        69.4 0.590 0.029 0.030 0.049  0.023 0.105 0.100
                                        65.1 0.539 0.038 0.027 0.047  0.021  0.110 0.123
                                        70.0 0.567 0.020 0.023 0.046  0.021 0.127 0.131
                                        74.0 0.449 0.022 0.027 0.054  0.021  0.237 0.144
                                        67.1 0.579 0.024 0.031 0.059  0.021  0.112 0.107
                                        69.1 0.625 0.025 0.026 0.057  0.021  0.079 0.095
                                        69.2 0.538 0.043 0.030 0.061  0.021  0.106 0.133
                                        69.1 0.529 0.034 0.036 0.059 0.022 0.126 0.123
                                        66.6 0.552 0.035 0.025 0.059  0.021  0.118 0.115
Akron 1, OH
Atlanta 1, GA
Atlanta 1, GA
Atlanta 1, GA
Austin 1, TX
Baltiiore 1, MD
Baton Rouge 1, LA
Baton Rouge 1, LA
Boston 2, KA
Boston 2, MA
Bridgeport 1, CT
Bronx 1, HY
Bronx 1, NY
Brooklyn l, HY
Chicago 1, 11
Chicago 1, IL
Chicago 2, IL
Chicago 6, IL
Cincinnati 1, OH
Cleveland 1, OH
Cleveland 1, OB
Dallas 1, IX
Dallas 1, TX
Dallas 2, TX
Dallas 2, TX
Dallas 2, H
Denver 1, CO
Detroit 1, Id
Detroit 2, n
Port north 1, w
Fort north 1, TX
Fort north 1, TX
Port north 1, M
Houston 2, TX
Indianapolis 1, IK
Kansas City 1, »
Kansas City 1, MO
Manhattan 1, »Y
Manhattan 1, RY
Manhattan 9, R
lashville 1, Tl
lashville 2, Tl
Xev Haven 1, CT
lev York 1, IV
84
84
86
67
88
86
85
87
87
88
86
87
38
86
86
87
86
88
84
85
88
84
85
86
87
88
86
88
88
84
85
86
87
86
84
84
85
87
88
88
88
88
86
86
10 4.7 64.!
9 5.3 71.<
14 5.0 66.1
17 5.1 70.]
15 6.9 85.!
8 4.9 66.1
15 4.5 61.2
15 4.5 62.4
17 4.8 67.2
11 6.2 84.4
15 4.9 65.3
14 5.6 73.3
1 5.2 69.5
16 5.1 68.5
10 5.3 70.9
20 5.0 67.8
14 5.1 69.1
2 5.2 71.4
7 6.1 79.3
17 4.7 64.7
15 4.7 63.6
13 5.2 70.0
21 4.9 67.2
13 4.9 65.6
11 4.9 65.9
13 4.7 64.8
14 4.7 64.0
13 4.7 64.4
6 4.8 64.3
13 4.9 66.4
19 4.8 66.1
16 5.0 67.2
9 5.1 69.7
12 4.9 66.2
10 5.1 69.8
11 5.1 69.4
15 4.8 65.1
12 5.2 70.0
7 5.6 74.0
11 5.0 67.8
9 5.0 69.1
1 5.1 69.2
15 5.2 69.1
11 4.9 66.6
1 0.002 0.108
1 0.003 0.051
0.005 0.070
1 0.003 0.066
0.001 0.030
1 0.003 0.077
0.003 0.115
0.002 0.100
0.001 0.042
0.001 0.034
0.002 0.071
0.002 0.053
0.003 0.069
0.002 0.062
0.002 0.057
0.001 0.076
0.002 0.060
0.001 0.064
0.004 0.028
0.001 0.099
0.002 0.110
0.004 0.072
0.004 0.078
0.003 0.090
0.001 0.090
0.002 0.090
0.002 0.092
0.002 0.092
0.001 0.098
0.002 0.084
0.002 0.080
0.002 0.073
0.001 0.055
0.003 0.076
0.001 0.070
0.002 0.072
0.003 0.091
5,001 C.066
0.002 0.045
0.002 0.065
0.016 0.057
0.004 0.065
0.003 0.067
0.002 0.073
672
1490
849
772
2336
1202
759
858
831
1159
787
829
502
1179
1946
1625
1397
1574
2050
1524
1233
1021
1103
907
681
708
1262
1084
994
1482
1108
916
1203
1578
1402
1376
819
835
2377
1097
619
1339
972
908
1453
1622
1662
1576
1760
1638
1323
1219
1296
1345
1780
1571
1533
1652
1591
1472
1594
1456
1727
1461
1390
1507
1546
1561
1481
1501
1465
1602
1637
1482
1560
1579
1445
1629
1528
1421
1574
1504
1765
1521
1438
1701
1697
1579
                                                           808

-------
                                                  TABLE I (continued)

                                  Various Statistics for Aibient VOCs froi Urban Sites
                         Nc.      Avg   Avg                                                     Average        Standardized
City/State          Year  Saiples  Cto. ffl   PAR   m   OLE   ALD2  FORK  TOL   XYL   ISOP  MR    Reactivity     Reactivity

Newark 1, KJ          96       14   4.9   66.7 0.502 0.042 0.035 0.055 0.020 0.133 0.134 0.001 0.076   1632            1722
Newark 1, W          87       11   4.9   66.3 0.534 0.016 0.033 0.055 0.021 0.119 D.132 0.001 O.OBB    765            1564
Kevark 1, H          88        7   5.1   70.0 0.557 0.011 0.032 0.064 0.021 0.150 0.103 0.002 0.059   1585            1531
Philadelphia 1, PA    85       10   5.0   67.7 0.556 0.027 0.029 0.052 0.022 0.111 0.122 0.002 0.081   1107            1494
Philadelphia 1, FA    86       12   4.8   65.7 0.609 0.025 0.029 0.045 0.021 0.098 0.09] 0.001 0.079    613            1393
Portland 1, HE        85       10   4.9   67.6 0.618 0.022 0.028 0.066 0.021 0.091 0.086 0.003 0.06}    866            1400
Providence 1, H      88       11   5.4   73.0 0.541 0.029 0.03] 0,052 0.022 0.127 0.131 0.003 0.061    738            1615
Salt Lake City 1,  DT  86       15   4.6   63.9 0.622 0.023 0.041 0.059 0.020 0.070 0.069 0.001 0.095   1835            1133
Salt Lake City 1,  OT  87       12   5.0   68.8 0.651 0.011 0.022 0.047 0.020 0.087 0.088 0.001 0.073    919            1271
San Diego 1, CA       87        9   5.0   61.4 0.547 0.023 0.017 0.042 0.021 0.118 0.144 0.002 0.087    503            1463
San FranciSCO 1, CA   87       23   5.4   72.8 0.531 0.023 0.023 0.040 0.021 0.148 0.141 0.001 0.073    458            1507
Suringfield 1, HA     88        8   5.0   68.9 0.613 0 021 D.031 0.079 0.021 0.096 0.089 0.002 0.048   1494            1535
St LOUIS 1, NO        85       17   5.1   68.5 0.551 0.028 0.025 0.049 0.022 0.117 0.116 0.003 0.089    945            1(78
St LOUIS 1, NO        87       ID   6.8   85.9 0.584 0.005 0.019 0.041 0.021 0.167 0.116 0.002 0.045   1813            1405
St LOUIS 1, HO        88       12   5.3   71.7 0.509 0.016 0.029 0.046 0.021 0.186 0.112 0.002 0.078   1089            1495
^ISjl  a;           86       IS   (.4   60.90.6280.0200.0240.0460.0200.0600.0790.0030.120    572            1243
Visalia'l, CA         87       14   4.5   60.8 0.525 0.015 0.017 0.037 0.020 0.105 0.145 0.001 0.133    457            1358
Bjshjnsta) 1( DC      84       11   5.2   70.3 0.551 0.038 0.037 0.056 0.023 0.118 0.122 0.004 0,051   1506            1641
HashiMton 1, DC      85        9   5.0   66.9 0.508 0.043 0.032 0.054 0.0210.126 0.144 0.005 0.067   1006            1722
Lhiwton 1, DC      86        7   4.9   66.2 0.538 0.034 0.023 0.046 0.020 0.12) 0.131 0.004 0.081    494            1581
aorcester 1, MA       88       13   5.2   70.3 0.518 0.040 0.031 0.058 0.021 0.123 0.137 0.003 0.067    880            1691
" pali Beach 1, PL   84        8   5.8   78.6 0.621 0.022 0.033 0.044 0.027 0.113 0.1D2 0.003 0.035    665            1427

                              795   5.1   68.50.5660.0270.0290.0540.0210.1130.1140.0020.073   1091            1526
                                                           809

-------
                          TABLE II

         ACTIVITY SDUHARY  DALLAS 1985
DATE     PPBC     PAR
OLE
AROH
         TOTAL
         AVERAGE
OTHER    REACTIVITY
6/10/85
6/21/85
6/26/85
7/1/85
7/5/85
7/9/85
7/10/85
7/11/85
7/23/85
8/1/85
8/2/85
8/7/85
8/12/85
8/28/85
9/3/85
9/5/85
9/11/85
9/12/85
9/16/85
9/16/85
9/20/85
875
621
542
1237
334
543
507
654
1771
323
1209
469
858
800
560
334
605
685
610
598
843
282
184
163
439
107
162
168
201
561
117
381
157
253
267
155
113
212
237
209
208
295
481
327
302
390
140
318
270
373
961
153
669
245
514
461
276
176
305
427
423
382
522
589
493
493
810
222
486
317
409
1201
197
883
310
522
499
591
227
333
389
329
324
423
5 1357
4 1008
2 960
3 1641
1 470
2 968
2 757
3 986
15 2738
1 468
1 1939
3 714
5 1334
7 1234
2 1024
2 517
4 859
4 1057
2 963
3 917
7 1252
TOTAL
STANDARDIZED
REACTIVITY

   1550
   162*
   1773
   1327
   1407
   1782
   1493
   1508
   1546
   1449
   1604
   14(8
   1556
   1542
   1827
   1547
   1420
   1543
   1579
   1532
   1485
                                                        TABLE III

                             PREVALENT VOC COHPODHDS 11 URBAN SAKPLES AHALYZED  IK THS
              Isopentane
              H-Butane
              Toluene
              Propane
              X 4 P Xylene
              H-Pentane
              Ethane
              C-10 Aroiatic
              Isobatane
              Acetylene
              2-Hethylpentane

              TOTAL
                Percent of Total

                      7.7
                      7.5
                      6.9
                      4.0
                      3.5
                      3.4
                      3.2
                      3.0
                      2.9
                      2.8
                      2.8
                      2.3

                     50.0
                                            810

-------
                                What is  the
            Monitoring Technology  Information Center(AMTIC)?

                             Joseph Burns Elkins, Jr.
                       U.S. Environmental Protection Agency
                 Office of Air Quality Planning and Standards (MD-14)
                        Research Triangle Park, N.C. 2771 1

ABSTRACT

      The Ambient Monitoring Technology Information Center (AMTIC) is operated by the
• I §  Environmental Protection Agency's Office of Air Quality  Planning  and Standards
/OAQpS' through the Technical Support Division in the Monitoring and Reports Branch. The
f cos of AMTIC is to encourage the exchange of ambient  air monitoring technology
; forrnation.  The two vehicles AMTIC currently uses to provide that information are a
  uarterly news bulletin, The AMTIC NEWS, and the AMTIC Electronic Bulletin Board System

'     The establishment of AMTIC is a part of an ongoing effort by OAQPS to efficiently
   tribute jnformation to its clients and henceforth allow these customers to more effectively
conduct their business.

|NTRODUCTION

      The  Ambient Monitoring Technology Information Center (AMTIC) is operated by the
  5  Environmental Protection Agency's Office of Air Quality  Planning  and Standards
~IAQPS) through the Technical Support Division in the Monitoring and Reports Branch. The
J cus of AMTIC is to encourage the exchange of ambient  air monitoring technology
•formation.  The two vehicles AMTIC currently uses to provide that information are a
'uarterly news bulletin, The AMTIC NEWS, and the AMTIC Electronic Bulletin Board System
(BBS)-

    AMTIC NEWS
      The AMTIC NEWS is a quarterly publication of  U.S.EPA's  AMTIC.  It  contains
•  formation on all reference and equivalent methods for criteria pollutants in each issue. It
'n  contains articles of general interest to the ambient monitoring community pertaining to:
   rning ambient monitoring regulatory changesO.e. enhanced ozone, Part 58 changes, lead,
°tc ); emerging ambient monitoring technology (i.e. open path); ambient monitoring studies
 * interest; upcoming meetings and training  of interest; ambient air quality trends; quality
   prance issues related to ambient air; etc.
                                      811

-------
 The Ambient Monitoring Technology Information Center Electronic Bulletin Board

      The  AMTIC  Bulletin Board  System (BBS)  is accessed  through  EPA's OAQPS
 Technology Transfer Network (TTN). It is open to all persons interested in ambient air
 monitoring. To access the AMTIC BBS an IBM or IBM-compatible computer, modem, and
 communication software capable of communicating at 1200, 2400, or 9600 baud, set to
 8 data bits, 1  stop bit, and no parity (8-N-1) are needed. First time users will be asked to
 identify themselves by answering a short registration questionnaire. Access will be restricted
 until the Technology Transfer Network (TTN) BBS System Operator (SYSOP) has reviewed
 the registration. The TTN BBS SYSOP usually approves the registration the next business
 day and then the individual has full access to the AMTIC BBS. The BBS telephone numbers
 are :
      919-541-5742    (1200 or 2400 baud)
      919-541-1447    (9600 baud)
      The AMTIC BBS is formatted  such that each time you log on to the system you will
 have the opportunity to read alerts related to ambient air monitoring technology. Beyond the
 AMTIC ALERTS is the Main AMTIC BBS menu. It has four major categories which are:
 Utilities, File Transfers, AMTIC Communications, and Public Communications. A review of
 each of these areas will follow.

 AMTIC Utilities

      The AMTIC Utilities  section presently allows the user to subscribe to the  AMTIC
 NEWS and/or register to  receive a copy of the "National Air Quality and Emissions Trends
 Report, 1990." The section also provides the opportunity to read a welcome to AMTIC and
 includes a brief description of this BBS.  Additionally available through this section is the
 opportunity to read the  AMTIC  alerts again.   There are  other system utilities that are
 available through this section by returning to the TTN Top Menu.The other feature available
 through this area is to exit not only  the AMTIC BBS but the entire TTN BBS by using the
 Goodbye feature. Table I below is the AMTIC UTILITIES section menu of the AMTIC BBS.

 Table  I. The AMTIC  BBS  UTILITIES Section.

                        •*   AMTIC UTILITIES   *»
      ELCOME TO AMTIC
      ead AMTIC Alerts
      ubscribe to AMTIC NEWS
      Request 1990 Trends Report
      <-> Return to Top Menu
      oodbye
Table II are the system utilities available through the TTN Top Menu that may be accessed
by depressing <-> from the AMTIC Main Menu.
                                      812

-------
Tab'e II. The TTN BBS Utilities.
                               SYSTEM UTILITIES
ystem Information
ecent Callers
Chat with SYSOP
hange Terminal Conftg
< A > rchievers/Dearchievers
 TTN User's Manual
                                  ho else is on
                                  eave SYSOP a Message
                                  

Change Password ser Registry elp Downloading/Uploading The AMTIC COMMUNICATIONS section of this BBScontains information in four areas "•ch are indicated In Table III below. tion Menu. JNICATIONS ews Points of Contact Studies of Interest Vgi(abJe Related Training ^ _^^__^^=a5a^^s^gs^:^=^=^=s==== 1 a*>ove mentioned < N >ews area fs particularly interesting in that it contains manv ambient monitoring topics including an °PP^unity to read the text . IEWS bulletins, the IMPROVE newsletter, On the MR wjh AMBB, JJ^J™* of Interest, and examine ambient monitoring news that is Around the Corner The -Around the Corner News" section contains informat,on concern.nfl^ cntena Lo::;«nts, monitoring news from the EPA regional offices, momtonng news from State and ^ agencies, InfoVmatior concerning ambfent monftoring related traln.ng, and a Cel|aneous section. —«A*^^_^t^^U£]^jljU,^^KHLIU^^UG The AMTIC Communfcations section of this BBS allows users to send private onic mail to other TTN users or to post public messages for other ™ users to review !!**"11 of Private electronic rnafl and public messages will automatically be. no^fied thev Io8 Int« the TTN. Distribution systems can be established that altow the user to the same message to multiple TTN useis. , The Publlc Message portion has been used for a variety of ambient related topics 'nfl the Information rented to Federal Register notices, flow controllers open, perth or8, N0x analyzers, etc. It is recommended that a user review the Publlc Message Board re logging off. 813


-------
 AMTIC File Transfers

      The File Transfer section of the AMTIC BBS contains the majority of the information
 contained within this BBS.  Table 4 below contains the major categories of information
 available through the File Transfer section.


 Table IV. The AMTIC FILE TRANSFER Section Main Menu.

                                 FILE TRANSFERS

        Ambient Monitoring Methods
         Ambient Monitoring QA & QC
         Available Related Publications
         Code of Federal Regulations
       < D >  Trend & Nonattainment Information
         Visibility Information

      There are six pollutants that have National Ambient Air Quality Standards (NAAQS):
 paniculate matter as PM-10, sulfur dioxide (S02), carbon monoxide (CO), nitrogen dioxide
 (N02),  ozone (O3), and lead (Pb).  In the Ambient Monitoring Methods section there is
 information  on  each of the approved 84 reference and equivalent methods for these
 pollutants.  There is also information concerning noncriteria pollutants such as five of the
 trace organic methods (T01-T05). The Ambient Monitoring QA & QC section contains much
 information including a complete electronic copy of "Quality Assurance Handbook for  Air
 Pollution Measurement Systems, Volume I."  The  Available Related Publications section
 contains information on  several topics including  how  to  obtain hard  copies of EPA
 documents.  The Code of Federal Regulations (CFR) contains electronic copies of the Federal
 Regulations pertaining to ambient air monitoring and some of the proposed regulations in this
 area including 40 CFR 50,  40 CFR  53,  40 CFR 58, and the proposed enhanced ozone
 regulations with accompanying guidance documents. The Trend and Nonattainment section
 contains among other items maps of the nonattainment areas and a trends slide show. The
 Visibility Information  section contains all  the currently available Interagency Monitoring of
 Protected Visual  Environments (IMPROVE) optical data.

 CONCLUSION

     Information management  is becoming critical in the  efficient performance of our
 missions. The U.S. EPA through its OAQPS is establishing information centers to provide
 users with convenient access to specialty air information centers. The AMTIC is an  example
of this.  The AMTIC contains Information on methodology, Federal regulations, quality
assurance, trends, available related publications and documents, data, visibility, points of
contact, news, etc. related to ambient air. The AMTIC uses a quarterly news bulletin and
an electronic bulletin board as  its primary mechanisms to distribute  this information.
Additional information on either may be obtained by contacting:
AMTIC, OAQPS,TSD(MD-14),Research Triangle Park, NC 27711.
                                       814

-------
          SUMMARY   OF   NMOC ,   NO:>c  AND

                    NMOC/N03C   DATA

                      BETWEEN   1 ^ 8 4  AND   3.988
                          Keith Baugues
                    Emission Inventory Branch
           Office of Air Quality Planning and Standards
                             U.S.  EPA
              Research Triangle Park, North Carolina
ABSTRACT
     This paper discusses the NMOC data collected during the 6-9
a.m. canister  program between the years 1984  and  1988.   Various
statistics are computed and discussed.  In particular, the analysis
focuses on:
  1) variability of values between sites (where a city has 2 sites)
  2) trends in NMOC, NOx and NMOC/NOx ratios and
  3) NMOC, NOx and NMOC/NOx ratios on low and high ozone days.

INTRODUCTION

     During the  summers of  1984  through 1988,  morning (6-9 a.m.)
measurements of  ambient nonraethane organic compounds (NMOC) were
collected at numerous cities across the United States.  NMOC levels
were  determined using  cryogenic preconcentration  direct flame-
ionization detection  (PDFID)  as  described  by McElroy et. al.1  A
collocated NOx  instrument was  to have been operated at each NMOC
site.
     participation in this program was voluntary.   Thus, there was
no long term fixed monitoring network for NMOC.  This review also
includes data collected in a similar program which was managed by
Region  III  EPA during the summers  of 1987 and 1988.   The total
number  of sites  included across  the U.S.  were:  21  (1984),  19
(1985), 23 (1986), 35  (1987) and 51  (1988).
     Generally, NMOC sites were located so as to determine "city-
wide"  values.    However,  some sites were located  in industrial
areas,  others  in  rural or suburban locations, while  some were
located  in  small  urban areas  which  have  a large  industrial
corop°nent*   Tne  decree  to  which  each site  reflects  city-wide
conditions  affects   conclusions  regarding  all   the  variables
considered in this paper.

     This paper focuses on three topics:
i\ trends in NMOC, NOx and NMOC/NOx ratios
2) site to site differences in these three parameters and
                               815

-------
3) NMOC, NOx and NMOC/NOx ratios on high and low ozone days.

TRENDS

     The data available for trend analyses are extremely limited.
Much  more than  five years  of data  are necessary  to establish
meaningful trends.   The NMOC program had six  sites with four or
more years of data.  These sites include: Beaumont, Texas; Dallas,
Texas;   Fort  Worth,   Texas;   Houston,  Texas;   Philadelphia,
Pennsylvania and Washington, DC.
     HMQC  Figure 1 displays the median,  10th and 90th perce^tiles
for NMOC for the Dallas site.   The Spearman Rank correlation test
was  performed  for  the  10 and  90th  percentiles and  the median.
While the true significance level would be affected by the lack of
independence  for  these  three  tests,  a  90%  level  was  used  to
classify trends  for the purpose of this paper.   For Dallas, all
three  cases,  10  and 90th  percentiles  and  median,  exhibited  a
downward trend,  it should be noted that the Dallas NMOC site was
moved after the  1985 monitoring period.   While it was only moved
100 yards, this may have some impact  on the conclusions.  The Fort
Worth  site exhibited  a  downward  trend,  but only  in  the 90th
percent!le values.  The Houston site  exhibited  an upward trend for
the 10th percentile values.
     MOx  Figure 2 displays the median, 10th and 90th percentiles
for  NOx for  the  Dallas  site.   Results  of  the  Spearman Rank
correlation test indicate  that the 10th percentiles in Beaumont and
the median values  in Washington, DC exhibited  a downward trend at
the 95 * confidence level.  Median levels in Houston displayed an
upward trend.
     patio  Figure 3 displays the median, 10th and 90th percentiles
for NMOC/NOx ratios for the Dallas site.  Results of the Spearman
Rank correlation test indicate that only the median values for the
Dallas  site  indicate a trend  (downward)  at the  95 % confidence
level.

SITE TO SITE DIFFERENCES

     While the  NMOC sites  were located to  measure neighborhood
scale NMOC values, these  levels may not be  representative of an
entire urban area*  Multiple NMOC sites are recommended for this
reason.  Over the  five  years covered in this analysis twanty-six
pairs of NMOC monitors are available for comparison.
     NMOC  The Mann Whitney U test was performed to determine if
the differences between the median NMOC levels were statistically
significant.  Table I lists the cities, years and sites, the median
NMOC  levels   and  whether   the  differences  in  medians  are
statistically significant  at the 95 % confidence level,  in sixteen
of the twenty-six  cases the medians  are statistically different.
However, in only twelve cases are the comparisons between sites of
similar types (urban vs. urban and suburban vs.  suburban).  Four of
the nine  urban comparisons  are statistically significant.   All
three of  the  computed differences  at  the  suburban sites  are
                               816

-------
statistically significant.
     UQX  The differences  for  thirteen  of  the nineteen NOx cases
available for comparison are statistically  significant.  Only nine
Of  the  comparisons are between sites of  similar type.   For the
eight urban comparisons, five are statistically significant.  The
only suburban comparison is also statistically significant.
     patio   Nineteen  pairs of  sites  with  NMOC/NOx  ratios  are
available for comparison.   In nine of the cases the differences are
statistically significant.  For nine of the cases the comparisons
are  between sites of  similar type.   Four  of  the  nine  urban
comparisons  and the only  suburban comparison  are  statistically
significant.

HIGH VERSUS LOW OZONE DAYS

     The values of most interest are those which occur on days with
high ozone  levels.   Thirty-two sites were selected for analysis.
These consisted of the most recent year  of  data  sampled at each of
•the urban NHOC sites.  Ozone levels were selected by assuming that
the highest  ozone  value measured  at any monitoring site within a
Metropolitan Statistical Area  (MSA) or  Consolidated Metropolitan
Statistical Area (CMSA) was associated with that MSA or  CMSA.  High
ozone days were designated as  all days  with ozone exceedances or
the top ten ozone days if  fewer than ten exceedances were measured
during the NMOC monitoring period.  Some cities had as many as 27
 vceedances  included in  the computations, while others  had no
exceedances.

jjMOC: High versus  Low Ozone Days

     Median  NMOC  values on high and low ozone  days are shown in
•rable II-   Tne  median  NMOC levels on high ozone days were higher
than values  on  low ozone days for  31 of the  32 cases.  The  lone
exception is in Houston, TX.  However, in only 20 of these  cases is
fne difference  statistically significant  at  the  95 % confidence
level.   The Houston case was not  significant.   In two cases the
Difference between NMOC levels on high  and low  ozone days  is  more
than a factor of two (San  Francisco  and Newark).

NOX: High versus Low Ozone Days

     Median  NOx values on high and low ozone  days are shown in
Table II-   Tne median  NOx  levels  on high ozone days  were  higher
than values on low ozone days  for  23 of the 32  cases.  In  only 13
cases, are  the  differences statistically significant  at the  95  %
confidence level.  In five cases  the NOx level  on high ozone  days
la over twice the  level on  low ozone days,  in  San  Francisco, the
iox level on high ozone days is nearly three times the value on low
ozone days.

         Ratio: High versus  Low Ozone Days
                                817

-------
     Median NMOC/NOx ratios on high and low ozone days are shown in
Table II.  The median NMOC/NOx ratios on high ozone days are higher
than values on low ozone days for 23 of the 32 cases.  In only 7 of
these cases are the differences statistically significant at the 95
% confidence  level.  In 7  cases, the median NMOC/NOx ratios on low
ozone  days  were  higher  than values on  the  high  ozone  days.
However,   in  only   one case,  Austin,   TX,   was   the  difference
statistically significant at the 95 % confidence  level.

CONCLUSIONS

     Very  few significant  trends are seen in  the data.  The Dallas
site did show a downward trend for  NMOC.   Considerable variation in
NMOC, NOx  and NMOC/NOx ratios  exists between sites with  a  given
city.  NMOC and NOx levels are typically higher on  high ozone days.
NMOC/NOx ratios are  not significantly  different on high versus low
ozone days for most  cities.

REFERENCES

XF.F.  McElroy,  V.L.  Thompson, D.M.   Holland et  al.,  "Cryogenic
Preconcentration-Direct FID Method for Measurement of Ambient NMOC:
Refinement and Comparison  with GC  Speciation", Jpurpa^l  of  the Air
Pollution  Control Association.  p710-714  (June 1986).


                              TABLE I

                 Comparison of Data Between Sites

Year  City        Sites   WOC i moc 2 Sig  K)x 1  KOx  2 Sag   Ratio 1  Ratio 2  Sig

                                                        7.5    Y
                                                        9.1    Y
                                                       12.4    Y
                                                        9.3    Y
                                                       10.0    I

                                                        7.6
                                                        5.8
                                                        5.7
                                                        9.5
                                                        6.9
                                                        8.3    Y
                                                        6.5    I
                                                        8.7    Y
                                                       16.7    V
                                                        7.9    II
85
86
86
86
86
86
87
87
87
87
87
87
88
88
88
88
88
88
88
88
Philadelphia 1 ( 2
Chicago 1 & 2
Denver 1 & 2
Houston 1(2
Mew York 1(2
Salt Lake City 1 ( 2
Atlanta 1 & 2
Baltimore 1 & 2
Boston 1 & 2
Rev York 1 & 2
Philadelphia 1 ( 2
Salt Lake City 1 ( 2
BaXersf ield 2 4 3
Baltiiore 1(2
Cleveland 1(2
Detroit 1 ( 2
Keipbis 1(2
Miaii 2 ( 3
Xasfaville 1 ( 2
lev York 1 ( 3
0.488
1.308
1.245
1.030
0.480
0.700
0.645
0.445
0.300
0.710
0.545
0.715
0.755
0.580
0.755
0.510
0.928
0.693
0.440
0.663
0.650
0.955
0.820
0.940
0.525
1.140
0.365
0.560
0.474
0.620
0.662
0.835
0.200
0.415
0.640
0.625
0.440
0.122
0.685
0.700
Y
Y
Y
N
1
Y
Y
Y
Y
K
Y
N
Y
Y
I
1
Y
Y
Y
1
0.066
0.160
0.164
0.052
0.046


0.069
0.052
0.051
0.066
0.072
	
.....
0.097
0.117
—..
-_.„_
0.060
0.024
0.075
0.065
0.086
0.071
0.102
0.056

0.049
0.098
0.078
0.064
0.095
	
.....
0.051
0.102
.....
	
0.010
0.041
0.090
N
Y
Y
Y
K
-
Y
Y
Y
N
Y
-
-
Y
N
.
-
Y
Y
N
6.5
7.2
7.4
13.2
11.5


8.5
8.0
5.5
10.1
7.7

....
5.8
6.2
....
	
11.6
12.8
8.6
                                818

-------
      TABLE I  (continued)
Coiparison of Data Between Sites
Year city sites HHOC 1 HHOC 2
88 Philadelphia l s 3 0
88 Phoenix 1 s 2 0
88 sacraiento 1 s 2 0
88 Springfield 1 S 2 0
88 St Petersburg 142 0
88 Taipa i a 2 o

HHOC, »
Hed Hed
HHOC NHOC
Si&QCgai High_Q, Low01
***<»» OH 84 0.925 0.560
Atlanta, GA 87 1.054 0.599
Austin, TX 88 1.085 0.702
n «, » *«vvi/ v» rvtr
Wltliore, HD 88 0.622 0.446
jaton Rouge, LA 87 1.157 0.636
Boston, HA 88 0.602 0.527
fridgeport, CT 86 0.543 0.378
Jcago, IL 88 0.863 0.695
Cincinnati, OB 84 1.105 0.700
Cleveland, OB 88 1.154 0.693
"alias, TX 88 0.600 0.473
fcnver, co 86 1.340 1.214
J«t Worth, TX 87 0.903 0.649
"OUston, TX 86 0.887 0.989
indpls, IH 84 0.920 0.670
[ansas City, MO 85 0.555 0.400
jasnville, TN 88 0.956 0.636
** Haven, CT 86 0.748 0.378
"WarX, HJ 88 0.917 0.436
JJf Y<*k, NY 88 0.961 0.626
^mwftlphici *PA 8S o 656 o 439
Jutland, HE 85 0.'625 0,'440
evidence, RI 88 0.554 0.394
«JUake, OT87 0.960 0.688
^Jiego, CA87 0.492 0.312
rrfran., CA 87 0.611 0.236
Wield, HA 88 0.489 0.425
*• K>Uis, HO 88 0.823 0.530
ViT?f * 86 °-967 °-598
fcS. ;CA87 °'556 O-418
2r>lngton DC 88 0.489 0.383
wrc*ter, HA88 0.604 -0.418
.465 0.510
.190 0.366
.215 0.185
.427 0.410
.383 0.445
.545 0.250

Sig HOx 1 MOx 2 Sig
H 0.071 0
Y — —
Y 	
H 0.076 0
N 0.048 0
Y 0.059 0
TABLE II
Ox and NHOC/HOx Ratios on High
Difference
Significant
Yes
Yes
No
Yes
Yes
No
Yes
Ho
Yes
Yes
Ho
No
Ho
Ho
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
No
No
Yes
Yes
Ho
Yes
Yes
No
Yes
No
Hed Hed
Wlw VftY
HOX flux
HigbO, LfiSLfii
0.068 0.047
0.067 0.073
0.143 0.057
0.075 0.077
0.053 0.045
0.071 0.071
0.054 0.050
0.115 0.118
0.168 0.059
0.161 0.116
0.075 0.053
0.157 0.165
0.071 0.060
0.093 0.105
0.104 0.051
0.062 0.049
0.056 0.039
0.079 0.068
0.127 0.061
0.103 0.076
0.078 0.067
0.050 0.037
0.038 0.037
0.085 0.070
0.073 0.040
0.095 0.033
0.066 0.083
0,081 0.053
0.066 0.047
0.043 0.037
0.040 0.040
0.063 0.067
.059 Y
-«•-- "

.065 N
.030 Y
.033 Y

and Low Ozone
Difference
Significant
Yes
No
Yes
No
No
NO
No
No
Yes
No
Yes
Mo
Yes
No
Yes
No
Yes
No
Yes
Yes
Yes
Ho
No
No
Yes
Yes
Mo
Yes
No
NO
Mo
«_
NO
Ratio 1
6.1

___
6.0
8.5
8.1

Days
Hed
HHOC/HOX
High 0]
12.5
9.7
7.8
7.4
20.3
8.1
8.3
6.8
7.7
9.0
8.2
7.2
10.8
9.7
8.8
9.1
14.5
8.4
7.7
9.0
7.9
11.4
12.8
10.1
6.8
7f
»b
6.4
10.1
14.8
12.9
12.4
1 £
i*0
Ratio 2
7.6

M«
5.4
1 J £
14.6
7j
.4


Hed
NHOC/KOx
LPJLP,
13.0
7.4
12.0
6.4
13.2
6.2
8.3
6.1
9.4
6.0
8.2
7.4
10.2
9.2
12.0
8.1
16.3
6.0
6^
.5
7.8
61
.1
9.4
11.0
9.9
7.4
6Q
. 7
5.9
9.7
12.8
10.3
7.9
6.5

Sig
Y




"


Difference
Significant
No
|t_
NO
Yes
Yes
!/-_
Yes
UAM
Yes
No
No
Ho
Yes
list
10
If _
Ho
No
1I«.
Ho
y_
NO
VA
NO
NO
«•__
Yes
UA
no
VA
HO
Voc
leo
HO
NO
NO
NO
NO
HO
Ho
Ho
No
Yes
Ho

              819

-------
                       OB!las,  Texas Site
     HOC (19H -  1MB)
(10. SO tna 9Otn
           FIGURE 2

      N> (1964 - 19883
CIO, 50 mra BOth Prccm.il*>)
                                       I"
             1996
       -i	(      I	r—
1W4    19 B5   1996    1987   1988
                                  i«ta
                                   820

-------
  Comparing Nonmethane Organic Compound, NO,, and Daily Maximum Ozone
                        Concentrations by Site and by Year

                                 Robert A. McAllister
                                   Phyllis L. O'Hara
                                   John E.  Robbins
                                  Radian Corporation
                                   P. O. Box 13000
                      Research Triangle Park, North Carolina  27709
                                        and
                                     T. W.  Sager
                            The University of Texas at Austin
                     Center for Statistical Sciences, MSIS-CBA 5,202
                               Austin, Texas 78712-1175


      Summer  nonmethane  organic compound (NMOC),  NCv and  daily maximum  ozone'
       Z) concentration distributions were compared between Beaumont, TX and Houston, TX.
        data for the Beaumont site (BMTX) extended from 1984 through 1991, while the Houston
s«e (HlTX) data ranged from 1985 through 1989.  NMOC and NOX concentrations were whole
ambient air integrated from 6:00 a.m. to 9:00 a.m., while MAXOZ concentrations were the daily
      \im of hourly ozone concentrations.
      For the BMTX site 1985 and  1990 NMOC concentrations were  higher than in adjacent
      MAXOZ for those years was lower than adjacent years.  NMOC concentrations at H1TX
                lower than in adjacent years.  BMTX NMOC concentrations were higher than
      in 1985, but lower in all other years. On a global basis BMTX experienced a significant
l
                                      .
lncrease in NMOC from 1985 to 1990, and in NO, from 1985 to 1990.
j_    The main thrust of this paper is to determine significant changes in NMOC, NOj, and
T^OZ monitoring data at given locations from year to yean The paper also compares NMOC
J?Mnrtrations between Beaumont and Houston, TX, for 1985, 1986, 1987, 1988, 1989, and  1991.
a.in I   ^"f^ntotions, measured as integrated concentrations sampled between 6:00 a.m. and 9:00
a, ' local civil time, Monday through Friday, have been monitored from June through September
n*evcral urban locations since  1984.  The ozone concentration of most interest  is the  daily
/J^mum of the hourly ozone concentrations (MAXOZ), expressed as parts per million by volume
to onn ' NO" concentrations used in this study are three-hour integrated averages from 6:00 aon.
non   a'm' reP°rted m PProv units. Comparisons between sites or between years were made using
  nparametric statistics.  In each  comparison two frequency distributions are to be compared to
fro  mine whether it is possible to discern a difference in mean {or median) concentration level,
thp  year to *ear or site to site ^th a high probability (> 95 confidence) of properly  interpreting
 « results. The method chosen for the comparisons used in this study was to compare years in
for tKUS'nfi the nonparametric Wilcoxon two-sample test.  The Wilcoxon test ranks all of the data
   "ie  two years of the comparison to derive the statistics used to make judgements about tne
                                        821

-------
equality between the two distributions. The Wilcoxon test has the advantage of not requiring any
assumptions about the form of the distribution of the data  used.  Other tests used for similar
comparisons, e.g., t-tests, require that the data are normally (or lognormally) distributed. Sager,
et. al.,1 have shown that statistical assumptions matter in data  analysis and the nonnormality of air
monitoring concentration data is well known.
       Monitoring sites at Beaumont, Texas (AIRS Site 48-245-0009) and Houston, Texas (AIRS
Site 48-201-1034) were chosen to compare NMOC, NOX, and MAXOZ concentrations. NMOC
concentration data were available for the summer months from 1984 through 1991 for Beaumont
and from 1985 through 1991 (with the exception of 1990) at Houston. The two sites are near the
Gulf of Mexico coast and about 90 miles apart, thus would enjoy similar meteorological conditions.
Each site is located  within about 100 yards of traffic arteries,  and within 25 miles of a number of
major petrochemical faculties. Comparisons were made between the Beaumont and Houston sites
for the years that both sites had  NMOC monitoring data. In addition,  paired year-to-year
comparisons were made for the Beaumont site for the years between 1984 and 1991, and for the
Houston site  for 1985 through 1991.

RESULTS
      The technique used to compare the pairs of sites or pairs of years to determine significant
concentration increases  (or decreases) from year to year or site to site for NMOC, NO,,, and
MAXOZ will be discussed  briefly.  We adopt a common significance level of 0.05 for judging
whether a pair represents a true difference.  That is, if the test reports a P value  <0.05 then we
declare the difference to be inconsistent with the null hypothesis that the mean ranks are truly
equal. Adopting this procedure guarantees that if the null hypothesis for a given pair is really true,
then the chance of erroneously rejecting it will be less than 0.05.  However, it should be noted that
testing pairs of distributions does not control the experimentwise error rate. To test whether the
NMOC concentrations were normally, or lognormally distributed, NMOC concentrations and their
logarithms for 1986 and 1990 were tested for normality using the Shapiro-Wilk Statistic2. The test
showed that the data were neither normally nor lognormally distributed. The test also showed that
the data were more  nearly lognormal than normal.
      All NMOC concentration data from 1984 through 1991 were ranked and then the ranked
means for each year were calculated.  The sorted and ranked  data set was then used to transpose
the ranked mean into the ppmC equivalent of the ranked mean used in the tables. Figures 1 and
2 display  the ranked  sampling distributions for NMOC, NOX, and MAXOZ in boxplot format. The
ordinates in the figures are  dimensionless  and are numerically in the rank transformation of the
concentration data.   Tables 1 and 2 show results of the year-to-year paired  comparisons for
Beaumont and Houston. The tables give the yearly mean concentrations in the measured units,
ppmC for NMOC, ppmv for NO,, and ppmv for MAXOZ.  In addition, the tables give the ppmC
equivalents to the rank means. Significant differences between years were taken at the 0.05 level
of significance. For the BMTX site 1985 and 1990 were noticeably different years than the adjacent
years for NMOC, NO,,  and MAXOZ.  For Houston, 1989  had  a significantly lower MAXOZ
concentration than the remaining years.  No significant trends were noticeable among the NO,
measurements in Houston in  the paired comparisons  shown. The NMOC concentrations were
significantly higher  in 1986 at the  H1TX site, and lower in 1989 than in the adjacent years
measured.
                                          822

-------
       Table 3 presents the paired annual comparisons between the BMTX and the H1TX sites
for  the  years 1985, 1986, 1987,  1988, 1989,  and 1991.  The  data show that the NMOC
concentrations were higher in BMTX  than H1TX in 1985.  For 1986, 1987, 1988,  and 1991,
however, NMOC values were significantly higher at the H1TX site.  Only in 1989 were the NMOC
concentrations at BMTX and H1TX sites indistinguishable.  NOX  concentrations at H1TX were
significantly higher than at BMTX for every year compared, except for 1985 in which the NO,
concentrations were indistinguishable.  Only in 1985 was the MAXOZ concentration in H1TX
higher than in BMTX. For  all other years the MAXOZ concentrations were indistinguishable
Between the two sites.
       Comparing year-to-year pollutant levels  is  important for understanding short-run effects.
However, there  is also a need to understand whether year-to-year and site-to-site differences
discovered be these methods remain significant in the context of  the several years' run of data
taken as a whole.  Because the comparisons using pairs performed above were done separately,
there is the possibility that some differences were declared significant because a large number of
tests were made.  That is, the experimentwise error rate was not controlled, although each
'ndividual  test was controlled at the  0.05 level.  A global analysis will  permit control  of
 xperimentwise error rate, so that we can say confidently that all differences simultaneously are
 •onificant at the 0.05 level. Additionally, a global analysis will enable us to judge whether there
? an overall trend. We performed one-factor ANOVAs on ranks with YEAR and SITE as factors.
With one factor, ANOVA on ranks is equivalent to the well-known Kruskal-Wallis test. We also
 erformed two-factor ANOVAs on ranks with YEAR and SITE as the factors and included their
Alterations as an effect. Tukey's "honestly significant difference (HSD)" procedure3 was used for
 he comparisons using pairs.  Tukey's HSD test controls the experimentwise Type I error rate at
0 05- T*16 data for this analysis was u'mited to 1984-1990 for Beaumont and 1985 to 1990 for
Houston.

CONCLUSIONS
       Summary conclusions follow:  Significant year-to-year differences were found for Beaumont
for 1984-1985 (NMOC), 1985-1986 (NMOC, NO* MAXOZ), 1988-1989 (NO^ MAXOZ), and 1989-
1990 (NMOC, NOX). For Houston, the significant year-to-year differences were 1988-1989 (NMOC,
vlAXOZ), and 1989-1990 (MAXOZ). Beaumont and Houston were significantly different in terms
of NO, and MAXOZ, but not in terms of NMOC.  From 1984 to 1990, Beaumont experienced a
significant increase is NMOC and in NO, from 1985 to 1990. Corresponding Houston differences
from the beginning of the data period to the end were not significant.


REFERENCES
i      Sager, T. W., A. D. Vaquiax, and M. W. Hemphill, J. Air Waste Manage. Assoc. 40:199-202
       (1990).
,.     ffAS* Procedures Guide. Release 6.03 Editi^, Test of Normality, SAS Institute, Inc., Cary,
       NC
-     5AS»/STATQ Users Guide. Release fi.M  Edition  Comparison of Means, The GLM
       procedure, SAS Institute Inc., Gary, NC
                                          823

-------
                  TABLE L.  faired Annual Comparisons -- Beaumont. Texas. 1984 through  1991




Tear
1984
1985
1986
1987
1988
1989
1990
1991



Mean
pp«C
0.888
1.755
0.810
0.686
0.720
0.821
1.723
0.658
HHOC
ppmC
EquiT.
than
Rank
0.713
1.460
0.672
0.566
0.608
0.678
1.392
0.613
Paired
Annual
Bank
Comparf cone


+
.
.
0
+
+
'



Mean
ppmr
0.0204
0.0262
0.0220
0.0260
0.0205
0.0124
0.0195
0.021«
HO.
ppmV
BqnlT.
Mean
Rank
0.0191
0.0248
0.0187
0.0169
0.0187
0.0127
0.0185
0.0198*

Paired
Annual
Rank
Comparisons

+
-
0
0
.
•»•
0
MAXOZ


Mean
ppmv
0.0583
0.0382
0.0597
0.0554
0.0579
0.0462
0.0406
0.0653*
ppmv
Equlv.
Mean
Rank
0.0543
0.0369
0.0578
0.0535
0.0544
0.0499
0.0416
0.0585"
Paired
Annual
Rank
Comparisons

m
+
0
0
0

+
                   TABLE 2.  Paired Annual Comparison* -- Houston,  Texas,  198S  through 1991




Tear
1984
1985
1986
1987
1988
1989
1990
1991



Mean
ppmC

0.916
1.120
0.967
1.066
0.790
--
0.973
HHOC
ppmC
Equlv.
Mean
lank

0.818
0.968
0.866
0.944
0.732
..
0.888
Paired
Annual
Rank
Comparisons


+
.
0
-

+
HO.


Mean
ppenr

0.0545
0.0573
0.0608
0.0641
0.0593
0.0600
0.0554*
ppanr
EquiT.
Mean
Rank

0.0515
0.0527
0.054)
0.0590
0.0536
O.OS46
0.0508*
Paired
Annual
Rank
Comparisons


0
0
0
0
0
0
HAZOZ


Mean
ppsrr

0.0732
0.0634
0.0600
0.0641
0.0503
0.0671
0.0714*
pp*v
Eqnlv.
Keen
Rank

0.0643
0.0481
0.0533
0.0584
0.0465
0.608
0.0634*
Paired
Annual
Rank
Comparisons


.
0
0
0
+
+
*June 1991 data only.

+     The concentration for this year is significantly higher than the concentration for the year
      Immediately above this row.

0     There la no significant concentration difference between this year and the year Immediately above this
      row.
      The concentration for this year  la significantly lower than the concentration for the year Imatediately
      •bom chia row.

-------
           3.  fmirtd Annual  Co*p*ritoni  0aew*«a  the ScauBont,  TX Sice and tb« Houston,  IX Slt«
/
fleic
I SIMS
1 Compared
|l2S5
1 BeatiBonc. TX1
Houston. TX
19lj{
Beatwmt. TX
Nous con, TX
1987
BeauBont, TX
Houston, TX
1988
Beaumont, TX
Houston, TX
1989
Beau»ont, TX
Houston. TX
122ft
BeauBont, TX
Houston, TX
1991
BeauBont. TX
Houston, TX
NMOC
HMH
ppBC
1.755
0.916
0.779
1.136
0.686
0.967
0.720
1.066
0.821
0.782
--
0.658
0.973
Mtelisn
DfwC
1.629
0.742
0.639
1.0S2
0.466
o.en
0,556
0.951
0.648
0.622
--
0.602
0.960
pp*c
EqnlT.
Mean Ksnk
1.460
0.818
0.672
0.968
0.566
0.866
0.608
0.944
0.678
0.732
--
0.613
0.886
ppmr Equivalent CO
Ketn lank
*>.
ppmr
0.0248
0.0515
0.0187
0.0527
0.0169
0.0543
0.0187
O.OS90
0.0127
0.0536
0.0185
0.0546
0.0198
0.0508
HAXOZ
PPW
0.0369
0.0643
0.0578
0.0481
0.0535
0.0533
0.0544
0.0584
0.0499
0.0465
0.0416
0.0608
0.0585
0.0634
Paired Annual Kank Comparisons
NMOC
ppftC

+
•V
+
0

•«•
HO,
PP-JT
0
+
+
+
+
+
+
KAXOZ
pp«v
+
0
0
t
0
+
+
The concentration Cor this site  Is significantly higher than the  concentration for the  site
            above this row.
tfaer* is no significant concentration difference between this site  and the  site  iMedlttely above this
ton.
The concentration for this  site  Is significantly lower than the concentration for the  site
above this row.

-------
        • *
        -
        n -
         0 -
                                  1M1




1
T

T
E

I




*

r


<
l


•
r
i

*
T



•

r
r*
]L
j



i
~




• T
             N04  t*M  tMt tWT 1M* MM 1MO
      c:   n    ,nn

i
*
I
(
tl
1
T
T

I
•?•
I

1
•

1
T

1
«•
T
*
Hguml. Swiping dartbudom far rantodmonlorino date from Beaumont. TX;
                Ata8to48-24SOOOe.
Ftaum2.
nyui
aa -
400 -
IK -
MO -
1

1
*
T

m

M .
m -
I":
S--
too -
M ~
M -
0 -
I




-i

1
IM
SM -
r ~
!"• "
SIM -
IW -
n -
M -
a -





±
T


1
-*-
T
J
—i

i i
u

+
T

1
T
I 1 1
• IN* 1M7 MM INO tMO IMI
v*«
[

L






+





i
t

L.



h


K—
^J
1
+

T
1


-»-

T
"MII
| 1 III
1 WH IM7 IM IfOO IMO IMI
Uv '

^


]




i
»







*

fTl
1




— g—L.
,



^

T
1


<*•
y


MM tM MM^MH IM* IMO IMI
e«»jbw, HMHh.Mno.inr mnteri monfenflna data Iron
                AIRS «*• 48401-1(04.

-------
Performance of the Annular Denuder System in an Outdoor Ambient Air Pollution Study

Steven C Mauch
Roy F. Weston, Inc.
Weston Way, Building 5-1
West Chester, PA  19380

ABSTRACT

The annular denuder sampling system (ADS) was used in an outdoor ambient air characterization study
^ *•« summer of 1991. The target analytes of the study included ammonia, trace metals (Ba, Ca, Na,
M8> K) and various anions (Cl, NO,, NO3, CIO, C1O2, SO3, SO4). During the latter portion of the study,
we samplers were run continuously (except for train changeouts every 48 hours) for two months.  The
ADS trains used consisted of a cyclone, two NajCO3-coated denuders. a citric acid-coated denuder, and
a s"igle Teflon filter. The second NapDj denuder was included to test for possible breakthrough and
t° assess the collection efficiency of a single-tube train.  The precision of collocated duplicate samples
c°llected  as part of the quality assurance plan are summarized.  For the dual-NajCO, denuder trains, a
summary of the collection efficiency of the denuder tube based on the field data is presented.

PRODUCTION

A* outdoor ambient air study was conducted  during the summer of 1991, focusing on inorganic ak
c°Maminants. Because both aerosols and gases were of  interest, the annular denuder sampling system
w*s selected fM use in the study. The annular demider system was selected because of its unique ability
to effectively collect both aerosols and gases simultaneously, and providing sensitive detection limits.
"* alternative of filter/impinger trains typically used for source and industrial hygiene sampling were
<**sidercd.  The filter/impingei trains were judged inadequate because of their greater detection limits,
*"  operational considerations (It, pump flow faults and refreshing impinger ice baths).

*° ^s study, the precision and efficiency of the ADS were of particular interest, since the sampling
Astern had  never ^^ bccn used by WESTON.  Because  one goal of the study was to identify
P^ble increases in pollutant levels downwind of a chemical manufacturing facility, the ability of the
     to prcciselv J^ anihtent concentrationS was important During the cononuovis-coveTage
       g  portion of the study, saturation of the denuder tubes and subsequent breakduough were  of
       -  * was also desired to assess the gas collection efficiency of the denuder tubes  This paper
       a brief summary of the precision and collection  efficiency data obtauied during the study.

     ANNULAR DENUDER SYSTEM

    jnnolar  denuder system (ADS) is the basis of EPA Method DM  (EPA, 1989) for  indoor air
     »*  However, the ADS is also useful for ambient air sampling applications.  The basic ADS
    guration is shown in Figure 1 (adapted from IP-9>, The air sample (collected at a constant 10 LPM
    ««e> enters through the cyclone, which collects aerosols greater than 2.5 urn in diameter by inerdal
          ^ ^ *en passes through the denuder tubes,  which remove reactive gases by diffusion onto
         reactive coatings (i.e., NatcO, for acid gases, or citric acid for basic gases). Flow witmn fte
         *S is lammar/allow/ng Oie fine particles not removed by the cyclone to pass feough £e
       010* ^8 Collected.  T£C remaining fine particles are collected on the Teflon fiher on Ae
       Cnd of *e system.  For this study, the ADS trains consisted of a cyclone, two Na1COJ-coated
       s,  a citric  acid-coated denuder, and a single Teflon filter in the filter pack.
                                            827

-------
 ANALYTICAL METHOD

 The  gases,  extracted  using  deionized  water  from the  denuder tubes, were  analyzed by ion
 chromatography. The aerosols collected in the cyclone were extracted using deionized water, and the
 Teflon filter was extracted using ethanol. The two aerosol extracts were combined, and the total extract
 was split for two analyses. Part of the extract was analyzed by flame absorption spectroscopy for the
 trace metals, and the anions were determined by ion chromatography. Analytical detection limits for the
 aerosol extract obtained using these methods ranged from 0.007 ug/ms for barium to 2.1 ug/m3 for
 potassium.  Analytical detection limits achieved for gaseous ions ranged from 0.03 ug/m3
 for chloride and sulfate to 0.1 pg/m3 for nitrite.

 GENERAL OPERATION

 The ADS systems operated without major problems or malfunctions throughout the entire study. The
 pressure-differential flow controllers maintained  close to the desired 10 LPM flow rate consistently, as
 verified by flow meters connected to the system exhausts during the second phase of the study.  Each
 of the three samplers used in the study was in operation roughly 47 hours of every 48 hour period for
 two months, for a total of over 4,000 pump-hours of operation with no mechanical problems.

 The only difficulty encountered with the units was  occasional condensation of water inside the pump
 unit, ahead of the flow controller. The internal water trap would sometimes fill during the night, and on
 rare occasions water would be found in the rotameter just ahead of the exhaust from the system. Regular
 emptying of the trap in the morning or during a nighttime  check of the system mitigated this occasional
 problem.

 METHOD PRECISION

 During the latter phase of the study, a total of 12 48-hour collocated duplicate samples were collected.
 The two samplers were located on the same sampling platform, eight feet apart  Both samplers were
 run at the same flow rate (10 LPM) over the same period.  The precision results by analyte, determined
 as the difference between each pair of collocated samples, are summarized in Table I. The precisions
 were quite good, ranging from 0.1  to 0.9 pg/m3 for aerosols and 0.2 to 2.7 ug/m3 for gases. Sulfur-
 bearing ions from the denuder tubes had the greatest differences and standard deviations of differences.
 Sulfate and sulfite (gas-borne) tended to be detected together in many samples, and at greatly variying
 levels. This variability may be responsible for the higher values.

 COLLECTION EFFICD2NCY

Also during the second phase of the study, two NajCOj denuder tubes were used in series  to determine
whether breakthrough of contaminants was occurring.  A total of 34 of these dual-tube samples  were
collected.  Small amounts of several analytes were detected on the second tube, generally in proportion
to the amount collected on the first tube.  This indicates  that no  breakthrough (saturation) of the first
tube was occurring,  but instead  that the first tube was not quite  100%  effective  at capturing the
pollutants.  The greatest amount of analyte collected on the leading denuder tube was around 1,000 pg
for sulfate.  This result indicates that the  tubes have a large collection capacity before becoming
saturated.

The amount of material collected on the second tube, divided by  the total amount of material collectd
on both tubes was used as an effective indication of the collection effieciency of a single tube. Table
                                            828

-------
jj presents a summary of the efficiency of the first denuder tube by analyte for the four most frequently
detected analytes.  The mean values range from 82.9% to 98.9%, with standard deviations from 1.0 to
9 g. These values indicate that the denuder's efficiency does not typically vary by more than about 10%,
     that a single tube is generally 90% or more effecient in collecting the target gases.
SUMMARY

The ADS was evaluated during a field  air quality study during the summer of 1991.  The system
performed with minimal operational problems, and proved very reliable during over 4,000 pump-hours
 f operation.  Sampling precision for aerosol analytes ranged in  absolute value from 0.1 to 0.9 ug/m3
for 48-hour samples, while gaseous analytes had precisions ranging from 0.2 to 2.7 fig/m3. The efficiency
 f a single denuder tube, estimated by ratioing results from two tubes in series, ranged from 83% to
09%.  These results are from a field study, rather than a controlled laboratory experiment.  However,
 .   e results indicate that the ADS is a reliable and precise measurement system  for aerosols and
particles in ambient air.

REFERENCES

ITS EPA,  1989.  Compendium Chapter IP-9.  Determination  of Reactive  Acidic  and  Basic Gases anc
    ini1"*" M After in Indoor Air. Atmospheric Research and Exposure  Assessment  Laboratory, U.S.
              Protection Agency, Research Triangle park, North Carolina, 27711.
                                            829

-------
                                             TEMf. CONT.
                                             AIR OUTLET
12V[
                                              DENUDER H
                                              CITRIC AC ID
                                              COATING
                                                              HOUR
                                                              METER
                                              DENUDER 12
                                                 C03 COATIN
    TEMT. COMT FAH   CYCLONE
                                                            VACUUM aAUfle
Figure 1.  Typical annular denuder sampling system with pump and sampling case.

-------
Table I.  ADS precision summary for frequently detected analytes.

AEROSOLS
Chloride
Nitrate
Sulfate
GASES
Chloride
Nitrite
Nitrate
Sulfite
Sulfate
Mean Precision
ug/m3
0.85
0.06
-0.37

-0.28
0.33
-0.21
-2.7
-2.5
Standard Deviation
ug/m3
3.9
1.9
0.80

0.71
1.4
0.66
7.5
7.8
Table II. Efficiency of Na2CO3 denuder tube for frequently detected analytes.

GASES
Chloride
Nitrite
Nitrate
Sulfate
Mean Efficiency
%
95.9
90.8
82.9
98.9
Standard Deviation
%
8.8
8.1
9.6
1.0
                                       831

-------
 THE KODAK PARK AMBIENT AIR MONITORING NETWORK:
              RESULTS AFTER 2 YEARS OF OPERATION
                                  Donna M. Hendricks
                                 Eastman Kodak Company
                                  Rochester, New York

                                    Suresh Santanam
                                   Galson Corporation
                                  E. Syracuse, New York

                         Raymond G. Merrill & Michael A. Zapkin
                                   Radian Corporation
                                  Rochester, New York


ABSTRACT
      An ambient air monitoring network began operation at the Kodak Park industrial complex in
1990. The network was designed to track air quality improvements resulting from a dichloromethane
(DCM) emission reduction program.  The program calls for a 70% reduction in DCM air emissions
from Kodak Park between 1988 and 1995, with accompanying reductions in emissions of other volatile
materials.
      The network design strategy was summarized in an earlier publication (1).  Seven monitoring
sites around Kodak Park are included  in the program.  Integrated samples (24-hr) are collected every
sixth day, coinciding with the National Air Monitoring Station / State & Local Air Monitoring Station
(NAMS/SLAMS) schedule. Target analytes include dichloromethane and nine other volatile organics.
A gas chromatographic multiple-detector (GC/MD) system is used to achieve low detection levels.  Data
are reported to the New York State Department of Environmental Conservation (NYSDEC) and the
local public each quarter; results are summarized annually.
      This paper presents results obtained after  2  years of operation.   Sampling  and  analytical
completeness results and data quality  measures are compared to goals established at the start of the
program; factors affecting completeness and data quality are discussed. Ambient DCM concentrations
monitored over the course of the program are presented along with a discussion of statistical methods
used to detect trends in air quality.  Monitored  concentrations are compared to dispersion model
estimates.  The  objectives  established  at the outset of the program are being met  or exceeded at this
time.
                                         832

-------
jNTRODUCTION
       Eastman Kodak Company (Kodak) has been operating an ambient air monitoring network at its
   dak  Park plant  site since February,  1990.   The  network was designed to track air  quality
•   orovements resulting from air emission reductions made at the plant over a time period of several
'   rs  The approach taken to design the network was summarized in an  earlier publication (1). The
   roose of this paper is to share results and experience gained from 2 years of operating the network.

Description of Kodak Park
       Kodak Park is located in Rochester, New York.  It covers an area of over 7 square miles and
   oloys over 20,000 people. The plant is often described as a "city within a city'. It houses a wide range
 f buildings and utilities to support manufacturing operations, including power plants, waste treatment
°  terns  a fire department, medical facilities, a railroad, and a bus line. The major manufacturing and
S^ duction areas consist of both continuous and batch operations which produce nearly 1000  types of
?1°  250 kinds of photographic paper, and more than 900 chemical formulations. Many of the chemical
f  rmulations are used in the processing of photographic film and paper.  Organic chemicals are also
   duced and supplied to research institutions, laboratories, and industry.
^r°    Kodak Park is a mixture of new and old; ground was broken on the facility in 1890 and new
     (ruction continues today. Recently, plans were made to expand film base manufacturing capacity.
C°n   formal agreement between Kodak and the  New York State Department of Environmental
     ervation  (NYSDEC),  the expansion  proceeded and was accompanied by a program to reduce
C>°hloromethane  emissions  to  the  air  from  Kodak  Park  by 70%  between 1988 and 1995.
   • hlorornethane is one of the primary solvents used in making film base. Reductions in emissions of
  tier volatile materials are planned as well. The ambient air monitoring network described here was
    ened to track improvements in local air quality resulting from the air emission reductions.

Monitoring Program Goals
       Several qualitative and quantitative goals were  established during the design of the network.
     sures of these goals are reviewed at least annually to gauge the success of the monitoring program.
2rh  first g°al 's to Provide measurements of annual average concentration of the target compounds at
   h monitoring site with enough precision to allow meaningful year-to-year comparisons; detection of
eaj.,/-tions in ambient concentration of 16-24% annually with 95% confidence is desired. Second, the
         sampling and analytical completeness is 90% or better.  Third,  individual analytes are to be
       _J with an overall precision,  as determined by field sample duplicate and replicate analyses,
     „. 50% CV near the method detection limit of each analyte. Fourth, measurements of each analyte
    to' be provided with an analytical accuracy, as determined by analyses of internal and third-party
    dards, of +/- 50%. Finally, a less quantitative, yet key measure of the program's success is public
S^A  efiulatory agency acceptance of the monitoring results.

   ,,*»VIEW OF MONITORING METHODS
O*
c  moling and Analytical Methods
        The network consists of 7  sampling locations around the perimeter of Kodak Park (1).  The
    tions were chosen carefully, using dispersion model estimates, so that dichloromethane levels would
l°c*  tectable both before and after  emission reductions were made.  Air samples (24-hr composites) are
be <*e ^ in 6_ijter SUMMA™ canisters every 6th day, coinciding  with the NAMS/SLAMS schedule.
                                              833

-------
Samples are analyzed for  10 target compounds:   dichloromethane, 1,2-dichloropropane, methanol,
toluene, acetone, isopropanol, ethanol, n-heptane, n-hexanc, and cyclohexanc.  The analysis method is
TO-14 (2).  All compounds are measured at the part-per-billion (ppb) level or less.  Two additional
compounds are tracked annually by dispersion modeling only: 2-methoxyethanol and propylene oxide.

Meteorological Data CoUection
       A  150-ft meteorological tower is sited approximately in  the center of the sampling network.
Meteorological data,   including   wind speed,  wind  direction,  temperature, barometric  pressure,
precipitation, solar radiation, and stability class are collected continuously.

Dispersion Modeling Techniques
       Kodak maintains an emission inventory database of over 1200 air emission point sources as well
as non-point sources.   Using information  from the database, estimates of annual  average ambient air
concentration of compounds of interest are computed through a system based on the Industrial Source
Complex  Short Term  (ISCST) and CAVITY models (3). The CAVITY model  supplements ISCST
estimations at locations very near emission sources.  The estimation techniques are consistent  with
guidance issued by the U.S. Environmental Protection Agency (4).
RESULTS

Sampling & Analytical Completeness
       Sampling and analytical completeness of this program exceeded 95%, significantly better than
the established goal of 90%.  The major factor affecting sampling completeness was a power outage
resulting from a local  ice-storm.  Analytical completeness on selected compounds was affected by
contamination during laboratory pressure-check procedures,  which were immediately modified upon
discovery to minimize loss of data. The high level of overall completeness is attributed to laboratory
standard operating procedures developed in conjunction with system and performance audits, and
prioritizing of site operational issues to prevent sample loss.

Data Quality Measures
       Data quality objectives and observations are summarized in Table 1.  The observed level of data
quality met all established objectives. In addition, there was no evidence of sample contamination from
transportation and handling in trip blanks.  Monthly laboratory calibration curves have met acceptance
criteria throughout the program.  Daily system blank and calibration check samples demonstrated the
performance of the analytical system.  Quarterly performance audit sample results consistently met the
accuracy objectives for all of the target analytes.  Annual sampler recertification  and quarterly
preventative maintenance procedures ensured the acceptable performance of the samplers. Blank check
results on all sample canisters have met acceptance criteria prior to shipment to the field. Calculations
of precision on a quarterly  and annual basis exceeded acceptance criteria.  An analysis of variance
(ANOVA) of the 1991 precision data indicates that the measurement error due to sampling and analysis
was less than 2% of the observed day-to-day variability.  Carefully designed and installed sampling
equipment and constant attention  to maintenance of laboratory equipment is key to attaining the high
data quality level.
                                            834

-------
                                Table 1: DCM Data Quality Measures
	 YEAR



1990
1991 	
PRECISION
GOAL

(% CV)
<50%
<50%
OBSERVED
PRECISION

(% CV)
42%
3%
ACCURACY
GOAL

(% Recovery)
50-150%
50-150%
OBSERVED
ACCURACY

(% Recovery)
81-125%
60-96%
#OF
AUDIT
SAMPLES

5
6
Ambient Concentrations
        The end-product of 2 years of operation is a high-quality dataset which represents a baseline
  friod (1990) and the first comparison year (1991).  Annual average concentrations for both years and
P   jng annual averages for 1991 have been calculated for each analyte at each site. The running
r°ual average is calculated on a quarterly basis and represents an arithmetic mean  of data from the
311     quarter and the previous three quarters.  In addition, quarterly and annual medians, maximums,
        maximums and percentages of detection are calculated and reported. In all calculations, a value
       of the method detection limit is used for results reported as "Not Detected".
        The  data  have  shown  a strong relationship  between  wind  direction  and concentration,
   rticulariy for DCM, which is the major analyte in the program.  Using daily average wind direction
P I     ftom the meteorological  system, this relationship can be presented in the form  of an "ambient
va  ce sector plot".  An example plot for 1991 DCM results at the Merrill Street Site is presented in
^tfure 1.  Th's P^ot sh°ws tnat tne highest observed concentrations are associated with wind directions
^l   sen 160 and 240 degrees (south-southwest).  This is the general direction in which the major DCM
**    es in Kodak Park are located.  An examination of the hourly meteorological data showed that
        DCM concentrations were generally  associated with the higher number of hours wind was
        d tQ be m tm-s  Sect0r.  The other sites also showed  an association between specific  wind
    ctional sectors corresponding to influences of Kodak Park sources and observed concentration.
        A  statistical evaluation  of  the  data  has been performed to determine if  there  have  been
  •  ificant changes in the concentration of DCM at each site in 1991, relative to the baseline year.  In
S1^   to select  an evaluation method, a distribution analysis was performed  on each site-compound
  K  et for each year using the Shapiro-Wilk test. The distribution analyses indicated that the ambient
  •monitoring  data are neither normally nor log-normally distributed; thus,  traditional methods of
ajr maring means (e.g. Student t-test) were not appropriate. Instead, the means of these data sets were
00         usin  the Wilcoxon rank sum test.  This is a non-parametric test which uses the rank of each
         using the Wilcoxon rank sum test. This is a non-parametric test which uses the rank of each
°^surement for comparison calculations.
*6*8         ilcoxon test  was performed to
            Wilcoxon test  was performed  to  determine if the mean concentrations in 1991  were
    'ficantly different from the mean concentrations during the baseline period.  For cases where the
    '      test indicated a significant change using a 2-tailed analysis at the 95% confidence level, the
          of the change (increase or decrease) was determined by comparing the means of the ranks,
          al average values for the two years and the results of the Wilcoxon analysis for DCM at the
        tes js presented in Table 2. DCM concentrations were numerically lower in 1991 (vs. 1990) at 6
 ev?1 7 monitoring sites. The difference was statistically significant at 3 of the sites.
                                              835

-------
                      FIGURE 1: AMBIENT SOURCE SECTOR PLOT
                          SCAl*
                     (pu-U p«r billion)
                        100
                          0
                        Direction
                        North
                          0

                          t
                         1BO
                                  crv
                            Table!: Monitoring Results for DCM
SITE

Irondequoit
Hanford Landing
Merrill Street
School 41
Rand Street
Koda-Vista
Ridgewav
1990 ANNUAL AVG
CONCENTRATION
(ppbv)

8.3
25
20
7.2
24
18
1.2
1991 ANNUAL AVG
CONCENTRATION
(ppbv)

4.3
20
21
3.5
7.8
17
0.23
WILCOXON
RANK SUM TEST
RESULT

No Significant Change
No Significant Change
No Significant Change
Decrease
Decrease
No Significant Change
Decrease
Ambient Air Concentrations vs. Dispersion Model Estimates
      Industrial  Source Complex  (ISC)  dispersion  model  estimates  of  ambient  levels  of
dichloromethane were calculated for each of the  sampling sites based on emissions information
representative of the 1990 calendar year.  Results were compared to monitoring data as presented in
Figures 2 and 3.  The estimated dichloromethane concentrations were within a factor of 3 or less of the
monitored concentrations at all sites.  This level of model accuracy is consistent with other published
studies of Gaussian dispersion models (5).   These results are of particular interest when the complexity
and distribution of the sources  at Kodak Park are considered  Model performance will be tracked
annually to identify potential improvements.
                                           836

-------
                                         Figure 2:
                ANNUAL AVERAGE DICHLOROMETHANE LEVELS
                                                                • ESTIMATED

                                                                D MEASURED
                                       SITE
CONCLUSIONS
      The Kodak Park Ambient Air Monitoring Program provides high quality data which is useful for
  ' quality evaluation, trend tracking, and dispersion model validation.  All data quality  objectives
established at the outset of the program have been exceeded.  Ambient concentrations were observed to
 e very dependent on wind direction and ambient source sector plots proved useful in demonstrating
 hls relationship.  The monitored DCM levels were within a factor of 3 of levels estimated by dispersion
 ^deling.  This level of agreement  is consistent with other published studies of Gaussian dispersion
'•nodels.  Non-parametric statistical tools were used to compare mean concentrations between 1990 and
   1  because the data were neither normally nor log-normally distributed.  Relative to 1990, annual
^erage DCM concentrations were lower in 1991  at 3 of the 7 monitoring sites at the 95% confidence
level.
      (1) B.M. Wirsig, R.G. Merrill,  and S. Santanam, "Development of a State-of-the-Art Ambient
      Air Monitoring Network for the Kodak Park Industrial Complex"  in Proceedings of the  1991
               AnnV?l Mating, 91-80.9, Air & Waste Management Association, Pittsburgh, 1991.
      (2)   W.T. Winberry, Jr.,  N.T.  Murphy  and  R.M. Riggin, Compendium of Methods for the
      Determination  of Toxic  Organic Compounds  in  Ambient Air.  EPA-600-4-84-041,  U.S.
      Environmental Protection Agency, Research Triangle Park, 1988.

      (3)  D.M. Muschett and L.  Davis, "Clearing the Air at Kodak", Pollution Engineering. (1988).

      (4)   Guideline on Air Quality  Models (Revised), EPA-450/2-78-027R,  U.S.  Environmental
      Protection Agency, Research Triangle Park, July 1986.

      (5)  C.W. Miller and L.M. Hively, "A Review of Validation Studies for the Gaussian Plume
      Atmospheric Dispersion Model."  Nuclear Safety 28-4, (1987).
                                           837

-------
   Near Real-Time Measurements of Pentachlorophenol in Ambient Air By
                          Mobile Mass Spectrometry
                Gary B. De Brou, Andy C. Ng and Nicholas S. Karellas
              Air Resources Branch, Ontario Ministry of the Environment
                           880 Bay Street, Fourth Floor
                        Toronto, Ontario M5S 1Z8, Canada

 ABSTRACT
       A mobile tandem mass spectrometer' (TAGA) in conjunction with a pre-concentrator,
 is used to monitor ambient pentachlorophenol (PCP) at sub ppb levels. The monitoring
 method consists of PCP trapping, desorption, and MS/MS analysis. PCP molecules (M) yield
 parent positive ions M* at 264+x amu and negative ions (M-l)' at 263+x amu as well as (M-
 20) at 244+x amu, where x=0,2,4,6,8.  Monitoring either positive or negative ions leads to
 PCP  identification  by  examining MCl/rCl ratios.   In  the  presence  of other isobaric
 compounds, the MS/MS capabilities of the mass spectrometer are utilized. Under conditions
 of collision activated dissociation (CAD), fragmentation of negative  PCP parent ions is not
 significant, however, positive parent ions readily lose Cl, HCl, Cl, and CO yielding a variety
 of daughter ions. Monitoring of parent/daughter ion pairs is used to affirm the identity of
 PCP.   Quantitation of PCP involves calibration of the mass spectrometer using a heated
 nebulizer for  injecting known amounts of PCP liquid standards. The mobile monitoring
 technique was used in  the  determination of ambient PCP levels at various distances
 downwind of a wood treatment facility in Ontario. The average limit of detection for PCP
 was 40 ng/m1  (4 ppt).

 INTRODUCTION
       PCP, which is widely used as a wood preservative, is known to cause lung, liver and
 kidney damage. At elevated temperatures, PCP has a very pungent odour. In 1989 while
 monitoring a  wood  treatment plant for PAHs  using the  Ministry's  first mobile single
quadrupole MS system (TAGA 3000), trace amounts of PCP were detected. This and other
 recent PCP related incidents created a need for real time measurements of PCP in ambient
air. Thus a technique capable of measuring ppt levels of PCP was developed by the Ontario
Ministry of the Environment.  This monitoring technique, which combines an automated
short term adsorber (ASTA) unit and a mobile mass spectrometer, provides near real time
measurements of PCP. This method was initially developed in the early 80's for monitoring
PCBs.  In  1987  the  Ministry upgraded this procedure by acquiring a mobile tandem
quadrupole mass spectrometer (MS/MS), the TAGA 6000.  Advantages of  the MS/MS
system include minimization of chemical interferences and lower detection limits. To date,
the mobile TAGA 6000 has been used  for  on-site monitoring of  several environmental
emergencies and numerous contaminants from a variety of industrial sources in Ontario. To
quantitate PCP, a heated  nebulizer is used to  inject controlled amounts of PCP liquid
standards into the TAGA ion source.  This technique allows for calibrating the TAGA
sensitivity thus establishing the limits of detection for PCP. The ASTA/TAGA technique was
recently used  to monitor point and fugitive PCP emissions from a wood treatment facility
in Ontario. The monitoring technique is described and results are presented in this paper.
                                      838

-------
EXPERIMENTAL

ASTA Sampling System
       For most chemical classes, the TAGA is extraordinarily sensitive for determining trace
levels of organic contaminants.  However, the absolute sensitivity for PCP is insufficient for
real-time  detection.   Thus, a  simple sampling device is used to concentrate  PCP  for
immediate analysis by the mobile TAGA.  This device, an automated short term adsorber
(ASTA), has been described in the past.1  A schematic diagram of the ASTA is  shown in
Figure 1.  The two nichrome probes, coated with a chromatographic stationary phase, can
be rotated to place them alternatively in the ambient air stream or in the benzene/zero air
stream. Several phases' of various polarities were examined: DEGL-SP, SE-54, OV-17, OV-
225, OV-275.  Of the phases tested, OV-17 was found to exhibit the best adsorb/desorb
characteristics.  PCP molecules adsorbed to the probe are thermally desorbed into TAGA's
jonization chamber where positive and negative PCP ions are formed. These ions are mass-
analyzed by the TAGA.  The time to complete one full cycle, or analysis, is 2 minutes and
8 seconds. A half-hour concentration of PCP is determined by averaging  15 consecutive 2-
minute adsorption/desorption cycles.

TAGA 6000 MS/MS Analyzer
       A schematic diagram of the TAGA 6000 is shown in Figure 2.  The basic operation
is governed  by the principles of APCI (atmospheric pressure chemical ionization) tandem
mass spectrometry. Parent ions, formed in the APCI region, pass through an orifice into the
vacuum chamber where they are separated by the first quadrupole (Ql) and fragmented via
c0Uision  (CAD) with  argon gas in the RF only second quadrupole (Q2). The resultant
fragments, or daughter ions, are analyzed by the third quadrupole (Q3).
       Compound identification is achieved by comparing daughter ion spectra of real
samples to standard TAGA CAD library spectra. In this work both MS and MS/MS were
used to monitor negative and positive PCP ions respectively. The criteria for identification
are  based on chlorine isotopic ratios of  the ions monitored  and on desorption profile
characteristics such as times of desorption peaks, integrated areas, net PCP concentrations
and  signal to noise ratios.
       Quantitation of PCP is accomplished by injecting aqueous standards upstream of the
adsorbing probe  via a heated  nebulizer shown  in Figure 3.  Vaporized PCP  from the
standard is mixed with the ambient airflow then trapped by the ASTA's  adsorption probe
for subsequent desorption and analysis. Nebulizer injection flow rates from 0 to 20 /iL/min
provided a PCP concentration  range of 0 to 5 ppb  to be generated in the APCI source.
Five-point calibrations are performed by simultaneously recording the responses to selected
pCP ions. The response factors of the TAGA to PCP is determined from the slope of the
calibration curves.  The analytical detection limits are determined from the standard
deviations of the background and the corresponding response factors.

RESULTS AND DISCUSSION
       The ion chemistry of PCP under APCI conditions is relatively simple: PCP molecules,
vf undergo  charge transfer reactions with benzene to yield M* positive ions; H-abstraction
reactions  yield  (M-l)' negative ions and rearrangement reactions produce (M-HC1+O)'
negative ions.  Owing to  the MC1 and  "Cl  isotopes and the  five Cl atoms in the  PCP
molecule, positive ions at 264, 266,268,270,272 and negative ions at 263,265, 267,269,271,
244, 246, 248, 250, 252 amu were observed.  Ion signals corresponding to all five Cl atoms
being 37C1, were negJigi016- Under CAD conditions, positive molecular ions yield daughter
.  ns via loss of CO, Cl, HC1 and Cl,. Unlike positive ions, fragmentation of negative ions
                                       839

-------
under CAD conditions is not significant. When PCP levels are so low that signals are no
sufficient for MS/MS analysis, only MS is employed to monitor the negative ions (M-1J a
(M-HCI+O).
      MS analysis was used in the determination of ambient PCP levels near a
treatment plant.  The wood treatment facility consists of two basins containing a mixture
PCP and oil, where poles up to 80 feet in length are immersed for treatment. Treatmen
is complete after 24 hours, with the poles being removed for drying on-site in an open are •
Odours were  particularly noticeable near piles of freshly treated poles.   Mobile ai
monitoring was conducted in order to assure compliance of the Ministry's PCP guideline
for allowable ambient levels.  PCP was measured by the TAGA at several locations 01
various distances from the facility.  The downwind monitoring sites are shown "\Figure  -
PCP was detected as far as 1 km, but levels never approached the Ministry guideline.  Nea^
real-time PCP measurements are shown in Figure 5; half-hour average concentrations a
determined from the 15  consecutive two-minute adsorption/desorption cycles. TwentJ' p
half-hour samples were acquired and the data are summarized in Table 1.  Average r
concentrations as a function of distance from the plant are shown in Figure 6.  The
shown for each distance represent an average concentration of several half-hour samp  •
Modellers can use such information to predict the effects of emission rates and meteoro ogy
on ambient downwind concentrations. The mobile TAGA data are an important sourc ;
real-time data to validate those theoretical models.  For ground level emissions, tn£°Je ea\.
curves do in fact exhibit  similar characteristics to curves synthesized  from the TAGA r
time data; maximum concentrations occur at ground level near the source and a slow dec
is  observed from 200 m to 2 km.

CONCLUSIONS                                                            .   or
       PCP can be measured  by the TAGA  under APCI conditions either in posi" w ^
negative mode. The choice of operating with MS or MS/MS depends on the magni tu a
PCP concentrations.  The technique was successfully applied to monitoring ambient
emissions from a wood treatment facility. Near real-time PCP concentrations were rec
several times, at levels  between 50 to  4400 ng/m1 at times when  odours were pre   ^
During removal of freshly treated poles, although odours were readily recognizable, ele   ^
in PCP levels was not significant.  This suggests that the cause of odours was not  solely
to PCP.  All levels recorded by the TAGA were far below the Ministry guideline of «J,"""
ng/m' for a half-hour average  concentration of PCP which is based on health effects.

REFERENCES
 1. B.I. Shushan, G.B. De Brou, S.H. Mo et al, "Mobile field monitoring of volatile
and toxic air pollutants using a mobile tandem mass spectrometry system", -roce
the Dangerous Goods and Hazardous Waste Management Conference". 1987, pp

2.   N.S. Karellas, G.B.  De Brou and A.C Ng,  "Application  of  a mobile MS/MS |^
monitoring system during PCB incineration in Smithville, Ontario", fVv'"'dings QUO- — -
Technical Seminar on Chemical Spills". 1991, pp 189-198.

 3. Supelco, Canada Chromatography Products Catalogue 29, 1991, pp 123-125.

-------
    Table 1. Mobile TAGA 6000 Air Monitoring Survey, June 1991
     Pentachlorophenol (PCP) Concentrations (1/2-Hour Averages)
                Downwind of a Wood Treatment Plant
Day
Day 1
	 • — • —
~~Day2
__ 	
	 	 • 	
— 	
— — • 	
__ 	 —
	
_ 	 • 	
Day 3




•"^^



*~~Day 4
'

""~~^
1 	
— ^
^— 	 '
Sample
Number
SOI
S02
S03
S04
SOS
S06
S07
SOS
S09
S10
Sll
S12
S13
S14
S15
S16
S17
S18
S19
S20
S21
S22
S23
S24
S25
S26
Site
A
B
C
C
C
C
D
D
E
E
F
F
F
F
F
F
G
G
G
H
H
H
H
H
H
H
AT
28
28
22
23
24
25
25
26
26
27
29
30
30
29
29
31
33
33
33
30
30
30
30
30
30
30
Met. Data
WS WD
05-15
00-10
10-25
10-25
10-25
10-30
10-25
05-25
10-20
10-20
05-15
00-10
00-10
00-15
00-15
00-10
00-15
05-15
05-15
20-30
15-30
15-30
20-30
20-35
20-35
20-35
E
E
E
E
E
E
E
E
E
SE
N
N
N
N
NW
W
W
W
W
NW
W
W
W
W
NW
NW
[PCP]
ng/m3; SD=20%
4400
1400
nd (35)
nd (35)
nd (35)
nd (35)
51
ISO
180
410
510
140
210
320
340
170
82
240
280
570
590
630
810
650
700
680

tes: Monitoring sites are shown in Figure 4.  AT = Ambient Temperature (C); W
  ' Wind Speed (km/hr); WD = Wind Direction; SD = Standard Deviation; nd =
   detected (less than the TAGA's detection limit of 35 ng/m3).
WS =
  not
                                 841

-------
                                                            Ambient Air
                                                            1OO  L/min

                                                                  4
      Air Pump
      Zero Air
      5  L/min
                                  Adsorb Position
Deaorb  Position
                                       ASTA
                                                                        TAGA 6000
           DC  Power
           Supply  On
 Figure 1. Schematic of the ASTA
      Sompling
       Orifice v.
                  SCHEMATIC   DIAGRAM  OF  THE  TAGA  6OOO
                      Atmosphere  to
                    Vacuum  Interface
                      (N2 Membrane)
                                                                         Ion Detector
       Corona Discharge
       lonisation  Needle
   Cryogenic
Vacuum Pump
Figure 2. Schematic of the TAGA 6000 APC1/MS/MS system
                                                                 100 L/min AMBIENT AIR
                                                                         SVL 11 ~T PIECE
        LIQUID CALIBRATION
        STANDARD INPUT
             Q  Q
                                       1/2"  01* (304 SS)
                    NEBULIZING AIR FLOW     H!GH  TEMP. JACKET
                       PURGE AIR FLOW
                             AOJ.  NUT
                                                                   HEATCO TIP
                                                                   CROSS SECTION
                                               NEBULIZING TIP
Figure 3. Schematic of the heated nebulizer
                                           842

-------
                          Nichol Twp. 6-7
                      E
                 Wood
               Treatment
                 Facility
/Wellington Rd.  #22
                                                       Wood Treatment
                                                        \  Facility
                                                                r,
Figure 4. TAGA monitoring locations downwind of a wood treatment plant
    1000 -
    76O -

 ng/m3

    eoo -
    26O -
 2-Minute  Average
POP Concentrations
                                                  Half-Hour Average
                   3   4   66   7   S   e   10  11   12  13   14   15
                          SEQUENCE # (2. MIN/SEQ)
Figure 5. TAGA measurements of ambient PCP downwind of a wood treatment plant
  ng/m3
    4 BOO


    3760 -


    3000


    2260 -


    15OO


     760 -


       O -
      44OO
                             Half-Hour Average POP Concentrations
               260   BOO
                            76O   1OOO   126O  16OO   174SO  2OOO  228O
                                Distance (m)
Figure 6. TAGA measurements of ambient PCP vs distance from a wood treatment plant
                                   843

-------
Massachusetts 1991 NMOC  Monitoring Program
             Thomas R.  McGrath
             Air Quality Surveillance Branch
             Division of Air Quality Control
             Massachusetts Department of
             Environmental Protection
             Lawrence Experiment Station
             37 Shattuck Street
             Lawrence,  Massachusetts
                    844

-------
     The  1990  Clean Air Act mandates "enhanced ozone" monitoring
to  address the  measurement of  ozone precursors.   In  a  phased
approach,  states  with  designated  "serious"  and  "severe"  ozone
noncompliance  areas will be expected to monitor ozone related air
oollution  parameters at a  number of locations prescribed  by an
overall network design.  The overall network design appears to be
based  on assumptions regarding  transport meteorology  and  local
source characteristics  and density.  Draft monitoring regulations
also  include  specific  sampler placement criteria  which closely
follow traditional NAAQS monitor placement specifications for other
measured pollutants.

     Massachusetts DEP  and other New England air pollution agency
officials felt that the  validity of assumptions  and recommendations
for ozone precursor monitoring approaches needs to be empirically
investigated  before  official  acceptance,  especially  given  the
history  of previous  efforts  to  monitor these  parameters on  a
regional  scale.    This  especially applies  to volatile organic
compounds  (VOCs) ,  where a significant historical ambient database
does  not  exist   and   where  an  efficient,  consistent,  proven
measurement methodology (especially for individual compounds)  has
yet to be universally accepted.

     The  Air  Quality  Surveillance Branch  of the Massachusetts
Department of  Environmental Protection (DEP) , in cooperation with
Region I of the USEPA and NESCAUM, conducted a special VOC  (NMOC)
monitoring program last summer.  This  program was comprised of two
distinct monitoring studies.  For one study, nonmethane hydrocarbon
/NMOC) and speciation voc samples were taken over eleven (11) three
hour sampling  events, at six (6)  ambient locations in the Boston
area.  Sampling equipment and analytical  services  for this part of
tne  program were  provided  by  the Radian Corporation  (RTF, NC) ,
under an EPA contract.

    Additionally,  Massachusetts participated in a  second, one site
/per state) , New England regional NMOC study, which required five
days Per week  (Mon - Fri) , 6 to 9 am samples.  These samples were
analyzed  by  the  State of  Maryland  laboratory.   The overall
,nonit°rin9 Program was  designed  so that  data generated  from each
etudy is directly comparable and sampling events are complementary.
     Three primary objectives were identified for the study.  The
first,  objective  was  to  verify  the  placement  guidance  for the
Highest priority enhanced ozone monitoring site.  This location has
been  previously assumed  to  be the  "downwind"  edge  of  the city
Central business  district.   Our  state has purchased an automated
^as  chromatograph VOC analyzer  to  presumedly be placed  at this
location,  to monitor the downwind ambient  results  of the area's
highest density of ozone  precursor sources.
                                845

-------
      It  was  thought that  the  placement of  samplers  at three
locations  in  the  immediate  area  to the northeast, north-northeast
and directly  north  of Boston  (in addition to a sampler  located in
downtown Boston) would provide information relative  to whether the
central city  is the dominant local VOC area  source,  or whether the
emissions  are  more metropolitan  in nature,  given  the  current
distribution  of industry and heavily travelled roadways.   Data from
this  study could  be used to aid in  the  selection of one  or more
enhanced ozone monitoring sites  and to designate  their  categories
according  to  the  intensity  which they warrant.

      A second objective was related to the overall  sensitivity of
the methodology.   Given the expected low concentrations of ozone
precursor   species,   is  the   methodology  sensitive   enough  to
accurately yield  needed expected ambient  data regarding the ozone
formation  mechanics on a spatial, meteorological  and  time  related
basis?  For this objective,  upwind (prevailing  in  the  Boston area)
and  far downwind  (30+  miles)  locations were  included  in  the
network.

     Another  component  to this objective is the placement of the
VOC sampler,  relative to local  potential sources.    The DEP has
noticed a profound influence of vehicle emissions  on local  ambient
VOC concentrations, during several years  of monitoring them as air
toxics at  various  locations.    We have  been concerned that the
employment of traditional guidelines  for  the placement of samplers
relative to roadways and other VOC sources may not be  sufficent to
differentiate   local   or   even  neighborhood   emissions  from
concentrations resulting  from area wide  emissions  or  regionally
transported sources.

     For this reason, we attempted to locate the samplers in the
remotest locations  possible (furthest from significant  vehicular
sources),  given the sampler  support requirements and the nature of
the area under  study.  Sampling  locations included  several state
hospitals,   a  lighthouse and the twenty-second  floor of  a  federal
office building in Boston.

     A third objective,  which  could be overlooked during  the
investigation of  the  other  two, is the  NMOC/VOC  ozone  precursor
data which would  be collected at these  six  locations during the
1991 ozone season.

Monitoring Program

     All monitoring was performed utilizing Method T012  according
to the USEPA*s "Compendium  for the Determination of Toxic Organic
Compounds in Ambient Air" (EPA 600/6-84 updated  1987).  This method
prescribes the collection of whole air samples in SUMMA polished
canisters  (usually  6 liters) at  two  atmospheres  (from an  initial
30 inch Hg vacuum).
                               846

-------
Canisters  are analyzed  (in this year's case by Radian Corporation
and the State of Maryland) for overall nonmethane hydrocarbon total
concentrations   using  a  flame   ionization   detector  (without
separation column) based analytical system.  Selected samples
were  analyzed  for individual  compounds by  Maryland  using  gas
chromatograph - mass spectrometer  (GC-MS) and a gas chromatograph -
dual detector  (two flame ionization detectors) system by Radian.

     All  sampling events  associated with  both  NMOC monitoring
programs were three hours in duration.  The Northeast U.S. regional
study  site,  located  at  the  DEP  Chelsea  Soldier's  Home  Air
Monitoring Station, operated on a  6 to 9 am,  five  day (Mon. - Fri.)
t?er week sampling schedule.  Samples from this program  were shipped
to the  State of Maryland air monitoring laboratory for analysis.
in  addition  to the  standard  FID total nonmethane  hydrocarbon
analyses,  samples  from every sixth calendar  day  (which means we
missed weekend  analyses) were analyzed using GC-MS  for individual
compounds.      This program commenced on June  17  and  concluded on
September  16.

     Sampling events were scheduled for the additional  five special
study sites based on projected high ozone meteorology and southwest
wind directions.  The "window" for the selection of eleven sampling
events (based on predicted presumed high ozone conditions) was July
f 5 through August 31).  The original plan called for a total of
eleven three hour  sampling events  with six 6 to 9 am, three 3-6
on  and two 9 - 12 pm episodes.  However, weather, building access
 nd personnel considerations resulted in eight morning sessions and
three afternoon events.    The afternoon samples  were to be taken
on the same day as morning ones.  A second sampler (in addition to
the morning  "Maryland" sampler) was installed  at  the  Chelsea  site
ao  that afternoon and  evening samples  could be  taken without
interupting  the daily morning schedule.
     The  Chelsea  air monitoring station  is  equipped with  wind
      m . J __ -3  ,J J *«t A>«^ 4 ^SW*  4 **.£•* ^ V»"l *1M.A**.4» •*. ^ * ^«B   ______ n ^  _      * •
       and direction data from the  Chelsea site was used  for all
       _   •  ..*_«__ _^_.. .9. _  1_ __..l_.l_l_J_*i       _       _.
fites during the study, but this data was also confirmed wj
ft0J& two  sites  further inland  (North Easton  and Lawrence).
     A  map  which  shows  the six  sampling  locations  has  been
 ttached.   As stated previously, a goal during this study  was  to
 valuate  the  results  of  locating  samplers  in  places  primarily
 elected  for their reasonable isolation from local VOC  sources.
f!f-  DEP Chelsea air monitoring station is located on the grounds
 f  the Chelsea Soldier's  Home  facility  on  Powder Hill.    This
° cation  is  north-northeast of  Boston,  within  5 miles of the
  ntral business  district,  at significantly higher elevation than
     surrounding area.
                                847

-------
      NMOC (and air toxics) monitoring programs have been conducted
 here during previous years.  Lower than expected NMOC values found
 in this location had cast doubt on the suitability of this site for
 measuring Boston area  VOC emissions.   It was  thought that  the
 results  from  the 1991  study could put  these measured values  in
 perspective.

     The  southwest  (from  Boston),  upwind site was  located at  an
 inactive  monitoring  station  on  the grounds of  Medfield  State
 Hospital,  presumedly  far  away  from  any heavily travelled roadway.

      The   north of Boston site, was placed in a house converted to
 an office by  the Massachusetts Water  Resources  Authority  on  the
 shores of  Spot Pond in Stoneham, approximately 12 to 15 miles from
 the  center city.   Although  a  major interstate highway  is  within
 several miles  upwind  (southwest)  of this location,  it is buffered
 from any  local influences in that direction by the  pond.

      The site thought to be most directly downwind of Boston during
 southwest  wind conditions was  placed  in the  city  of Lynn  Water
 Treatment  Plant, in the third  floor vestibule.   This site is also
 on elevated terrain, removing it from the predominent influence of
 local traffic  emissions and is located  within 10 miles  directly
 northeast  of  Boston.    Lynn  has  been  heavily  considered  as a
 location of the DEP's first  enhanced ozone monitoring station.

     A far downwind (30-35 miles)  site in this network was located
 in the East Point Coast Guard Lighthouse  in Gloucester.  The Boston
 skyline is visible,  looking directly southwest from this location.

     Although  the  original  monitoring  plan did  not prescribe a
 central city sampling site,  Region  I USEPA forwarded the  idea  of
 placing a  sampler on a high floor of a downtown federal  office
 building.  This idea appeared to satisfy our criteria regarding the
 placement  of  NMOC  samplers  away  from  predominent  nearby  VOC
 emitters, and a sixth site {fifth special study site)  was added to
 the program on the twenty-second floor of the  Post Office Building
 in downtown Boston.

 Results

     Southwest winds were recorded during almost  all  special  study
 sampling episodes, although not all sampling events occurred during
hot weather or high ozone conditions.    The  commencement of  the
 study coincided  with classic  hot,  high ozone  conditions, when
measured temperatures in  New England ultimately approached   100
degrees F and a  number exceedences of  the  ozone  standard were
recorded.   Four sets  of special  study samples  were taken during
this time period.   Instead of  the original ten samples scheduled
 for speciations,  the study budget  allowed for  a total  of seventeen
samples were speciated.
                               848

-------
     Our  Chelsea site averaged  0.282  ppmc NMOC over  55  morning
samples taken during the summer of 1991, which ranked ninth out of
eleven regional locations studied. Average NMOC concentrations at
Chelsea during "Saturation Study" sampling events was 0.397 ppmc,
which reflects the more uniform southwest wind direction specified
for  this  component of the  study.   The attached table  (Table 1)
summarizes Saturation Study NMOC results.
     Results  from  this  study,  as  well as other information,  were
used to  select the Lynn Water Treatment facility as the location
for Boston's  1993  Type  2 enhanced ozone monitoring site.

     Only  a  limited number  of  samples were  taken during  the
•• saturation"  component of the study.   However, we believe that the
results  did yield  valuable information about VOC ozone precursor
monitoring procedures and their levels at various locations in the
Boston area.  We do not believe that a  sufficiently representative
number of samples were analyzed for hydrocarbon species to draw any
definative  conclusions.     However,   interesting  results  were
observed.  A  copy  of some of  these results  has been attached as
Table  2.  An  artifact  (Cyclotetrasiloxane)  appears  to  have been
consistantly  detected in samples from  the Stoneham site.

     Below is a  summary of some of the conclusions which we based
on our review of the study results:

i  siting Issues - As stated above, results confirm our selection
of Lynn  as  Boston's "Type 2"  Monitoring Location.   At least one
sample  from  the upwind  (Medfield)  station  may  have  shown the
influence of  unusual vehicular traffic in the area.  The question
of site  comparability was brought up by dramitically  low values at
a coastal site (Gloucester) during afternoon  Seabreeze conditions
and the low average NMOC values at the downtown Boston (22nd floor)
location.
o  Method sensitivity - Although not many samples were taken during
fne Saturation Study, rises  in falls  in  Total NMOC and  individual
Compound concentrations relative to location  (upwind/downwind) and
£ime were readily  observable.   Contrary  to our  initial  fears, VOC
concentrations did not drop to insignificant  levels, when samplers
Sere placed in remote locations, but actually did appear  to measure
transported and  area generated VOC levels.
!|   1991  Data - NMOC  concentrations  measured  during  55 morning
Dimpling events  at the  Chelsea site were again  low, when compared
f o study locations in other states. However,  the  addition  of five
 ther sites for  at least a few of those  events  helps to put those
Results  into perspective relative to concurrent upwind and downwind
 « well  as suggests nearby  locations where  more representative,
 iaher VOC concentrations may  be measurable.

     More extensive conclusions and discussion can be found in the
     report.  Readers are encouraged to draw  their own conclusions
     reviewing the data.
                                849

-------
        LOUCESTER
850

-------
                         Table 1

                saturation study 1991 Ambient NMOC Data
               Sampling Locations  fSee Attached
               1. Chelsea Soldier's Home
               2. Post Office Buiding, Boston
               3. Medfield State Hospital
               4. MWRA Office, stoneham
               5. Water Treatment Facility, Lynn
               6. Coast Guard East Point Lighthouse, Gloucester

7/17/91
/6 - 9 am)
7/18/91
if, - 9 am)
I O •* '
7/19/91
/A - 9 am)
I O »-— t
/i —6 pm)
* j »* r •*
•ff?\ »>
* ^ -* »••••/•
- 6 pm)
8/14/91
/A - 9 am)
I O ^ '
8/15/91
,6-9 am)
I O '
8/15/91
/ •> — 6 pm )
o /23/91
/ 6 — 9 am)
8/26/91
(6-9 am)
A M«A'i*^hCT0
*
ws
8
4
6
4
3
1
4
4
8
6
15
11
5
2
6
6
5
4
8
3
3
4

Concentrations (parts per million total
WD 1 2 3 4 5
252
249
254
260
265
220
74
162
257
260
271
281
261
243
223
230
211
222
245
220
227
209

A^f ^V ^ "^ »
Majci.mun Valu*
if«x Data


0.308
0.401
1.070
0.439
0.400
0.233
NS

0.654
0.228
0.176
0.174
0.284

0.178
0.397
1.070
7/19
0.553**
0.162
0.323
0.447

NS
0.075

NS
NS
0.132
0.099

0.126
0.240
0.553
7/17
0.165
0.819
0.340
NS

0.097
0.218

0.148
0.167
0.100
0.140

0.244
0.244
0.819
7/18
0.316
0.444
0.554
0.524

NS
NS

0.521
1.586
0.416
0.213

0.223
0.533
1.586
8/15
0.103
0.166
NS
0.521

0.457
0.416

0.168
0.264
1.814
0.223

0.239
0.437
1.814
8/15
NMOC)
6
0.134
0.149
0.317
0.093

NS
0.283

0.190
NS
0.074
0.191

0.060
0.166
0.317
7/19
   First wind speed and wind  direction averages from Chelsea  DEP
 tr  Monitoring Station.   Second averages  from Lawrence DEP  Air
   nitoring Station.
M° 7/17 Saturation  NMOC  concentrations calculated  from some  of
   eciated   VOC  concentrations.     No   Total   NMOC  analysis  was
 a-r formed.
P  tes:  All 6 - 9 am Chelsea samples  (except 8/26) analyzed by State
    Maryland. All  other samples  analyzed  by Radian  Corporation.
        listed values  froa two 3  - 6 pm periods were  duplicate
      Ho Sample Collected,
                                851

-------
                          Table 2
            Summary of Saturation  Study Speciation Data
     Compounds Identified at >/= 2.0 parts per billion by Volume
            All Values Given in Parts Per Billion (ppbv)
 7/17/91 (6 to 9 am)

 Boston    Cyclopentane (2.9)
 (0.553)*   Ethane (3.1)
           Ethylene (2.9)
           n-Hexane (6.5)
Medfield
 (0.165)

Stoneham
 (0.316)

Lynn
 (0.103)
Gloucester
 (0.134)
n-Pentane  (2.4)
n-Butane  (3.0)
Isopentane  (7.9)
n-Pentane  (4.5)
Propane  (2.6)
Toluene  (5.6)
Unidentified  (3.5,  4.6,  3.0)

1.3.5 Trimethylbenzene  (2.1)
Unidentified  (2.3)

Ethane  (2.3)
Cyclotetrasiloxane  (5.8) Unidentified (25.1)
Ethane  (2.3)
               None
7/19/91  (6 to 9 am)
Stoneham
(0.554)
Acetylene  (2.3)
n-Butane (2.1)
Cyclotetra-
siloxane (16.3)
Ethane (5.4)
7/19/91  (3 to 6 pm)
Stoneham
(0.524)
n-Butane (2.2)
Cyclotetra-
siloxane (13.2)
8/2/91 (6 to 9 am)
Lynn
(0.457)
Ethane (2.4)
Ethylene (2.3)
8/2/91 (3 to 6 pm)

Lynn
(0.416)
               None
Ethylene  (2.1)
Ethylene  (4.1)
Isopentane  (2.9)
n-Pentane (2.3)
Toluene (2.4)
unidentified  (3.0, 8.0)
Ethylene (2.0)
n-Pentane  (4.2)
Unidentified  (8.4)
Unidentified  (2.7, 3.5)
* Total NMOC in parts per million carbon
                               852

-------
                         Table 2 (continued)
           Summary of Saturation  Study Speciation Data
    Compounds Identified at >/= 2.0 parts per billion by Volume
           All Values Given in Parts Per Billion  (ppbv)
         (6 to 9 am)

Stoneham  Cyclotetra-
n.586)   siloxane  (8.2)
v         Ethane  (2.0)

         6 to 9
(0.264)
v
Lvnn
7l 814)
1
cnelsea
(0.178)

cost on
(0.126)
          Acetylene  (3.2)
          n-Butane  (3.0)
          Ethane  (4.1)
          Ethylene  (3.9)

         (3 to 6 pm)

          n-Decane  (2.4)
          Ethane  (2.6)
          Ethylene  (2.4)
          n-Hexane  (3.4)
          Isobutane  (10.0)
          Isopentane  (87.3)
          3-Methylpentane  (4.9)

         (6 to 9 am)

          Acetylene  (2.3)
          Ethane  (2.9)

          Acetylene  (5.8)
          Ethane  (2.1)
ctoneham  Cyclotetra-
(0.223)   siloxane  (5.9)
  nn
(0.239)

Glouceste
          Acetylene  (2.6)
          n-Butane  (3.0)
                                   Ethylene  (2.1)
                                   o-Ethyltoluene  (2.5)
                                   Unidentified  (2.0,  5.9)
Isopentane (3.7)
Propane (2.6)
Toluene (2.2)
Unidentified (2.5)
n-Pentane (69.9)
Propyne (2.5)
Toluene (13.9)
1,2,3 Trimethylbenzene  (2.1)
m+p Xylene (2.5)
Unidentified  (2.0, 2.0, 3.7)
              (4.6, 6.7)
Isopentane  (2.1)
Ethylene  (3.2)
                                    Unidentified (4.0)
Ethylene  (3.6)
Isopentane  (3.3)
                         None
* Total NMOC  in parts per million  carbon
                               853

-------
Acknowledgements

1. I would like to acknowledge the contributions of Alan Oi, Mary
Jane Cuzzupe and staff at USEPA Region I Laboratory in Lexington,
Mass, to this project.

2.  I would  like to  acknowledge the  contributions of  Alan Van
Arsdale of NESCAUM in Boston, Mass, to this project.

3. I would like to acknowledge the contributions of Massachusetts
DEP, Air  Quality Surveillance Branch  including Diana Ainsworth,
Bruce Franklin and Victor  Pozza  to this  project.   Network Map by
Victor Pozza.

4. I would like to acknowledge the work of the State of Maryland,
Department of  the  Environment,  Division of  Special Sampling and
Toxics, Walter Cooney and staff.

5. I would like to  acknowledge the work of the Radian Corporation,
Research Triangle Park, North Carolina, Bob Jongleux and staff.


References

"Compendium  of  Methods  for  the  Measurement  of  Toxic  Organic
Compounds in Air"  (Methods  TO-11  and  TO-12).   U.S. Environmental
Protection Agency,  Environmental Monitoring  Systems  Laboratory,
Research Triangle Park, North Carolina 27711.   EPA-600/4-84/041.
Updated June 1987.
                               854

-------
               Session 19
        VOC Monitoring Techniques
Larry Ogle and Delbert Eatough, Chairmen

-------
 Noncryogenic Concentration of Ambient Hydrocarbons
 For Subsequent Nonmethane and Volatile Organic
 Compound Analysis


 Dario A. Levaggi. Walter Oyung
 and Rodolfo V. Zerrudo
 Bay Area Air Quality Management District
 939 Ellis Street
 San Francisco, California 94109

 ABSTRACT

       The data  requirement lor nonmethane organic compounds {NMOC) and speciated
 volatile organic compound (VOC) analysis, has been and continues to be of prime importance.
 These kinds  of  hydrocarbon data  are used  specifically in developing  federally  required
 implementation plans tar ozone nonattainmanl areas.  Current methods for NMOC and VOC
 analysis require  concentrating whole  air samples prior to analysis by use of either liquid
 nitrogen or argon. To avoid the expensive and cumbersome cryogenic method an investigation
 1or an alternative approach was initiated. The ability to concentrate  hydrocarbons in  the C% -
 CIQ range at room temperature was evaluated using various absorbants.  With the exception of
 one compound,  acetylene,  it was found  possible to concentrate whole air  samples with
 complete recovery and analysis ol alJ hydrocarbons, by using  approximately 600 mg of a
 mixture of three absorbents, contained in a 10" X 1/8" stainless steel tubing. This paper will
 discuss the laboratory results of the evaluation  of various absorbents, and show data
 comparing  the current acceptable  methods to this new  noncryogenic technique.  This
 procedure should prove to be extremely valuable for simplifying  current  methods  and, in
 particular, for utilization in automated gas chromatographs used  for speciation  of ambient air
 VOC's.

 INTRODUCTION

       Present methodologies used for the sampling  and analysis  of ambient air for volatile
 organic gases (VOC) are described in detail in a recently published text, which is essentially a
 compendium  of  USEPA approved procedures.1   Trie two procedures commonly used for
 measurements of C2 - CIQ hydrocarbons  (HC). are method T012 for  nonmethane  organic
 compounds (NMOC),  and TO14 for  the  more complicated method which  speciates the
 hydrocarbons.  Both methods require the use of cryogenics to concentrate the HC. since
 ambient concentrations are too low for direct measurement.

       The literature is replete with HC data obtained from U.S. cities.  The measurements are
 important in the  development of attainment  plans for regions not meeting the ambient air
standard tor ozone. The  NMOC data are used for input  to a simple photochemical model
Xnownas EKMA.  Speciated HC data are for the complex photochemical models, which require
HC class reactivities.  In March 1992 a proposed rule for enhanced monitoring of ambient HC
was proposed by the U.S.EPA.2   This rule is necessary  to  comply with the Clean Air
Amendments of 1990.  The rule will cost millions  of dollars per year,  and  demonstrates clearly
the significance of ambient HC measurements.

       This paper focuses on the work done to find a substitute means to concentrate the HC
prior to analysis. The ease and cost of these kinds of analysis would be impacted dramatically
by noncryogenic concentration.
                                        857

-------
 EXPERIMENTAL

        Improvements  in ambient  HC analysis  have occurred  through the years ultimately
 resulting  in the  present TO12 and T014 methods.  However, there appear to have been no
 concerted studies devoted to the elimination of the cryogenic concentration step used in T012
 and T014.  A review of available adsorbents for  HC collection and subsequent desorption led
 us to believe it was possible to find a combination trap which could efficiently concentrate and
 desorb all the C2 to C-|2 HC.3'4

        To  evaluate the adsorption/desorption  properties  of various trap combinations a
 Tekmar 5010 was utilized.  Figure 1 shows a schematic of the unit.  A Perkin Elmer model 8500
 gas chromatograph, with FID, was coupled (via a heated transfer line at 150°C) to the Tekmar
 to monitor HC mixtures. A 25 m Megabore Chrompak PLOT fused silica AI203/KCI analytical
 column was used  to separate  the individual HC.  The  column  was operated at  an initial
 temperature of 30 "C for 5 minutes, then  programmed at 7°C/min to 190°C and held for 5
 minutes.  If NMOC determinations were made,  the analytical column was replaced with an
 empty 1/16" ss line.

        Gas mixtures were prepared in stainless steel canisters.  A  number of mixes were
 prepared  which  contained at one time or another all the normal C2 - C^Q paraffins, some
 olefins, and the following aromatics,  benzene,  toluene, m and  o-xylene, and IP and  NP
 benzene.   Acetylene mixtures were evaluated extensively because this compound was found
 the most difficult to concentrate from whole air samples. The compounds evaluated were in the
 200 to 500 PPB C range,

        The adsorption  traps to be tested were prepared from 10" x 1/8" stainless steel tubes,
 complete  with an insulated heating tape.   These traps are commercially  available  from the
 Tekmar Company.  Adsorbents added to the trap were carefully weighed to .01 g. There was no
 attempt to separate adsorbents with glass  wool or other material. The ends of the traps were
 plugged with  a  small  amount of glass wool.   A "full" trap  contained approximately 9" of
 adsorbents. Traps were cleaned by purging overnight @ 260 - 300 "C with helium.

       The basic protocol for evaluating specific compound adsorption/desorption was to pass
 a sample  through a trap at 40cc/min. for 5 minutes  (200cc), The trap was then purged with
 helium at  40cc/min  for  3 minutes (120cc), for residual  methane and moisture removal. The
 sample adsorption and  purge cycle were carried out @ 30 °C ± 2°C. Ballistic heating from
 30 °C to 260 *C  was utilized to desorb the concentrated samples for transport to the gas
 chromatograph.

 RESULTS AND CONCLUSIONS

       Based  on the current literature it was felt that some combination of the so called "light
adsorbents" had the possibility of concentrating C2 - C-io HC from whole  air  samples at room
temperature.   Adsorbents were  selected for their hydrophobia  properties and  hydrocarbon
adsorption capabilities.   The absorbents chosen and  their known hydrocarbon adsorption
capabilities were  Tenax  TA (C4 - CIQ), Carbotrap (C4 - CIQ) and Carbosieve S-lll (C2 • C-\Q).
The adsorbents  were first checked individually  for retention and desorption  of  HC.  Two
hundred cc samples were taken using the procedure and trap size described previously.
Results are shown in Table 1.  Tenax TA did not retain C2 - C$, partially retained nC^ and was
fine for the C$  - CIQ HC.  Carbotrap did not retain the C2 and only partially the 03, but does
not desorb completely all the HC.   Undesorbed compounds were the  Cg + alkanes and the
aromatics  o-xylene, IP and  NP benzene. Carbosieve S-lll was the only adsorbent capable of
retaining and desorbing C2 and C$  compounds.  However, C$ and higher compounds are so
firmly held in the small pores of this carbon molecular sieve  material that even butane is only
                                         858

-------
 desorbed in trace quantities. Tenax TA was later replaced with Tenax GR because of its greater
 trapping capacity for low boiling compounds.

        Five potential  absorption traps were then prepared varying the amounts of the three
 absorbents, and one was prepared containing no Tenax. The adsorbtion efficiency of the traps
 and their compositions are contained in Table  1.  The trap with no Tenax showed excellent
 recovery of acetylene,  but very poor recovery of the high boiling compounds.  Traps 5 thru 8 all
 showed excellent results for all hydrocarbons with the exception of acetylene.  The acetylene
 recovery for Traps 5 and 8 was however high, about 75%.  Since acetylene makes up only 3 •
 5% of the NMOC in urban atmospheres, recovering 75% is considered quite acceptable.5'6
 Trap  8 was  then selected over Trap  5  to continue further studies  because of its higher
 Carbosieve S-lll content.

        The breakthrough volume for the low boiling, difficult to adsorb C%  and 03 HC, was
 examined more carefully, since the possibility of increasing sample size would be beneficial for
 analytical applications. Table 2 shows Trap 8 data for retention of sample sizes from 100cc to
 400cc, with and without the 120cc helium purge cycle.  Ethane and propane  are quantitatively
 recovered for 400cc samples even with a purge  cycle, (ethylene  from  earlier runs, yielded
 recoveries similar to ethane).  Acetylene recoveries for 100,200, 300 and 400cc samples with a
 purge cycle were respectively, 100%, 75%, 60% and 45%.  This indicates clearly that acetylene
 begins to pass through the trap after 220cc of volume  (100cc sample  +120cc of purge). As
 stated earlier the relatively  low amounts of acetylene present in urban atmospheres makes
 these recoveries in  our view acceptable.  The recoveries are reproducible and thus one may
 apply a correction factor for acetylene recovery if  desired.  Acetylene  recoveries for the four
 sample volumes, 100,  200,300 and 400cc without a purge cycle were respectively 100%, 100%,
 85% and 75%. These superior recoveries were expected and offer the possibility of an excellent
 acetylene recovery (75%) for a 400cc sample.  Recall that the sample adsorption temperature
 used was 30' C ± 2 • C, a limitation of the experimental system.  Acetylene retention may well
 be improved  by simply lowering the temperature during the sample adsorption step.  A T014
 application (speciation of HC) is possible without  a purge cycle because the only methane
 present would be  that contained in the free volume available  in  the  trap.   For TO12
 determinations, a purge cycle may be  necessary, depending on the system used.  In either
 case it is probable that a purge volume less than 120cc may be found which  is satisfactory. A
 lower purge volume  would also improve acetylene recovery.

        Precision runs for NMOC  were made on a high and low  concentration  ambient air
 sample using Trap 8.  The analyzes  were performed over a two day period, and the data are
 shown in Table 3.   Results  compare well with TO12 criteria that calibration  standards run in
triplicate should have a relative standard deviation (RSD). of 3% or less.1  The data generated in
Table 3 were from 200cc samples, a larger sample size is possible and would improve the
 precision.

       After the satisfactory general performance of Trap 8, whole  air  samples were taken in
San Francisco and San Jose for NMOC analysis.  The  samples were analyzed by TO12, and
the noncryo technique.  The  results in Table 4 indicate the methods  are to  a considerable
extent comparable.  The percent difference  for  twelve samples ranged from 91-115, with no
apparent concentration bias. NMOC data from a large nationwide study reported the average
of absolute values  of  10.1%  difference between duplicate analyzes.7  Data  in  Table 4 are
comparable to this study  performed  by an experienced laboratory, but a more severe test in
that it represents data of two different procedures.  More importantly this level  of comparibility is
more than adequate for the data applications.

       Following are some  miscellaneous comments related to this study. The experimental
apparatus used in this  study did not allow T014 comparisons because of insufficient separation
                                          859

-------
 capability of the analytical column   A few ambient samples were  run using the analytical
 column and the general compound makeup was what one would expect in urban air.  Figure 2
 is a chromatogram of a fifteen compound mixture used during the evaluations. The sharpness
 of the compound peaks was surprising considering tnat no cryofocusing was involved, only
 ballistic heating of the trap to 230'C for three minutes arvd direct transport to the G.C..  The
 maximum desorbmg temperature used m the final protocol  was 230' C. It was found early on
 that Tenax had an artifact peak at the retention t;me of benzene rf a 260' C desorb temperature
 was used   The peak area was  equal to apprommatefy  9 PPB C. unacceptable for TO14
 analysis Thus the change was made to 230'C where no measurable artifact was noted. Trap
 8 has been involved wlh  over 100 analyses and has shown no performance changes

        Additional experiments win be performed using a siKjhtSy longer trap size to see If the
 addition of more Carbos>eve S-SH W.H retain ail  of the acetylene   We wish also to experiment
 with Trap 8 applications for chlorinated hydrocarbons and other toxic compounds in air.

 CONCLUSIONS

        An adsorption trap has been evaluated wtucn  wsn  concentrate Cj - CIQ HC in air at
 room  temperature  Important advantages to such an aosorpton fap are:

        •      Simplification of Methods T012  and T0i4
        •      Reduced  cost of analyses for Methods T012 and TQ14
        •      NMOC (T012) determination wthout cryogenics
        •      Easy adaptation to automated  gas chromatographs  now being developed to
              perform T014 analyses 8
        •      Ukely adaptation for gaseous toxic analytical schemes

 REFERENCES:

 1      W.T. Winberry. Jr,  N T  Murphy and R M.  Rigg.n,  Methods fpr the Determination of
        TQXIC Organic Compounds m Air. Noyes Data Corporation New Jersey 1990, pp 332-
        369 & 467-583

 2      Federal Register Voi 57. No  43  Wednesday March 4. 1992, pg 7687-7701.

 3      WR  Betj et ai 'Characterizatton of Carbon Mofecuiar Steves and Activated Charcoal
       tOf Use  m Airborne Contaminant Sampling,' Am Ind Hyp Assoc  J 50 (4)-  181-187
        (1989)

 4      G  Bertoni, F Bruner, A UDerti and C Pernno 'Some Critical Parameters tn Collection,
       Recovery and Gas Chromatograprvc  Analyse of Organ-c Pollutants in  Ambient Air
       Using Ugnl Adsorbents,' J  Chromatog^ 203. 263-270 (1981)

5      F F. M^iroy, V L. Thompson et, aJ. "Cryogenic Preconcentratton-Oirect FID Method for
       Measurement of Ambient NMOC Refinement and  Comparison with GC Speciation,"
       JAPCA36 710-714(1986)

6.      W A. Lonneman. R L Sella. and S A  Meeks. •Non-Methane Organic Composition in the
       Lincoln Tunnel.* Enwpn So  Technpl 20, 790-7% (1986).

7      Radian Corporation. '1988 Nonmethane Organic Compound Monrtonno Proarpm Final
       Report VQJijme I*.  December 1988. EPA-450 4-89-003
                                         860

-------
 8.
D.L Smith, M.W. Holdren and W.A. McClenny, "Design and Operational Characteristics
of the Chrompack Model 9000 as an Automated Gas Chromatograph," in Proceedings
nf the 19?1 USEPA/A&WMA International Symposium on  Measurement of Toxic and
Ralated Air Pollutants." VIP-21, Air and Waste Management Association Pittsburgh,
1991 pp 398-402.
 TABLE  1. Efficiency Of Adsorption Traps For Sixteen Hydrocarbons; 200cc Samples With A
 120CC Purge
                                 ADSORPTION TRAP, % RECOVERED
                                 2     3     4       5      6     7
ACETYLENE
ETHANE
PROPANE
BUTANE
pENTANE
HEXANE
HEPTANE
OCTANE
MONANE
DECANE
BENZENE
TOLUENE
M-XYLENE
O-XYLENE
fp BENZENE
fp BENZENE
0
0
0
15
100
100
100
100
100
100
100
100
100
100
100
100
0
0
12
100
100
100
100
100
90
75
100
100
100
85
85
75
100
100
100
TR
TR
0
0
0
0
0
0
0
0
0
0
0
100
60
80
100
80
55
25
TR
20
TR
70
20
TR
TR
TR
TR
78
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
45
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
30
100
90
100
100
100
100
100
100
100
100
100
100
100
100
100
75
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
TRAP1 TENAXTA,   TRAP 2  CARBOTRAP,   TRAP 3 CARBOSIEVE S-lll
TENAX GR
rARBOTRAP
CARBOSIEVE S-IH
                   TRAP 4
                     0
                    .12g
                    .SOg
TRAPS
 .03g
 ,09g
 .44g
TRAPS
 .06g
 .06g
 .440.
TRAP 7
 .08g
 .12g
 .22g
TRAPS
 .05g
 .04g
 .51 g
                                       861

-------
   TABLE 2. Breakthrough Volume Evaluation Of Low Boiling Compounds: Trap 8 with
   120cc Purge, Deaorb <& 230 * C, and Analytical Column. Area Count Comparison*.
   Compound
       lOOcc
                                             Sample Size
                                       _2QQcc     _    300CC
400CC
Acetylene1
Acetylene
Ethane
Propane
10.5
10.7
6.5
5.8
20-2
154
12.7
12.9
27.1
19.0
18.9
17.0
31.7
19.3
23.8
23.4
   1 No purge cycle, average of two runs
     Acetylene cone, approx. 500 ppb, ethane and propane appro*. 300 ppb.
TABLE 3. Precision Data For The NMOC Determination Using The Noncryo Technique:
Trap 8. Sample Sire ZOOcc. 1 20cc purge, and desort) at 23O ' C.
         Sample
Day/Run
PPBC
                                                Day/Run
                                                          Sample 2
                                                 PPBC
1/t
1/2
1/3
1/4
2/1
2/2
2/3
2/4
2/5
Ave » 420 PPB C, STD
% RSO 3 98
433
421
420
410
433
395
410
392
391
DEV16












1/1
1/2
1/3
1/4
1/5

2/1
2/2
273
Ave *

1870
1833
1866
1806
1750

1728
1696
1759
1 788 PPBC. STD DEV 65
% RSO 3.63
TABLE 4.  Analyse* Of Ambient Whole AJr Samples By TO12 And The Noncryo Technique
Sample
  TQ12
                                 Noncrvo
1
2
3
4
5
6
7
8
9
10
11
12
Noncryo
TO12
353
407
416
453
518
534
538
638
714
717
795
1735
Trap 8; 200cc *amp4«,
339
412
380
423
598
555
534
593
808
631
780
1788
i2Occ purge, and desort) at
96
101
91
83
115
104
99
93
113
88
98
103
230*C
Sample size 260cc. Nutech Ovo concentrator
                                     862

-------
          SAMPLE CONCENTRATION & DESORPTION
             SYSTEM UTILIZING A TEKMAR 5010
                          "^""D



1 1
)4



)

ADSORPTION TRAP
<
^


i t
] : i ' :


D^QON
/
)
i
W8P
'— ^
	 *







2



                                              Figure 1
}? "
*» IP
•
o*



•A
^^^^i™
cf

a
rt
-^M
N
C
]
$


B>
                                    EO £
                                    ««
                                     M  i
                                           *• N.
                                                          1
FIGURE 2. Chrometogram Of A Fifteen Compound Mixture Of nC2 - nC10 Plus Aromallcs.
Trap 8,200cc Sample, 230 • C Desorb, Chromplot Column. All Compounds In The Range
200 to 300 PPB C.
                             863

-------
 DIRECT MEASUREMENT OF VOLATILE  ORGANICS
          IN LIQUID PESTICIDE FORMULATIONS

             Max R. Peterson, Yvonne R Straley, and It K. M. Jayanty
           Research Triangk Institute, Research Triangle Park, NC 27709

                       Tracey D. Shea and Gary D. McAllster
      U.S. Environmental Protection Agency, Research Triangle Park, NC 27711


                                  ABSTRACT

      Total concentration of nonvolatiles present in a pesticide is typically determined by
Ihermogravimetric analysis (TGA). The sample is purged with a chemically inert gas (e.g-.
nitrogen or helium) at S4°C until a constant weight is achieved or for a maximum of 4 hours,
whichever conies first.  Concentration of volalites is calculated as 100% minus the
concentration of nonvolatiles. Water, if present, may be measured by Karl Fischer titration.
Total concentration of volatile organics (VO) present is then computed as the difference
between volatile content and water content. The  method is less precise for water-based
formulations than it is for solvent-based formulations, and the imprecision increases as water
content increases. In addition, TGA equipment is quite expensive.
      Recently, a method was developed at RTI (under contract to EPA) by which  VOC in
water-based coatings is measured directly. This method has been adapted to analyze pesticide
formulations.  The procedure involves purging a weighed sample of the pesticide with dry
nitrogen at 54°C, adsorption of VO in ihe volatile fraction onto activated carbon in pre-
weighed lubes, determination of final weights for both the sample residue and the charcoal
tubes, and computation of weight percent VO in the original  sample. In this case, VO is
measured directly as weight gained by the charcoal tubes.  Water content can also be
measured directly by adding pre-weighed tubes containing a dessicant (e.g., Drierite*)
downstream from the charcoal tubes-
      Total nonvolatile content  was determined  by both TGA and the  RTI method  for
thirteen pesticides sold  as emulsifiable concentrates.  Results of analyses by the two methods
were similar and agreed with information from Material Safety Data Sheets (MSDS's) when
such information was available.  The precision of the two methods is similar.  The RTI
method offers the potential for speciation of target compounds through desorption of the
charcoal used to trap VOC and analysis of the desorbed material by gas chromatography
mass spectrometric detection (GC-MSD).
                                 INTRODUCTION

       Two methods for measuring the volatile organic (VO) content of liquid pesticides
 evaluated.  The first method, widely used in the industry, involved measurement of volatile
 content by thermogravimetric analysis (TGA),1 measurement of water content by Karl Fischer
 titration, and calculation of VO content as the difference.  The second method, a modified
                                         864

-------
 version of EPA Method 24, allows direct gravimetric measurement of nonvolatiles, VO, and
 water in a single analysis.2-3
                                   EXPERIMENTAL

 Thermogravlmetrk Analysis

       The determination of volatile material in pesticide formulations is typically determined
 by thermogravimetric analysis (TGA).1 Samples of the pesticide are purged with nitrogen or
 helium at 54°C until a constant weight is achieved or for a maximum  of 4 hours, whichever
 comes first.  A temperature of 54°C is used to test the chemical stability of agricultural
 formulations during development.  Litlle or no decomposition of any type is considered to
 occur at that temperature.  Water content of a pesticide may be determined  by Karl Fischer
 titration.  Volatile organic (VO) content can then be calculated  as the  difference between
 volatile content and water content.  The method is less precise for water-based formulations
 than it is for solvent-based formulations, and the imprecision increases as water content
 increases.  In addition, TGA equipment is quite expensive.

 Volatile Organlcs In Pesticides Method

       Recently, a method that allows the direct measurement of volatile organic compound
 (VOC) content of water-based coatings was adapted to pesticide analysis.  The method,
 developed at RTI under an EPA contract, is a modified version of EPA Method 24 and is
 hereafter referred to as the volatile organics in pesticide (VOP)  method.  The procedure
 involves purging volatiles from a weighed sample of material with dry nitrogen at an
 appropriate temperature (54°C for pesticide formulations), adsorption of VO in the volatile
 fraction onto activated charcoal in pre-weighed tubes, determination of final weights for both
 the sample residue and the charcoal tubes, and computation of weight  percent of VO in the
 original sample.
       Water, if present, can also be measured directly by adding collection tubes containing
 an anhydrous material (e.g., Drierite) to the exit port of the last charcoal tube.  Water, which
 is not sorbed by charcoal, is collected quantitatively on the Drierite. The weight gain of the
 Drierite tubes represents the weight of water present in the original sample. The weight
 percent of water in the original liquid pesticide can be calculated in the usual way.
       Nonvolatiles are measured directly by determining the weight of the residue after
 heating.  Weight percent nonvolatiles is then calculated in the usual way.
       Mass balance can be demonstrated by computing the sum of weight  percent VO,
weight percent water, and weight percent nonvolatiles. The sum is typically in the range of
 96-99%,  if the sum is less than 95%, the results should be discarded.  This problem is
generally attributed to a leak that develops during the four-hour heating period.
       This method removes some of the inherent imprecision in the TGA/Karl Fischer
 method and could be easily extended to include speciation of VO.  This could be
 accomplished by desorption (liquid or thermal) of the charcoal (or other suitable sorbent) and
 analysis by gas chromatography with mass selective detection (GC-MS). Individual VO could
be identified by library matching of mass spectral  data and quantified by the use of
appropriate standards.
                                          865

-------
Comparison of TGA mod MM24
       In the current study, weight percent nonvolatiles measured by thermogravimetric
analysis (TGA) and by the VOP method were compared to see if there was any relative bias
in the two methods.  Twelve commercial pesticides, sold as emulsiflable concentrates, were
used in the study.  Of the twelve, ten were solvent-based and two were water-based.  Alt ten
of the solvent-based and one of the water-based pesticides were analyzed by TGA. All
twelve pesticides were analyzed by the VOP method.
       A summary of TGA data for the eleven pesticides analyzed  is presented in Table 1.
All TGA data was collected at 54*C and the sample size was approximately 25 mg. All TGA
analyses except the one with Lasso were allowed to run for 4 hours (240 min). All volatiles
had been removed from Lasso within the first 90 min. Weight percent nonvolatiles ranged
from 28.65% to 88.28%.  The one water-based pesticide (Blazer) is indistinguishable from  the
solvent-based pesticides.
       Hourly measurements for the  samples analyzed by the VOP method were obtained by
stopping the run, disassembling the apparatus, allowing the sealed components to cool to
room temperature, weighing the appropriate components, reassembling the apparatus, and
continuing the run.  Using this approach, ten pesticides were allowed to run for a total heating
time of 6 hours, one (Basagran) for 4 hours, and one (Lasso) for 2  hours. A summary of
weight percent nonvolatiles measured by the VOP method,  paired with the appropriate TGA
data, is presented in Table 2.
       A statistical analysis of the paired VOP and TGA data for nonvolatiles at the end of
4 hours (2 hours for Lasso) confirmed that the two methods give equivalent results for
nonvolatiles at the 95% confidence level. A summary of the statistical comparison is
presented in Table 3.
       A summary of the VOP analysis of two water-based pesticides is given in Table 4.
According to the Material Safety Data Sheet (MSDS)  for Blazer, the formulation contains
8.5% butyl cellosorve, which has a boiling point of 171'C  Because of its high boiling point,
only 3.78% of the butyl cellosorve was collected on the charcoal tubes after 6 hours at 54*C
The MSDS for Basagran daims no VO is present and none (-0 21%) was measured by the
VOP method after 3 hours at 54*C


                                  CONCLUSIONS

       The two methods, TGA and VOP. give equivalent results for nonvolatiles.  The VOP
method offers the added advantage of also directly measuring VO and water in the same
analysis.  Neither of the two methods differentiates between volatile organics from solvent,
from emulsifiers, or from active ingredients.  The VOP method has the potential for
speciation, which would allow subtraction of volatilized active ingredients, and/or other
exempt compounds, from the total VO.


                                   REFERENCES

1.   ASTM. "Standard Test Method for Compositional Analysis by  Thermogravimetry,"
    Designation:  E 1131-86, American Society for Testing and Materials, Philadelphia. 1986.
                                         $66

-------
2.  Max R. Peterson, R. K. M. Jayanty, Bruce A. Pate, Yvonne H. Straley, Mike W. Benson,
    and Johnny R. Albritton, Method Development for Measuring the VOC Content of
    Water-Based Coatings.  Work funded under contract 68D90055, work assignments 28
    and 40, U.S. Environmental Protection Agency, Research Triangle Park, NC, 1991.

3.  Max R. Peterson, R. K. M. Jayanty, Gary D. McAlister, and Joseph E. Knoll, "Direct
    Measurement of VOC in Water-Based Coatings," Proceedings of the 1991 U.S.
    EPA/A&WMA International Symposium on Measurement of Toxic and Related Air
    Pollutants, pp. 1006-1011, Air and Waste Management Association, Pittsburgh, PA, 1991.
                                                 vent
                                                      2nd Dttertto tub*
                                                     1st Drteriw tubo
                   2 L/nUn Nt
                   1 L/min Ns
                                                     2nd charcoal tifce
                                                     1st charcoal tub*
                                                           oven
                      FIGURE 1. ASSEMBLED APPARATUS
                                         867

-------
           TABLE 1. VOP METHOD RESULTS AT 240 MINUTES
Pesticide
%Noovot    %VO    %H,0
                                                              Total
Acclaim(R) 1EC Herbicide
Basagnn T/O Herbicide
Baythroid 2
Blazer Herbicide
Buctrii(R) Herbicide
Fokx(R) 6 EC Cotton Defoliant
Gar)oo(R) 4 Herbicide
Uiso(R) Herbicide
Poast(R) Herbicide
Poast(R) Plus Herbicide
Prowl(R) *E
Treflan(R) E.C. Herbicide
Weedooe(R) LV6 Broadleaf Herbicide



TABLE2. VOP METHOD
Sample
Garion(R) 4 Herbicide
Poast(R) Herbicide
Weedooe
-------
     TABLE 3.  STATISTICAL COMPARISON OF VOP METHOD AND TGA
Pesticide
Nonvolatile (Wt. %)'          Paired-Data Statistical Analysis
   VOP               Difference
        I      TGA
                          x,        (x, - X)       (x, - X)'
                  Method
Acclaim 1EC
Baythroid 2
Blazed
Buctril
Folex 6 EC
Garlon 4

poast
Poast Plus
Prowl 4E
Treflan E.C.
\Veedone LV6


46.35%
76.56%
38.80%
42.11%
74.53%
71.27%
51.59%c
28.03%
87.13%
56.90%
64.34%
88.57%


49.25%
76.99%
39.83%
42.94%
75.24%
69.36%
52.92%'
28.64%
87.77%
58.98%
60.16%
88.28%
EX.
n
TT
-2.90
-0.43
-1.03
-0.83
-0.71
1.90
-1.33
-0.61
•0.64
-2.08
4.18
0.29
= -4.18
4 «*
* 12
_ _rt *ijlO
-2.62
-0.15
-0.68
-0.54
-0.42
2.19
-1.04
-0.33
-0.36
-1.79
4.47
0.58


6.84
0.02
0.47
0.30
0.18
4.80
1.08
0.11
0.13
3.20
19.97
0.34
Z(X,-X)2 - 37.46
^ ' ' m 0 ST27
                                  Student's t test:

                              t-df=ll,a«0.05 - ±2.201

                                   U - — - -0-653
                                         **

    The two methods give equivalent results for nonvolatile! at the 95% confidence level
•Volatiles were purged at 54°C for 240 min for all pesticides except Lasso.
"•Blazer is water-based; all others in list are solvent-based.
•All volatiles had been removed from Lasso in 120 min.
••Average of two 120-min TGA runs.
                                        869

-------
                PCBs BY PERCHLORINATION: A METHOD TAILORED TO AMBIENT
                   AIR FIELD SAMPLES RICH IN PAHs BUT LEAN IN PCBs

                       R.  Dombro,  J.  Hurley,  C.Crowley,
                       E.  Simpson  and H.  Edwards
                       Illinois  EPA
                       2200 Churchill  Rd.
                       Springfield,  IL  62706

                       L.  Ogle
                       Radian Corporation
                       8501  MoPac  Blvd.
                       Austin, TX  78720

                                      ABSTRACT

      The  State of  Illinois has  monitored  ambient air  PCBs at  three  sites  In  the
 Chicago area  since  1984.  Filtered  samples  are  collected  on  a PUF/Florlsll/PUF
 cartridge  1n a  GMW PS-1   sampler.  Identification and  measurement of  the  collected
 PCBs  was performed  by Radian  Corp.  using  a GC/HS  method.  Because  PCB  levels  were
 almost  always  low,  typically 0.1  to  Ilng/m3,  a  simpler method  was  sought to  screen
 for PCBs.
      Radian  Corp. and the Illinois EPA  jointly  developed  a  "laboratory optimized
 method"  based  on a PERCHLORINATION GC/ECD  technique  adopted  from previous work  by
 others  1n the field. Application  of  this method converts almost  all  PCBs to a  single
 compound,  decachloroblphenyl   (DCB).  As a  result,  DCB  Is  separated  by  GC  from
 Interfering  compounds which  survive  the  clean-up  steps but  which  are  formed  by
 perchlorlnatlon.   The traditional  GC/MS analysis  would  continue  to  be  used as  a
 confirmatory  procedure when  PCBs  measured  as  DCB  exceeds  a  threshold  level   of
 10ng/m3.
      The presentation will  focus  on the details of sample  processing which result  In
 reliable  data  and  on  the  advantages  and  limitations  of  the perchlorlnatlon  GC/ECD
 technique.

 INTRODUCTION
      The  purpose  of  this  study Is to develop a  perchlorlnatlon GC/ECD method based
 on  existing methods  and   to  use  It  as  a  screening  technique  to   measure  small
 quantities  of  PCBs  present  along  with  much  higher  levels  of  PAHs  and   sulfur
 containing  Interferences   '•'.   This   method   Is  viewed   as   an  adjunct  to  the
 traditionally  used  GC/MS method  '  from  the  point of view that If the  concentration
 of  DCB, the  product  of   PCB   perchlorlnatlon,  exceeds  10ng/m3,  the  quantity  and
 Identity of PCBs can be confirmed.
      Perchlorlnatlon  of  PCBs has been practiced with  variable  success since about
 1970  3. Our  starting point  was with  the  best  available  method  based on previous
 studies and  further jointly developed by Radian  Corp.  and  the Illinois  EPA  4. This
 method  was  transferred to  our  EPA  laboratory  where  It was  applied with some method
 changes  to  samples  for   the   purpose  of  optimization  leading   to  an  established
 tailored field tested perchlorlnatlon GC/ECD method.
      Following  will  be   a discussion  of  sampling,   the  chemical  make-up  of  the
 samples, problems  1n the  application  of the  lab optimized method  to QC samples, a
 description   of    the    tailored   field    optimized   method,    key   parameters,
 advantages/limitations and  evaluation of the field data.

 SAMPLING
     Samplers were  designed by USEPA  and  are  commercially  available  from  General
 Metal  Works  Co.  They  are  known  as  the  PS-1 type.  The glass  cartridge part  of the
 sampler  contains  a  pre-extracted PUF/Florlsll/PUF  composite  preceded  by  a  glass
fibre filter. Figure 1.
     Sampling takes  place by pulling  known quantities  of air through  the filter and
 cartridge at about Bcfm or 0.2m3/mln. for a  total  volume of about 325m3  '.
                                          870

-------
     Within  hours  of  retrieval,  samples  and  coolant  are  placed  In  Insulated
containers and sent to the analytical lab. Each sample set  submitted  for  analysis  1s
accompanied by  a  trip blank which has  not been exposed but  is  otherwise handled  as
the sample set.

CHEMICAL MAKE-UP
     Selected  field  sample  extracts  were  analyzed  by  low  resolution  GC/MS   to
identify   compounds   collected   along    with   PCBs.  Identification  and   typical
concentrations  of some  major  Interferences  and  the  PCBs  are  shown  In  Table  I.  A
typical  chromatogram Is shown In Figure  2.
         Irtf-ptlfleatrlnn of 1nffrf»ri,nr« cmpp^n^ hsforP ™mn1fl d«n-UQ.
                               average concentration
Compound                               ng/m3
PCBs    " -- IT
low MH hydrocarbon waxes
"Jgh MH hydrocarbon waxes
°1nydro-5-1sopropyl-3<2H)-furanone
i-(3,3-d1methy]ox1ranyl Jethanone
6-methyl-3-heptanol
substituted phthalates
"apthalene
fluorene                                92
Phenanthrene                           160
fluoranthene                            56
pyrene                                  36
Jenzo(b and k)fluoranthene              25
oenzo(a) pyrene                           7
b«rtzo(a)anthracene
cnrysene
1ndeno(l12,3-cd>pyrene
sulfur
substituted dlbenzothlophenes
substituted thloureas

^erage concentrations of ten random samples collected on ten days.

^PLICATION OF THE LAB OPTIMIZED METHOD
     The steps  of the lab optimized method  developed by Radian but modified  by our
Jaboratory to remove  the high  levels  of Interference  compounds  cosampled  with the

   S Stepsri?flExtt!Ictnedsan.p1e  on  the   filter   and  PUF/Florlsll/PUF  with   Freon
               (CFC-113).                           „ _   _
           Z.   Concentrate extracts by  evaporation of the Freon.
           3.   Divide concentrate  1n  half.   One  half Is solvent exchanged  to  hexane
               for quaUtatWe  GC/ECO  determination of  PCBs  by  pattern  matching
               after  clean-up. Tfre other half Is  perchlorlnated after clean-up.
           4.   Clean-up  the  concentrate   in  Freon   with   fuming   sulfurlc  add
               (modification to Radian's method).
           5.   Separate  the  cleaned  Freon  concentrate  from  acid  and   mix  with
               anhydrous sodium carbonate.                                    ,*•«„.
           6.   Perchlorlnate  under  anhydrous   conditions   with   excess   antimony
               pentachlortde In the presence of  Iron at 205C for 10  mtn.
           7.   Neutralize reaction mixture,  separate Freon layer now  containing  DCB,
               solvent exchange  to hexane and concentrate.
           8.   Analyze by GC/ECD to measure  DCB.

     Results from the application of this method  to a set of QC samples comprising
                                          871

-------
  three cartridges  at  three  spike  levels  of a  50/50  mixture  of  Aroclor  1242/1260
  revealed that  recoveries  based on OCB were below acceptable  levels, Table  II.

  Table II.  Recoveries of PCHs as measured by DCB and bv  oattern
PCBs
PCB spike
(nq>
497.5
750.8
1248.4
blank
average
by perchlorinatlon

389
449
703
29
—
1R
78
60
56
_
65
      An  extensive  Investigation  of  the  method  parameters  was  Initiated following
 these  results.  These parameters  were:   I)  efficiency of  cartridge  extraction;  2)
 overheating  of  samples during  concentration of extracts or  air-down procedures;  3)
 clean-up  with  acid; 4)  purity  of  the  antimony pentachlorlde;  5)  conditions  under
 which  perchlorinatlon  takes place;  6)  stolchlometry; 7)  comparison of  the  PCB and
 OCB  standards  used for  GC/ECD  calibrations; 8)  recoveries  versus  spike  level  and
 recoveries versus Aroclor type.
      Several  of   these  parameters   were   found   to   significantly   Impact   the
 effectiveness of the method. These are discussed below.

 Overheating of the Samples
      Loss of low  molecular  weight PCBs can  take place  during concentration of  the
 extract by  distillation because  of the overheating  of  the dry  walls of  the  glass
 flask towards the end of the distillation. To counter this  potential  loss  of  low  MM
 PCBs,  concentration of  the extracts  by  distillation was  taken  only to  the  point
 where at least lOcc of concentrate remained  In the flask.

 Clean-up with Concentrated and Fuming Sulfurlc Acids
      Because field  samples  were rich  In PAHs. It was  feTt  that strong measures  were
 necessary to remove then before  perchlorlnatlon.   Table III  shows  that  Aroclors  rich
 In low HH PCBs  lose these  congeners along  with the PAHs by this treatment *.

 IaJilt—111.  Effect  of sulfurlc add clean-up on PCB recoveries.	
                                 I  Recovery
             net perch!or!nation              with  perchlorlnatlon
 Aroclor  cone. H2S04    fua. H2S04	cone.  H2S04     fum.  H2S04
  1242        88              72                 79            30
  1248       100              88                 50            48


 Perchlorlnatlon Conditions
      The  conditions  selected  for  perchlorlnatlon  Is  the best available  *.  These
 conditions are as  follows:
 PCBs  In Freon or other suitable  halogenated solvent  Is  placed  In a sealed test tube.
 *lxed with  excess  pure  antimony  pentachlorlde  plus Iron  powder  under  anhydrous
 conditions  and  heated at  a temperature  of  20SC *  5C for  at  least  10  mln.   Any
 departure  from  these conditions  result  In Incomplete  chlortnatlon and  therefore low
 yields of DCB. Figure 3 shows the  yield of DCB with  time and temperature *.

 Recoveries versus Aroclor Type
      It has  been  observed  that  samples  rich  In  mono  to  tetrachloroblphenyls do not
 always perchlorlnate quantitatively '.  He so»et1«es  observe  that Aroclor  1242  and
 1248  used  as an  external  standard  resulted   In  recoveries <701,  while Aroclor 1254
 always  resulted  In  recoveries  >70I. He theorize that sterlc  hindrance  of certain
octa  to nonochloroblphenyl congeners toward complete chlorlnatlon could  contribute
                                          872

-------
 to  "less than optimum" recoveries.
     Following  this  study a refined  method  evolved which  Incorporates  the  changes
 already
 mentioned.  Hgures 4,5 arid  6  show GC/ECD chroma tograms  of a typical  sample  after
 cleanup steps and after perchlorlnatlon  by  the refined method.

 RESULTS
     Application of the Refined Method to two sets  of OC  samples led  to the  results
 shown  In  Table  IV.   Note  that the  second set  was also  spiked  with  lOO.OOOng  of
 fluorene as the Interference  compound. Recovery data  shows  an  overall  Improvement  as
 a result of  the changes  made to the lab optimized method. The low 67%  recovery was
 Probably   caused   by   poor   freon   extraction   of   an  excessively   compressed
                 cartridge.
      TV, R^oveHss of pr-R* *<  ™*™                   PCBs
^o spike     by perchlortnatton
	Cng)                '   -
249
498
995
751
751
751
227
357
811
603
499
677
91
71
81
81
67
90



+ fluorene
+ fluorene
+ fluorene
     Application of the Refined Method to field  samples  led  to  the  results  shown  In
     > V.

Table V. Analytical  results from the application of the tailored
         field  optimized perchlorfnation GC/ECD method to field samples.
^^•^^^                          	         ^^^^^^^^^r^^_^^^_^^^^^^M
                               PCBs	OC     	
                           by       by    by               * R
                  DCB   DCB X 0,52   PM   GC/MS  Aroclor  by   by
{}ii	na/m3    nq/ni3    na/m3  na/m3  spike	PM  perch 1.

(summer)

«                 !U      il      "   M    IIS    iS  iS
?.                ill      ':'      1.1   l:«    i»     "    «
2
2.1
1.5
1.1
0.8
2.1
2.8
1254
1242
U54
96
99
,.21-
128
79
 ;lP and lab blanks for this data ranged from 0.04  to  0.3ng/m3  as DCB.   Blanks are
not subtracted from data.

,    RellabHIty  of  th« data was judged by  comparing the  PCBs as measured by the DCB
 °"centratlon X 0 52  to th* quailUtlw estimation of PCBS  by pattern matching 
-------
CONCLUSION
     Successful  use of this method depends 1n part on the following parameters:

1.   To reduce Interferences which  can mask the  results,  use fresh PUF and Florist*
     for each  sampling event.   Store  the PUF  material  1n  the dark  to  prevent 1«
     breakdown  by  light.  Extract  the  PUF/Florisll/PUF  composite  in  the  g'asj
     cartridge wtth Freon   or  similar  solvent.  It  has been  observed that
     fewer Interference compounds are  removed  from the PUF material than are removed
     by solvents such as hexane/ether or acetone combinations.

2.   To clean-up the extracted  samples without  loss  of the low MH  PCBs,  avoid harsh
     methods such as  sulfurlc  acid. Make sure that sulfur compounds, If present, are
     removed by  treatment of  the  sample with  mercury  or by  other methods.  Their
     presence could destroy the chlorinating agent used In the perchlorlnation step-

3.   To Insure  complete chlorlnatlon  of the PCBs.  control  the  reaction temperature
     at 205C to  within ± 5C.  Transfer the  reagents  to the reaction test  tube  under
     anhydrous conditions and  seal.

4.   To avoid  loss of PCBs on  transfer  of  solutions and  on  air-down  to concentrate
     solutions,  use  extra solvent  rinses  and  control  the  temperature  to  <40t
     respectively.

     The advantages of  this "tailored  field optimized perchlorlnation GC/ECD" me*^
as practiced by  the Illinois  EPA reside  In  the  fact that  the  small  amount  of PC0s
collected  along   with  much    larger   quantities  of   Interference   compounds  are
measurable. In particular, the  method  can pick out traces  of PCBs  primarily because
one strongly ECO  sensitive compound Is generated which  can easily  be separated fro"
Interference compounds surviving the clean-up steps but which area also chlorinated.
     Limitations of the method  reside  in the fact that It takes five days to process
a  set  of  samples.  Secondly,  recoveries are  determined  not by  using a  surrogate
standard as  in  the  GC/NS method, but by using  an external PCB standard spiked onto a
cartridge which  is  then carried  through the  entire  process along  with the  set  OT
samples. Thirdly, the perchlorlnation of low MH   PCBs  tend  to  result   in  poorer
yields  of  OCB.   He theorize  that  as  a  result  of  perchlorlnatlon,  octachloro ano
nonachloro  tsomers  with nonchlorlnated  2.2',6 or 6' positions on  the  biphenyl ring
may form.   These congeners may  be  resistant  to  chlortnatton  for  sterlc  reasons*
Finally, application  of the basic  perchlorlnation method  must be  tailored  througn
R/0 to handle the matrix In which PCBs  are found.

FUTURE
     The future  lies  with  the  application of  supercritical fluid  extraction of
from sorbents. Not  only would  the time  now required to  process  samples  be  g
reduced but the sensitivity of  the entire analytical  process could be Increased

ACKNOWLEDGMENTS
     He thank Edward  Marti  of  Triangle Labs., Tom  Bellar  of US  EPA In  Cincinnati
Kathy  Boggess  of  Midwest Research  Institute and  Professor  Terry Bldleman of
University of South Carolina for their  valuable input and service.

REFERENCES
l.a.  D.Kolaz. R.Hutton  and  J.Buckert,  Prolcct  Plan for the Sampling  and
     PCBs in Chicago.  Illinois  EPA.  IEPA/APC/8&-011.	
  b,  T.Campbell."Analysis  of   PUF/Florlsil  Cartridges  To  Monitor   PCBs   In
     Air". Proceedings of the  1986 USEPA/AHMA  International Symposium on Kea
     of Tonic and Related Atr Pollutants. AHHA. Pittsburgh, iQflfi.  pp.205-216"
2.   T.BIdlesan.  Univ.  of  South Carolina,  Columbia,  S.C..personal  communication.
     1990.
3.   H.D.Erlckson, Analytical Chemistry of PCBs.  Ann  Arbor Science,  Boston.
                                          874

-------
L.Ogle, Final  Report  on  the Development of a Perchlorlnatlon Procedure for PCBs
Col 1ected from Ambient Air, Radian Corp.,
Austin TX, Nov. 1989.
C.Stratton, S.WMtlock and  J.Allan,  A Method for the  Sampling and  Analysis  of
PCBs \n Ambient Air. EPA-600/4-78-048, USEPA, Washington, O.C., 1978, p.36.
H.Stetnwandter,  "Chlorlnatlon  of   Organic   Compounds  II.   Kinetics  of  PCB
Perchlorlnatlon." Fresenlus Z, Anal.  Chem., 317:  869-871
(1984).
Draft Method 3841.  "Screening for PCBs bv Perchlorlnatlon and GC/ECD: Capillary
Column Technique."  SW  846,  Nov. 1990.
                                    875

-------
Figure 2.  Field tuple GC/ECD chromatogroi before  cleanup.
                                                   i .
Figure 4.      i suple GC/ECD chromatogram after Florisll clean-up.
  PCB
Fj
                                                  .
Figure 5.  Field «a*ple GC/ECD chroMCogra* after Floriall and oercury


 Figure  6.   Field  »a«pl« CC/ECD chrcMutograv after cl«*n-up and perchlorio*'
                                    176

-------
      FIELD EVALUATION OF SEVERAL METHODS FOR MONITORING
       ETHYLENE OXIDE EMISSIONS FROM HOSPITAL STERILIZERS
                                    Kevin Monger
                           Monitoring and Laboratory Division
                             California Air Resources Board
                                    P.O. Box 2815
                                Sacramento, CA  95812
 (CA fit Direct interface gas chromatographic (GC) method, California Air  Resources Board
 ste V    Method 431, for monitoring ethylene oxide (EtO) emissions from hospital equipment
 me?KrS ^and aerators) was compared to a Tedlar bag sampling/GC analytical procedure.  Both
   tnods were evaluated at two hospitals, both of which had sterilizer systems (3M and AMSCO)
 foir1?ed ^ catdytic oxidation (cat/ox) control units.  The direct interface/GC method was
   und to be inappropriate f6r testing of the 3M units due to a pulsed chamber exhaust  flow.
 we» u°n profiles generated with the direct interface/GC and Tedlar bag/GC methods compared
  «i though at a facility with cat/ox control unit and uninterrupted sterilization chamber exhaust
 teA •  Et°  was  sh°wn to be  stable in stack gas matrices for up to 18 hours.  A  calculation
 the T ?C for estimating the mass of EtO delivered to the control unit was evaluated.  The bias of
    'edlar bag/GC procedure at the control unit outlet was approximated.
 for  ^^ * ^ently proposing to conduct EtO compliance tests using the estimation technique
   control unit inlet mass and integrated Tedlar bag sampling for the outlet.

 INTRODUCTION
     An "Ethylene Oxide Airborne Toxic Control Measure (ATCM) for Sterilizers and Aerators"
 oftld°pted ty CARS (17 CCR, Section 93108) on May 22, 1991.  The ATCM requires control
 ft,  ^lene oxide (EtO) emissions based on annual usage.  The "control efficiency" is defined as
 bv rK*ne oxide mass or concentration reduction efficiency across a control device as determined
 * CB Test Method 431 (Title  17, CCR, Section 94143, adopted September 12, 1989).  The
      efficiency is expressed as a percentage calculated across the control device using equation
  quation 1.   __ EEtO in - EEtO out x 100 = % Control Efficiency
                      EEtOin

P   California Air Resources Board (CARB) Method 431, "Determination of Ethylene Oxide
^ssions from Stationary Sources", was based on work done by Radian Corporation for the United
2S?n*r°nmentalPro^
*tethod Evaluation for Ethylene Oxide Emissions and Control Unit Efficiency Determinations .
Off ^ibQA is applicable to the determination of EtO emissions from sterilization chambers m
Pounds per sterilization cycle. The method requires direct interface GC/FID momtonng of EtO
 aussions.  Thg  ATCM requires that the inlet and outlet of the control device be sampled
    Itaneously during testing to measure the control efficiency.  Volumetric flow of vented gas is
   nored and total EtO emissions are calculated  for the sterilization cycle using curves of flow
   concentration determined over time.
     CARB staff has conducted field tests at several hospital sterilizers to further evaluate Method
                                        877

-------
431. The results indicate that Method 431 may not be the roost appropriate method for compliance
testing purposes. Several primary issues have been identified, as follows:
      •  The sampling frequency possible with the on-site GC method may not be sufficient to
         properly define the sterilizer chamber emission profiles of some EtO control equipment
         configurations.
      •  The  on-site,  direct  GC method  is relatively expensive  and difficult (compared to
         container sampling methods) to perform under field conditions.
      •  The high concentrations of EtO found at the control unit inlet may present a health and
         hazard risk to test personnel.
     CARB staff are now considering modifications to Method 431 and the ATCM to address
these  issues. A Tedlar bag sampling/GC analysis procedure has been evaluated  for compliance
testing purposes. The results of field comparisons between the direct GC and Tedlar bag methods
are presented here.  Stability of EtO in emission matrices in Tedlar bags and bias and precision
of the bag procedure are discussed. A technique to estimate the inlet mass (calculated chamber
charge) is also discussed.

FIELD EVALUATION TESTS
     CARB staff conducted field tests in November, 1991 and March,  1992  at hospitals with
sterilization systems equipped with cat/ox control units.  A 3M sterilization system (4.8 cubic foot
chamber, Donaldson 50 scfm EtO-Abator, 100% EtO sterilam) was tested in November and an
AMSCO unit (24 cubic foot chamber, Donaldson 100 scfm EtO Abater,  12/88 EtO/freon-12
sterilant) was tested in March.  In both cases the primary project goals were to:
      •  Compare  the emission  profiles generated with Method 431 to  the  emission profile5
         generated with 'grab' bag sampling (consecutive, integrated 2 minute bag samples). The
         comparison was designed to investigate a possible lack of profile definition (insufficient
         sample frequency) using Method 431.
      •  Compare the total mass of EtO emitted from the chamber as measured with integrated
         bags at the control unit inlet to the expected or calculated charge.
      •  Document the stability  of EtO  in stack gas matrices in Tedlar bags under  field
         conditions.
      •  Demonstrate the validity of an integrated bag sampling method using procedures outlined
         in EPA Method 301.                                        **
     A private consultant  firm, Chips Environmental Consultants,  performed the Method 431
compliance tests at the hospitals while CARB staff simultaneously performed the bag sampling/GC
analyses.

DISCUSSION
     Mdhod 431 Proftk vs. 'Grab' Tedl.r  R.f p^fr,  The results of Method 431 and grab (2
minute) Tedlar bag testing at the inlet [outlet results were below the  limit of quantitation (LOQ)J
of the 3M unit (November, 1991 test) are shown in Figure 1. The sterilizer chamber exhaust flo*
on the 3M  unit was microprocessor controlled to create a pulsed flow to the control unit  The
chamber  flow was repetitively  pulsed "on" for 5.66 seconds and 'off  for 3.73 seconds for the &**
16 minutes of the first evacuation.  After 16 minutes, a restricted, constant flow was maintained
until the  end of the first evacuation (approximately 20 minutes).  The wash cycle involved »"
"unrestricted" flow of air through the chamber to the control unit for approximately 30 minutes-
The sterilizer chamber exhaust was diluted to  approximately  60 scfm with ambient air before
passing through the  catalytic bed
     Figure 1 shows a great  fluctuation in EtO concentration at  the inlet, as  measured
Method 431, during the first 16 minutes of the first evacuation. The Method 431 GC

-------
frequency of approximately 2 minutes) was sampling at random during "on" flow periods, i,e. high
Concentrations, and "off flow periods, i.e. concentrations declining to zero. After 16 minutes the
Method 431 data show a more consistent decline in concentration through the end of the first
evacuation and on through the chamber wasbf due to the constant flow from the chamber
     Figure 1 shows a gradual decline in EtO concentration at the inlet, as measured with the grab
(2 minute) bag samples, for the first 16 minutes, followed by an increase, due to the increased
chamber flow until the end of the first evacuation (grab bags were not taken during the wash). The
bafi samples were integrated over the 2 minute sampling intervals and so, in effect, averaged the
on/off puked flow/concentrations delivered to the control unit from the chamber.  Tedlar bag
samples integrated over the entire first evacuation produced results that were close (6% relative
Difference) to the average of the grab bag samples. It can be concluded, based on the emission
Profile comparison, that Method 431 is not appropriate for compliance testing of this type of
sterilization system, due to the pulsed chamber exhaust flows.                        A^c™
   .  The results of Method 431 and grab (3 minute) Tedlar bag testing at the inlet of the AMSCO
*°* (March, 1992 test) are shown in Figure 2.  Only results of the first evacuation are shown in
figure 2. The chamber exhaust flow was restricted (e.g. critical orifice) for approximately the first
« minutes  and unrestricted  for the  remainder of the first evacuation.  The sterilizer chamber
exhaust was diluted to approximately 150 scfm with ambient air before passing through the calalytic
Dea- The Method 431 sampling frequency was approximately every 3 minutes.
l   .  Rgure 2 shows good comparability between Method 431 and the bag samphngat the-control
2"  inlet  The measured amounts of  EtO  (first evacuation only) and  relative  differences
Difference/average x 100) between the results  of the two methods are listed tn Table 1.

   Table 1,   Measured amounts of EtO for the March, 1992 test
             at the control unit inlet and outlet, first evacuation.

             Measured Amounts of EtO (pounds)    _
Inlet
jvLccnoa 43 1
,088
.001
ieCl'*r riaft«
.097
.001
9.8%
0%
   The results of Method 431 and bag sampling at the control unit outlet also showed good
separability.  TheVe resulte at^ast indicate that Method 431 and the Tedlar bag procedure
Produce "equivalent" results for testing of catalytic oxidation control units where flow from the
        chamber is uninterrupted.
             rhfln.h»r rh.rp* vs. Amo™* ***»*«*« .t the Inlet. Actual testing at the control
             not be necessary since the amount of EtO charged to the sterilization chamber can
Jj accurately calculated (from weight loss in the charging cylinder, from flow measurements from
«* charging cylinder, or from chamber pressure/volume relationships). This estimation procedure
*««mes that there is no loss of EtO to the chamber, chamber contents, transfer plumbing or pumps
^a that there are no significant leaks before the control unit.
c,  Curing each of fou Aterilization cycles, for the November 1991 test an empty chamber -WM
  ar   with 100 grains of EtO from a disposable cartridge. The "soak" cycle was uitentionally
       approximatelyS minutes after the charge, after which the chamber went direcuy into  he
       s^ge.  ReS ™  Tab]e 2, the amount of EtO measured at the  inlet, with integrated
    • Wed from 69 to 83 grams (Gr7t evacuation only).  No Tedlar bag samples were  aken dunng
   Post evacuation washef during this test. However,  Method 431 results are available for the
                                         879

-------
wash stages associated'with these four cycles.  The chamber exhaust flow was uninterrupted during
the wash and so the Method 431 results (for the wash) should be accurate. The values for total
mass of EtO measured at the inlet were obtained by summing the integrated bag result for the first
evacuation and the Method 431 result for the wash. The total amount measured at the inlet ranged
from 82 to 100 grams.  Thus the bias between estimated amount and measured amount ranged
from -18% to 0% with an average bias of -7.5%.

      Table 2. Total amount  (grams) of EtO measured at the control unit
              inlet, for four cycles during the November 1991 test.

                    First
      -Qick	Evacuation	Wash	Total	Bias
         1          79.7             15.2          94.9        -5.1%
         2          83-1             17.1         100.2       +0.2%
         3          69.0             12.7          81.7       -18.3%
         4          78.4             14.9          93.3         -6.7%

     During the March 1992 test, a loaded chamber was charged with 1.5 pounds (as determined
by chamber pressure/volume relationships) of EtO from a cylinder. The "soak" cycle was run as
normal (1 hr. and 45 minutes), after which the chamber went into the exhaust stage.  The cycle was
run  normally (loaded chamber and full soak  cycle) to  conform with  compliance  testing
requirements. The amount of EtO measured at the inlet, with integrated bags, was 1.21 pounds
for the first evacuation and .44 pounds for the post-evacuation wash for a total of 1.65 P°u°^
delivered to the control unit. The bias between measured and expected was  + 9.3%. The AMSCU
systems are designed such that sterilant gas may be added to the chamber during the soak cycle
to maintain a constant chamber pressure. The amount of "make-up" sterilant gas added can no
be estimated by the pressure/volume calculation.  Thus, slightly more than 1.5 pounds of EtO may
have actually been introduced to the chamber. This problem would be minimized by testing of an
empty chamber with a "shortened" soak cycle.
     The results of these tests indicate that the estimation technique provides  a reasonable
approximation of the amount  of EtO delivered during both the first evacuation and wash to tne
control unit.
under
used
     Stability of EtO in Tedlar hflg«  The stability of EtO in emission matrices in Tedlar bags
  der field conditions was investigated. The Tedlar bags were manufactured by GARB staff an«
  ed Mininert* Teflon fittings. Stability of EtO in other bag configurations (e.g., with stainless steei
quick connect fittings) has not been tested.
     Two bag samples (one each inlet and outlet) collected during the November 1991 test were
analyzed at several time intervals up to 53 hours. The level of EtO in the inlet bag was 1631 pp/n*
at .9 hours and dropped 7% to 1517 ppmv over the 53 hours.  The level of EtO in the *»tfe* "^
was .15 ppmv (this concentration was < LOQ but > than LOD) at .9 hours and dropped 209& t°
.12 ppmv over the 53 hours.  Note that this facility used 100% EtO as the sterilant gas.
     Two bag samples (one each inlet and outlet) collected during the March 1992 test were ais
analyzed at several time intervals to check for loss of EtO. The level of EtO in the inlet bag *as
293 ppmv  at 3.3 hours and was 302 ppmv at 28 hours (i.e., no loss). The level of EtO in the outiei
bag was 1.8 ppmv at 3.3 hours and had dropped 6% to 1.7 ppmv over 18 hours and 179* to iJ
ppmv over 28 hours. Note that this facility used 12/88 EtO/freon-12 as the  sterilant mixture.
GARB staff has not conducted stability studies for EtO in dilute-acid hydrolytic scrubber emissi
A report prepared by Coast to Coast Analytical Services, Inc.2 for the CARB suggested that
                                           880

-------
«usts in emissions from hydrolytic scrubber units might cause decomposition of EtO in whole air
samples. The report also suggests that a sodium bicarbonate cartridge can be used to strip acid
     from sample streams without affecting the EtO.
    lias and PnvKk>n of fhe Terilar Bag Method. For *^ pm^ rfjto^tl^ J* V^%
of the integrated bag sampling approach, a procedure outlined ia USEPA Method 301,  Field
Validation of Emission Concentrations from Stationary Sources", was followed. Tests to determine
    bias and precision  of bae sampling at  the control  unit outlet (low concentration) were
conducted.
     ce.
A    Analyte spiking (option 5.3 of Method 301), or the method of standard addition, was used to
determine bias of the integrated bag sampling at the outlet of the catalytic oxidation control unit
during the November 1991 test  The testing involved quadruplet, collocated samples collected
during six replicate cycles  Two of the four samples from each run were spiked with a known
Amount of EtO (approximately 2.5 ppmv).  The spiking involved metering a know  volume of
standard gas into the bag sample (e.g., after stack sampling).  The bias for the spiked samples
rz»nged from -17% to + 10% with an average of -2,2%.
.   ,  The precision (as in section 6.3,6 of Method 301) of the unspfod ouUeJ samples could I not
£ determined for the above test because the concentration of EtO m aU outlet samples was be low
he LOQ. The precision  of bag sampling of high levels (control unit inlet) may be W™"^
"% though. This precision wal approximated as 2 x RSD from the ^eraged integrated bag e u  s
« 8 replicate cycles(e.g., average of 8 bags, 1 each for 8 cycles). Note that the variability of ^results
from multipie ^cles\includes *rocess variability) is probably greater than that ^of col located rut*
of a  single  cycle.  Also,  the variability of bag sampling of low EtO concentrations  (outlet) is
Probably greater than that for high levels (inlet).

CONCLUSIONS                                                           .        ,-fi
     Based on the information obtained from field testing, CARB staff are proposing to modify
     od 431.  The estimation technique will be recommended for determination of contro Urn
    mass loading. The integrated Tedlar bag sampling procedure will be used at Oe control umt
     with  moniforing of both the first evacuation and wash stages.  CA^.staf^^n^
     ing a maximum bag sample hold time (before analysis) of 8 hours.  This proposed CARB
       would then be consistent with an EPA draft method  for EtO compliance testing.
ACKNOWLEDGMENT
. .    CARB staff would like to thank Mr. Mark Chips, of Chip's Environmental Consultants, for
** cooperation and significant contributions to the field portions of this project.
          APHY
  L  J-  Steger and  W. Gergen, -«-ii *T"* • Sampling Analytical M^hod EvaMon for
     £thvlene n^H. pm-...-Sn. »nd Cor^ TTnit Rffidenrv Determinations, EPA - 68-02-4119,
     Radian Corporation, Research Triangle Park,  1988.

  2-  S.C. Havlicek, L.R. Hilpert, D. Pierotti, G, Dai, Diyft Final Rgmrr -
     Qjdde r^n%nt^± TnTFrni^ions *n™ Rt.riliMtion f ^ ^mip.t
            ^nnt        nrn                                    Processes, Coast-to-
           Analytical Services, Inc., San Luis Obispo, CA, 1992.
                                         881

-------
2500
                  Figure 1
     Ethylene Oxide at Inlet, Nov. 91 Test
    ppmv
   0     5     10    15    20    25   30   35

                    minutes
     — 2 minute Tedlar bags •+• CARB Method 431
600
500
                   Figure 2
    Ethylene Oxide at Inlet, March 92 Test
   ppmv
       5    10    15   20   25    30   35   40

                    minutes
     — 3 minute Tedlar Bags -*-CARB Method 431
                     882

-------
                                                                    total non-
  THE  EVALUATION  OF  THE  CONCENTRATION  OF
  SEMIVOLATILE  HYDROCARBONS   (IN  THE  C12-C18
      RANGE)  EMITTED  FROM  MOTOR  VEHICLES


        Barbara Zielinska, Desert Research Institute, P.O. Box 60220, Reno, NV
  K<*hy K. Fung, AtmAA, Inc., 21354 Nordhoff Street, Suite 113, Chatsworth, CA 913U


ABSTRACT                                                         „    .
      Sampling  was earned  out in the Caldecort Tunnel, located  in  the San Francisco
(California) area.  Three daily samples were collected, using stainless steel canisters and" Tenax-
TA solid adsorbent cartridges, over two days in June 1991. The samples were analyzed using
high resolution gas chromatographic separation and Fourier transform infrared/mass sP^m
detection (GC/IRD/MSD) or flame ionization detection (FID) of individual hydrocarbons
comparison of hydrocarbon  concentrations found in the  Tenax and canister samples and
assessment of the contribution of semivolatile hydrocarbons (CI2-C18 range) to total
*cOvane hydrocarbons (C2-C11), as measured by the canister method, is presented.

INTRODUCTION
      Hydrocarbons,  which are emitted from many naturally occurring and > •
      t are important contributors to the formation of ozone and organic aerosds. They ^exhibit
      range of volatility and are hence distributed in the atmosphere between the &*  and
       Phases,  U has Ln shown for ambient a* samples collected in a heavdy ^ed
     ain tunnel that n-alkanes up to C26 could be delected '»*>£^3^V™KZ
      1982s; I98n  In me same study, the n-altar* *nes bec«ne detec tabk *£l4in to
     » Phase. Thui in some airsheds a hydrocarbon fraction existog m Ae p» phue caaW be
   tti for hyd^aroT r^ flTci2 to CIS (or  higher), i^dto I—
hydrocarbons (SVHC1 Since eas-phase hydrocarboDS contribute to ozone and organ* a
""nation. ft S^^^KS. ^hVW^ * SVHC  and » esmnaie
owWwtai to total gas-pnase hydiocarbons. However, the commonly used earner
"fcftods  for total non-methane hydrocarbon (NMHQ  measurements and for hy
'Peciations (tomte USEPA Methods TO-12 and TO-14) do not accoum for SVHC.
Q™«*y, only aS nation of the C9 to C12 compounds have been idendfied and  few
^ts have been madeTextend EPA Method TO14 to analysis of 8«-ph^^o^bons
^ond C12,  This study attempted to determine the composition and concentrations of semi-
?^ hy ?^h ^"^
     SdSfi areas of Contra Costa and Alameda Counties, ft is a three-bore tunnel
        per bore. The center bom is altered in either direction^ which
       date peak-hour  traffic westbound in the morning and four
       Its length is approximately 3.600 ft from portal to portal, and in
^Sc through the tunnel was -110,000 vehicles per day. The tunnel has a -4*
***** tSfic rSg ujhi0. The sampling site was located in the «*JJ
    e easfcound bore.
                                                                     wrth
                 .
***** of June (June 26-28), 199L Three daily samples
12«>. and 16XJO-1800, over a two-day period (Wednesday, J
                                              June 26,
                                    883

-------
Volatile hydrocarbons, in the range of C2 through C12, were collected using the stainless steel
canister sampling method Semi-volatile hydrocarbons, in the range of C8-C18, were collected
using Tenax-TA solid adsorbent The canister and Tenax samplers were located side by side in
the exhaust duct directly over  the eastbound tube of the  tunnel, with  Teflon sampling lines
extended from the samplers through the ceiling louvers into the tunnel area. The Volatile Organic
Toxic Air (VOTA) collection system (General Metal Works. Inc.,) was used for Tenax sample
collection. The sampling unit drew four parallel streams of air at -0.35 L/min per stream.  Each
stream was fitted with two tandem  Tenax cartridges (front and back-up Tenax, in order to
evaluate breakthrough effect). Two Tenax tandem cartridges collected samples from filtered air,
the remaining two streams were  not filtered fin order to evaluate the contribution of hydrocarbons
>C14 present in the particle phase).  Filtering was accomplished by locating a Teflon-coated
glass-fiber (TIGF) filter upstream of the cartridge.  Prior to use, Tenax-TA solid adsorbent was
cleaned by Soxhlet extraction and thermally conditioned for four hours by  heating at 280  C
under nitrogen purge.  Approximately 10% of the precleaned Tenax cartridges were KSU^^.
GC/FID for purity prior to sampling.  After sampling, the Tenax cartridges were placed in capped
glass test tubes and placed on ice until transported to a laboratory freezer.
       Stainless steel  Summa-polished canisters of 6  L capacity were employed for volatile
hydrocarbon  (C2-C12) collection. Prior to  sampling,  the canisters were cleaned by repeated
evacuation and pressurization with humidified zero air, and certified as described by U.S. EPA
Methods TO-12 and TO-14.   The  sampling procedure essentially  followed the pressurized
sampling method described  by  EPA Methods TO-12 and TO-14.

       Analysis.  Tenax  samples   were analyzed  by  the  thermal desorption-cryogente.
preconcentration method, followed by high resolution gas chromatographic separation and Foune
transform infrared/mass spcctromctric detection (GQTRD/MSD; Hewlett Packard 5890 H GC with
5979 MSD and 59658 IRD) or flame ionization detection (FID) of individual hydrocarbons.  The
Chrompack Thermal Desocption-Cold Trap Injection CTCT) unit, which can be attached to either
the GC/FID  or the GC/IRD/MSD  system, was  used for  sample desorption and cryogenic
preconcentration.  A 60 m (0.32 id, 0.25 urn  film thickness) DB-1 capillary column  (J«w
Scientific.. Inc) was used and the chromatographic conditions were as follows: initial column
temperature 30 °C for two minutes followed by programming at 6 "Cfymn to a final temperature
of 290 °C and held isothermal for five minutes. One tandem of Tenax cartridges (front and back-
up Tenax), from each sampling  period and sampling location was analyzed by the GC/IRD/MSD
technique in order to identify individual hydrocarbons. Identification of individual components
was made based on their retention times and  mass and infrared spectra  matching  those of
authentic standards. If authentic standards were not available, the National Institute of Standards
and Technology (NIST) mass spectral library (containing over 43.000 mass spectra) and the U.S.
EPA infrared spectra library were used for compound identification.  The quantificationot
hydrocarbons collected on  all  remaining Tenax cartridges was accomplished by the GC/FIU
technique. For calibration of the GC/FID. a set of standard Tenax cartridges was prepared by
 spiking the cartridges with  a methanol solution of standard SVHG  High-purity commercially
 available  C9-C18  aliphatic and aromatic hydrocarbons (AUtech) were employed  for systern
calibrations.  Ethy(benzene, 13.5-trirnethylbenzene, n-dodecane, and n-tetradecane were used m
 the concentration range from -7-8 ng/Tenax up to 200-300 ng/Tenax.  The solvent was then
 removed with a stream of  N,  and the Tenax cartridges were thermally desorbed into the
 system, as described above.  At least four concentrations of standard compounds were cro?10
 Area response factors per nanognun of compound were calculated for each concentration
each hydrocarbon and then the response factors were averaged to give one factor for H*
 hvdrocarbons measured.
        The stainless steel canister samples were analyzed for volatile (< C12) hydrocarbons using
 high resolution capillary gas chromatography with flame ionization detector (GC/FID)
                                          8*4

-------
cryogenic  sample concentration, following the U.S, EPA  Method  TO-14.  The modified
Chrompack Purge and Trap Injector (PTJ) was used as a cryogenic trapping unit (the TCT unit
used for Tenax cartridges is a part of this PTI unit and the switehing between the two different
n*thods of operation can be done in a matter of minutes). The piece of capillary column serving
as a cold trap (approximately 30 cm long, 0.52 cm W.) can be easily replaced  A deactivated
fused silica capillary tubing packed with glass wool was used as a cold trap for analysis of C4-
C12 hydrocarbons. Since this trap does not retain C2 and C3 hydrocarbons quantitavely. a piece
of PoraPLOT Q capillary column (Chrompack) was used as a cold nap for analysis of these light
hydrocarbons.  Stainless steel canister samples were analyzed by GC/FID system only. A 50 m
<°-32 id, 1.2 pm film thickness) CP-Sil 5 CB (Chrompack) capillary column was used  and the
chromatographic conditions were as follows:  initial column temperature -30 C held tor two
^nutes followed by programming at 6 °C/rnin to 220 CC and at 10 °C/min to a final temperature
of 260 «c and held isothermal for five minutes.  Calibration  was performed using Standard
Reference Material 1805, i.e., 254 ppb benzene in air, purchased from NIST.  Ultra-high punty
80 was mixed with SRM 1805 in the calibration system in an appropriate proportion to obtain
**»*» concentrations in the range of 5-200 ppbC.  Measured volumes of this diluted standard
w*e then injected into the system (at least three points and humidified zero air) and an average
     response factor for 1  ppbC of benzene was calculated.  This response factor was then
         for calculating the concentrations of all C2-C12 hydrocarbons detected.
      HYdrbnfi.  As mentioned above, one tandem of Tenax cartridges (a fiont
JWrttfand a back-up cartridge) from each sampling period and sampling location was analyzed
^ the GCARD/MSD technique in order to identify individual hydrocarbons.  The oiher  two
£nax tandem cartridges (one collecting filtered and one unfiltered a*) ^.j££***"
GC/FK> technique in order to quantify individual hydrocarbons. Since no significant difference
was observed between  the filtered and unfiliered Tenax samples, these pairs jare treated as
collocated samples. The analysis of back-up cartridge* indicaied no sign rffcant ^^>^f
«hylbenzene  (CS-aromadc with the lowest retention time) rt^i^W*™*"*
H°w«ver,  the concentrations of toluene and n-octaw on  the back-up Tenax were usually
significant Thus, ethylbenzene is the first hydrocarbon for which a concentration is reported.
      Theidenti^cauonoftnc^^
*** comparison of mass spectra and infrared Or) spectra with those ^^^""JJ*
Jj*ea available) or with masTand ir spectra libraries.  Figure  1 shows GQFTO traces for the
T«|ax sampjes iuect^inTcaldeco^Tunnel on June 27,  1600-1800 »••££»«
^•vidual species in the canister samples was based on the companson of the hn
J"» indices (RI) calculated from the chromatographic data, *~j^*V" *
^tz (1963)', with those of authentic standards as well as with data available m the
.     Appr^v ^40 compounds  «. the range of <^ V~n'S^"cS£
^Ples and 67 compiunds (in uVrange of C8-C18) in Tenax •^tt^**f£2Sl
J"nnel.  The conceptions and identification of all these compounds are presented elsewhere
Welinska and Fung, 19924),

 L     Corrmiiri^n of ran»^ *«A Tsnax Data.  Since it is not practically possible to compare
j! ^^tottion  of eve^ compound quantified in the Tenax and "^•"J^SS
*P«antative compoundTwere  selected to check the agreement between ihesc two «^«
^PHng and ana^TIhe selected compounds had to be «^^ab±ti^^c^



                              -^
                                         885

-------
1,2,4-trimethylbenzene and naphthalene.
       Table 1 shows the ratios of concentrations of selected compounds found in Tenax and
canister samples collected in the Caldecott Tunnel. In general, the agreement found between these
two methods of sampling and analysis is very good.  The overall precision of measurements,
calculated for duplicate canister and Tenax samples, was 4% and 10%, respectively.
Table I.  Ratios of concentrations of selected compounds found in Tenax and canister samples collected in the
Caktecon Tunnel, CA (Tenax/canister).
Compound
6/26
1600-
1800

0600-
0800
6/27
1000-
1200
6/28
1600-
1800
0600-
0800
1000-
1200
Mean
±SD
Ethylbenzene       0.90     0.93      0.91     0.98        0.87      0.85      0.91 ±  0.05
m-&p-Xylene     0.88     0.94      0.92     0.97        0.82      0.88      0.90 ±  0.05
o-Xylenc          0.93     0.67      0.76     0.77        0.68      0.88      0.78 ±  0.10
n-Propylbenzene    0.90     1.11      1.33     1.26        1.19      0.83      1.10 ±  0.20
  1,2,4-
Trimethylbenzene   1.24     1.34      1.27     1.29        1.20      1.11      1.24 ±  007
Naphthalene       1.78     1.02      1.48     1.64        1.04      1.05      1.33 ±  0.34
The Assessment of the SVHC Contributions to the Total Gas-Phase NMHC.  Since naphthalene
(which elutes just before n-dodecane from the nonpolar capillary columns, such as DB-1) was
the last compound quantified from our canister samples, for the assessment of the contribution
of the SVHC to TNMHC it was  assumed that  die  SVHC  range  starts with  the aliphatic
compounds having carbon number C12 and includes some Cl 1 aromatic compounds.  In other
words, for comparison purposes, the C2-C18 hydrocarbon range was divided into two groups:
1) the volatile TNMHC group, from C2 up to Cll, including naphthalene (the first polycyclic
aromatic hydrocarbon), which can be quantified from the canister samples; and 2) the SVHC
group, starting from C12 (but including some Cll aromatic compounds), which was quantified
only from Tenax samples.  Table 2 shows the assessment of the contribution  of SVHC to
TNMHC, done as described above, for the Caldecott Tunnel.
       As can be seen from this table, the percent contribution of SVHC to TNMHC ranges from
1-1.4%.  However, if the hydrocarbons are quantified only up to CIO or even C9  from canister
samples, the percent contribution of SVHC, defined as compounds in  the range of CIO to CIS,
will be  considerably higher.   Also,  the light-duty gasoline vehicles are  the  main  traffic
components in the Caldecott Tunnel, and the heavy-duty diesel trucks, which are presumably the
main  source of SVHC, are largely absent in the tunnel.  In addition, it  has to be pointed out that
a contribution of 1.0-1.4% as measured in the samples collected in the Caldecott Tunnel,
corresponds to approximately 20-50 ppbC (2-4 ppb). 1- and 2-Methylnaphthalene concentrations
account  for at least 50%  of the total SVHC concentration  range,  and other aromatic C6-
substituted benzene isomers and C2-substituted 1,2-dihydroindene isomers are relatively abundant
in this SVHC concentration range, as compared to saturated  aliphatic hydrocarbons.  These
aromatic and polycyclic aromatic hydrocarbons are precursors of nitro-derivatives formed from
the atmospheric transformations (reaction with OH radicals in the presence of NOx and with
      in ambient air (see, for example, Zielinska et al., 1989s;  Atkinson et al.,  1987*;
                                          886

-------
 Table II.  Assessment of the SVHC (C12-CI8, Tenax) contribution to the TNMHC (C2-C1 l.canisters) in Caldecott
 Tunnel, CA (ppbC).
Method
6/26
1600-
1800

0600-
0800
6/27
1000-
1200
6/28
1600-
1800
0600-
0800
1000-
1200
      C, Canister (C2-C11,
   including naphthalene)       2520      1950      3100     3380     1620    2065
      Tenax (C12-C18.
   excluding naphthalene)       29.6       19.2       33.5      46.7      22.0    22.6

   Contribution                 1.2        1.0        1.1       1-4       1-4     1-1
 ^y « al., 19897).   Many of these nitro-derivatives are potent mutagens  and/or suspected
 carcinogens,

 CONCLUSIONS
       The total concentration of SVHC in the range of C12-C18, emitted from motor vehicles,
 "fcges from -20-50 ppbC (2-4 ppb), as measured in the Caldecott Tunnel in California.  The
 ^ato compone
 and C2-substitu
 which could be

 REFERENCES
 1; C.V. Hampton, W.R. Pierson, T.M. Harvey, W.S. Updegrove, and R.S. Marano. "Hydrocarbon
 ^•ases Emitted from Vehicles  on  the  Road,   1.   A Qualitative Gas Chromatography/Mass
 Spectrometry Survey."  Rnvimn. $ci. Technol.. 16, 287,1982.
 *; C.V. Hampton. W.R. Pierson, T.M. Harvey, and D. Schuetzle.  "Hydrocarbon Gases Emitted
 J>m Vehicles on the Road. 2. Determination of Emission Rales from Diesel and Spark-Ignidon
 Vehicles." Environ. Sci. Technol. 17, 699-708, 1983.
 * H. Van Den Dool and P.O. Kratz. "A Generalization of the Retention Index System Including
J^«ar Temperature  Programmed  Gas-Liquid  Partition  Chromatography."    Jpurnal  pf
^^"""ItogrqpliYi H» 463-471, 1962.
J; B. Zielinska and K. Fung. " Composition and Concentrations of Semi-Volatile Hudrocarbons"
 J">al Report for the California Air Resources Board, Sacramento, CA, 1992.
 * B- Zielinska, J. Arey R Atkinson, and P.A. McElroy.  "Formation of Methylnitronaphthalenes
JP1" the Gas-Phase Reactions of 1- and 2-MethylnaphthaIene with OH Radicals and N,OS and
Jheir Occurrence in Ambient Air." Brirn Sd. Technol.. 23,  723-729, 1989.
Jl «• Atkinson, J. Arey, B. Zielinska, and S.M. Aschmann.  "Kinetics and Producu of the Gas-
Phase Reactions of OH Radicals and NA with Naphthalene and Biphenyl.  Environ. Scu
         21 1014-1021 1987
          B'. Zielinska,k. Atkinson,andS.M. Aschmann./Nitroarene*£»*£?"*<*;
                                                                      ical and NA-
              KUUMUI, i\.. nuuuw", >»••«• — •--—	         • t I.  r«J
     	u«,,s of Volatile Polycyclic Aromatic Hydrocarbons with the OH
^SU^Cjjgm. Kinetic*. 21, 775-799, 1989.
                                        887

-------
                    10
 20
Minutes
30
40
Figure 1.     GC/FID traces of Tentx stmpk collected in (he Cakkcott Tunnel on 6/27/91.
             1600-1800 hours.   Peak identities:  (1) ethylbenzene, (2) m- & p-xylene. (7)
             o-xylene,  (14)  m-ethyltoluene,  (21) 12.4-crimethylbenzene,  (22)  n-decanc,
             (23) 1,2,3-trimeihylbenzene, (24) C4-beniene + artifact peak, (25) C4-benzcne,
             (29)  Ethyldimethylbenzene,  (30)   Tetramethylbenzene,  (31)  n-undecane,
             (32) 1.2,4.5-tetramethylbenzene,   (33)    1 ^,3,5-tetramethylbenzene,   (34)
             2,3 dihydromethyundene. (47) naphthalene. (49) n-dodecane, (51 and 52)  2,3
             dlhydrodimethylindenes, (56) 2-methybaphthakne, (57) 1 -methy(naphthalene, (59)
             biphenyl.  (60 and 62) dimethylnaphthaknes,  (63) n-pentadecane, and (64) n-
             hexadecane.

-------
        MOISTURE MANAGEMENT TECHNIQUES APPLICABLE TO
           WHOLE AIR SAMPLES ANALYZED BY METHOD TO-14
          Uny D. Ogle, David A, Brymer, Christopher J. Jones and Pat A. Nahas
                               Radian Corporation
                              8501 North Mopac Blvd.
                                 P.O. Box 201088
                             Austin, Texas 78720-1088
 ^    Analysis of polar organic compounds collected in canisters using US EPA Compendium
 Method TO-14 is of interest to a number of industries and agencies. However, it is commonly
 3*r> that moisture in the sample can interfere with the analysis. Most methods used to remove
 **<« also remove the light polar compounds.  This paper will describe a method developed^
 ^uce the amount of water delivered to the analytical system after cryogenic concentration. The
 *;thod has been determined to improve compound retention time stability, increase a^tical
 Pjeci«Qn, and give more reproducible recoveries of polar and non-polar compounds independent
  sample relative humidity.
         CTION
duri  Cryogenic concentration, and thermal desorption of water fo achr^


^^S^^^^^^^f^
  « "K                                     n dtt«ior or HC«d tte ***** '•
                                                      and sorbMB ray be used to

                                     889

-------
concentration. The temperature of the device is regulated by an 80 W cartridge heater controlled
by an Omega temperature controller.
      The system is configured such that the sample flows through the MMS during concentration.
During thermal desorption, the chromatographic carrier gas flow backflushes the traps and transfers
the desorbed organics and water vapor through the MMS. Thermal desorption of the cryotraps at
600°/minute supersaturates the helium gas with water vapor which then condenses in the cool MMS
region. Through the manipulation of temperature, desorption time and system configuration, the
amount of water removed and the recoveries of organic compounds of interest can be maximized.
      Table I shows the parameters chosen for the statistical analysis of the MMS.  As can be
observed, a complex study design was chosen to determine the effects of the MMS temperature on
compound recovery and precision. The study design also determined the effects of variables such
as canister size, relative humidity in the canister, concentration of the analytes, different mixtures
of compounds, and the manifold position on the automated interface on precision and accuracy.
The  experimental matrix was designed to evaluate treatment combinations in such a manner to
determine the main effects and interactions of greatest  interest. A randomized scheme was used
to assign treatment combinations to  the experimental units.
      Each canister was analyzed four times over a period of five days with  the MMS at 130°C,
twice at  0°C and then  again at 130°C.  Between the second and  third analyses, canisters on
manifold positions I and 2 were switched with those on positions 8 and 7, respectively. All analyses
were by Flame lonization Detector.  Four determinations were lost due to a liquid nitrogen leak
exhausting the supply of liquid nitrogen during the analyses. This loss did not adversely effect the
outcome of the study.
      The results of this study led to a second study designed to maximize compound recoveries
and  minimize water transfer to the column through optimization of the operating temperature for
the  MMS and the cryotrap desorption time.  These variables were systematically changed and
compound recoveries  and reproducibilities were calculated.  The optimum conditions  were
determined  and seven replicate analyses of a standard  canister were made to establish precision
and  accuracy.

RESULTS AND DISCUSSION
       The results of the study outlined in Table I were analyzed using a SAS statistical program.
The following conclusions were drawn from this statistical analysis:  the valve position on the
manifold was not significant; recoveries of methanol, ethanol, isopropanol, and 1,4-dioxane were
affected when the MMS was at 0°C; the recoveries of hydrocarbons, halogenates, aromatics, ethers,
aldehydes and ketones were not affected; there were  no observed effects caused by compound
concentrations; recoveries of compounds not affected by the MMS were weakly, but significantly)
affected by compound mixture and relative humidity; the effects of the MMS on these compounds
was  less than the effects of mixture and humidity; and the residual effects after removing the effect8
of the tested parameters represented system, including hardware, variability and were less than one
percent at high concentrations and 4 to 5% at low concentrations.
       The recoveries  of the alcohols and 1,4-dioxane were depressed by the condensation of
moisture in the  MMS  at 0°C.  In addition, the quantitative results for  these compounds had a
higher degree of variability than the non-polar test compounds. The coefficients of variation for
the  four analyses ranged between 50% at high concentrations and 20% at low concentrations.
Coefficients of variation for the non-polar compounds (unaffected by the MMS) were around 19»
at high concentrations  and 5% at low concentrations.
       The conclusion that relative humidity and compound mixture have an affect on the results
was expected. Even though most of the moisture is removed by the MMS, the amount of moisture
representing saturation of the carrier gas at that particular temperature will be transferred to the
                                           890

-------
 column.  Since the injection time was six minutes and the MMS was slowly wanning from 0°C to
 around 25°C during  this time  due to  conductive  heating from the cryotrap, some water was
 transferred to the column which affected the chroraatography of all compounds in the retention
 window in which water eluted.  The weak significance of compound mixture verifies that there is
 some interaction between compounds during trapping and chromatography.  However, most of the
 interaction is thought to  be in the chromatography and subsequent integration of the peaks.
       A number of experiments were then performed to determine the optimum temperature for
 the MMS, since operation at 0°C affected the reproducibility of the polar organics (Study 2).  The
 optimum temperature was found to be 15°C with a six minute injection time. A standard canister
 of mixture 1 (Table I) at 70% relative humidity and polar compound concentrations between 3 and
 50 ppb was analyzed six times within one day. Table II provides a comparison of retention times
 and  recoveries determined for  a selected group of compounds on analytical systems with and
 without a MMS. Reproducibility data for Studies 1 and 2 are presented in Table HI.

 CONCLUSIONS
       The Moisture Management System is an effective tool for reducing the amount of water
 delivered to the column during analysis of VOCs. The operating parameters must be optimized,
 but under optimum conditions, the reproducibility and recovery of all organics is excellent* PPj>
 fcvek. Recoveries of heavier VOCs and a variety of compound classes are unaffected by the MMS.
 Compound mixture and relative humidity were determined in Study 1 to have small effects on the
 reproducibility of analyses.  Effects of system variability on VOC analyses  was  concentration
 dependent, but was measured at 1 to 5% in this study.
                                    REFERENCES
l-    J-D. Pleil, W.A. McClenny and K.D. Oliver, "Dealing with water in GC/MS analyses of
      whole air samples", presented at the  1989 Pittsburgh Conference  and Exposition on
      Analytical Chemistry and Applied Spectroscopy, Atlanta, GA, March, 1989.

Z    m Plei], K.D. Oliver and W.A. Mcdenny, "Enhanced performance of nafion dryers in
      removing water from air samplesprior to gas chromatograpm'c analysis*, J£E£A, 37:244-248,
      1987.

3>    LD.  Ogle, R,B.  White, DA Brymer and M.C.  Shepherd, "Applicability of GC/MS
      instrumentation for the analysis of undried air toxic samples",  Proceedings of the  1989
      EPA/APCA International Symposium on Measurement of Toxic and Related Air Pollutants,
      Research Triangle Park, NC, May, 1989, pp. 824-829.

4-    D.B. Cardin and C C Lin, "Analysis of selected polar and non-polar compounds in air using
      automated 2-dimensionaI chromatography", Proceedings of the 1991 US. EPA/A&WMA
      International Symposium on Measurement of Toxic and Related Air Pollutants, Research
      Triangle Park, NC, May, 1991, pp. 552-557.
                                         891

-------
S
                                                                          Table I
                                                          MMS Validation Experimental Design
Temp, of
MMS
0° and 130"C
Canister
Number
1
2
3
4
5
6
7
8
Canister
Size(L)
15
6
6
15
6
15
15
6
Component
Mixture*
1
1
1&2
1
1&2
1&2
1
1&2
Relative
Humidity (%)
70
70
70
10
70
10
10
10
Relative
Concentration"
High
Low
High
Low
Low
Low
High
High
Manifold
Positions
2-7
6
4
8-1
1-8
3
5
7-2
                  * Mixture 1 contains vinyl chloride, methanol, ethanol, acetone, diethyl ether, isopropanol, methylene chloride,
                  1,2-dichloroethane, benzene, cyctohexane, 1,4-dioxane, trichloroethylene, and toluene.

                  Mixture 2 contains propionaldehyde, 2^-dimetnyJbutane, 2-butanone,  2-pentanone, methyfoobutylketone, 1-octene,  1-nonene, p-
                  ctuorotoluene, 1-deccne, t-butylbenzene, and n-undecane.
                    High; Mixture 1: 57tol400ppbv
                    Low; Mixture 1:  1 to 28 ppbv
Mixture 2:  150 to 250 ppbv
Mixture 2:  3 to 5 ppbv

-------
                                                                            Table II
oo
s
                                                     Comparison of Retention Times and Recoveries for
                                                      Selected Compounds With and Without a MMS

COMPOUND
Vinyl chloride
Methanol
Ethanol
Acetone
Diethyl ether
Isopropanol
Methylene chloride
n-Hexane
1 ,2-DichIoroethane
Benzene
Cyctohexane
1,4-Dioxane
Trichtoroethylene
Toluene
WITHOUT MMS
Retention
Time
(min)a
9.07
11.03
13.76
14.18
15.3S
15.60
NA
NA
NA
22.35
22.73
NA
NA
26.72
R.T.
Std.
Dev.
0.076
0.43
0.21
0.96
0.13
0.10
NA
NA
NA
0.064
0.056
NA
NA
0.045
Recovery6
10% RH
135
88.8
73.5
125
77.0
65.4
125
NA
112
100
102

56.3*
NA
Recovery"
70% RH
119
289
177
145
115
102
116
NA
104
100
86.2
95e
12!
WITH MMS
Retention
Time
(min)c
8.22
10.09
12.94
13.35
14.88
14.66
NA
NA
NA
21.60
21.97
NA
NA
26.05
R.T.
Std.
Dev.
0.017
0.13
0.051
0.021
0.004
0.025
NA
NA
NA
0.012
0.058
NA
NA
0.024
Recovery1"
(15*C/70%
RH)
98.4
61.0
43.5
76.7
54.5d
85.6
103
98.6
100
90.3
36.1
96.0
98.3
                      •Represents 2 analyses each at 0, 50, 100 and 100+ percent RH
                      ''Normalized to Benzene
                      'Represents 3 analyses each at 30 and 70 percent RH
                      "Diethyl ether and isopropanol coeluttd during these determinations
                      Trichloroethylene and 1,4-dioxane coeluted during these determinations

-------
                                                  Table III
                      Reproducibility of Replicate Analyses Under Study 1 Conditions and
                           Optimum MMS Conditions for Low ppb Concentrations
Compound
Vinyl chloride
Methanol
Ethanol
Acetone
Diethyl ether
Isopropanol
Methylene chloride
1,2-Dichloroethane
Benzene
Cyclohexane
1,4-Dioxane
Trichloroethylene
Toluene
Relative Standard Deviations
Study 1 Conditions*
RH = 70%
5.8
14
13
6.2
1.0
4.0
11
5.1
2.8
18
18"
13
RH= 10%
6.4
30
24
10
2,8
22
15
6.3
3.4
11
10
1.5
Relative Standard Deviations
MMS at m*
1.1
3.1
4.0
1.6
2.6C
4.2
2.7
1.3
1.8
20
13
0.8
* Four replicates 5 days, MMS at 0°C for 2 runs and 130°C for 2 runs.
b Six replicates within the same day, RH = 70%
c Diethyl ether and Isopropanol summed due to incomplete separation
* 1,4-Dioxane and Trichloroethylenc summed due to incomplete separation.

-------
   A NOVEL APPROACH FOR GATHERING DATA ON
                   SOLVENT CLEANING
          M. A. Serageldin, J. C. Berry, and D. I. Salman
               U.S Environmental Protection Agency
            Research Triangle Park, North Carolina 27711
Presented  at  the 1992 EPA/ A&WMA International Symposium on,
 Measurement of Toxic and  Related Air Pollutants," May 3-8, 1992;
'Jmni Durham Convention Center, Durham, North Carolina
                            895

-------
ABSTRACT
Cleaning is done  in  industry for different purposes: to maintain
industrial equipment and work areas; to remove contaminants such as
dirt and process materials from the interior of process equipment;
and  to prepare  surfaces  before the  next  stage  in  a  process.
Cleaning tools and removable parts also require  cleaning.  As a
result of  these  activities  solvents  containing  volatile  organic
compounds  (VOCs)  are evaporated  into the atmosphere, contributing
to  the air  quality  problem.    A  number   of  solvents  used are
classified as hazardous air pollutants in Section  112 of  the  Clean
Air Act Amendments (CAAA).   The EPA selected the source category
of industrial  cleanup solvents for one  of the  control  technique
guidelines (CTG)  prescribed by the 1990 CAAA.

     The purpose of this paper is to discuss the methodology  being
adopted by EPA to determine accurate VOC emissions from  cleaning.
It is  founded  on  the concept of a "unit operation system  (UOS),"
which was developed to define the emission  streams that need  to be
considered for a material balance.  The focus, for the purpose of
the material balance, is the "unit operation" being  cleaned.


INTRODUCTION
This project was designed to develop guidance for States to  write
regulations that would reduce the VOC emissions from all industrial
uses of solvent for cleaning, except those  for which  a CTG  already
existed.   Further,  we were  to  quantify  the nationwide  emissions
from such solvent use and estimate the potential emission  reduction
and cost associated with any action we recommended.  The task, at
nrst,  seemed unmanageable  because of  the diverse reasons for
solvent cleaning.   imagine Boeing Corporation solvent cleaning a
747, a Durham newspaper washing spilled ink from the floor, and
Glaxo Incorporated (a pharmaceutical company) washing the  inside of
a reactor tank,  is there a common denominator?

«^r-,-ofter Paring the  enormity  of the  task  and a  few  false
starts,  we established an  innovative plan for collecting and
evaluating data from all manner of companies. We have implemented
this plan, and responses  have arrived from industry.   It is the
S??^iCJLUf«    H°  coilect  data  that is the  subject of this paper.
KPV Sii?Iii*  a desc/iPtion of the methodology that was used by EPA.
Key definitions and concepts are also  provided.  Highlights of the
approach will be given within the discussion section


DATA ON CLEANING: HISTORICAL
Information  on  cleaning  is  scattered in the literature  under
various  subheadings.    when reporting  was  done  under  the  term
"cleaning," it was not usually clear what was included under this
heading.  Documenting information on cleaning was not considered a
priority for industry.  Some companies had  not installed adequate
                               896

-------
                 to measure the amount of solvent used for cleaning
 separately from that used for manufactaring.  Keeping accurate data
 ori  cleaning  was  uncommon.    Further,  there  was  no  accepted
 methodology  for deriving the data  on cleaning.   To  estimate the
 nationwide   impact   of   the  CTG,   a  legislative   requirement
 necessitates  the development of  such  data.

      In  the more recent  published literature  the emissions  due to
 cleaning are  sometimes reported under headings  that  indicate the
 Purpose  for cleaning: for example, surface preparation; cleaning of
 tools or jigs; and maintenance and housekeeping.  This approach was
 adopted  by  the  South Coast Air  Quality  Management District  for
 their regulations  on cleaning.   The emissions from cleaning  were
 summarized under four main cleaning categories  in their  rule No.
 1:L7l  (June  1991)  entitled,  "Solvent Cleaning Operations."  Their
 categories  were  selected to  group  emissions   according  to  the
 "reason  for cleaning,"  (e.g., repair  and maintenance).


 SOME KEY OBJECTIVES
     The EPA had a number of  objectives to satisfy:

 1-   To  establish   ^mrate ay*  renreaentative data  on  actual
      (baseline) emissions of VOC's from current, cleaning practices
     that use solvents.

 2-   To   determine   potential   control   measures    and  their
     effectiveness.

 3-   To  provide  the  State and local agencies and industry with a
     common method for data documentation and reporting.  Such a
     method should facilitate communication between the two groups,
     to   achieve   reductions  in  VOC  emissions  and  determine
     compliance with  any emission limits.

 4-   To  develop  a method of communicating concepts  in order  to
     collect information and guide compliance efforts.


MATERIAL BALANCE
     We began with the assumption that a company first  determines
what it  is going to  clean before it selects  the method and tools
 for cleaning,  it seemed appropriate  for us to focus on the "unit
QPeration" being cleaned.  This  led  to the  concept  of  a "unit
operation system."   For  the  purposes of this project, the  jiQit
SE££ation fnri)  was defined ae "an industrial operation,  classified
°r grouped according  to  its  function  in an operating environment
 te-9-, distillation column, paint mixing vessel (tank), paint spray
booth, printing machine,  or parts cleaner].  A unit operation may
involve one  or more items of equipment,  e.g., a unit operation may
include both a reactor and a mixing vessel."

     The unit operation Astern fUOSl  was defined as "the ensemble
Qn which the material  balance for a. unit  operation is performed.
                               897

-------
It  includes  all possible  points/sources leading  to evaporative
emission losses asgoqiated with the cleaning of a unit operation,
including losses  during dispensing  of the solvent,  handling of
residuals in cleaning tools (such as  rags), solvent storage and so
on.   A piece  of  equipment that is used or designed for cleaning
parts is also  a unit operation  by definition,  therefore,  losses
during  removal of  parts should  also be  considered,"   The EPA
recognized  that  there   may be  considerable variation in  unit
operation systems from one  industry to another.   (The decision on
what  to include  in any specific (OS)  was  left to  the company
queried.)   The difference, then,  between the UO and  the  UOS is
essentially those associated  activities that result in emissions
such  as dispensing  of  the cleaning  fluid,  dispensing  with the
soiled wiping media with its retained solvent, and removing parts
from a parts cleaner.

     A  second  assumption  was   that  within  a   large  industrial
complex,  there  likely  were   "cost   centers"  which  maintained
individual  records  of the  cost  of manufacturing goods.  If  true,
then the total solvent purchased by a  company might  leave a paper
trail to the individual  cost centers that would help identify how
much of the total is  used  in various parts of the complex.

     The  key,  therefore,  to obtaining  good "baseline"  data on
actual  emissions is  being able  to  complete a  solvent material
balance  around a unit operation  system  as  explained above.   Tne
method  requires visual  representation  of  key   information  in  a
simple  and  systematic way.  An  example of a unit operation system
for wiping  of  an "external surface" is shown in Figure 1.   Since
the solvent container and  the  container for soiled rags have no
covers,  evaporation  proceeds  freely.   We refer  to this  as a°
"uncontrolled" cleaning operation,  if a special  solvent dispenser
was used and the container  for the soiled rags had a tight  lid, we
would have  referred to this as  a "controlled" cleaning operation-


CLEANING CLASSIFICATIONS
     While  the focus has been the "unit operation,"  EPA identified
three broad cleaning classifications for documenting information on
cleaning.    The first is  "cleaning of external  surfaces,"  
-------
 the columns in Figure l» entitled "unit operations systems," should
 equal  the  total  plant emissions due to cleanup solvent use.


 DISOTSSION
     The   approach  described  here   requires   that  sufficient
 information on cleaning be provided to close the material balance
 around a boundary of a well-defined "unit operation system."  In
 this  approach,   the  history of  a. solvent  used  for  cleaning  is
 documented -  from the moment it enters the plant up to the moment
 it leaves  the plant  boundaries.

     When virgin solvents are used for cleaning, the emissions from
 storage  tanks need  to be apportioned between manufacturing and
 cleaning before being included under the appropriate unit operation
 system.  Emissions from waste management systems (e.g.,  recycling
 and treatment] have to be reported as  separate UOSs, except wnen a
 waste management  system is considered to b« an "integral- part of
 the unit operation or when all the reclaimed solvent is "reused  in
 that same unit operation.  When developing a flow chart «nuJ;« J-°
 Figure  i,  solvents  used to  clean floors  preferably should  be
 stated  as  a  separate  item  (i.e.,  all the floors in a plant are
 treated as one unit  operation system).   If the  emissions  due  to
 floor cleaning around a specific unit  operation are included under
 a unit operation  system, the amount should toe clearly identified on
 the drawing representing  the unit  operation system /e.g.,  Figure
 1) .   The floor construction material (cement, wood, vinyl)  needs to
 be given.

      Once a plant has completed this phase of the calculations it
 can  readily  complete  Table 1,  which provides a simple way for
 combining  and identifying cleaning solvent  usage within  a  plant.
 The  table  alao  provides  a cross-check  to assure  that  all  the
 solvent brought into the plant for that purpose is  accounted for.
 Emissions by UOS  can  be readily identified as well as the extent to
 which a solvent is used in other UOSs.

     There are other  gains from breaking up cleaning emissions from
a plant according to UOSs (i.e.,  modules)  rather  than reporting a
 single total value for plaiit cleaning emissions,  For example, one
 benefit is that adopting practices that reduce emissions  from the
use  of cleanup   solvents  can  be  evaluated  and compared  in  a
 systematic way.   These practices  include  solvent  substitution,
 equipment and process  modification, and recycling  ("in-house"  or
 "closed -loop" ).

     In addition  to  the information  presented in  Figure 1,  the
                     x?
and  recording  special features  of  a part  being cleaned,  e.g.,
excessive porositv   some of this information is useful to develop
          P           Mission data within an  industry  and,  when
                               899

-------
possible,  to  extrapolate such  data  across industries.    "Case
studies"  conducted by a  plant  that compare "before" and  "after"
cleaning  procedures,  resulting  emissions,  and the  cost  associated
with  the  change  can be easily documented  following this approach.
      Some unit operations may be cleaned by more than one "cleaning
activity"  (method) such as wiping and flushing.  When more than one
cleaning  activity is  involved,  the  emissions contribution  of  each
cleaning activity must be estimated by  the  plant as a percentage of
the total  emissions from  that UOS.


CONCLUSIONS
l.    The  "UOS"  provides  an effective  and visually easy to grasp
method  to present data  on emissions  from the  different  sources
during cleaning of a "unit operation"  (and cleaning of parts).  It
also  provides an easy cross-check for total plant emissions due to
cleaning.

2.    It appears  that  the best way  realistically to estimate VOC
emissions  from cleaning  is  through the use of a material  balance
around well-defined boundaries.   (The  focus  is the unit operation
and not the product being manufactured.)

3.    This modular approach,  based on the UOS, provides a practical
format  for  evaluating emission  reduction  opportunities, and the
costs (or savings) incurred with the adoption of selected  control
technologies.

4.    Case studies can be  conveniently  presented  using the  UOS, to
show costs and emissions  "before" and "after" the adoption  of some
technology.

5.   The  UOS  provides   an  easy   setting   for  an   integrated
environmental management  program  in  which  VOC  releases  to all
environmental media are accounted for.
                         ACKNOWLEDGEMENTS

     The authors  wish to  thank Ms.  Carole Lasky  for preparing
Figure 1 and Table 1.
                               900

-------
SYSTEM
BOUNDARY
SOLVENT
INPUT- F
(100%VOCs)
            EVAPORATIVE
            LOSS
EVAPORATIVE
LOSS
                USED SOLVENT
                OUTPUT. L (1 -X >
EVAPORATIVE
LOSS
                 UNCOVERED
                 CONTAINER
                  FOR USED
                   RAGS
                                                            EVAPORATIVE
                                                            LOSS
                                                                V
                                                                  4
               SOLVENT
               ' IN RAGS, L (1-X)
               USED SOLVENT IN
               RAG CONTAINER, L (1-X J
                          2  Z
        VOC EMISSIONS = F - L (1-X J-L (1-X )-L (1-X ) ;X= %WT CONTAMINANTS

     FIGURE 1 - UOS FOR CLEANUP OF AN EXTERNAL SURFACE
             UNCOVERED CONTAINERS-UNCONTROLLED EMISSIONS
                (STATION NO.. DESCRIBED BY THIS OPERATION)
               TABLE 1: SUMMARY OF VOC EMISSIONS
SOLVENT
A
B
C
M
UOS
TOTAL
UNIT OPERATION SYSTEM (UOS) -- WEIGHT PER YEAR
1





2





3





4





...15





SOLVENT
TOTAL




PLANT
TOTAL

                                  901

-------
           Session 20
Semivolatile Organic Measurements
      Gary Hunt, Chairman

-------
     STATE-OF-THE-ART   CAPABILITY  FOR DETERMINATION   OF
          CHLORINATED  DIOXINS  AND  DIBENZOFURANS  IN
                                    AMBIENT  AIR
                    C TasMroV R-R dement, P. Steer3, C. Cbht and T. Dam*

             1 Wellington Laboratories, 398 Laird Road, Guelph, Ontario, Canada NIG 3X7
           2 Environment Ontario, Laboratory Services Branch, 125 Resources Road, Rexdale,
                                  Ontario, Canada, M9W 5L1
           3 Environment Ontario, Air Resources Branch, 880 Bay Street, 4th Floor, Toronto,
                                  Ontario, Canada, M5S 1Z8
          4 Environment Canada, Environmental  Technology Centre, 3439 River Road, Ottawa,
                                  Ontario, Canada, K1A OH3
ABSTRACT
       A round-robin study Jo determine the state-of-the art capability for chlorinated dibcnzo-p-dioxms
(PCDD) and chlorinated dibenzofurans (PCDF) to ambient air extracts was conducted. Eighteen laboratories
took part b the study: 12 used high  resolution mass spectrometers (HRMS), 4 used low resolution mass
spectrometers (LRMS), one used an ion trap and one used a triple quad MS-MS (TSQ) system. Real Hi-Vol
samples were extracted and pooled to provide a high level sample and a low level sample for the round robin,
Each laboratory was provided with blind duplicates of each sample. In addition, calibration, spiking, and recovery
standards were supplied to each laboratory. The results show that excellent wkhin-lab and betwecn-lab precision
k  possible for this  difficult, ultra-trace determination.  However, some outliers were  present  for most
PCDD/PCDF congeners determined in the study, so the range of reported values sometimes spanned more than
a factor of ten. Laboratories equipped with HRMS clearly outperformed laboratories that used LRMS or ion
lfaps for the low level sample. For the higher  level sample, performance was more comparable.  Average
detection limits were 10 times lower for the labs that used HRMS when compared to LRMS.
       In 1989, the Canadian Council of Ministers of the Environment (CCME) sponsored a round robin to
determine the capability of Canadian laboratories for the analysis of PCDD/PCDF in ambient air. Laboratories
were provided with an exposed  PUF/filter combination and an ambient air extract and asked to provide
PCDD/PCDF results.  It was determined that a number of laboratories possessed the capability for the
'eque&ted analysis; however, there was a large variability in the results indicating further analytical methodology
development was required1. In this study, only LRMS was used.

In the past two to three years, more laboratories have started to use HRMS for the analysis of PCDD and PCDF
^ the analysis of ambient air samples for PCDD and PCDF has become more uniform. Akoa w** ™»
of "^-labelled surrogate PCDD and PCDF are now available.  As a followiip to the CCME i*tal round
"«•, a second round robin study was designed by Environment Oatano and Enwonment Canada.  More
                                           905

-------
laboratories, both Canadian and U.S., were included in the second study, which focused on the analysis of
ambient air extracts only.

STUDY DESIGN

        The objective  of the CCME study  was to  evaluate the capability of laboratories to perform
PCDD/PCDF ambient air analysis.

        Ambient air HiVol samples were collected in two areas in Ontario over a number of days.  The areas
were chosen to provide  a sample of relatively low ambient  air concentrations and one of much higher
PCDD/PCDF concentrations. The exposed Teflon-coated glass fibre filters and polyurethane foam plugs fro™
the two locations were extracted without spiking. The extracts from each location were pooled to provide two
composite samples. The high sample was also spiked with a municipal incinerator flyash extract to ensure that
PCDD/PCDF levels were at least 10 times greater than in the low sample. Blind duplicates of each of the two
samples were sent to the participants.  Calibration, spiking and recovery standards were also supplied to each
laboratory. The labs were instructed to use their own methodology and report total pg in each sample for the
2378-substituted isomers and total congeners. Detection limits and percent recoveries were also requested.

        The eighteen laboratories that participated are  listed below;

        12 HRMS LABS;
        Atta Labs, BC Research, Cal Enseco, Environment Canada, Envirotcst, Midwest Research Institute,
        Seakem (AXYS), Triangle Labs, Twin Cities Testing, Wellington, Wright State University and Zenon

        4 LRMS T.ARS-
        Beak Analytical Services, ELI Ecologic, Mann Testing,  and Novalab

              LAB:
        Environment Ontario

        1 ION TRAP LAR;
        Environmental Protection Labs


RESULTS AND DISCUSSION

        Tables 1 and 2 are summaries of the HRMS (13 labs including TSQ) results obtained for the high and
low concentration samples, respectively.  The 'actual' mean is the mean of all the HRMS data received for each
sample, excluding not detected values. The percent relative standard deviation (% rsd) is also given. Since the
samples used were not standard reference materials, as none of this type are available an "expected" value was
calculated in an iterative process from the "actual" value. Any data that fell outside two standard deviations of
the mean was rejected and the "expected* value was calculated.  In a few cases, this process was repeated. Of
the 1391 data points submitted, 155 were rejected.

        For the high sample results in Table 1, there is generally good agreement between the "actual* and
"expected" values.  The % rsd for the "actual" value ranges from 12 to 140%, indicating variability in the analysis
of some of the isomers.  The % rsd is low for the congener group totals. The % rsd for the "actual* values of
the low sample is greater,  indicating the difficulty in the analysis of the lower level sample. Again, there <«
generally good agreement between the "actual" mean and the "expected" mean.

        The results for the LRMS labs were not included in these tables due to their widely varying results. The
high sample results were somewhat comparable, but the superiority of HRMS over LRMS was evident in the
results submitted for the low sample. A number of isomers easily seen by the HRMS systems were completely
missed by the LRMS systems. Only 14% of the 2378-substituted congeners were detected by the five LRMS labs,
                                                906

-------
compared to 88% by the HRMS labs.  When total CDD and total CDF were calculated, there was acceptable
agreement between the HRMS and LRMS labs for the high sample.  The agreement was better for the total
CDD in the low sample than total CDF. One LRMS laboratory failed to see any positives in (he low sample.

        Table 3 shows a comparison of the mean detection limits for HRMS  versus LRMS  reported by the
laboratories.  Standard deviation and % rsd are also given. HRMS detection limits are on average ten  times
lower than LRMS. The large %rsd for both HRMS and LRMS indicates variability in the sensitivity of the mass
spectrometers and variability in the reporting of detection limits. Methods of determining detection limits vary
from lab to lab.  It was not  determined whether some labs reported instrumental detection limits or method
detection limits.

       The mean percent recoveries for the surrogate spikes used are reported in Table 4 for both the high
and low concentration samples. A comparison of HRMS and LRMS results  is given.  AD reported recoveries
were well within  acceptable  limits. There  was no major difference between the HRMS and LRMS labs or
between the high and low samples.

SUMMARY

       For the  high  level  sample,  the average concentrations for  the 2378-substituted congeners  were
comparable for HRMS and LRMS.  HRMS lab results were comparable to each other for the low concentration
sample but LRMS lab results for the same sample were unacceptable.  One laboratory consistently reported not
detecied values for the 2378-substituted isomers but also reported detection lunits well Wow the expected
values of the isomers. In general, HRMS detection limits were ten times lower than for LRMS.

       Performance characteristics from laboratories that carry out state-of-the-art analysis for PCDD/PCDF

      161. Av^e detection limits of 3 to 20 pg for final sample extract (compares to 1-8 fg/m3 in ambient air)
       2. Surrogate spike recoveries of 40-120%
       3.10% -15% relative standard deviation
From the data obtained in the round robin study, labs using HRMS or TSQ can meet these requirements.
REFERENCE

1. C. Tashiro, R£. Clement, S. Davies, T. Dann, P. Steer, M. Bumbaco, B. Oliver, T. Munshaw, J. Fenwick, B.
Chittim, M.G. Foster, 'Ambient Air Analysis Round VM*.' Chemosphere 20(10-12):1319 (1990).
                                              907

-------
Table 1. Actual versus expected values for high concentration sample.
                         (total pg/sample)
High Concentration Sample

2378-TCDD
total TCDD
12378-5CDD
totalSCDD
123478-6CDD
123678-6CDD
123789-6CDD
total 6CDD
1234678-7CDD
total 7CDD
OCDD
total CDD
2378-TCDF
total TCDF
12378-5CDF
23478-5CDF
total 5CDF
123478-6CDF
123678-6CDF
123789-6CDF
234678-6CDF
total 6CDF
1234678-7CDF
1234789-7CDF
total 7CDF
OCDF
total CDF
total
CDD + CDF
Actual
Mean
47.4
2170
218
5690
373
691
732
8460
3480
6200
3750
26300
252
1650
99.6
220
2170
461
258
199
238
2390
1080
127
1860
846
8530
35200
%rsd
110
24
22
12
51
72
42
41
12
15
26
15
52
,.-25.::
12
19
15
28
35
75
67
10
13
24
18
140
19
14
Expected
Mean
31
2300
230
5500
320
550
640
7300
3400
5900
4000
25000
300
1700
98
220
2200
460
230
54
340
2400
1100
120
1800
470
8700
34000
s.d.
5.5
290
16
420
36
68
110
610
290
530
210
1500
49
140
10
35
260
130
20
34
48
200
79
24
220
39
820
2800
% rsd
18
13
7
8
11
12
17
8
9
9
'•••••'S :r';
6
16
8
11
16
12
28
9
63
14
8
7
20
12
8
9
8
                              908

-------
Table 2.  Actual versus expected values for low concentration sample.
                        (total pg/sample)
Low Concentration Sample

2378-TCDD
total TCDD
12378-5CDD
total 5CDD
123478-6CDD
123678-6CDD
123789-6CDD
total 6CDD
1234678-7CDD
total 7CDD
OCDD
total CDD
2378-TCDF
total TCDF
12378-5CDF
23478-5CDF
total 5CDF
123478-6CDF
123678-6CDF
123789-6CDF
234678-6CDF
total 6CDF
1234678-7CDF
1234789-7CDF
total 7CDF
OCDF
total CDF
total
CDD+CDF
Actual
Mean
3.6
5Z9
11.2
105
15.2
24.3
29.2
300
270
569
826
1850
35.7
250
13.2
19.3
191
35.9
18.1
67.7
48
243
81.9
12.6
164
103
945
2790
% rsd
81
43
44
36
30
33
37
24
29
29
50
34
43
29
25
32
22
23
27
61
79
21
35
45
81
81
27
30
Expected
Mean
3.6
51
11
no
15
22
29
290
250
520
730
1700
36
250
13
18
200
33
17
89
19
. 240
75
11
140
84
910
2600
s.d.
3.0
21
4.2
31
4.0
4.9
5.3
54
29
49
62
120
15
46
23
2.7
36
5.7
3.7
14
4.2
48
10
1.1
23
16
130
280
%rsd
83
41
38
28
27
22
18
19
12
9
8
7
42
18
18
15
18
17
22
16
22
20
13
10
16
19
14
1
                          909

-------
Table 3.  Mean detection limits - HRMS versus LRMS (pg)


2378-TCDD
12378-5CDD
123478-6CDD
123678-6CDD
123789-6CDD
1234678-7CDD
K<&fy OGDD
2378-TCDF
12378-5CDF
23478-5CDF
123478-6CDF
123678-6CDF
123789-6CDF
234678-6CDF
1234678-7CDF
1234789-7CDF
^"^OOCDF.
HRMS
mean
3.3
8
7.4
6.7
7.0
10
« 23 <
2.9
5.0
5.3
6.7
5.6
5.7
5.8
8.3
8.1
t^l6'':
s.d.
2.7
6.6
4.9
4.4
4.6
7.5
20'
2.3
4.1
5.0
5.5
4.1
3.8
3.8
8.2
6.4
',-13 —
%rsd
44
100
110
110
85
74
190
79
82
93
83
73
68
65
99
78
--,82 ^
LRMS
mean
48
140
110
97
88
75
* 180 i*
48
53
41
48
45
49
54
74
93
*,'- 150 . -
s.d.
39
140
100
86
78
56
VMSO^
42
48
34
42
42
47
46
62
68

-------
   GAS EXCHANGE OF HEXACHLOROCYCLOHEXANE IN THE GREAT LAKES

Laura L. McConnelf'-3, William E. Gotham1, Terry F. Bidleman1'2
University of South Carolina, 'Department of Chemistry and Biochemistry, 2Marine
Science Program and Belle W. Baruch Institute for Marine Biology and Coastal
Research, Columbia, South Carolina 29208. 3Present Address:  USDA, Agricultural
Research Service, Environmental Chemistry Laboratory, Beltsvitle, MD  20705.

INTRODUCTION
      Wet deposition, dry deposition and gas exchange across the air-water interface
are the three major transport pathways for atmospheric inputs of organic pollutants in
the Great Lakes. Unlike wet and dry deposition, gas exchange has a "two-way street"
nature where invasion or evasion of gases can occur.  For many organic pollutants
such as polychlorinated biphenyls (PCBs), and DDTs, volatilization is a major output
pathway, and tor lakes Superior, Michigan and Huron the estimated net annual flux of
these compounds fs out of the lakes(f).
      Accurate determination of gas exchange an elusive process. Simultaneous
measurements of fugacity in water and air are needed.  These values depend on the
fraction of pollutant in the truly dissolved  and gaseous states. Also the Henry's law
constant (H) of the compound must be well characterized over a range of
temperatures.                                                      .   ....
      The goal of this project was to determine the direction and magnitude of the flux
for a- and y-HCH in the four tower Great Lakes. Simultaneous air and water samples
were collected  during two trips. The first was a preliminary survey limited to Green
Bay in June, 1989. The second trip was  more comprehensive, and samples were
collected in the four lower Great Lakes during August, 1990. The fugacity gradient
across the air-water interface was used to determine the direction of the flux. The
magnitude was estimated using a fugacity-based model derived from the two-film
resistance model originally developed by  Whitman (2) and later applied to
environmental volatilization of gases by Liss and Slater (3).
RESULTS AND DISCUSSION
      Air-Water Gas Exchange. In the two-film mode), total resistance to mass
transfer across the air water interface, R,, is equal to the resistance across the air film,
ra, and the water film, rw.
                             R, = r. + rw  (eq. 1)

The relative importance of the air and water film resistance depends on the mass
transfer coefficient tor the two phases and the magnitude of the Henry's law constant
(4). HCHs have low Henry's law constants at environmental temperatures and their
exchange is gas phase controlled (5).  Thus:
                           Rt-r.-HT/HK.  (eq. 2),
where k, (m s
        (m s'1) is the gas-phase mass transfer coefficient, R is the universal gas
constant (Pa m* mof1), and T is the absolute temperature (K) (6).  Values for k, were
calculated using the mean wind speed for each lake from an equation developed by
                                     911

-------
Mackay and Yuen (7).

            ka = 1 x 10"3 + 46.2 x lO^e.l + 0.63U10)a5UtoSc-°87  (eq. 3)

where U10 is the wind speed at 10 m (m s"1) and Sc is the gas phase Schmidt
number(dimensionless). A value of 2.9 was chosen for Sc for both a- and Y-HCH (7).
      Once ka is determined, flux calculations are made using fugacity-based
equations.  These types of equations have been extensively used by others, and are
extremely useful in modeling transport  of pollutants (6,7,8,9).  Basic definitions and
conversions are listed in Table I. Direction of the flux is determined from the fugactty
gradient, r,

                        r = fw/fa (dimensionless)  (eq. 4)
                        fw = 10* Cd/MW Z,  (Pa)   (eq. 5)
                        f, " 10-8CQ/MW2a (Pa)  (eq.6).

Cd and C0  are defined as the  dissolved HCH concentration, (ng L'1) and the gaseous
HCH concentration, (ng nr3) respectively.  If r = 1 the system is in equilibrium and
there is no net exchange;  r >  1 denotes a volatilization flux,  and r < 1 means a
deposition  flux. The magnitude of the  flux, N, is given by:

                  N = 109 MW Daw(fw - fa) (ng rrf2 day1)  (eq. 7)
                     Daw  "  ka/RT (mol m'2 day'1 Pa'1)   (eq. 8)

A volatilization flux is defined by a positive value of N.
       Flux Results.  Henry's law constants of a- and Y-HCH were calculated for each
sample using the measured water temperature and relationships of Kucklick et al.(f2).
In June, Green Bay surface water was "undersaturated" with respect to the air for both
a- and Y-HCH (r <  1), and this disequilibrium drives the flux into the water.  The
magnitude of the flux was estimated at -96 and -49 ng m"2 day"1 for a- and y-HCH
respectively. Volatilization of  HCHs was observed during August due to higher surface
water temperatures (fluxes 33 and 32  ng m'2 day'1 for a- and  Y-HCH, combined mean
from all four lakes).
       Two major factors seem to play a part in changing fhe direction of the flux from
deposition to volatilization in this case. First, water temperatures in Michigan and
Huron in August are over twice that in June. This elevates the Henry's Law constant,
thus increasing fw (eq. 5).  Second, the structure of the water column changes
drastically  from June to August. In spring, the Lakes are well-mixed and the entire
volume is available for exchange. In August the Lakes are stratified,  and the top 15-20
m is isolated. With increased fugacity in the water, and a limited volume available for
exchange, the Lakes change from a reservoir for to a source of  HCHs. This situation
 is probably short-lived, however, since the stratified conditions are only present during
the  summer months (July - September).
       Estimated Annual Loadings. An attempt to estimate the annual flux to each lake
 by gas exchange can be made using  the monthly air concentration data from Hoff et
                                       912

-------
 a|- (7t);  this is the only annual record of HCHs in air for the Great Lakes.  The
 average water concentration for each lake from the August survey was assumed for
 each month since HCH concentrations measured in the hypolimnon (representing
 winter surface water) were similar to those observed at the surface.  Average monthly
 surface water temperatures for each lake were used to calculate Henry's law constants
 (12-13),  Monthly wind  speed data from land stations  around the lakes was essentially
 constant at 5 m s'1. Results of these calculations are shown in Figure I.
      By adding together the monthly fluxes, an annual flux can be estimated for each
 lake. AN tour lakes exhibit a overall deposition flux for the year:  a-HCH + y-HCH =
 -4850, -7460, -6080, -10470 ng m* year1 for Michigan, Huron, Erie and Ontario
 respectively.  The annual  input by direct gas exchange can also be found by using the
 surface area of each lake: a-HCH + y-HCH =  282, 449, 160, 207 kg Michigan, Huron
 Erie and Ontario respectively. The amount of HCH being deposited to the lake may
 be effected by fee cover as this reduces the amount of surface area available for
 exchange.
      While rt appears  that a-HCH and to a much smaller extent,  y-HCH, is volatilizing
 from the lakes during the  summer, the overall flux by direct gas  exchange is for HCHs
 >s probably deposttional.  Since the magnitude of these fluxes change drastically with
 wind speed, air concentrations, water concentrations, and water temperature, detailed
 monitoring of all these factors in each lake is the only way to obtain more accurate
 measurements of gas exchange.

Table t:  Fugaclly-based definitions
 Constant                       Definition                        Value
 MW                    Molecular Weight (g mof1}                 291
 k,               Gas-phase mass transfer coefficient (m s-1)         Eq. 3
fw                         Fugacity in water (Pa)                   Eq- 5
f*                          Fugacity in air (Pa)                   Eq-6
 Cd                    Dissolved Concentration (ng L')
 CB                    Gaseous Concentration  (ng mp
2*                 Fugacity Capacity Water (mol Pa"1 mr3)           1/H
2.                  Fugacity Capacity Air (mol Pa'1  m*)             1/RT
H                  Henry's Law Constant {Pa m3 mor1)
R                    Gas Constant (Pa md mo!'11C1)              8.3
T                      Absolute Temperature (K)


REFERENCES
(1)   Strachan, W. M. J., Elsenreich, S. J. Mass  Balancing of Chemical Pollutants In
toe Great Lakes;  The Hole of Atmospheric Deposition, International Joint Commission
Report:  Windsor, Ontario, Region Office, 1988.
 (2)   Whitman, W. G. Cnem. Metal. Eng.  1923, 29, 146-148.
(3)   Use, P. S., Slater, P.  G. Nature, 1974, 181-217.
(4)   Mackay, K., Shiu, W. Y.  and Sutherland, R.  P. Environ. Sci.  Techno!., 1979,13,
333-337.TO
(5)   Hinkley, D. A., Bidleman, T. F., rice, C. P. J. Geophys. Res., 1991, 96, 7201-
                                     913

-------
7213.
(6)   Mackay, D., Paterson, S., Schroeder, W. H. Environ. Sci. Technol., 1986, 20,
810-816.
(7)   Mackay, D, Yuen, A. T. K. Environ. Sci. Technol., 1983,  17, 211-217.
(8)  Mackay, D. J. Great Lakes fles., 1989, 15, 283-297.
(9)  Mackay, D. and Paterson, S. Environ. Sci. Technol., 1991, 25, 427-436.(31)Keizer,
P. D., Gordon, D. C., and Dale, J. J. Fish. Res. Board. Can. 1977, 34, 347-353.
(10) Kucklick, J. R., Hinckley, D. A., and Bidlernan, T. F. Marine Chem.,  1991, 34,
197-209.
(11) Hoff, R. M., Muir, D. C. G., Grift, N. P.  Environ. Sci. Technol., 1992, 26. 266-275.
(12) Rockwell, D. C., Salisbury,  D.  K., Lesht, B. M. Water  Quality in the  Middle Great
Lakes:  Results of the 1985 U. S. E. P. A. Survey of Lakes  Erie. Huron, and Michigan.
(13) Stevens, R. J. J. A review of Lake Ontario water quality with emphasis on the
1981-1982 intensive years. A Report to the Surveillance Subcommittee of the Great
Lakes Water Quality Board. International Joint Commission. Great Lakes Regional
Office. Windsor. Ontario. October. 1988.
     1500


     1000


      500
-1000





-JOOO


 1000


 SCO
    -1000
    -.WOO
           MICHIGAN
                                 •
         JAM rte two *f» utr ju» jui *uc SEP OCI NOV DCC
           HURON
                                       r
                    UA.T JUH JUt AuC S£P OCI MOW DEC
1200
9OO
600
300
-300
-600
-900

-3100

-300
-«00
-000
-1COO

f
-2100
•
1 1 - 7-HCH
•1 - a-HCH




•

ERIE
]|
1
^r


r



\
u* m MAI A» BAT JUM Jin. AUC nr ocr NOV OK
rrfp


• ONTARIO
-1
HI



1



: 	 1 	
                                                JA* m MAX tr« HAT IU» JUL AUC SCf OCT »O» DtC
                   Figure I:  Estimated monthly fluxes (ng m2 month'1)
                                      914

-------
          AMBIENT IMPACTS OF COKE AND COKE BY-PRODUCTS
 MANUFACTURING ON SELECTED POLLUTANT LEVELS IN NEIGHBORING
     COMMUNITIES:  II - RESULTS FROM A SIX-MONTH AMBIENT AIR
         PARTICULATE-PHASE POLLUTANT MONITORING STUDY


                                   Ronald Harfcov
                  ENSR Consulting and Engineering, Somerset, New Jersey

                               Adrianne C. Olsakorsky
                     ENSR Consulting and Engineering, Pittsburgh, PA

                                    John P. FWo
                     ENSR. Consulting and Engineering, Pittsburgh, PA


 ABSTRACT
 ^    Coke and coke by-products manufacturing results in the release of several toxic air pollutants.
 •Jhese substances include but are not limited to, PM10( volatile organic compounds (VOC) »«ch as
 yzene, polycyclic aromatic hydrocarbons (PAH) such as benzo(a)pyrene, and sulfate. USS Clairton
 ^orks requested that ENSR Consulting and Engineering conduct an ambient air monitoring study to
 rfermine the impacts facility emissions are  having on ambient levels  of PM10, benzene and
 :en2D
-------
METHODS

Monitoring Sites
      The three monitoring sites were located at the South Allegheny High School (SAHS), Coursw
Hollow (CH) and Clairton Public Works building (CPW), as shown in Figure 1.  These sites were
thought to be representative of maximum and background concentrations of the target parameters in the
vicinity of  USS Clairton Works. The location of ENSR's monitors facilitated a comparison of the
measured results with corresponding PM10 collected by AICo,  because of their  proximity to  sites
currently used by AICo for benzene monitoring and/or for paniculate (TSP, PMlfl) sampling.

PM10 Collection
      All samples were collected on quartz fiber filters using high volume samplers that meet the EPA
PM10 sampler performance criteria as listed in 40 CFR Part 50.  The filters were prepared in the ENSK
Wilmington, MA laboratory per standard EPA procedures.
      The high volume samplers were equipped with 10 micron (jim) size-selective Wedding tote&>
which are identical to those currently used by AICo for PM10 monitoring.  The Wedding inlet is &
omni-directional cyclone that allows particle entry from all angles of approach, and is fitted with a
critical flow device to regulate the proper flow rate at all times.  The critical flow rate of the sampler8
was maintained at 40 ± 2 cubic feet per minute (CFM).  Particulate matter accumulated on the filters
during the  24-hour sampling  period.
       Inlet maintenance has been shown to have an important impact on PM10 sampler performance
(Purdue, et al. 1986). The samplers were inspected monthly and appropriate maintenance procedures
(e.g., periodic brush cleaning of the primary collection surface of the inlet)  were used, as needed.
Sampler calibration was performed  prior to and  following each sampling  event.  Multi-point  flo*
calibrations were performed at the beginning, mid-point, and end of the project. Single point checks
were performed on a monthly basis.  An audit of the PMW samplers was conducted at the midpoint and
end of the  sampling project.

PM,0, Sulfate, Trace Elements and PAH Analysis
       All filters  were properly conditioned before and  after collection  per EPA filter handling
requirements (40 CFR Part 50, Appendix J) and all procedures in ENSR SOP 6000-201 were followed-
Filter cutting procedures followed those outlined in 40 CFR Part 50, Appendix G. These procedures
require the use of clean pizza cutter, template, and cutting board to properly cut the filter strips. A * *
8" strip was extracted with double distilled, deionized water and the extract was analyzed for sutfate
via ion chromatography.  PAH were extracted from a 3" x 8" filter strip with dichloromethane and
analyzed per EPA  Method SW-846 Method 8270. Finally, trace elements were extracted from a 4 *
8" filter strip with a HNO,-HC1 mixture and were analyzed per EPA SW-846 Method 7000.

Quality Assurance
       The entire study was conducted in accordance with a quality assurance plan developed prior w
sample  collection  and analysis  (ENSR 1989).   The quality objectives for the present study yf6
expressed  in terms of precision,  accuracy,  completeness, representativeness  and comparability'
Measurement precision was based on the analysis of replicate sample aliquots from the  same samples-
The PM10 precision was based on a side-by-side collection with AICo at the  SAHS  site.
precision for the relevant chemicals was determined through comparison of samples spiked wi
                                                                samples
 samples collected.  Data validation was utilized throughout the field and laboratory efforts.
                                             916

-------
 e*ample, the QA manager assured that SOPs  were properly followed,  that the proper analytical
 Procedures were utilized and  that all calculations were performed properly.  These quality control
 measures were used to ensure the generation of reliable data from all sampling and analysis activities.

 °^ Analysis Approach
       The method utilized for analyzing the atmospheric conditions associated with each sampling day
 °f interest was to create a database of air quality (AQ) and meteorological (MET) data provided by
 AJCo for the three monitoring sites during the monitoring study period of July  1989 through January
 J9*>.  The AICo monitor collects hourly MET data (wind direction and wind speed) at we SAHS site.
 ^P1" data from the Greater Pittsburgh International airport, located approximately 24 miles northwest
 Pf SAHS, was compared to SAHS data, and was used when SAHS MET data were missing. Because
 kstortcal measurement and modeling results predict elevated pollution levels for the SAHS site, data
 ^m this monitor forms a central focus for the remaining discussion. Daily weather observation data
 8116618 were reviewed for each sampling day to obtain an understanding of the atmospheric conditions
 P*5861" during the sampling event that may have affected sampled concentrations.  Particular attention
 w* directed towards the identification of temperature and/or subsidence inversions that are common
 °Ccurrences in the Allegheny County region during the fall season.
       TheairquaUtya^yiswasperfonnedonanevent-spedficbasis.  An air pollution event was
 Defined as any daily air quality measurement  that indicated elevated levels  of any contaminant at one
 ^ more of the monitoring sites.  The concentrations used as an indicator of elevated concentrations
 We«; PM10, 125  oe/m5' B(a)P  5 ng/m1: and SO<, 25 /tg/mj.  Any measured pollutant concentration
 Skater than or equal to the listed threshold concentration was considered to be elevated for the purposes
 Jf this monitoring study.  As a measure of meteorological conditions on a specific day, prevailing wind
 Jfection, mean wind speed and persistence were calculated using the surface  observations obtained
 ^m the SAHS monitor^nofsky and Brier 1958), A persistence greater than 0.9 was considered a
 good meaa^ to ^SSSS of  wind direction.  In the present study, for  a direct wind
 ^tioti/poliutant concentration relationship wilh USS Clairton Works, a southwesterly wind direction
 «implied for the SAHS and CH sites, while a northeasterly  wind directionis taplied^ CPW.
      Tlw AQ and MET data were transferred  from the database into LOTUS 1-2-3 (Version 2.2)
 *°J*sheets  and classified  by month.   Spearman-Rank correlations  (rsp) were  <*taOtiea using
 Sciagraphies (Version 2 1) as an initial indication of the relationship between pollutants dunng
^"^monthsofthestudy.  Spearnian-rank correlation coefficiente equal to or greater than 0.7were
 Bartered indicative of stroni relationships between various air pollution measures in thepresent study.
^Phical representations of pollutant concentration variability within and between monitoring sites
throughout the network were used to assist in the analysis of possible source-receptor relationships.
      ii£Ust 1989                                                                   .   .
      There were no project measured exceedances of the 24-hour ^oNAA^fem me motoring
   t-up date of July 13,1989, through the end of August. Due to a mid-month start-up, the data for
   month of My were'combroed with the data for August for the present analysis.
      Four of the five sampling days during August 1989 were associated with elevated B(a)P levels.
   1 devated B(a)P concentration measured at CH on August 6 occurred during mc^erately persistent
-J0.88) southwest winds. Elevated B(a)P concentrations on August 12 «*^ * S^Hf "™P*
^ Poorly persistent (p-0.42) easterly winds. B(a)P concentrations werealso elevated at CPW on
Au§ust 18 and 24  Moderately persistent 
-------
to August 1989 sampling period were below SO /xg/m3. Four of the five sampling days in August were
associated with elevated B(a)P concentrations and low PM|0 concentrations. Correlations between PMto
and B(a)P at SAHS was rsp-0.74 for the inclusive time period of July to August 1989.

September 1989
      The average measured PM,0 concentrations at SAHS, CH, and CPW during September 1989
were 37, 36, and 27 Mg/m3, respectively. There were no measured PM10 exceedances of the NAAQS
during September 1989. With the exception of measured PM10 concentrations of 100 /xg/m3 at SAHS,
and 76 /ig/m3 at CH on September 29, all measured PM10 concentrations during September were less
than 50 pg/m3.
      The B(a)P concentrations were elevated  at the SAHS and CH sites on September  11. This
corresponded to moderate (p=0.79) north-northeast wind persistence.  Elevated levels of B(a)P were
measured at SAHS and CH on September 29. The winds on this day were strongly persistent (p-0.91)
from the southwest.   Correlations between measured PMio, B(a)P, and SO4 at SAHS were strong
(>0.9) during September 1989.

October 1989
      The monthly average PMIO concentrations measured at SAHS, CH, and CPW were 75, 93, and
50 /xg/m3, respectively. The only project measured exceedance of the 24-hour PMW NAAQS occurred
on October 23 at the CH site.  On October 23,  measured B(a)P, and SO4 levels were elevated at the
SAHS and CH sites in addition to elevated PM,0 levels at SAHS.  The B(a)P concentrations were also
elevated at CPW on this day.  The B(a)P concentration of 216 ng/m3 at CH was the highest value
measured for this contaminant during the entire project.  The winds occurring on October 23 were light
(< 1.0 mi/hr) and variable (poorly persistent). These data, plus the field technician's observations of
the presence of a fog or haze condition, light wind, and a reduced sulfur  smell suggest that an air
inversion existed on this day.
      Concentrations of PMIO, B(a)P, and S04 were elevated at all sites on  October 29. On this day,
PMIO and B(a)P concentrations were the highest at CH, while SO4 concentrations were highest at SAHS.
The wind was moderately persistent (p=0.79) from the east, with light winds (< 1 mi/hr).  The field
technician noted that the air quality was poor on this day.  At the CH site the field technician observed
a haze layer in the river valley, indicative of an inversion and detected a reduced sulfur presence
through smell and taste. It is likely that inversion conditions persisted during  and between the sampling
events of October 23 and 29 that would have prevented normal atmospheric dispersion of pollutants,
and hence increased ambient concentration levels.  Further support for this conclusion is offered by a
review of AICo air quality data and Greater Pittsburgh International Airport MET data.
      AICo measured elevated B(a)P levels on  October 25 at SAHS, and recorded two exceedances
of the 24-hour PM10 NAAQS (October 27,28) at SAHS.  The MET data indicated that the time period
from October 23 through October 29 was characterized by light and variable winds, above average high
daily temperatures (70°F), average cool lows (40 to 44°F), clear evenings on the 25, 26, and 28th, and
a fog/haze condition, which persisted daily until late morning (with the exception of the 24th).
      In addition to the two event days, elevated B(a)P levels were measured on October 5, 11, and
17 at the SAHS site, and on October 5 and 11 at the CH site. Concentrations of PM10 on these days
were less than 55 /ig/m3.  The winds on October 5 and 11 were strongly persistent (p=0.97 and 0.90,
respectively) from the southwest while winds on October 17 were poorly persistent.  The correlations
between PM10 and B(a)P, and PMU and SO4 at the SAHS site were high during October (rsp=0.99,
0.99, respectively). Similar correlations at CH and CPW were also high.
                                           918

-------
November and December 1989. January 1990,
. _    The November monthly average PM10 concentrations at SAHS, CH, and CPW were 20,22, and
15 Kg/mJ, respectively. AUmeasBicdPMI0cow^tration&weielmthan50j*g/nf- B(a)P levels were
wevatiMi n_ XT	. ** ,   .  ._  . _.,.:»	j m~r —j ~t mi rm KTnvi»mlv>r 28. The winds were
       , respectively. AUnia^PM.oCOBceatation&v^lmthaaSO^. Bg)P levels were
       on November 4 and 10, at SAHS and CH, and at CH on November 28. The wnk were
 ?«terately persittent on November 4 (p»0.83), from foe east-southeast, strongly perastent 
 J* 
-------
residential combustion of coal and lignite (Grimmer 1983).   Harkov et al.  (1987) reported mean
dibenzo(a,h)anthracene  levels  as  <0.08 ng/m? at four  New  Jersey  monitoring  sites.   The
dibenzo(a,h)anthracene levels were the lowest of the IS PAHs measured in this study. In New Jersey*
residential coal combustion is virtually non-existent and there are no coke facilities in the state.
       The levels of B(a)P measured in the present study are higher than typical concentrations found
most urban areas (Table 4), which is in part due to the influence of USS Clairton Works on the ambient
PAH concentrations. During the past two decades, average urban B(a)P levels have declined to values
typically < 1 ng/m*. For example, Faoro and Manning (1981) reported that average B(a)P levels in
urban areas associated with coke plants declined from about 5 ng/m3  to  < 1 ng/m3 during the P61^
from 1966 through 1977.  Harkov and Greenberg (1985) reported that mean urban B(a)P level measured
at 13 sites in New Jersey during 1982 was 0.6 ng/m3.  The B(a)P results from the present study suggest
that the ambient air levels in the environment surrounding  USS Clairton Works are an order of
magnitude greater than found in typical urban areas.
       During the present study, PAHs were the best indicator for influence of the coke  plant on
measured ambient PMlo levels. Using B(a)P as a surrogate for PAH levels indicates that concentration
changes for this  substance were highly correlated with daily changes  in PMW concentrations.
Conversely, trace metal  levels were uniformally low and day-to-day changes in the fraction  of the
various metals in collected samples was fairly constant during the entire study.  These findings are
consistent with existing emissions data and suggest that the major particulate emission streams fro1"
 coking operations are associated primarily with organic materials (EPA 1977).
       Throughout the  measurement program, SO4 was a  major component of the PMW niass.
Assuming that SO4 was in the form of NH+HSO^ based on the mean measured values, this constituent
of PMIO represented from 36  to 42  percent of the total collected particle  mass.  These results a»
consistent with similar measurement studies (Spengler and Thurston 1983)  During specific air pollution
 events, SO4 represented from about 29 to 45 percent of the collected particle  mass and these results are
consistent with the mean measured concentrations.  This latter observation indicates that while the coke
plant is a large source of sulfur emissions, SQ, levels in the vicinity of the facility are not significant
influenced by these releases.  Thus, prevailing meteorology has the most significant influence  on P«
ambient levels of SO4 in  the vicinity of the coke plant.

CONCLUSIONS
       The long term ambient air monitoring program in the vicinity of USS Clairton  Works was
conducted  to establish a  comprehensive air toxics monitoring network that  would focus on pollutant
 "hotspots".  In addition, a preliminary assessment regarding the impact of fugitive coke ovea emission*
on the measured ambient air concentrations of selected target parameters was completed. Of particular
interest, was whether the ambient levels for B(a)P may warrant further control of coke oven
 emissions.
       During the six months of PM10 measurements, only one event was associated with an
       air concentration > 150 pg/m3, the 24 hour NAAQS,

       Levels of B(a)P measured in the present study were an order-of-magnitude higher than the &&
       of concentrations found in most urban areas.

       The levels  of trace elements and  SO4  were  consistent  with  most urban  ambient &
       concentrations.
                                             920

-------
 *     The presence of persistent winds from either the southwest or the northeast greatly enhanced the
       probability of measuring elevated pollutant concentrations at those sites downwind from the
       facility.

 *     Temperature inversions were responsible for elevated concentrations for many target chemicals
       at all sites during selected periods of time between late September and November.

       The present  study is a comprehensive air quality assessment in the vicinity of USS Clairton
 Works.  This information can be utilized to develop quantitative source-receptor estimates for selected
 target parameters.  The overall accuracy of such an effort would be limited by the extent of chemical
 c!laracterization data that existed for release sources at the facility.  However, on a qualitative basis,
 a* quality impacts from USS Clairton Works can be commonly resolved using both meteorological and
 atmospheric chemistry data.

 REFERENCES

       Quality A^irfmPi. Plan for Long-T>rm Benzene and PM.n MPllitorinF Program In the VJCinitY
        s
-------
NAS, Particulate polycyclic organic matter. NAS Press, Washington, D.C., 1972.

Panofsky, H.A, and G.W. Brier, Some Applications of Statistics to Meteorology. Pennsylvania State
University Press, University Park, PA,  1958, pp. 20-24.

Potvin, R.R. et al., "Ambient PAH levels near a steel mill in northern Ontario," in Proceedings of the
5* International PAH Symposium, Battelle  Press, Columbus, OH, 1981.

Purdue, L.J. et al., "Intercomparison of high-volume PM10 samplers at a site with high particulate
concentrations," JAPCA 36:917, 1986.

Spengler, J.D,  and G.D. Thurston, "Mass and elemental composition of fine and course particles in six
US cities," JAPCA 33:1162, 1983.
                                          922

-------
Table I. Site Specific Data Averages.


Sample
CATTC ntjf
"•"ifllji ffflin
B(a)P
SO4
"ttlkjf
"llrt
B(a)P
S04
B(a)P
S04
*mM'
Table n. Project
*-
PH0 (Mg/ltf)
B
-------
Table m. Polycyclic Aromatic Hydrocarbon Sampling Results.
CoursinHUl
Pollutant
Benzo(b)fluoranthene
Benzo(k)fluoranthene
Benzo(e)pyrene
Benzo(a)pyrene
Indeno(c,d)pyrene
Dibenzo(a,h)anthracene
Benzo(g,h,i)perylene
South Allegheny HS
Pollutant
Benzo(b)fluoranthene
Benzo(k)fluoranthene
Benzo(e)pyrene
Benzo(a)pyrene
Indeno(c,d)pyrene
Dibenzo(a,h)anthracene
Benzo(g,h,i)perylene
Clairton Public Works
Pollutant
Benzo(b)fluoranthene
Benzo(k)fluoranthene
Benzo(e)pyrene
Benzo(a)pyrene
Indeno(c,d)pyrene
Dibenzo(a,h)anthracene
Benzo(g,h,i)perylene
Mean Concentration
(nt/rn*)
21.3
17.3
11.8
18.9
15.3
4.2
14.3
Mean Concentration
(ng/m3)
19.7
15.1
10.1
17.6
13.5
3.9
12.3
Mean Concentration
(ng/m1)
3.8
2.8
1.9
2.8
2.7
0.7
2.7
Maximum Concentration
Gog/in3) __
222.2
209.5
133.3
215.9
171.4
58.4
158.9
Maximum Concentration
(ng/m3) 	
192.7
147.7
96.3
179.8
134.9
49.5
122.0
Maximum Concentration
(ng/m3) 	
36.3
25.4
18.1
27.2
27.2
7.8
26.6
                                        924

-------
     IV.  Typical Ambient Levels of Benzo(A)Pyrene.
27 Sites in
New Jersey

6 Los Angeles
Sites

4 Sites Near
Ontario Steel
Mill
iSUei
      in
NASN Sites

Pittsburgh, PA
      Site
Date

1982


1981-1982


1971-1979



1981-1982


1966-1970


1969
Concentration ftip/mib

   0.19 - 7.9           Harkov and Greenberg (1985)
   0.04 - 3.23
   0.21-1.15
   1.6 - 5.2
                                       2.0 - 3.0
   6.0-21.3
Grosjean (1983)
Potvin et al. (1981)
Matsumato and Kashimoto (1985)
                      EPA (1974)
NAS (1972)
                                          925

-------
LEGEND



 ^k  MonMortngSM
                                        FIGURE 1



                  MONITORING SITE LOCATIONS IN THE VICINITY OF COKE FACILITY
                                              926

-------
          IMPACT OF  WEST VIRGINIA FOREST FIRES ON
                              OHIO AIR QUALITY
                       Karen Riggs, William Pllspanen, Jane Chuang
                                         Battelte
                                    505 King Avenue
                                     Columbus, Ohio
                                       PaulKoval
                                       Ohio EPA
                                     Columbus, Ohio


 ABSTRACT
    In late October 1991, smoke from West Virginia forest fires was transported on southeast winds
 t^ugh most of Ohio. Battelle, responding to an emergency request from the Ohio EPA, collected
 ambient air samples in Columbus, Ohio, during the period of decreased visibility.  PS-1 samplers
 were used to collect ambient air samples for PAH and PCDD/PCDF analyses.  A SUMMA canister
 was used to  collect volatile organic compounds  for  analysis.   Analytical results  indicated mat
 CQQcentrations of more volatile  2-  to 4-ring PAH compounds  were significantly  higher in the
 October,  1991  sampling  than  in  previous ambient  air  sampling conducted  in  Columbus.
 ^DD/PCDF concentrations were not significantly different than typical Ohio ambient levels and
 Were lower than concentrations determined directly in forest fire plumes.  Light hydrocarbons  (i.e.,
 e*ane) also had increased concentrations in the October 1991 sampling.

 lNTRODyCTION
    Emissions which have typically been measured from forest fires include carbon monoxide (CO),
 j^trogen oxides (NO,), and non-methane total hydrocarbons (NMTHC).  Some of these studies  have
 ^^ actual open burns while others have studied the open burning of wood  for heating  or cooking.
 For CO, increases of approximately  10 percent over background have been measured.1 Levels of
 Approximately 60 ppb NO, have been reported in the actual plume of an open bum.2 NO, values as
 togh as 353 ppb have been found in open fires in urban areas.3
   Measurements  of organic species have primarily  focused on either the volatile non-methane
 fottponents or benzo(a)pvrene (BaP)  a known carcinogenic material.  Studies of wood fire cooking
 ui Asia  have  found BaP levels increased by a factor of 12 over emissions from  cigarette smoke
 levels.4
   The  paniculate material  emitted  during  wood  combustion is primarily very  fine paniculate
Approximately 0.3 pm in diameter.2  The attractable organic material from the paniculate is highly
JJJriable  but can contain  a wide range of compounds such as polycyclic aromatic hydrocarbons
(PAH) and polychlorinated dibenzo-p-dioxins and dibenzofurans (PCDD/PCDF).
   In late October  1991,  fires  in  West Virginia, Georgia,  Kentucky, South  Carolina, North
Carolina, Tennessee  and Virginia burned  over 100,000 acres of forest and brush.  Smoke from the
     Virginia fires was carried on southeast winds blowing at low levels through Ohio. The  low
                                         927

-------
level winds plus a high pressure air system prevented vertical mixing of the smoke and haze,  fo
central Ohio, approximately 200 miles northwest of the fires, visibility was limited to about 1 mile
on Wednesday, October 30, approximately five days after the fires had started.  On October 30 at
3:15 p.m., Battelle initiated ambient air sampling using two  PS-1 samplers with polyurethane foam
plugs (PUP).  Sampling  was conducted on the roof of the southernmost building at the Battelle
complex in  Columbus,  Ohio.    The  samplers  were  positioned 21  feet  above  ground leva.
approximately one quarter of a mile due east of a major north-south expressway. The general area
is residential with a few light industrial sources to the south  and west.  Meteorological data for the
sampling period is presented in Table I.  On October 31 after the wind direction had shifted to the
north,  the samplers were shut down and the samples were  recovered and returned for analysis of
PAH and PCDD/PCDF.   On November 1, with a return of the  wood  smoke air parcel, a grab
sample of the ambient air was taken with a SUMMA canister and analyzed for volatile organic
compounds (VOC) and selected inorganic species.

EXPERIMENTAL METHODS
    For PAH analysis, the particulate filter and PUP from  one PS-1 sampler were combined  and
extracted in Soxhlet apparatus for 16 hours with n-hexane containing 10 percent diethyl ether.  The
resulting  extracts  were concentrated  using  K-D  techniques,   and an  internal  standard, 9-
phenylanthracene,  was added for quantification purposes.  The sample extracts were analyzed for
selected PAH compounds using gas chromatography/mass spectrometry  techniques.  One field blank
and a laboratory method blank were also analyzed.
    The second  PS-1  ambient air sample  was prepared and analyzed  for PCDD/PCDF.  Sample
preparation  consisted of solvent extraction of the combined PUF and filter in Soxhlet apparatus and
acid/base washing and silica, alumina,  and carbon column  cleanup  of the resulting extract.   The
cleaned extract was analyzed  for  PCDD/PCDF using  gas chromatography/high  resolution  mass
spectrometry techniques.  A second  PS-1 field blank and a  laboratory method blank were  also
analyzed.
    Analysis of the SUMMA canister sample consisted of cryogenic preconcentration to transfer the
canister contents to the analytical system.  Analysis was conducted by gas chromatography using
 flame ionization detection.

 RESULTS AND DISCUSSION
    The results  of the VOC  analysis are  compared to typical ambient concentrations  in Table fl-
 Most  VOC  concentrations were significantly  higher in the Columbus 1991 forest  fire  sampling'
 Similar results were found in a monitoring of emissions from slash burning with ethane as the major
 component  of the emissions.5  The volatile analysis also included the total nitrogen oxide species
 (NCy) which was 60 ppb of which approximately 48 ppb was NO,.
    The results of the PAH analysis are presented in Figure  1 for the four PAH compounds detected
 at highest levels in the  forest  fire air samples. The figure also includes comparative data from a
 1984  study  conducted by Battelle which used PUF as a collection media and a 1988 study which
 used XAD-2 resin as a collection media. The XAD-2 resin  is the preferred trapping media for PAH
 compounds  due to the higher trapping efficiency for the more volatile  compounds  however,  only
 pre-cleaned PUF was available at the  time of the air pollution incident.  As shown, ambient air
 concentrations in Columbus for these four PAH compounds  were significantly higher on October 30,
  1991  than  on previous  dates.   Retene, an expected PAH  emission from wood combustion, was
 detected at 32 ng/m3 compared to typical ambient concentrations of approximately 0.5 ng/m*.  Less
 volatile PAH compounds (i.e., BaP) showed no significant change in concentration.  Current results
  have been corrected for blank levels which for some compounds were somewhat above normal blank
  levels.
                                              928

-------
    Results ftom PCDD/PCDF analysis are presented in Figures 2 and 3.   Concentrations were
   ow 1.2 pg/m3 for all PCDD congener classes. TCDD were not  detected.  For PCDF congener
 classes, the highest concentration was  obtained for TCDF which was 0.3 pg/m3.   PCDD/PCDF
 feadts are also compared to typical ambient concentrations in Figures 2 and 3 using PCDD/PCDF
 ambient  air data collected at several Ohio locations.6   This comparison shows  PCDD/PCDF
 concentrations in (he October 1991 sampling were not significantly different than typical ambient
 levels.  In Figure 4, PCDD/PCDF data from this study are compared to ambient air concentrations
 Jefermined directly in a  forest fire plume.7  Concentrations of HxCDD,  HpCDD, OCDD, and
 TCDF congener classes were highest of all PCDD/PCDF congener classes in both the direct plume
 analyses  and the Columbus 1991 data.  The  Columbus 1991 concentrations, however, were  much
 J^er man the direct forest fire data suggesting that PCDD/PCDF were not generated in the West
 Virginia forest fires or, if generated, were not transported as tar as Columbus.


 CONCLUSIONS
 t  The results of the one day sampling event conducted during a severe air pollution episode caused
 V emissions from forest fires indicate: (1) emissions of volatile hydrocarbons especially ethane are
 ^creased as expected: (2) levels of many of the 2- to 4-ring PAH compounds were significantly
 ^creased but BaP which is usually associated with combustion sources did  not show a significant
 ^crease;  and  (3) PCDD/PCDF concentrations were not significantly different than typical ambient
 levels and were lower than levels determined directly in forest fire plumes.

 REFERENCES

 *• W.R.  cofer m,  J.S. Levine, D.I. Sebacher, EX. Winstead, PJ.  Riggan, B.J  Stocks,  LA
   *ass, V.G. Ambrosia and PJ. Boston, 'Trace gas emissions ftom chaparral and boreal forest
   fres." J. Geophys BMaamh 94(D2): 2255 (1989).
2- J.L. Stith, L.F. Radke and P.V. Hobbs, "Particle emissions and £e Production of ozone and
   nitrogen oxides from the burning of forest slash/ Alimffi. Environ. 15: 73 (1981).

3- D- A. Heee L F  Uadte P V Hobbs and C.A. Brock, "Nitrogen and sulfur emissions ftom the
          lSf fores*! products* near  large urban areas,'  J  rKPpfiys.  Research 92(D12):  14,701
                    products
   (1987).

4' K.R. Smith, 'Air pollutant emissions, concenttations, and exposures ftom biomass combustion:
   «te cigarette^ analogy," in PjfflffifoP "f ^  1QJU ACS Meeting" Dlvl"on of Fael Gffimsttv'
   American Chemical Society, Washington, DC,  August, 1984.

5- D.V. Sandberg, 'Emissions from  slash burning and the influence of chemicals," J.  Ail Poll.
   C&QL^Ajs^ 25(3) (1975).

6' S.A. Edgerton,  J.M. Czuczwa, J.D. Rench,  ILF  Hodanbosi and P^.Koval,  "Ambient ak
   concentrations  of polychlorinated-p-dioxins  and  dibenzofurans in  Ohio: source  and  nsk
   assessment," Chemosphere 18:1713 (1989).

7> R-E  Clement and C Tashiro  "Forest fires as a source of PCDDs and PCDFs," in Abstiactt of
                                                       aTKl Kclated CQmPwnda,  Research
   Triangle Park, 1991, pS34.
                                         929

-------
Table I. Meteorological conditions during forest fire sampling.
Date
Oct. 30
Oct. 30
Oct. 30
Oct. 31
Wind
Time Direction
(EST) (Degrees)
00:50 120
12:50 130
23:50 20
05:50 350
Wind Speed
(Knots)
5
3
3
5
Table II. VOC concentrations in Columbus
Compound
Ethane
Ethene
Propane
Acetylene
i-Butane
n-Butane
Propene








Forest Fire
48
14
16
9
4
10
21
Barometric
Pressure
Temp. (°F) (in. Hg)
61 29.42
65 29.34
56 29.25
54 29.24
ambient air (ppb).
Typical Range
2-8
3-6
1-4
1-3
1-3
3-8
0.5-2
                            930

-------
   Fluorene  Phenanthrene Ruoranthene   Pyrene
           OCT91
1988
1984
Figure 1.  PAH concentrations in Columbus ambient air.
Tetra-CDD Penta-CDD Hexa-CDD Hepta-CDD Octa-CDD
               OCT91
      1989
Figure 2.  PCDD concentrations in Columbus ambient air
                   931

-------
  Tetra-CDF Penta-CDF Hexa-CDF Hepta-CDF Octa-CDF
                 OCT91
1989
 Figure 3. PCDF concentrations in Columbus ambient air.
 TCDD PeCDD HxCDD HpCDD OCDD TCDF PeCDF HxCDF HpCDF OCDF
        COLUMBUS 1991
 CANADA 1990
Figure 4. Comparison of PCDD/PCDF levels in forest fires.
                       932

-------
            EVALUATION of the IMPACTS  of an

          RDF  FUELLED  INCINERATOR on AIR

              TOXIC CONCENTRATIONS in the

                         WINDSOR AREA

                                  T. Dann
                             Environment Canada
                          Conservation and Protection
                   RRETC, River Road, Ottawa, Ontario Kl A OH3
 ABSTRACT
   The
                                                                .     ,
  he construction in Detroit of a large (2,400 ton/day) RDF fuelled mcinerato, 'jWonly
  control technology aroused concerns over its potential impacte on air quality in the
  sor area. In rSn« to these concerns, Environment Canada began « comDrehenaJve
  oring program for PCDD/PCDF, PAH, chlorinated benzenes, chlorinated Phenols and
  s at one site in Windsor (6.5 kin from the incinerator) and one rural site on Walpole
   . (55 km Lm ^eincirferator). The monitoring began two years before ' commgs'onmg
   incinerator and has continued since the facility began ^^Sj^^
  '^?ent the results from the measurement program for 1987 to ^f ™JJ
   sis on PCDD/PCDF data. Use of high resolution mass spectrometry and
fjft volumes allowed detection levels of f fg/m3 to be ^^^S
Fs during the samuline program.  Statistical analysis of the pre and
         ng  e samune program.   a
         data i^C^tKTanalysis of correlations between wind; direction and
                                               at the Windsor site.  This
f pressed as 27-TC]toic equivalents, was
equalled 30% of the total loading from all sources.

INTRODUCTION
„   Late in 1986  the Greater Detroit Resource Recovery Authority (GDRRA) began
instruction of a munfcipa? waste incinerator in Detroit Tlie unit was i design ed to b urn
2>400 tons per day of refuse derived fuel (RDF) to produce steam and electric ty. Since the
fa«litv was located oSy 6 km from the Canada-United States border and since pollution
ffiTOV'fc'SS consisted I of electrostatic precipite tors rather than the *e^ scrubber
Jabric Hlter combination considered to be best available control technology (BACT), public
«*cerns were raiSTgSSmg the potential impacts of the incinerator on air quality  in

J^^^to&SS^ Environment Canada established a. comprehensive
£°aitoring p^am £ U?e Windsor area for toxic substances associated ^incineration.
£ July i|8? ^1^^ began  at a site in Windsor located 6 km south of the ' ODRRA
gcmer ator and in January 1988 monitoring began at a rural site on Walpole Island in Lake
°^Clair located 55 km ENE of the facility.    .     .....     ,...  jata „,,-„. *« the
    The monitoring program began gathering ambient air quality data prior to the
      cial operation oftS incinerator so that a realistic assessment of the impacts of the
      on air quality in the Windsor/Walpole area could be carried out
pARAMETERS MEASURED AND SAMPLING METHODS     .       nmt>n^ nf
                                   933

-------
polychlorinated biphenyls (PCB), chlorinated benzenes (CB), chlorinated phenols (CP),
polycyclic aromatic hydrocarbons (PAH), volatile organic compounds (VOC), inhalable
participate matter (EP) and associated metals and ions. A summary of the  monitoring
protocols employed for each parameter, the  target detection levels and the sampling
frequency are given in Table I. Complete descriptions of sampling and analytical protocols
are available.1 Samples were normally collected over a 24 h period (midnight to midnight).
At both sites, dioxin/furan samples were collected over a 48 h sampling period beginning m
September 1988.  For the impact evaluation, data at both sites  were available from site
start-up to October 1990 for all parameters except PCDD/PCDF; these data were available
only to May 1990.

                Table I. Environment Canada ambient  monitoring protocols
                              Windsor / Walpole  Island.
Compound
PCDD/PCDF
PCDD/PCDF1
PCB
CB2
CP
PAH
Particulates

-------
     It should be noted that the incinerator is presently undergoing a retrofit program
which  will result in replacement of the electrostatic precipitators with dry scrubbers and
fabric filters  Each of the three boilers will undergo the retrofit with installation of BACT
on the first boiler scheduled for completion in December of 1992.  The program will be
complete by 1996.

RESULTS AND DISCUSSION
Overview of Results                              ,                ,   4 .,   ,„.  ,
     Table H presents mean concentrations of selected species measured at the Windsor
and Walpole Island sites that are known or suspect human carcinogens  Also contained in
the table are published EPA unit risk factors. A unit risk is the excess lifetime risk due to a
     ms o   eir conruon o  o                       ..    ,
considered absolute due to numerous factors including: uncertainties                  nf
factors, representativeness of monitoring site location, missing important pollutants, iacK ol
personal and indoor exposure data and lack  of data on exposure pathways other-than
inhalation. Exposure to PCDD/PCDFs expressed as 2.3,7,8-TpDD toxic equ,valente(TEQs)
accounted for approximately two percent of the calculated inhalation cancer risk at the
Windsor site and less than one percent of the total at the Walpole Island site.

         Table II. Mean concentrations (pg/m3) of selected toxics measured at Windsor and
Compound Name
*POM>
1,3-Butadiene
Benzene
Chromium'
Formaldehyde
Carbon tetrachloride
1,2-Dibromoethane (BOB)
Cadmium
Chloroform
Arsenic
2.3.7,8-TCDD (TEQ)
*Sum PAH*
Other

Mean Cone, at
Windsor Site

0.6 x 10 3
0.3
15
2 x 10 *
1.7
1.0
<0.1
11x103
0.2
1x10-3
0.11 x 10<
HL7 x 10 3
—

EPA Unit Risk
(per fig/m3)
0.92
2.8 x 10*
g.3 x 10 *
1.2 x 10 2
1.3 x 10 *
1.5 x 10-*
2.2 x 10 *
1.8 x 10 •*
2.3 x 10 *
«,3 x 10-3
33
2.2 x 10 '
—

Lifetime
Cancer Risk

8.U x 10 *
2.9x10*
2,il x 10 *
2.2x105
1.5 x 10 *
< 2.2 x 10 s
7.2 x 10 «
H.6 x 10 *
4.3x10-6
3.6x10*
3.2x10*
8.5 x 10*
Uxl(rMo«.2xlO-<
    1  B(a) P used as a surrogate for all polycyclics, EPA frCity Risk Factor Used
    2  Sum of 11 PAH with carcinogenic potency factor used.
       hexavalent form.                    .   .  _   ,
       Only one of the two values was used to calculate the Total.
                                .               D
*»H concentrate on Windsor PCDD/PCDF data.
                                        935

-------
PCDD and PCDF Measurements
     Prior to May 1989 the five homologue group totals (CU through Cla: tetra through
octa) were reported for both PCDDs and PCDFs.  Beginning in May 1989 isomer specific
analyses were conducted for PCDDs and PCDFs using a high resolution mass spectrometer
(HRMS). The HRMS technique provided results for seventeen 2,3,7,8 substituted isomers
and for PCDD/PCDF homologue group totals. Detection levels improved by factors of 10 (for
octa-CDDs) to 50 (for tetra-CDDs and tetra-CDFs) when HRMS analyses began.
     To ensure that the change in analytical methodology would not be a factor in the
impact analysis, two samples from each site were  selected for analysis by both low
resolution mass spectrometry and high resolution mass spectrometry.  For three of the
samples, results for homologue group totals agreed within five to ten percent. For one of the
Walpole samples the HRMS penta and hexa-CDF results were higher than the LRMS
results by a factor of approximately three.
     Total TEOs for the PCDD/PCDF mixtures were calculated for each day with HRMS
data by multiplying the concentration of each 2,3,7,8 substituted isomer times its toxic
equivalency factor (using international TEFs) and summing. For values below detection,
the detection limit for the isomer was substituted. The relative distribution of PCDD/PCDF
isomers and homologue group  totals was very similar at the two sites.  At both sites the
PCDD homologue group concentrations increased with increasing chlorine substitution (Cls
 > Cl? > Cle etc.)  whereas the PCDF concentrations decreased with increasing chlorine
substitution.  Excluding octa-PCDD and octa-PCDF, the 2,3,7,8 substituted isomers found
in the highest concentrations were 1,2,3,4,6,7,8-heptachloro dibenzo-p-dioxin, 1,2,3,4,6,7,8-
heptachloro dibenzofuran, 2,3,7,8-tetrachloro dibenzofuran and 1,2,3,4,7,8-hexachloro
dibenzofuran.  At the Windsor and Walpole island sites the  2,3,7,8  substituted
dibenzofurans accounted for over 70%  of the computed TEQ values. Three furan isomers
alone accounted for over fifty percent of the TEQ; these were 2,3,4,7,8-pentachloro dibenzo-
p-dioxin, 2,3,7,8-tetrachloro dibenzofuran and 1,2,3,4,7,8-hexachloro dibenzofuran.  The
isomer  2,3,7,8-TCDD was detected in 12 out of 17 samples  at Windsor with a mean
concentration of 11 fg/m3 and in 4 out of 10  samples  at Walpole Island with a mean
concentration of less than 2 fg/m3.
     A correlation analysis was also  carried out between TEQ, the 2,3,7,8 substituted
 isomers and the homologue group totals. Because the furans accounted for most of the
 computed TEQ it is not surprising that there was an excellent correlation between TEQ and
 Total PCDF at both sites (r > 0.95).  Linear equations between TEQ and Total PCDFfor
 both sites were developed and these equations were used in turn to estimate the TEfeJ
 concentrations of samples collected prior to May 1989 which were analyzed using a LRMb
 technique. Despite total PCDD and PCDF concentrations being a factor of eight lower at
 Walpole Island than at Windsor the equations relating TEQ to PCDF were essentially the
 same for both sites. For the  period May 1989 to  1990 the mean TEQ concentration at
 Windsor was 0.17 pg/m3 and at Walpole Island it was 0.03 pg/m3. For 1987 to 1989 (using
 estimated TEQ) the mean TEQ concentration at Windsor was 0.11 pg/m3 and for 1988 to
 1989 the estimated mean TEQ for Walpole Island was 0.02 pg/m3.

 Impact Assessment for PCDD/PCDF at Windsor Site                           ,
      All PCDD/PCDF data for the period July 1987 to May 1990 (35 sampling periods) for
 the Windsor site were used in the assessment. Wind speed and wind direction data fro01
 Detroit City Airport were also obtained.                                           _,
      To evaluate the potential impacts of the GDRRA incinerator on PCDD/PCU*
 concentrations at the Windsor site, two statistical tests were used. The first involvefl
 grouping all measurements into two categories based on whether RDF fuel was burned at
 the facility. Samples collected on the days before the incinerator began operation plus those
 collected on days when the facility was shut down (ie.  0 tons of RDF burned) were put in the
 no RDF burned category. All other samples were put in the category of RDF burned. A
 Mann-Whitney test was used to determine if the median concentration measured on days
 when RDF was burned was significantly (at the 95% confidence level) greater than  the
 median concentration measured on days when no RDF was burned.
      As shown in Table m,  median  concentrations of tetra through hepta PCDD, total
 PCDD, tetra through octa PCDF and  total PCDF at Windsor were statistically greater on
 RDF burn  days than on no-burn days.  However, the  two  sample median
                                       936

-------
 test alone is not a conclusive indicator that the facility is responsible for increases in
 anibient air concentrations of toxics.  The RDF burn and no burn days are not randomly
 distributed throughout the data set but are associated with specific time periods i.e. all the
 burn days are in toe period January 1989 to May 1990 and almost all the no burn days were
 m the period July 1987 to January 1989.  Thus other factors such as the commissioning of
 new sources in the airshed, meteorological differences between 1987-89 and 1989-90 and/or
 changes in sampling and analytical methodology with time could  be responsible for the
 aPparent increase in selected parameter concentrations on days on which RDF was burned.

    Table 111. Comparison of median PCDD/PCDF concentrations (pg/m3) for RDF bum and no-
                *         .     _    	. +      ••    . •• _ _  j	
Parameter
TilCDD
PsCDD
H6CDD
H7CDD
OCDD
TOTAL PCDD
'I'uCDF
H5CDF
H6CDF
H7CDF
OCDF
IUTAL PCDF
*,3,7,8-TEQl
RDF Burned Days
No. of
Samples
16
16
16
16
16
16
16
16
16
16
16
16

No.<
Detect.
1
1
0
0
0
0
0
0
0
0
0
0
0
Median
0.219
0.397
0.777
0.937
0.962
3.966
0.822
0.955
1.079
0.559
0.176
3.958
0.108
No RDF Burned Days
No. of
Samples
19
19
19
19
19
19
19
19
19
19
19
19
19
No.<
Detect.

15
5
2
0
0
q
9
8
8
8
0
0
Median

0.065
0.217
0.416
0.810
1.513
0.190
0.065
0.083
0.090
0.105
0.420
0.020
Median Test
Signif. Level
0.01*
0.01*
0.01*
0.01*
1.00
0.01*
0.01*
0.01*
0.01*
0.01"
0.05*
0.01*
0.01*
' Median of RDF burn toy, significantly 'greater th n median ol no Kl» bun. toy* a( UU, Lo,,.lUc,,c« Lc««i
1 Estimated
          other
                         method applied was  multiple  regression.   The hourly
'eteorologicaTobservations were processed and the  following parameters were calculated
* each sampling day mean wind vector direction, mean wind vector magnitude, mean
|nd speedaSd^otal JoSs with wind from 22.5° sector centered on 354° (bearing between
    sor site and GDRRA). Recession analysis was then earned out between pollutant
expected between concentration and increasing ange o win  irecion.   n  -es was  en
u«ed to calculate the statistical significance of the slope of the linear equations relating
concentration to tons of M)F buried and relating concentration and  wind direction.  A
8tetistically inSSant F-value (at the 95% confidence  level) implies that there is no
Meaningful relafionship between the variables.  Table IV shows the computed correlation
c°efficie"£ ^betweeTconcenSns of selected PCDF congener classes for Windsor and tons
°f.RDF burned hou« of wind and mean wind vector. The strongest re ationships (for both
**nd direction and tons of RDF burned) were found for hexa, hepta and total PCDF.

     To further exnlore relationships between pollutant concentrations and wind direction
* serie ?of pollutSS ?rose plots were prepared. Tnese consist of a plot of concentration versus
Predominant ^SamplKriod^ndPdirection where wind directions were assigned to one of
                                       937

-------
               Table IV. Multiple Correlation Coefficients for PCDD / PCDF
                                Windsor 1987-1990.

RDF
HRS 3541
Wind Dir.z
T.CDF
0.509*
0.140
-0.353*
P,CDF
0.503*
0.204
-0.306
H(CDF
0.523*
0.393*
-O.M3*
HjCDF
0.478*
0.465*
-0.409*
OCDF
0.350*
0.148
-0.210
Total
PCDF
0.536*
0.295
-0.387*
                                  —i 6t.a sector centred on 35'l°
                     * Difference between mean wind vector direction and 35>r
                        * significant at 95 X confidence level or greater

sixteen 22.5° sectors. These plots show the association between concentration and wind
direction and can indicate locations of contributing sources.  Figure 1 provides mean total
PCDP concentration by wind direction at the Windsor site for RDF burn and no RDF burn
days. As shown in the figure, higher PCDF concentrations occur on RDF burn days and the
highest concentrations are associated with winds coming from the direction of the GDRRA
incinerator. Higher concentrations on RDF burn days also occurred with wind directions
from the west and west-southwest suggesting that there were  increased emissions from
other sources during the time that the GDRRA facility was operational.
                       North
     North
             No RDF Burned
                   19 Days
RDF  Burned
    16  Days
            Figure 1. Total PCDF concentrations (pg/m3) by wind direction • Windsor.
                                       938

-------
    Although there are still a number of uncertainties in the analysis, it appears that the
^wuaoissioning of the GDRRA incinerator resulted in an increase in total PCDF exposures
at the WinJ«n* »n^^iine site  since the parameter total PCDF was highly correlated with
                fculate a "worst-case" impact evaluation for the facility as shown
                 GDRRA Impact Evaluation - Windsor


 Mean TEQ Cone, on RDF Burn Days with Wind from NNW N 01r NNEi==836feJnS  (1)
 Mean TEQ Cone, on NO Burn Days with Wind from NNW, N or NNE - 26 fgfmS.   (2)

 AJ~— rSSlL" > - 309 fg/m   ^^ ^.^ w-nd fr()||J Dli-cctiuiis Other than NNW, N or
    	w wind rose for Detroit City Airport, wi nd directions from NNW, N and

    ^^cted'TEQDo^ASributabletoGDRRA Facility = 0.163*309 = SOfefe*.
       ibutobl? to Other?c-urces = 122 * 0.837 + 26 * 0.163 - 106 fg/m3
       L! >n of facility = 50/(50 + 106) = 32% of total.	



^.«sff^Baaff^£.?f^SSS3
  ... w?, ^-^gBaSS^asSsAs

                      risk for toxic substances in Windsor, 2,3,7,8-TCDD was act
                      "risk (2%) hence the GDRRA incinerator is not likely to be
                      nBKl___'TTC—j ««  thfl inhalation pathway a
   »eant contributor to overall risk (    ence e
^?. 'mportant factor in total risk assessment based on the inhalation

Wlndsorsite
             . 1M»tt
         1990. PMD90-8,
                            Monitoring
                                           DaU Report 4". BRETC,
                    ,

                ^^
     stion, Tampa, PL.
450/^0" .»• EpA (1990). "Cancer Risk from Outdoor Exposure to Air Tories". Report EPA-
 u'l-90-004a.

                  ^
         Quality", RRETC, Ottawa , February 1992. PMD 92-1.
                            939

-------
 THE DIOXIN/FURAN EMISSION PROFILE FOR
AN RDF FIRED RESOURCE RECOVERY FACILITY
                    By

              James C. Seme, PE

                     of

            ROY F. WESTON, INC.

              Raleigh, NC  27607
Presented at the EPA/AVVMA International Symposium


  Measurement of Toxic and Related Air Pollutants
                May 3 - «, 1992

            Durham, North Carolina
                     940

-------
                      INTRODUCTION AND BACKGROUND

       The stack emissions of dioxin/furan from resource recovery facilities (RRF) or
 municipal waste combustors (MWC) and the predicted ambient air quality impacts of the
 these emissions have been the focus of much research, as well as public concern. Although
 there are many other sources of dioxin/furan emissions, RRF or MWC have received much
 of the public's attention and opposition. EPA in February of 1991 set emission limits for
 dioxin/furan for MWC (40 CFR Part 60 Subpart Ea).   These emission limits  became
 effective on August 12,  1991, for facilities at which construction,  modification  or
 reconstruction commenced after December 20,  1989.   Dioxin/furan is defined in the
 regulations as the total tetra through octa chlorinated dibenzo-p-dioxins and dibenzofurans.
 For large MWC (greater than 250 tons per day MSW or RDF combustion capacity) the
 emission limit is 30 nanograms per dry standard cubic meter (dscm) corrected to 7 percent
 Oxygen.  EPA Reference Method 23 is specified for use in determining compliance with a
 minimum sample time of 4 hours per test run. An initial  compliance test and then annual
 performance tests for dioxin/furan are required for new MWC and RRF,

       EPA  also  set  emission  guidelines  for  MWC  that  commenced  construction,
 modification  or reconstruction on or before December 20, 1989.  (40 CFR Part 60 Subpart
                                                    ,
    . Different guideline values ranging from 60 to 250 nanograms per dry standard cubic
meter (dscm) corrected to 7% oxygen were specified based on the size and type of MWC
facility.

       Dioxin/furan emissions data from a very large RDF fired RRF are reported in this
Paper.  The facility processes municipal solid waste (MSW) using on-site shredders, sizing,
sorting and classifying equipment.  A fluff type RDF is produced that is burned in three
boilers each rated al approximately 1000 TPD.  Following  heat  recovery, a five field
electrostatic precipitator controls the emissions from the facility. The facility commenced
construction in the mid 1980's and began operation in July of 1989. The emission limit for
the facility contained on the permit is 0.0043 Ib/hr of total (tetra through octa) dioxins and
furans. The facility dioxin/furan emissions have been measured on six occasions since July
1989 and the permit limit mass emission rate has been met during all of these tests. Some
of the results of these dioxin/furan emission tests are summarized in the following pages.
h addition to  the compliance test programs, WESTON performed research or diagnostic
emission tests by sampling simultaneously at the inlet to the ESP and at the stack of each
°f the three boilers.

      The facility is currently retrofitting a new air pollution control system on each of the

-------
The control system retrofit for the first boiler is scheduled to completed in December 1992.
The second and third boiler control system retrofits are scheduled to be completed at the
end of 1994 and 1996, respectively.

      The  change  from ESP control to  scrubber-baghouse  control is  expected  to
significantly reduce the dioxin/furan emissions.  The retrofitted facility will meet the NSPS
(40 CFR Part 60 Subpart Ea) emission limit of 30 ng/dscm. Dioxin/furan emission data for
MWC facilities equipped with scrubber-baghouse control systems are presented in Reference
2.

                         TOTAL PCDD/PCDF EMISSIONS

       The facility permit limit for dioxin/furan and Subparts Ca and Ea for MWC apply
to the total tetra though octa chlorinated dibenzo-p-dioxins and dibenzofurans. Typically,
the reports documenting the emission test programs at the facility only reported total PCDD
and PCDF  emission concentrations and mass  rates for comparison to the permit value.
Four different testing firms have performed dioxin/furan emission testing at the facility.
Data from four of the six test programs are summarized in Table 1.

       Emissions data  for four different test programs performed between July 1989 and
October 1991 were reviewed. A total of eight sets (three test repetitions per set) of boiler
emission data were available. The total dioxin, total furan and total dioxin and furan results
were used to  determine the percentage or proportion of the total represented by dioxin.
The results were extremely consistent.  Total dioxin (tetra through octa) accounts for 75%
of the total dioxin and furan. The percentages ranged  from 21 to 31% with a single value
 at 4%, which appears to be an outlier. Conversely, total furan account for 75% of the total
 dioxin and  furan.  Furans consistently  represent about 70 to 80 percent of the combined
 total dioxin/furan emissions.  Each of the three boilers and air pollution control systems are
 similar in size  and design.  Dioxin/furan mass  emissions from the  three boilers were
 compared.  The mass  emission rate  from one of the boilers was often 50 to 100 percent
 higher than the other boilers during  the various test programs. No identifiable reason for
 this difference was found. All three  boilers  have consistently met the allowable or permit
 mass emission rate for dioxin/furan so  the boiler with the higher emissions was not subject
 to any special evaluation. The isomer specific  data discussed below are for the boiler with
 the higher emission rate.

                             ISOMER SPECIFIC DATA
                                         942

-------
        The analytical reports contained in the appendices of some of the test reports provide
 isomer specific dioxm/furan data.  These data were used to develop a isomeric profile of
 the facility emissions.  Table 2 provides isomer specific dioxin and furan data for one of the
 boilers for the average of three runs conducted during the initial compliance tests in July
 1989 and for the same boiler during tests conducted in October 1991.  These data are
 illustrated in Figures 1 and 2.

        Figure 1 illustrates the dioxin and furan isomer and homologue profile for the three
 test repetitions performed on Boiler #11 in July 1989. The tetra through octa homologues
 of dioxin are all present with the penta, hexa and hepta homologues found at slightly higher
 concentrations.  Tetra, penta and hexa homologues of furan are predominant with very little
 °cta furan present.

        Figure 2  illustrates the dioxin and furan isomer and homologue profile for three test
 repetitions performed in October 1991 on the same boiler. The profiles are similar although
 the relative concentration of the octa dioxin homologue is less than that present in the July
 1989 test program.

                        ESP INLET VERSUS OUTLET DATA

       The  dioxin/furan emissions while less than the permit limit, were higher than
 anticipated. In April of 1990, diagnostic emission test program was conducted by WESTON
 to study the dioxin/furan emissions from the stack, as well as at the  inlet to the ESPs on
 each of the three boilers. These samples were collected using EPA Method 0010 (Modified
 Method 5 train) and analyzed by Method 8290.  The front-half solvent and filter were
 combined and extracted to provide the paniculate portion of the sample train. The XAD-2
 resin, back-half condensate and back-half solvent portions were combined and extracted to
 provide the gaseous portion of the test train.

      The analysis thus yielded information on paniculate versus gaseous dioxin/furan,
 whereas most analyses combine all the sample fractions and yield only combined gaseous
 and  paniculate  dioxin/furan  data.   The analysis  also quantified  mono,  di, and tri-
 homologues in addition to the tetra through octa homologues generally reported.  The data
 for the  Boiler #11 ESP inlet sampling location are summarized  in Table 3,  Table 4
 provides these same data for the Boiler #11 stack location.

      The data from these tests indicated that the dioxin/furan  emissions increased
 significantly in the ESP.  Stack concentrations of total dioxin/furan ranged from 3 to 7 times
higher than the ESP inlet concentrations.  Table 5 provides a summary of the ESP inlet and
outlet data and the average  ratio of the outlet to inlet mass rate for each isomer.  The
                                       943

-------
formation of dioxins and furans in control devices such as ESPs has been researched by US
EPA in pilot scale or bench scale studies and has been reported by others. The percentage
of the total dioxin/furan accounted for by total dioxin was 24% at the ESP inlet and 29%
at the stack. These values are consistent with the results for stack tests reported earlier in
this paper.

                  GASEOUS VERSUS PARTICULATE FRACTION

      The portion of each homologue found in the particulate fraction ranged for 79% to
90% at the ESP inlet. The more chlorinated homologues of dioxin are more likely to be
found in the particulate fraction. The same observation holds true for the furans at the ESP
inlet. Table 6 provides a summary of the average percentage of each homologue reporting
in the particulate fraction of the sample train.

      At the stack, the difference  in distribution of dioxin between the particulate and
gaseous fractions at different numbers of chlorination was more evident. The mono and di
chlorinated dioxins are mostly found in the gaseous fraction of the sample train, while the
more highly  chlorinated dioxin homologues are predominantly  found  in the particulate
fraction. The furans follow this same pattern.  The temperature of the exhaust gas at the
ESP inlet was approximately 625 °F, and the stack gas temperature was  approximately 325
                     LESSER CHLORINATED HOMOLOGUES

       The mono, di and tri dioxin homologues accounted for about 12 % of the total mono
 through octa dioxin at the ESP inlet and 9% at the stack.  The mono, di and tri furan
 homologues account for about 42% at the ESP inlet and 24% at the stack of the total mono
 through octa furans.  The mono, di and tri homologues are generally not reported because
 their toxicity is low and the emission limits are typically specified in terms of tetra through
 octa PCDD and PCDF.

                                   SUMMARY

       An abundance of dioxin/furan emissions data are available for municipal waste
 combustors and resource recovery facilities, as a result of annual or semi annual compliance
 test requirements. Often only the total PCDD and PCDF emission concentration and mass
 emission rates are reported, although isomer specific analytical data often exist in these
 emission test reports.  Emission data for a large RRF burning  RDF was investigated to
 better understand the dioxin/furan emission profile and characteristics.

       Approximately 75% of the total PCDD/PCDF emissions are PCDF. The relative
 proportions  of  total dioxin and total furan is  very  consistent for  the  facility.  The
 dioxin/furan emission concentration and mass emission rate from similar boilers with similar
                                        944

-------
pollution abatement systems can be quite different.

      Dioxin/furan concentrations can significantly increase in an electrostatic precipitator.
The stack concentrations of dioxin/furan were 3 to 7 times higher than the concentrations
measured at the inlet to the ESP.

      The majority (over 70%) of the tetra through octa dioxin and furan are collected in
the paniculate fraction of the sampling train. Only a small amount, about 10%, of the total
dioxin are in the mono, di and tri homologues.  About 25% of the total'furan are in the
mono, di and tri  homologues.  These lesser chlorinated  homologues are generally not
reported.
                                 REFERENCES

!•     Federal Register Volume 56, Number 28
      February 11, 1991

2-     Siebert, Paul C, and Alston-Gulden, Denise
      "Air Toxics Emissions from Municipal, Hazardous, and Medical Waste Incinerators
      and the Effect of Control Equipment," Paper 91-103.15
      Presented at AWMA Annual Meeting, June 1991, Vancouver, BC.
                                     945

-------
                TABLE 1
SUMMARY OF TOTAL PCDD / PCDF EMISSIONS DATA
TEST DATE BOILER* RUN # TOTAL PCDD/PCOF PERCENT PCDD MASS EMISSIONS
(ng/dscm) (%) 0b/hr) ^__
July 1989 11 1
2
3
I Average |

12 | Average |

13 | Average |

September 1990 11 1
2
3
( Average |
12 1
2
3
[ Average |
13 1
2
3
j Average j

February 1991 11 1
2
3
| Average |
12 1
2
3
I Average |

October 1991 11 1
2
3
I Average |
13 1
2
3
I Average |
2,437
3,300
2,869
2,869
3,292
8,265
2,400
3,300
8,600
4,767
4,260
1,800
1,600
2,553
2,000
1,700
1,200
1,633
4,900
3,500
3,300
3,900
1,900
900
1,400
1,400
4,272
4,259
4,474
4,335
3,607
3,806
2,622
3,345
27
24
25
I 25 |

I 19 |

1 26|

24
20
29
1 261
24
22
24
1 23|
31
24
23
I 27' |

30
29
31
1 30|
24
31
4
I 20 |

25
24
21
1 231
22
23
24
1 231
0.00125
0.00157
0.00184
0.00155
0.00178
0.00445
0.00130
0.00190
0.00490
0.00270
0.00251
0.00120
0.00093
0.00155
0.00110
0.00095
0.00068
0.00091
0.00290
0.00210
0.00190
0.00230
0.00107
0.00050
0.00086
0.00081
0.00248
0.00245
0.00251
0.00248
0.00212
0.00225
0.00155
0.00197
                    946

-------
                       TABLE 2
        SUMMARY OF ISOMER SPECIFIC DATA
                     BOILER #11
Isomer

DIOXIN
2,3,7,8-TCDD
1,2,3,7,8-PeCDD
1,2,3,4,7,8-HxCDD
1,2,3,6,7,8-HxCDD
1,2,3,7,8,9-HxCDD
1,2,3,4,6,7,8-HpCDD
Total TCDD
Total PeCDD
Total HxCDD
Total HpCDD
OCDD
TOTAL PCDD
RJRAN
2,3,7,8-TCDF
1,2,3,7,8-PeCDF
2,3,4,7,8-PeCDF
1,2,3,4,7,8-HxCDF
1,2,3,6,7,8-HxCDF
o a A e t O-UvfnC
JULY 1989
(ng/dscm)

5.38
17.20
12.00
10.74
36.10
53.67
108.3
157.3
195.7
159.0
101.8
722.1

107.30
33.67
52.77
126.33
53.63
2.28
OCTOBER 1991
(ng/dscm)

23.60
33.30
20.03
26.77
56.23
101.53
292.3
348.3
362.0
198.3
80.9
1281.8

51.97
90.13
86.97
152.33
81.43
3.32
    1,2,3,7,8,9-HxCDF
  1,2,3,4,6,7,8-HpCDF
  1,2,3,4,7,8,9-HpCDF

Total TCDF
Total PeCDF
Total HxCDF
Total HpCDF
OCDF
 47.40
171.00
 10.47

 665.3
 618.7
 571.7
 250.3
  39.0
 61.70
117.93
 15.57
1776.7
1263.3
 681.7
 216.3
  36.8
                                         3974.8
TOTAL PCDD A PCDF
                       947

-------
          TABLE 3
ESP INLET DIOXIN / FURAN DATA
            (ng)
HOUOLOGUES
MonoCDD
01CCO
TriCCD
TetraCDO
PemaCOD
HsxaCOD
HeptaCDD
OctaCDD
Total Mono-Octa COD
Total Tetra-Octa COD
MonoCDF
DiCCF
TriCCF
TetraCDF
PentaCDF
HexeCOF
HeptaCOF
OctaCOF
Total Mono-Octa CDF
ToM Tetra-Octa COF
TOTAL PCDD 4 PCOF
PCDD%bi TOTAL
RATIOS


RUN1
%in
Parfculate Gaseous Total Particle*
0.40 NO 9.40 100%
43.8 2.80 46.6 94%
104 20.6 125 83%
254 67.6 322 79%
215 49.7 265 81%
253 48.0 300 84%
102 8.70 201 96%
164 12.1 176 93%
1,235 208 1.443 86%
1,078 185 1.263 85%
55.10 0.13 55.23 100%
602 14.6 617 08%
1.280 186 1.476 87%
426 104 620 60%
690 160 868 81%
353 70.3 423 83%
152 18.0 171 89%
4SJ 4.00 49.3 92%
3.822 657 4,279 85%
1.87S 456 2.132 79%
2,753 641 3.394 81%
39% 29% 37%
0.87 0.80 0.87
0.46 0.69 0.50
RUN 2
Paniculate Gaseous Total ParrJde*
NO NO NO NO
2.90 2.30 5.20 56%
30.3 16.8 47.1 64%
108 81.7 188 58%
88.2 57.5 146 81%
154 68.4 222 69%
125 35.1 160 78%
144 23.8 167 86%
650 286 936 69%
617 266 883 70%
0.25 0.18 0.41 81%
39.6 28.9 68.5 58%
465 353 818 57%
654 510 1.164 56%
485 285 770 63%
281 123 384 68%
110 38.4 146 75%
38.5 6.40 44.8 86%
2.053 1.343 3.396 60%
1.540 961 2.609 62%
2.166 1,227 3.393 64%
28% 22% 26%
0.95 0.93 0.94
0.75 0.72 0.74
RUNS
Paniculate Gaseous Total Particle*
1.10 1.50 2.60 42%
162 9.7 25.9 63%
79.7 15.3 95.0 84%
95.3 39.6 135 71%
86.3 22.1 108 80%
118 32.0 150 79%
100 14.0 115 87%
86.4 928 95.6 90%
583 144 727 80%
486 118 604 80%
13.7 29.7 43.4 32%
319 308 625 51%
1.020 360 1.380 74%
688 148 834 82%
540 138 678 80%
273 702 343 80%
104 20.8 125 83%
36.8 3.90 405 00%
2.902 1.077 4.069 74%
1,640 381 2,021 81%
2,126 499 2.624 81%
23% 24% 23%
0.83 0.82 0.83
0.66 0.3S 0.60
AVERAGE
ParticulatB
71%
71%
77%
69%
74%
77%
87%
90%
78%
79%
84%
69%
73%
69%
74%
77%
82%
89%
73%
74%
75%
0.88
0.58

-------
                                                  TABLE 4
                                        ESP OUTLET DKDXIN / FURAN DATA
HOUOLOGUE5
MoooCOO
mcco
TriCCO
TeHaCQD
PentaCDO
HwctCDO
H*f*«GDO
OetaCDO
Total Mono-Oota COD
Total Telra-OctuCDD
MonoCDF
DJCCF
TriCCF
T«tr«CDF
PentaCOF
ttexaCDF
ttopteCDF
OCUCOF
total Mono-OcUl CDF
Total T«ta-OetaCOF
TOT*LPCt»4PCDF
PCDD% In TOTAL
RATIOS
TBtn-OcntAlono-Octi D
Totra-OctnMono-Octa F
RUM
%in
ParBcuJnte Gumut Total Partfcto*
1 ND ND NO ND
01.3 94.2 166 39%
503 GOO 1,083 46%
ll 1,250 931 2.181 57%
i 1,310 664 1.074 66%
1.639 580 S JIB 74%
1.T79 323 1,502 70%
941 183 1.134 83%
I 8,884 3,375 10.25* «7%
«.3» 2.681 0j01 0 70U
ll 520 6.70 10.9 «1*
1 79* 1.290 2.084 38<)t
II 3.7SB S.I 10 «.369 42H
5.07B 4.300 10.278 58%
6.B5B 3,160 8.740 64U
3,379 1,«0 4.B90 72«*
1.260 380 1.640 77%
II 351 64 «* 81%
11 21.006 1S.679 36,766 57U
1«.«7 S.J73 25,801 64H
I 22,647 11,964 34.811 66W
I 26« 22% 2ftW
Si O.B2 OiO 0.33
0.78 O.S0 0.70
RUN 2

-------
                 TABLE 5
Summary of Dioxin/Furan Emissions in April 1990
                  (Ibsfftr)

Boiler dumber
HonolOQUe*
Tcoa
Mitet
Out**
TCDF:
brief
Outlet
PCDft
InteC
OutM:
PCOF:
Intot
Outlet
HxCDD:
Wet
Outlet
HxCOF:
Inlet
Outlet
HpCOtt
Met
Outtet
HpCOF:
Met
Outlet
ococt
Wet
Ouoet
OCOF:
Met
Outtet
TOTAL {MOON
Inlet
Outlet
TOTAL FURAW
WMfc
Outlet

11 12 T3 Awnge


3.SBE-OS 2.S1E-05 2.24E-05 2.91 E-05
ZJOE-04 1.31E-44 S.42E-05 1.48E-04

1.4SE-04 1ME-04 1.00E-04 1.48E-04
1.0SE-03 4.45E-04 3.31£-04 6.22E-04

2.B8E-OS 33SE-OS I.73E-05 2.85E-OS
212E-04 2.38E-04 1.23E-W 1.91 E-04

I^SE-04 2.02E-M 9.25E-05 1.41 E-04
9.M&04 B.ME-04 3.84E-4M 7.51 E-M

3.T4E-OS 4.58E-06 2.43E-05 3.S&E-OS
2.73E-04 3.ME-04 1.71 E-04 2.76E-O4

6.38E-05 1.33E-04 S.94E-05 S.SSE-OS
0.1 f E-04 •.32E-04 3.4ZE-M BOSB-O4

2.84E-05 2.7BE-06 t.3»E-OS J^TE-OS
1.81E-04 2.44E-04 1.3BE-04 1 B8E-04

2.4SE-05 4A5C-OS 2.106-06 3JfE-OS
2.17E-04 4.UE-04 1 45E-04 2.6IE-04

2.44E-OS 1,3tE-06 8.72E-08 1.WE-05
1.42E-04 V06C-04 7.4CE-OS 1.07E-04

7.4TE-OB 133C-OS 6.46E-08 »75E-Oe
«.o«e-o$ e.ose-os B.ITE-JK e.ME-<»

1A3E-04 1 .606-0* I.7C6-OS 1JOE-O4
1.03E-4S 1.10E-03 «.02E-04 9.11E-04

3.WEHM «.WE-04 2.79Er04 4.15E-O*
i.«et^» t.«SE-03 liStoa njzaE-ci
RATIO
OUTLETI
INLET


5. tO


4 JO


7J1


5.32


7.71


B.90


«JS


• .14


e.72


e.«4


7.00


(S.51

Bo9w Number
Itomera
2,3,7.8-TCDD:
Mat
Outlet
2A7.8-TCDF:
Met:
Outlet
2,3,7.8-PCC3D:
Met
Outlet
2,3.7.8-PCDF:
Jniet
Outtet
2.3,7.8-HxCOtt
Met
Outtat
2.3.7,8-HxCDF:
Met
Outlet
2A7,8-HpCDO:
tatot
Outh*
2.V^-HpCW=:
Met
OutM:

11 12 13 Average


1.73E-06 I2S6-Oe 1JWE-OB 1. TIE-OS
t. 096-06 5.356-06 4.17E-OB 6.79E-06

S.80E-06 7.94E-08 4.16E-08 5.B7E-06
7.31 E-OS 2.09E-05 3.13E-05 4.18E-O5

1.47E-06 2.56E-06 1i7E-08 1.77E-08
1.30E-05 1.87E-OS B.33E-OB 1.40E-OS

1.77E-OS 4.10E-05 1.53E-05 2.47E-OS
1.23E-04 1 .455-04 S.16E-05 1.07E-O4

8.71 E-08 1.57E-05 8.39E-06 1.f3C-OS
B.93E-05 1.17E-04 5.41E-05 S.02E-OS

2.8CE-05 e.flOE-05 2.84E-OS 4.13E-OS
2.48E-04 +JSE-04 1.74E-04 2.ME-04

1.34E-05 1.EOE-OS 7.SOE-06 1.20E-O5
8.S7E-05 1^1 E-04 7.24E-05 830E-O5

1.5SE-05 3.08E-05 1JJ3E-05 2.0SE-OS
1.43E-04 2.61E-04 1.13E-04 1.72E-04

RATIO
OUTtET/
INLET


394


7X»


7.03


4.33


7,lf


9M


7.75


t.42






UOMN + FUMN \
Met I Si2E-0* 7.4CE-04 J.B7E-M S.48E-04
Outlet 1 S.B8E-03 3.7AE-03 1.ME-OS 320E-O3
%OIQXW I
Met I M.»k 20.1H 2&.9M IS.WVi
OUDot: \ ».»% M.4V. Si.A«* !»-M*


S.*7




-------
                     TABLE 6
AVERAGE PERCENTAGE COLLECTED IN PARTICULATE FRACTION


HOMOLOGUES
MonoCDD
DtCCD
TriCCD
TetraCDD
PantaCDD
HaxaCOO
HeptaCDO
OctaCDD
Total Mono-Octa CPD
Total Tetra-Oeta CDD
MonoCDF
DiCCF
TrICCF
TetraCDF
PentaCDF
HexaCDF
HeptaCDF
OctaCDF
Total Mono-Ocla CDF
Total Tetra-Octa CDF
TOTAL PCDD & PCDF
^^— ~-r^^—i i^— 	 	 j^^^^^— ^
ESP INLET
AVERAGE % in
Paniculate
71%
71%
77%
69%
74%
77%
67%
90%
78%
79%
64%
69%
73%
69%
74%
77%
82%
89%
73%
74%
75%
— ^=^^=1^=^=^^=
ESP OUTLET
AVERAGE % in
Paniculate
31%
48%
59%
67%
73%
80%
83%
87%
76%
77%
32%
40%
57%
66%
72%
77%
81%
85%
€8%
72%
73%
.
                      951

-------
                               FIGURE  1
                          DIOXIN   PROFILE
                                   July DO
       a-TCDD  I a-H»CDD I c-HxCDD I        TCDD   I  H»CDD  I   OCDD
           a— PcCDD  b— HxCDO   a— HpCDD        P»CDD     HoCDD       TOTAL PCDD
                                DIOXIN ISOMERS
                        RUN 1
                                     RUN 2
                                                  RUN 3
                          FURAN  PROFILE
                                  July 1989
2.6

2.4

2.2

  2

i  <1




I  -!


'  I

  I

o.a

0.6

0.4

0.2
        B^Et -rnr, rfjUl PCa ^JU   	ilMjgl MWl   |

       i-TCDF lb-P«CDFlb-HxCDFW-H»CDFlb-HpCDF
          a-P«CDF a-HxCDF c-HxCDFo-HpCDF
                                FURAN ISOMERS
       •
                        RUN 1
                                     RUN 2
  . P«CDF  I HpCDF I   TOTAL PCDF
TCDF   HxCDF   OCOF
                                                  RUN 3
                                 952

-------
                              FIGURE 2
                         DIOXIN  PROFILE
 1.7
 1.6
 1.5
 1.4
 1.3
 1.2
 1 .1
  l
 O.9
 o.a
 O.7
 o.e
 0.3
 0.4
0.3 -
0.2 -
O.1
  1!
                                October 1991
"r71 T
 | o-HxCOD I e-HxCDD
-TCDD  I 0-HxCOD I e-HxCDD I       TCDD   I  HxCDCI   I  OCDD
   a-P.CDD  b-HxCDD  o-HpCDD       P-CDO    HpCDD
                      DIOXIN ISOMERS
               RUN 1   BgiSI RUN 2   V/SA RUN 3
                                                                 TOTAL PCDD
                        FURAN   PROFILE
                              October 1991
                                  RUN 2  E2S2 RUN 3
                              953

-------
         Session 21
Risk and Exposure Assessment
  Lance Wallace, Chairman

-------
   ASSESSING EXPOSURE AND RISK TO THE NATION'S
                     ECOLOGICAL RESOURCES
                           J.H.B. Garner, D. Eric Hvatt,*
                              and Daniel A. Vallero*
                      Environmental Criteria and Assessment Office
                                       and                     ^
                Atmospheric Research And Exposure Assessment Laboratory
                         U.S. Environmental Protection Agency
                      Research Triangle Park, North Carolina 27711


ABSTRACT                                                                    .
   The present condition of the nation's ecological resources is not well documented. A baseline^is
needed against which future changes in the condition of the nation's resources can be measured. The
mission of the Environmental Monitoring and Assessment Program (EMAP) is to monitor the current
condition of these resources and provide unbiased, quantitative information concerning their status. Data
obtained under the EMAP program will make possible the evaluation of the effectiveness of government
Policies and programs, and will help identify emerging problems before they become widespread.
EMAP is designed to evolve as new ecological issues arise and others are resolved.           .
   The concept  of environmental  risk  is inherent in the evolution of  an integrated national
environmental policy  EMAP is one of the cornerstones in the development of the U.S. Environmental
Protection Agency's (EPA's) Ecological Risk Assessment Program and, as such, is designed to provide
^logical information for EPA's risk assessment process.  When fully implemented, in cooperation
^th other agencies, this coordinated research, monitoring, and assessment effort will help to explain
f° the risk assessment community why a particular condition exists, and will enable them toi predict wM
« may be in the future under various management alternatives.  EMAP monitoring will be conducted
to Provide the data base appropriate and necessary for assessing ecological integrity.



feWM-ffSSL-M:


^ssment are the key to the success of EMAP and its potential for  influencing the state-of-the-saence
^ftin ecological risk assessment.

I*I}TRODUCTION                                                      ,.    , *
rep The public  has become increasingly concerned that the resources uponi whicM*jy*y for
                                      957

-------
currently impossible to assess quantitatively where and at what rate ecosystem degradation may be
occurring.  In addition, with available data it is not possible to determine whether present policies are
adequately  protecting the quality of our environment. Clearly, there is need for a national baseline
against which future changes in the condition of the nation's resources can be measured and the overall
effectiveness of our environmental policies evaluated.
    In 1988, EPA's Science Advisory Board (SAB) recommended implementing a program to monitor
the condition of the nation's ecological resources and to identify environmental problems before they
reach crises proportions.1  In response to SAB's recommendation, EMAP, a research, monitoring, and
assessment program, was set up under  the Office of Research and Development (ORD) of EPA.
EMAP will measure indicators of ecological status that could be useful signals of long-term regional,
national, and global trends,3

OBJECTIVES
    The goal of EMAP is to monitor the condition of the nation's ecological resources.  Data obtained
will make  possible the evaluation of the effectiveness of governmental  policies and programs and will
help identify emerging problems before they become widespread. EMAP is designed to evolve as new
ecological  issues arise and others are resolved.
    EMAP is one of the cornerstones of EPA's  Ecological Risk Assessment Program.  As such, it i»
designed  to provide ecological information for  EPA's Risk Assessment Process.   When  fully
implemented, in cooperation with other agencies, this coordinated research, monitoring, and assessment
effort will provide the information needed to document the present condition of the nation's ecological
resources,  help to explain why a particular condition exists, and predict what it might be under different
management alternatives.4 Such information will enable EPA to take proactive steps that will minimize
 future risk or revise current efforts that are falling short of their goals
    EMAP's objectives are to:
    •   estimate the status, extent, changes, and trends in indicators of the condition of the nation's
        ecological resources on a regional basis with known confidence;
     •   monitor indicators of pollutant exposure and haWtat condition and seek associations between
        human-induced stresses and ecological condition; and
     »   provide periodic statistical summaries and interpretive reports  on ecological status and trends
        to resource managers, the EPA Administrator, and the public.
    Several key questions are guiding EMAP  toward its goal.
    (1) What is the extent of our (the nation's) ecological resources, and how are they  distributed
        geographically?
    (2) What proportions of the resource are  in acceptable ecological condition?
    (3) What proportions are degrading or improvingt in what regions and  at what rates?
    (4) Are these changes correlated with patterns and trends in environmental stresses?
    (5) Are adversely affected resources improving in response to control and mitigation program^
Answering the above questions requires a long-term, regional and national environmental monitoring
program  involving other federal  agencies  and organizations with  responsibility  for maintaining
environmental quality or sustaining the nation's resources.

 APPROACH
    Several long-term, coordinated monitoring efforts are being implemented during the next five yea^.
 These programs, operating on  regional scales  over periods of years to  decades, will collect data fro™
the following ecological resources: (1) estuaries, (2) coastal waters, (3) inland and coastal wetlands.
 (4) the Great Lakes, (5)  lakes and  streams,  (6) forests,  (7)  agricultural ecosystems, and («)
ecosystems.
                                             9S8

-------
    The EMAP approach to monitoring is to:
    (1)  insure broad geographic coverage;
    (2)  make quantitative and unbiased estimates of ecological status and trends;
    (3)  facilitate analysis of associations among measurements of (a) habitat condition, (b) pollutant
         sources and exposure, and (c) biological condition (indicators); and
    (4) allow sufficient flexibility to accommodate sampling of multiple types of resources and to
        identify emerging environmental issues.
    The effort consists of the following principal activities:
    (!) strategic evaluation, development, and testing of indicators;
    (2) design and evaluation of integrated statistical monitoring frameworks and of protocols for
        collecting data;                                            .
    (3) nationwide characterization of the extent and location of ecological resources;
    «) demonstration studies and implementation of integrated sampling designs; and
    (5) development of data handling, quality assurance, and statistical analytical procedures.
    EMAP is an assessment-driven program;  therefore, assessment rather than *"*»"*?**
^Phasized.  Monitoring will be conducted to provide the data base necessary and appropriate for
assessing ecological integrity.  A major aim of the data collected will be landscape charactemaaon (i.e ,
Ascribing the physical  habitats that are associated  with the EMAP sampling frames).  Ecologically
oriented assessment monitoring will be emphasized.                                j«w-^«.nto-i
    EMAP assessments will emphasize  a "top-down", regional and nauonal  scale, tO*"™1*
approach. They are planned to be retrospective rather than predacttve and will evaluate ^the changes in
Communities and ecosystems directly. This is  in accordance with the statement by EPA s SAB that
^AP define the^ofalessments it will do.  Further, the SAB pointed out that ths is necessary
                     oaes                .         ,
       assessment can be visualized as a continuum of levels of increasing complexity. These are as
follows:

   Change Detection-Detect and characterize changes in the state of selected ecological indicators in
   ^ context of natural spatial and temporal variability (i.e., distinguish the signals of change from
   the noise of ecological variability).

   Ecological significance of the Cfew^-Evaluate and categorize the statu s of the ecological resources
   measured by the ecological endpoints and indicators, taking into account natural variability and
             importance,

   Mange/Stress ^odcffcm-Establish associations between statistical or spatial/temporal patterns,
   ^logical endpoints and indicators, and a particular anthropogenic stress.
   toWithmem 0/C^//rv-Establish cause-and-effect relationships be^een ^&d»^in
   ^logical endpoints and a particular anthropogenic stress with cognizance of interactions among
   multiple anthropogenic stresses and natural variability.





   assessment.

   ***** Risk .^"-involves  ^^^^^
    tress/response/recovery relationships specific to bort type of &^™^
           predictive effects assessments, risk characterization, and risk com
                                           959

-------
ORGANIZATION
    EMAP has four major elements:  (1) resource monitoring, (2) integration, (3) coordination, and
(4) developmental research.  Each element in turn is subdivided into several groups.

    (1)  Resource Monitoring—EMAP's objectives  call for monitoring the condition of the nation's
        ecological resources and providing estimates of changes and trends with known confidence.
        These objectives can be met only through  a statistically designed monitoring network using
        probability-based sampling of explicitly defined resource populations.

    The comprehensive ecological monitoring design uses two-tiered sampling based on a randomized
regular triangular grid with the sample selected according to strict probability protocols so that estimates
of ecological condition have known  quantifiable precision.   The randomized triangular grid  system
emphasizes the geographic distribution of ecological resources.5 The samples are taken in two stages.
The Tier 1 sample is used in conjunction with other information to estimate the extent and distribution
of a resource (i.e., number of lakes, total area of lakes, acreage of a forest, etc.) and to aid in selection
of the Tier 2 sample. The Tier 2 sample is usually a more detailed subsample of Tier 1.  The Tier 2
sample is selected  independently for each class of resources and usually requires field measurements.
The design can accommodate multiple spatial scales, both for sampling and reporting; can be used for
a variety of ecological resources; and is inherently capable of adapting to new ecological perspectives,
the emergence of new environmental issues, and changes in resource emphasis.

    (2)  Integration—Integration includes several functions that facilitate the acquisition, management,
        and interpretation of monitoring data.
        •  The Air and Deposition Group and the Landscape Characterization Group provide data and
           assist all Resource Groups in interpreting observations on  the condition of a resource;
        •  The EMAP  Information Management  Group  facilitates  storage of information and  its
           dissemination to and from the Program, as  well as among the Resource, Coordination, and
           other Integration Groups.
        •  The Integration  and Assessment  Group  oversees the acquisition of data  from other
           monitoring networks that cut across or are relevant to two or more Resource Groups.  This
           group also ensures that the scientific information collected is translated  into a form that can
           be used to answer management questions regarding regional- and national-scale problems.
           Among the projects under way are the completion of a final draft of "Integration and
           Assessment in EMAP: Critical Functions  for Achieving EMAP's Mission," development
           of the example  Integrated Assessment  Project, and completion of a draft of the EMAP
           Glossary. The latter will ensure the use of consistent definitions throughout EMAP, while
           the  example Integrated Assessment Report will serve as a guideline for  interpreting and
           evaluating policy-relevant information on a regional scale.

    (3) Coordination—The Coordination Groups ensure that data collection by the Resource Groups are
        conducted in standardized ways.  Their activities include: (a) network design and statistical
        analysis; (b) indicator selection, testing, and evaluation; (c) logistics; and (d) quality assurance.

    The Indicators Group completed two important documents during the  first half of  1991:  "The
 Indicator  Development  Strategy  for  the Environmental  Monitoring  and Assessment Program"
 (EPA/600/3-91/023) and "Analysis of Selected Extant Data for Birds in New England."
    The second  report serves as a first-year (1990) summary for the New England Biodiversity Project.
 This initial report suggests that the micro-habitat, the area within a 3 ha circle, and the macro-habitat,
 the area within a 50 ha circle, are equally useful for predicting the presence of common breeding bird
                                              960

-------
species in New England.  Report results suggest that common New England bird species with similar
Caging behavior and habitat typically exhibit similar population trends.  Results also support the idea
of trends in bird biodiversity.

    (4) Developmental Research-An  active research program is  essential  to ensure that EMAP
       responds  and adapts to  new issues;  capitalizes  on improved  scientific understanding; and
       incorporates advances in methods development, data analysis, and reporting techniques, while
       simultaneously retaining continuity in the long-term data set it develops.  All major ecological
       resource groups within EMAP conduct research  that is relevant to their specific resource or
       coordination and integration responsibility.  Four areas of research cut across all resource areas:
       (1) environmental statistics,
       (2) ecological indicator development,
       (3) landscape ecology, and
       (4) ecological risk characterization and assessment science.

 r . EMAP U ad integral part  of ORD's Ecological Risk Assessment Program that involves development
of formation to enable Wre scientifically based public policy. The first step is ^n^™ °f
*• hazard and the determination of whether the response lo stress is an adverse effect. -   O
     e identification of the  hazard, characterizatoi of  the exposure, and determination of
      seand stress-recovery relationships specific to both *e type of stress and             en
      also include predictive  effects Assessments,  *k  charactenzatoon   and
       e, EMAP data and assessments will  be a valuable tool for EPA's overall  Comparative Risk
        Program.
          sent condition of the nation's ecological resources is not well
           l bas*ne against which future changes in the T^^
    P was ^Wished to monitor the correm condition of test resources and ^:o proviae         ,
     tative inforraation cmemi^ ^ status.  Tte EMAP programs are an m egraJ part erf ORD s
    *fc«I »* Assessment Program and involve development of «
    infonnatioa will help to explain why a particular condition ex* s
    ent management alternatives, and to enable EPA to take proactive steps that
 sk or revise current efforts that are falling short of their goals.


      1 Enviranroental Prelection A^cy,
                                          fc-
        visory Board, Washington, September 25,
                                             961

-------
USE OF PERSONAL MEASUREMENTS FOR  OZONE
       EXPOSURE ASSESSMENT - A  PILOT STUDY
               Lee-Jane Sally Liu, Petros Koutrakis, and Helen H. Suh
                          Harvard School of Public Health
                     665 Huntington Avenue, Boston, MA 02215

                        James D. Mulik and Robert M. Burton
                        U.S. Environmental Protection Agency
                         Research Triangle Park, NC 27711


ABSTRACT
       During Summer 1991, indoor, outdoor, and personal ozone (O3) concentration and time-
activity pattern data were collected in State College, PA.  Monitoring was performed over an eight-
week period at 23 homes and at a stationary ambient monitoring (SAM) site. Passive O, samplers
were used to measure all O3 concentrations.  For method validation purposes, a continuous O3
monitor also was co-located with the passive samplers at the SAM site.
       Ozone concentrations measured with passive samplers were correlated with those obtained
using  the continuous monitor (r=0.91).  Outdoor O? concentrations  showed spatial variation
between rural and residential areas. They also were higher than both indoor concentrations and
personal exposures.  The mean ratio of indoor to outdoor O3 levels was  0.59±0.19,with significant
differences in  ratios between homes. The mean ratio of personal to outdoor levels was 0.63 ±0.57
and that of personal to indoor concentrations was 1.69 ±3.04.
       Indoor O3 concentrations were determined to be the most important predictors of personal
exposures with multiple regression analyses.  The microenvironmental model predicted personal
exposures well for participants who spent the majority of their day in or near their home, resulting
in an  R2 of 0.76 when estimates were regressed on measured personal  exposures.  However, for
other  participants, model predictions were poor and may be improved through the use of indoor
and outdoor concentration data from additional microenvironments.
INTRODUCTION
       Exposures to O3 as low as 120 ppb may result in a variety of adverse respiratory system
effects.1-2--' Ozone exposures have been associated with decrements in lung function,2'3'4'3 increased
incidence of cough, chest pain, and other symptomatic responses,113 changes in airway inflammation
and biochemistry,6 and increased epithelial permeability/
       While there is a great deal of knowledge about outdoor O3 concentrations, little is known
about indoor concentrations and even less about personal exposures.  Several studies have explored
the relationship between indoor and outdoor O3 concentrations8'9'10 and their influence on human
total exposures.11'12   These  studies demonstrated the need for direct personal O3 exposure
measurements and for further characterization of the relationship between personal exposures and
indoor  and outdoor concentrations.
       This  paper presents results from  an extensive indoor,  outdoor,  and  personal O3
measurements collected for 23 children using passive O3 samplers.  These data were used  to
investigate variations in outdoor and indoor O3 concentrations and to identify factors that may
affect personal O3 exposures.  Finally, stepwise multiple regression and time-weighted personal
exposure models for O3 also were developed.
                                        962

-------
 SAMPLING METHOD                          „ . .    .    ,    .,.
      The passive O, sampler, developed by Komrakis et el", « based on the oxidation reaction
 of nitrite (NO,') by O, that forms nitrate (NOj'). The amount of nitrate is then determined using
 ion chromatoerapny. The average O3 concentration is calculated from the measured nitrate
 concentrationtnd a known collection rate. The limit of detection (LOD) for the passive sampler
 is 17.5 ppb for 12 hour measurements.13                  .                   ,
      Continuous O, concentrations were measured by ultroviolet (UV) absorption using the
 Thermo-Electron Co Model 49 UV Photometric Ambient O3 Anajfzer.  This instrument is
 designated as an equivalent method for ambient O3 measurements by the U.S. EPA  The LOD of
 this method is 2 ppb with a precision of 2 ppb (Thermo Environmental Instruments Inc. 1987).


 STUDY DESIGN
      Ozone concentrations were measured in State College, PA, from July & through August 22,
 1991. indoor, outdoor, and personal samples were collected for 23 children[Jty^M ™2
 in non-smoking households. All homes were located within residential ne«bbor^fl JJS^g
 was conducted at each child's home over a 5-day period.  Three children were  monitored each

  en° 'At each home, indoor samples were collected over 12 hours for both ff^^^l
 and nighttime (Spjn-fiam) periods.  Passive samplers were placed in the main acuvitj'rooms 01
 children's homes at least 1 meter  from walls, windows, air conditioners, and other ventilation
 devices, and 1.2 meter above the floor.           .     .         .   . QUts:de homes, at
      Outdoor Ot concentrations were measured using passive samplers placed o«'*de home^ «
 least l meter from walls, trees, and other large objects. Outdoor samples we£Jg^6^;,




 samplers and continuously using the photometric *mb*ent*, 9fSS£n) using P*5^6 samplers.
  J •™-**l*r J-JJUIIJ twl JJlK L/tJ 1WJ« M. tmV*r*f •*•«•••• »       !".*_*	» •  »
transferred onto formatted time-activity sheets by field technicians.



RESUIfttfal of 99 passive samples and 236 indoor, outdoor, and personalsamples -reflected
« the SAM and home sites, respectively. Qzcne cojicentrauon data_ a« presented m p^r  ^




found to be 15% for daytime and 25% for nighttime samples.
      Outdoor 03 levels measured at the SAM site demonstrated a d™ PfJf^J"Sated
daytime concentration significantly higher than that for nighttime periods (p<0.01). B h |"«£«ea
niihttime concentrations were low, reaching a maximum of only M
flair*•««.<.	 _  .  .•   	i	j ~ MAMW««viiirtn nf Ov nnn_
                                                 . ppb, while 12-h integrated
w--»*»iiv vuuwciII-IdtlUlid r»ti & **->—» »w*w.-—~9 —
^SiSx^^^^^^^^^
t^-^^^s6^AK^^^^^'-^^
                                  963

-------
communities, which are less populated. The mean ratio of outdoor home to SAM site O3 levels was
calculated for each region. These ratios were compared to one another using ANOVA.  Significant
differences in mean ratios were found by region (p<0.06), with ratios of the less populated regions
3 and 6 higher than those for densely populated regions 1, 2, 4, and 5.
       Effective penetration rates, or  the ratios of indoor to  outdoor O3 concentrations, were
calculated  for  12-h daytime periods.  Due to the absence of 12-h  integrated outdoor home
measurements, 12-h  outdoor concentrations (C0)  were estimated for each  home using the
expression:                               C0  - C d * ( q, /  Cc )                        (1)
where Ccd is the 12-h integrated outdoor concentration at the SAM site, and q, and Cc the 24-h
integrated outdoor concentration at the home and SAM sites, respectively.
       The mean effective penetration rate for homes was 0.43±0.25,which falls within the range
of previously reported results.10'16'17'18'19 Mean penetration rates were found to differ significantly
by home (p < 0.01 ). Since windows generally were left open in the homes throughout the monitoring
day (only 3 of the 23 homes used air conditioners), differences in air exchange rates between homes
may be minor.  Thus,  observed penetration rate differences probably are due to dissimilar housing
materials.12 Penetration rate differences may be even greater when diverse indoor environments,
such as shopping malls, schools, and office buildings, are considered.
       Personal O3 exposures were found to be significantly lower than corresponding outdoor
concentrations (mean  ratio =0.63 ±0.57) and significantly higher than corresponding  indoor
concentrations (1,63±3.04, p<0.01) (Figure 3). Personal exposures, however, were correlated with
both indoor (r=0.55) and outdoor concentrations (r=0.38), with indoor concentrations the better
predictors of personal O3 exposures (Table I).
       Two types  of personal exposure models were developed.  First, models were constructed
using forward and backward stepwise linear regression analyses to determine the relative influences
of indoor and outdoor concentrations and time-activity patterns on personal exposures. For these
models, personal O3 exposures (Cp) were used as the outcome variable, while the estimated home
outdoor concentration (C0), the measured indoor concentration (q), the fraction of time spent
outdoors (F0), and the interaction terms, q*(l-F0) and C0*F0 were used as the covariates. Other
variables, including presence of air conditioners and gas stoves, were not included in these analyses
due to sample size considerations.
        Forward and  backward  stepwise  regression procedures  were performed  using 0.05
significance level criteria to add or drop variables from the model.  The forward and backward
selection procedures yielded identical results.  Both models found indoor O3 concentrations (C,) to
be the most significant predictor of personal exposures (Table II).  The interaction term C0*F0 was
the only other important predictor, indicating that outdoor O3 concentration (C0) is significant only
when weighted by the time spent outdoors (F0).  Models explained  34 percent of the variability in
personal exposures.
        A second type of model was constructed based on the simple microenvironmental exposure
concept.20'21*22  Personal exposures (Ce) were  expressed as:
                     Ce = (q *  F.)  + (C0 • F0)                    (2)
where F{ and F0 are the fraction of time spent indoors and outdoors during the daytime monitoring
period, respectively.  Model estimates generally were higher than measured personal exposures
(Figure 4), resulting in an R2 of 0.31, a  slope of 0.52 ±0.10, and  an intercept of 15.6 ±2.9 ppb when
regressed on measured personal exposures.
        Since O3 exhibits a distinct diurnal pattern, the time of day an individual spends outdoors
may be an important  determinant  of personal exposures. To incorporate this factor into the time-
weighted model, concentration and activity data were divided into  1-h intervals.  Hourly outdoor
and indoor concentrations were estimated using continuous O3 measurements collected from the
SAM  site.   Hourly  outdoor concentrations (Cok)  were calculated  for each home using the
expression:                        Ch
                                   cc
 where Ck is the 1-h integrated outdoor O3 concentration measured at the SAM site. Hourly indoor
 concentrations (C, k) were determined using a similar expression:
                                            964

-------
                                 \*rt      '^-'h
                         Cu  =  —  * 	  * Q               (4)
                                 C0      Cc
 Thus, the hourly microenvironmenta) model was calculated as;
                                           J •  \~Q,l *0,K'     /5J


                             i£t
where Fu and FetL is the fraction of time spent indoors and outdoors in the kth hour,
respectively.  Model estimates explained a slightly higher percentage of the variability in
measured personal exposures (tf=OJ9) than the 12-h simple microenvironmental model (Figure
5).  When Vegressed on measured personal exposures, however, model estimates yielded a
similar slope and intercept.   Further improvements in the accuracy of the hourly
microenZnmeirtal O3 models may be achieved by accounting for the contribution of dwerse
outdoor and indoor environment* to personal ozone exposures. Support for this  s given by
model results for participants who spent at least 95% of their time in or near ^^^m
only these participants were considered, ihe hourly model predicted P«»™«J™!^
(Figure 6)  Model  estimates explained 76% of the vanataltfy m measufedj^res and
resulted in a slope of 1.05±0.17 when regressed on measured personal exposures.

DISCUSSION AND CONCLUSIONS   _    .  _.  .  ___^_ rt _Mmtr.t!nrt, for state
       O^^^JSSS spatial variation in outdoor O3
             densely populated areas having lower O3 concen.rat.ons
 abQity to predict personal exposures from outdoor and ^f^^^^
 Poor, even when time-weighl^d concentrations were used The mabihg of the
 macroenvironmental model to estimate personal exposures ^^^
 only two microenvironmenis, indoor home and outdoor home, ^V^
 fiom these microenvironments did not accurately "^^^^^^
 "idoor and outdoor microenvironments.   When activmes ^^^^fa
 ^e home, the accuracy of the simple ™^*°^^^
 e^dent that contributions from diverse indoor and outdoor microenvirow
 considered in order to estimate personal ^^^^rSncentrations  in a variety of
  .     Future studies should characters ^^S^SfSdne factors that affect
 microenvironments within the same "^^^S^^S^e fac«ors may include
 indoor and outdoor O3 concentrations. For indoor ^n^«area  while for outdoor
 homing materials, ventilation rates, gas scoves, ^o^^^ndt^phy should be
 concentrations, the effect of NO concentration, population density, ami   v &  r /

 investigated.                     .           concentrations on personal exposures also
       The influence of diurna ^^^^^ O3 measurementrshould be
 *jUd be examined.  To do so, indoor ,^ outdoor, "2jSI3«2ie models for O, ako may be
 wUected over shorter periods Improvements in personal exp                 ^
 achieved by collecting personal samples for more cnuaren ovc,  &


ACKNOWLEDGEMENTS         t       R-sarch institute. The information in this
n      This work was funded by *^*™S£Z£Sd p££L Agency under #CRS16
Paper has been funded in part by the  U.S. ^^J^^^^e review,  and it has been
 ?4CK02. It has been subjected to ^f^'^^f'^^y^a!^ or commercial
approved for publication as an EPA document. Ment.onotrade nam
Products does not constitute endorsement or recommendation lor use.
                                         965

-------
REFERENCES
1. J.Q. Koenig, D.S. Covert, S.G. Marshall, G. van Belle, and W.E. Pcirson, Am. Rev. Rgspir,Pis. 136: 1152
(1987).
2. TJ. Kulle, L.R. Sauder, J.R. Hebel, and M.D. Chatham, Am. Rev. Resp. Pis. 132: 36 (1985).
3. W.F. McDonnell, D.H. Horstman, MJ. Hazucha, E. Seal, E.D. Haak, SA. Salaam, and D.E. House,  L
Appl. Physiol. 54:  1345 (1983).
4. M. Lippmann, PJ. Lioy, G. Keikauf, K.B. Green, D. Baxter, M. Morandi, B. Pastcrnack, D. Fife, and F.E.
Speizer, Adv. in Modern Environ. Toxicol. 5: 423 (1983).
5. D.M. Speklor, M. Lippmann, PJ. Lioy, G.D.  Thurston, K. Citak, DJ. James, N. Bode,  RE. Speizer, and
C. Hayes, Am. Rev, of Resp. Pis. 137: 313 (1988).
6. H.S. Koren, R.B. Devlin, D.E. Graham, R. Mann, D.E. House, W.F. McDonnell, and PA. Bromberg, AB
Rev. Respir. Disr 139: 407 (1989).
7. H.R. Kehrl, L.M. Vincent, RJ. Kowalsky, D.H. Horstman, JJ. O'Neil, W.H. McCartney, and RA.
Bromberg, Am. Rev. Resp. Pis. 135: 1174 (1987).
8. RJ. Allen and RA. Wadden, Environ. Research. 27:  136-149 (1982).
9. T.D. Davies, B. Ramer, G. Kaspyzok, and A.C. Pclany, JAPCA. 31(2): 135-137 (1984).
10. M.D. Lebowitz, G. Corman, M.K. O'Rourke, and CJ. Holberg, JAPCA. 34: 1035 (1984).
11. CJ. Weschler, H.C. Shields, and D.V. Nalk, JAPCA. 39: 1562-1568 (1989).
12. H. Ozkaynak, M. Schwab, DA. Butler, and J.D. Spcnglcr, A&WMA, for presentation at thf ft*th Annual
Meeting & Exhibition.  Vancouver, British Columbia (1991).
13. P. Koulrakis, J.M. Wolfson, A. Bunyaviroch, S.E. Frochlich, K. Kirano, and J.D. Mulik, Harvard School
of Public Health, Boston, MA 02215.  Submitted to Analytical Chemistry (March 1992).
14. Thermo Environmental Instruments Inc. Model 49/49PS U.V. Photometric Ambient O3
Analyzer/Calibrator, Instruction  Manual. 8 W. Forge Parkway, Franklin, Ma 02038 (1987).
15. C.W. Spicer, Sci. Total Environ. 24, 183 (1982).
16. R.H. Sabersky, DA. Sinema, and  F.H. Shair, Environ. Sci. Technol. 7: 347 (1973).
17. C.R. Thompson, E.G. Hensel, and G. Kats,  JAPCA 23: 881 (1973).
18. J.V. Berk, RA. Young, S.R. Brown, and C.D. Hollowell, Presented at 74th Annual Meeting ftf the air
Pollution control A^^pciation. Philadelphia, PA, LBL-12189, Lawrence Berkeley Laboratory (1981).
19. DJ. Moschandrcas, J.  Zabransky, and DJ. Pelton, Electric Power Research Institute,  Report  EA-1733,
Research Project 1309,  Palo Alto, California (1981).
20. M. Fugas, Proc. of the Int. Svmp.  on Env. Monitoring. Las Vegas, Nevada.  Institute of Electrical  and
Electronic Engineers, Inc. New York  2, 38-45 (1975).
21. N. Duan, SIMS Technical Report No. 47, Stanford University Department of Statistics.  Palo  Alto,
California (1981).
22. N. Duan, Env. Intl. 8, 305-309 (1982).

Table I.  Summary of Pearson's correlation coefficients (r).
Type of Samples
Home Outdoor Concentrations (Q)
Personal Concentrations (Cp)
Home Indoor Concentrations (Q)
C0
.
0.38
0.58
c,
.
0.55
-
c<*
•
035
0.53
c.
0.79
.
*
 All correlation coefficients are significant at a 95% confidence level.

Table II. Linear regression model obtained using both forward and backward selection procedures at the
0.05 significance level  F
0.0565
0.0001
0.0193
                                               966

-------
       FIGURE I. Chore Conceniranom Measured al II* Souoninr Ambiem Moniiannf
                           (SAM) >nd Home Silci.
'•"«pu.^D^_ir~
>•»•«£___„•,,„_
                    Figure 2. Stationary ambient monitoring
                    (SAM) and the six geographic regions in
                    State College, PA.
t • riiMud DvpHM
                                                                                      Figiare 4.
                                                                        Simple VUcroenrtronmcnta] Elpoiure Kodel
                                                                                C« » (Cl  • Fit + (Co • Co)
                                     .
            Indoor. Outdoor, and Pcr»oD«] Concentr«Uo
             (Meaji C«rUine CoDcentr«Uon« of 3 Homes)
                               Date
                                                                       9
                                                                       U
                                                                       1
                                                                                          Weosursd
                       Hourly Mlcroen«ronn.«D«J Erpo«r
-------
Public Exposure to Organic Vapors in Los Angeles

                        by
                  Steven D. Colome
                    A.L. Wilson
                      YiTian

           Integrated Environmental Services
                 4199 Campus Drive
              University Tower, Suite 280
                  Irvine, CA 92715
                       and

                    KochyFung
                      AtmAA
            21354 Nordhoff Street, Suite 113
                Chatsworth,CA9l311
                  Presented at the

         Air & Waste Management Association
                       and
              EPA/ AREAL Symposium

Measurement of Toxic and Related Air Pollutants

                     May 4-8
               Durham, North Carolina
                      968

-------
 ABSTRACT
 Measurements & fixed-site antoiem monitoring stations ait typical*? msed to determine pcspuiatioa exposures to
 todc air contaminants. Recent studies haw suggested, however, thai for many toxic air pollutants this approach
 may overestimate or underestimate popuMon exposure, and therefore health risk. Human exposures may be
 determined directly using portable monitors carried by a sample of people or indirectly by making measurements in
 specific locations combined with information on time and activity patterns of the population.

 ^ study was designed to measure benzene, formaldehyde, and othet selected organic compounds within gasoline
 stations, parking garages and office buildings in the Los Angeles Basin. A novel approach was developed in this
 stody for sanipUngmicroenvironments so that the locations wooU be representative of person-wits to each
 ^environmental class.  The microenvironments monitored were selected using a ^"^"^^.^
 though a random digit dialing technique.  An initial telephone survey of randomly contacted subjects was used to
 ifcnWy address, «J fof most recent S. and P»rf~*^**^"T5J^1CSi1
 ^Mip-nlOBMdBOMlDgmplifcan^
 Ofganic components,  Formaldehyde was determined using adsorbing cartridges impregnated with 2, 4-
     -                              acid.
 **ults are presented for sampling at 98 gasoline stations and for 10 office buildings and; patting garages during
 ^wifltwof7S  DiS^ofn^
 class of roicroenvifonmeiu; is presented for eleven toxic air pollutants.
                                                  new. During the mid
 ^ng in the field of airpoBution epidemiology that fixed-station momtorsthat had been ocate    ^P'31**
 that serves as inputs into risk assessment models1.

c*posur« to pollutants in nucroenvircmments.

^oplc spend a
toxic air corrtants.
commercial facilities such as gasoline stations,

                                ^
     ne, fodhydeandcarainonc                                      ntad^
engines, ta addition, benzene is evaporated « a ^SS^cc-^adi^veccm^nent. Also,
wmsumer products and building materials used indoors tnaCor^asuusoimniuHau.         e~
^nzene and carbon monoxide are rrieasedby dgareoe smdong.
                                                                                     bum&o
                                               969

-------
latter approach is known as the "indirect" method for assessing human exposures and is the approach that is to be
used in this study.

METHODS
Sample Identification
The sample of gasoline stations was identified through telephone interviews using a commercial RDD (random
digit dialed) sample designed to minimize nonworking telephone exchanges and business numbers. Members of
the IES staff were trained on the telephone interview form that was developed for this project.

The purpose of this approach to sampling was to identify random person-visits to gasoline stations. The sampling
approach was developed for this study as a novel method for identifying gasoline stations in proportion to the
likelihood of their use by the public.  By using probability sampling methods, the results of this survey can be
directly related to the sampled population. The smaller sample of parking garages and office buildings were
selected as a convenience sample and may not fully generalize.

Sampling Methods
Formaldehyde (and other carbonyl compounds as well) in air were collected using cartridges impregnated with
purified 2,4-dinitrophenylhydrazine (DNPH) and phosphoric acid.  When ambient air is drawn through the
cartridge, aldehydes  in the air sample react with DNPH to form hydrazones, which are separated and quantified
using high performance liquid chromatography2.

While the principle in the measurement remains the same, significant refinements have been made in critical areas
of the method to achieve routinely sub-ppb level sensitivities-*. The method was inter-compared  and validated
previously at the USEPA against a FTIR and most recently in the CARB-sponsored Carbonaceous Species Methods
Comparison Study, (CSMCS) conducted in Glendora, CA during August, 1986. In that study, the DNPH
technique employed by Dr. Fung successfully completed the 10-day formaldehyde measurements with favorable
results against other instruments such as a FTIR, DOAS, and TOLAS4'5.

VOC samples were taken in Tedlar bags using the same battery-operated pump system as was used to collect
formaldehyde samples on the adsorbent cartridges.  The pump system, flow regulator and rotameters were
integrated into a plastic box with two tubing connections on each side. An air tight plastic can was used as a bag
housing to provide a vacuum environment for the Tedlar bag and was also connected to the sampler.  As the pump
was turned on, the air in the bag housing was evacuated, thus the bag was filled. Air was simultaneously drawn
through the cartridge using the same pump. Tedlar bags and cartridges were sent back to the lab at the end of each
sampling day. Cartridges were stored in a cooler before and after exposure. Whole air measurements were made
without sample pre-concentration. That approach eliminates artifact and interference errors that result from using
adsorbent pre-concentration and thermal desorbtion techniques. Sample aliquots are transferred from the Tedlar
bag containers to gas sample valve injection systems having sample loop volumes that are specific to each method
and range from 0.2 to 8 nil.

Five (5) separate analyses were performed utilizing 2-dimensional chromatography. By taking this approach,
instrument sensitivity as well as stability were improved and interference from other components were minimized.
Typical accuracy is ± 10% or better, and precision is ± 3% or better. Two systems, each with high resolution
capillary columns in specific column configuration and electron capture detectors were used to measure the
halogens: ethylene dibromide, perchloroethylene, chloroform, carbon tetrachloride, and 1,1,1-trichloroethane.
Ethylene dichloride  was measured using packed columns having unique separation properties  and an electron
capture detector. Aromatic components were measured using capillary columns with a photoionization detector.
 1,3-butadiene was measured using an alumina PLOT column having unique separation properties and a flame
ionization detector.

Standards used to calibrate each component in these methods were prepared in high pressure cylinders by Scott
Specialty Gases Inc. and Scott-Manin, Inc. with component concentrations traceable to NIST and/or certified
accurate by the manufacturer.  Calibration for each of the five analytical procedures was performed using the
external standard method at three concentrations for each component.
                                                 970

-------
 Carbon monoxide was recorded continuously during each sampling day using  InterScan Series 5140-BX CO
 dosimeters. The dosimeter was a battery-operated, time history, computer-linked unit. It operated in diffusion-
 mode without a pump.  The detection element was an electrochemical voltammetric sensor. Sixty digital samples
 were averaged per minute by this dosimeter, but only minute-by-minute CO concentrations were stored in memory.
 These minute-by-minute recordings were extracted at the end of the day to a computer file via CX-5 Computer
 Interface.

         Gasoline Stations.  One hundred gasoline stations were identified from the telephone interviews and
 visits were completed by the IBS field engineer. Due to the sampling procedures employed in this study these
 stations should represent the distribution of stations as visited by SoCAB residents. A field engineer went to an
 identified station and set up the sampling equipment on a pumping island (preferably the central island), where
 people were filling their tanks.  Sampling height was approximately 5 feet above the ground.

 A fixed five-minute sampling interval was selected in order to collect concurrent samples for VOCs and
 formaldehyde. The time period was necessitated by the detection limit for formaldehyde. Based upon preliminary
 evaluations, it appeared as though a five minute sampling interval would be just sufficient to quantify
 formaldehyde in most of the samples.

        Parking Structures and Office Buildings.   Ten pairs of parking structures and office buildings were
 selected as a convenience sample within SoCAB. Ten grab air samples (5-minute averaging time) were collected
 each day — five in the garage, four in the office building and one in the ambient  All samples were taken at a
 height of approximately 5 feet above the floor and at only one location in the parking structure or office building.
 An underground level was chosen if the parking structure had any underground levels. VOCs and formaldehyde
 were collected using the same air sampling system as used in gasoline stations. Two CO dosimeters were
 employed.  One was located in the parking garage and was operated continuously.  The other was worn by the IBS
 field engineer to measure personal exposure. These two dosimeters were turned on at the same time in the
 morning and left running until the end of the day. At that time, the data were downloaded to a computer for
 analysis and storage.

 RESULTS
 Telephone Contact
 A total of 1336 telephone calls were made to the 583 telephone numbers that were assigned to the study. The
 protocol established for this project was to attempt on at least five occasions to contact the designated respondent
 (adult over the age of 18) in the household.  A standard telephone survey method was used to identity a designated
 respondent in the contacted household (such an approach is necessary since the first person to answer the telephone
 can not be considered as a random respondent).

 Of the 136 persons interviewed, a total of 122 (or approximately 90%) report that they drive a vehicle.
 Approximately 94% of the drivers report that they put fuel in a vehicle eight or fewer times a month and the vast
 majority put the fuel in themselves (83%). Nearly 60% of those that drive report that they put 10 or fewer gallons
of fuel in the vehicle during their last refueling.  Over 80% report that they generally use three or fewer service
stations (56% report that they usually go to a single service station). Ninety five percent of the sample that drive
report that they could recall the service station where they last refueled. For most of these respondents (for 88% of
the driving sample) we were able to identify the service station they last visited  station from cross streets and brand
names. Those that we could not locate were for reasons such as the respondent providing parallel streets for cross
streets. For this study no attempt was made to call back these few respondents to try again to locate the station.
Figure 1 shows the approximate locations of the 100 service stations sampled (two samples were voided due to
Tedlar bag leakage).

Forty two percent of the driving sample had not used a parking garage in the past year. Fewer than 20% report
"sing a parking garage more than once each quarter. Despite the relatively low rate of use by this sample of
                                                971

-------
                          FIGURE 1. Locations or 100 monitored gasoline stations.
enclosed parking garages we were, however, able to locate the last parking garage used for 57 respondents
(representing over 98% of those who reported using a parking garage in the past year).

Measurements
        Self-service Gasoline Stations.  Table 1 lists a summary of the S-minute sample of air toxics
concentrations at the 100 gasoline stations (two samples lost due to deflated sampling bags). The median benzene
concentration was observed to be 9 ppb with the maximum reported value of 101  ppb This data shows generally
lower benzene concentrations than have been previously reported for gasoline stations in other regions of the U.S.

                    TABLE 1.  Summary of pollutants measured at gasoline stations (ppb).

                                                  Std.     Geo.
Variable
1,1,1-Trichloroelhane
1 ,2 - Dichloroethane
1 ,3 - Butadiene
Benzene
Carbon Monoxide
Carbon Tetrachloride
Chloroform
Formaldehyde
m & p - Xylenes
Ortho - Xylenes
Perchloroethylene
Toluene
Trichloroethylene
Obs.
98
73
97
98
98
97
98
26*
98
98
98
98
98
Mean
5.2
0.1
1.04
14
4900
0.11
0.05
9
16
9
0.9
63
1.0
Dev.
7.7
0.0
1.46
15
3220
0.01
0.03
11
18
8
0.7
81
1.1
Mean
3.1
0.1
0.71
9
3780
0.11
0.05
4
13
8
0.7
40
0.7
Median
3.1
0.1
0.72
9
4300
0.11
0.04
4
13
7
0.8
36
0.6
Min.
0.4
0.1
0.08
2
200
0.08
0.04
0
1
3
0.1
8
0.2
Max.
61.8
0.3
13.30
101
15000
0.17
0.20
35
159
69
5.3
516
6.5
           * Note: missing data due to laboratory analysis interference.
                                                   972

-------
          Parking Garaeci mi Offices.  The Odd engineer visited one parfciiig garage and a nearby office
  building during one day's sampling.  Therefore, sampJing was conducted over 10 days.  Table 2 lists a summary of
  the concentrations of the selected air toxics for each of the parking garages, office buildings and the associated
  ambient measurements.

        TABLE 2. Summary of measurements made in parking garages, office buildings and outdoors (ppb).
Partdng Garages Office Buildlrws
, 	 fSOsanrwWh (40 samoles^ (1
Steeled Toxin*
M.i-Trichtoroethane
1,2-dfcMoroethane
1,3-butadlene
Benzene
Carbon Monoxide

^Woroform
^ornvaktehyde
w&p-xytenes
Orfho-Kytens
Perchtoroethylene
Toluene
Trfchloroethylanfl
Min
1.3
*
•f
2
0
0.10
II
11
4
3
0.1
8
0.1
Medj Max
4.9 12.7
0.1 0.8
2.24 13.10
21 88
11000 52000
0.12 0.35
0.04 0.51
34 75
43 437
16 120
0.6 1.8
49 153
0.3 0-7
Min
3.B
*
0.13
0
0
»
*>
16
3
2
0.2
3
0.1
Med
10.0
0.1
0.79
5
4000
0.12
0.10
36
9
4
0.7
26
1.6
Max
92.9
0.3
3.24
19
13000
0.28
0.17
93
181
51
3.0
100
4.2
Min
2.3
*
*
1
0
0.10
*
5
3
2
0.2
5
0.1
Ambient
0 samples3^
Medf
3.7
*
0.37
4
2000
0.12
0.09
20
9
5
0.7
29
0.5
Max)
21

1.02
17
7000
0.2
0.29
44
117
38
2
79
0.6
  Below detection limit
 »T«        -.
 3Ten offices, four samples from each office
  Ten ambient samples collected outside the office/garage complexes
 ^srss^

ftoa' air toxics,
ContriburJ
-------
REFERENCES
1.   EPA, U.S. Environmental Protection Agency (1987). The Risk Assessment Guidelines. EPA/600/8-87/045,
    U.S. EPA, Office of Health and Environmental Assessment, Washington, D.C.

2.   Fung, K. and Grosjean, D. (1981). Determination of Nanogram Amounts of Carbonyls as 2,4-
    Dinitrophenylhydrazones by High Performance Liquid Chromatography. Annals Chemistry, 53:168.

3.   Fung, K. and Wright. BJ. (1986). Monitoring of Benzene in Ambient Air with Organic Vapor Badges.
    Journal of the Air Pollution Control Association, Vol. 36, No. 7, 819-821,

4.   Fung, K. and Wright, B. (1988). Measurement of Formaldehyde and Acetaldehyde Using 2,4-
    Dinitrophenylhydrazine-impregnated Cartridges During the Carbonaceous Species Methods Comparison
    Study. Aerosol Science & Technology, Vol. 12,44-48.

5.   Lawson, D.R., Winer, A.M., Biermann, H.W. Tuazon, E.C., Mackay, G.J., Schiff, H.I., Kok, G.L., Dasgupta,
    P.K. and Fung, K. (1988). Formaldehyde Measurement Methods Evaluation and Ambient Concentrations
    During the Carbonaceous Species Methods Comparison Study. Aerosol Science & Technology, Vol. 12,64-76.
                                               974

-------
            An Exposure Assessment and Risk Assessment Regarding
            the Presence of Tetrachloroethene  fn  Human  Breastmllk
                            Judith S.  Schreiber
                     New York  State Department of Health
                           School of Public Health
       A novel application of physiologically-based  pharmacoMnetic  (PBPK)
  modeling is used to estimate human  breastmflk  co/icentrattorts of
  tetrachloroethene (perchloroethylene,  PCE)  for a variety of maternal
  occupational and residential  exposure  scenarios.   The breastmllk
  concentrations  can  be  predicted  from airborne  PCE  concentration* or from
  measured blood  PCE  concentrations.  The results Indicate that elevated
  breastmllk  PCE  concentrations are predicted to occur for many of the
  exposure scenarios  evaluated.  The PBPK-estfmated breastmJJk
 concentrations  agree very well with measured concentrations,  where
 available.

      The contamination  of human  breastmllk by  environmentally  stable
 halogenated organic  compounds such as PCBs, DOT  and metabolite*,  and  other
 persistent  compounds has  been recognized  for decade*.  The mothers'
 exposure to these substances usually occurs  via the ingestion of low
        of these  contaminants  in the diet followed by their storage  In
         tissue.  The  contaminants are subsequently mobilized from adipose
        to breastirfll. upon lactation.
     PCE has the potential to be present In the breastmllk of exposed
      because the solvent is readily absorbed upon inhalation, is highly
Upophillc and is not metabolized to an  appreciable extent,  PCE has been
identified in adipose tissue,  but very seldom has its presence In
         k been investigated.   Women are exposed to PCE 1n environment
                                   975

-------
as a  result of emissions from dry cleaning facl11 ties and other commercial
and residential  uses of PCE,   In addition,  many  indoor air environments
contain low levels of PCE due to the Introduction of dry cleaned clothes.

     In the present study,  seven exposure scenarios were evaluated.  Three
occupational exposure scenarios were evaluated,  representing maternal
exposure to 8-hour air concentrations of PCE  from 40 to 340 mg/m1,
followed by exposure to background residential indoor air  levels of 0.027
mg/ra1.  The breastmllk PCE concentrations predicted to result from these
occupational maternal exposures are  estimated to range from 857 to 8440
ug/1- (See  Table  1).

     Three residential exposure scenarios were  evaluated, representing
24-hour mean air concentrations of PCE 1n residences located above dry
cleaners.  Maternal  exposure to 24-hour mean Indoor residential air
concentrations of 0.2S to 45,8 mg/m' reported 1n these residences result
In estimated breastmllk  PCE  concentrations of 16 to 3000  ug/1.  Finally,
background Indoor residential air exposure of 0,027 mg/m1 Ss predicted
to result  In a milk,  PCE  level of about 1.5 ug/1, similar  to measured
levels  fn  samples from  the general population.  (See Table 1).

     For tha occupational exposure  scenarios evaluated,  the dose of PCE
Ingested by Infants  via  breastmllk  Is estimated  to  be  within  one order
of magnitude of  doses  associated with adverse effects.   In  addition,  the
cancer  risks associated  with these  exposures are significant,  ranging
from 58 to  600 excess  cancer risk per million Infants exposed via
breastmllk  for one  year.  (See Table 2).
                                   976

-------
        Mothers  and  Infants  living  in  residences above dry cleaners are
   exposed up  to 24-hours a day to elevated levels  of  PCE  in the indoor air.
   These elevated PCE concentrations contribute to  the infant's exposure via
   the  Inhalation of contaminated air and via the ingestion of contaminated
   breastmllk.   For these residential exposure scenarios,  the  Infant's
   exposure to PCE occurs primarily via Inhalation.  Breastmllk Ingestion
  also contributes to the Infant's exposure.   These exposures  are
  significant, especially In view of the continual  re-exposure, the child's
  large Inhalation  dose and  the  insidious  nature of the exposure.

       Lastly, maternal  exposure  to  a  background Indoor air concentration
 of 0.027 mg/m» Is predicted to result 1n low  levels of PCE 1n breastmllk
 which  have a large margin to  doses associated with adverse health effects
 and contribute little additional cancer risk.  In summary,  PBPK modeling
 suggests  that the presence of PCE in breastmllk can  be a significant
 source of exposure to the infant, under certain exposure conditions,  which
 has the potential  for adverse health effects and  Increased cancer  risk
 1" the exposed Infant.

      The potential adverse effects of Infant  exposure to PCE 1n breastmllk
 should not be evaluated without  an  assessment  of  the Benefits of
 breastfeeding.  The benefits of breastmllk for the health and welfare  of
 Infants  are well known.  Reduced neonatal mortality rates of about 2560
 to 4000  per million Infants nourished by breastmllk rather than formula
 have been  estimated by other Investigators.   Ideally,  providing an
""contaminated source of breastmllk Is the best choice.   From a public
health perspective,  the avoidance of risk by minimizing exposure to PCE
Is sound public  health  policy. If  the modeled PCE milk concentrations are
                                  977

-------
verified by monitoring data on heavily exposed women,  then public health
Interventions may be advisable.  The actual concentrations of PCE In milk
of exposed women  can only be known  with certainty  If monitoring of exposed
women Is conducted.   Due to the widespread exposure  potential,  these
studies should be undertaken so that  the appropriate risk management
alternatives can be evaluated.
                                       978

-------
                                  TABLE  i

                    PBPK-Slmulated Concentrations of PCE in

                              Biological Media1
Mother's Exposure
Scenario
A- 8 hr at 340 mg/m1,
then 16 hr at
27 ug/mj
B- 8 hr at 170 mg/m1,
then IS hr at 27
ug/m1
c- 8 hr at 40 mg/rn1,
then 16 hr at 27
ug/m*
D- 24 hr at 45.8 mg/m1
E- 24 hr at 7.7 mg/m1
F- 24 hr at 250 ug/m1
G- 24 hr at 27 ug/m*
M^ir^jm Simulated Concentration (ug/U
Blood
1320
557
132
470
79.
2.6
0.23
Fat
211,000
88,350
21,400
74,900
12,600
400
38
Mm1
8440
3530
857
3000
500
16.2
1.5

Infant Oose
from Milk1
(mg/kg/day)
0.82
0.34
0.08
0.3
0.05
0,0015
0,0001
i Slelken PBPK model  results
                                   ml br«.t.11k per day.
          ± milligrams per cubic meter
ug/m*     = mlcrograms per cubic meter
U9/1      = mlcrograms per liter
m9Ag/day * milHgrams per kilogram  per day
                                      979

-------
                                   TABLE  2

                             Excess Cancer Risk from
                          PCE Ingestlon Via Breastmilk
       Mother's
  Exposure Scenario
Exposure of Infant to
 PCE via Breastmllk,1
	  mg/kg/day
         Excess
       Cancer Risk1
A.  Chronic workplace  ex-
    posure at ACGIH TLV of
    50 ppm (340 mg/m1)

B.  Chronic workplace  ex-
    posure at OSHA PEL of
    25 ppm (170 mg/m')

C.  Chronic workplace  ex-
    posure at 40 mg/m1 for
    counter area workers
    at dry cleaners

0.  Non-occupational ex-
    posure to 45.8 mg/m1
E.  Non-occupational  ex-
    posure to 7.7 mg/m1
F.  Non-occupational ex-
    posure to 250 ug/m1
G.  Non-occupational ex-
    posure to 27 ug/m1
       0.82



       0.34



       0.08




       0.3



       0.05


       0.0015




       0.0001
         6 x 10-4       J  ,
(600 per million population;


        2.5 x 10-4      ,  .
(250 per million population;


        5.8 x 10-5         ^
( 58 per million population;
          2.2  x  10-4        *
(220 per  million  population;


          3.6  x  10-5        *
(36 per million population;

          1.4  x  10-6

1.4 per million population)


          1 x  10-7       .  n1
(0.1 per  million  population;
1 Assumes 7.2 kg Infant Ingests 700 ml breastmllk, per day

1 q,* of 5.1 x 10-2 (mg/kg/day)-l multiplied  times  the mg/kg/day exposure,
 multiplied by 0.0143 (1 year of exposure over a 70 year  lifetime)
                                   980

-------
   THE  TIME-COURSE AND SENSITIVITY OF MUCONIC ACID
        AS A BIOMARKER FOR HUMAN ENVIRONMENTAL
                          EXPOSURE  TO BENZENE


   Timothy J. Buckley1, Andrew B. LIndstrom1, V. Ross Highsmith1, William E. Bechtold2, and
                                   Linda S. Sheldon3


   'US EPA, Atmospheric Research and Exposure Assessment Laboratory (MD-56) RTF, NC 27711
                2Inhalation Toxicology Research Institute, Albuquerque, NM 87185
                 'Research Triangle Institute, P.O. Box 12194, RTP, NC 27709

  Preliminary results are presented that show the effect of increased benzene exposure on the urinary
  elimination of trans.trans-mucotdc acid (MA) for an adult male.  These results were generated from
  a p°ntrolled exposure experiment during which an individual was exposed to benzene during a shower
  *** gasoline-contaminated ground water.  Based on measured  air and water concentrations,  it is
  estimated that the 25 minute shower resulted in an inhalation and dermal absorbed dose of 122 ^g and
  190 /*g, respectively, yielding an average dose rate of 749 pg/h during the shower period.  The
  measured background dose rate of 1.2 pg/h was exceeded by a factor of 624 during the shower
  exposure. The average urinary MA elimination rate increased from 3.7 /*g/h during the 30 h period
  before the exposure to 17.9 ^g/h during the 22 h period after the exposure. The post-exposure profile
 °f muconic acid elimination ftig/h) was characterized by two minor peaks (47 and 35 /xg/h) occurring
       3 h and a major peak (61 jtg/h) at approximately 11 h.
       Mis paper has been reviewed in accordance with the U.S. Environmental Protection Agency's
Peer review and administrative review policies and approved for presentation and publication.  Mention
°f trade names or commercial products does not constitute endorsement or recommendation for use.

       This study was reviewed and approved by the Research Triangle Institute Committee for the
          of Human Subjects.
 .     Human exposure to benzene in community and occupational environments is common1. This
 fs*t, along with compelling evidence suggesting that benzene exposure causes leukemia in humans ,
 sives reason for evaluating and minimizing routes of exposure.
  L   Biomarkers can provide a powerful tool for assessing exposure and risk. The measurement of
* tic-marker can provide individual-based evidence that exposure has occurred ex ^ ft**-  A
^marker measurement establishes in fact a body burden that can otherwise only be e^mated trough
****! measurements of exposure.  Although a biomarker measurement may -in theory be a more
v^able means of assessing exposure, its practical value is dependent upon the reliability and validation
oftk biomarker                                                    .  , ,.   ,,   ,3 c
             urinary biomarkers of benzene exposure have been investigated including phenol , S-
                          iconic acid"-'. /m^/r^-Muconic acid (MA) shows  particular
                                       981

-------
promise as a biomarker for human environmental exposure due to its specificity and its presence at
detectable levels in individuals exposed to background benzene levels7.  Furthermore, MA provides an
indication of toxicological potential because it  is formed from the toxic  metabolic intermediate,
muconaldehyde9.
       It is the aim of this research to provide further data regarding the validation of muconic acid as
a biomarker of more subtle, non-occupational, benzene exposures.  Research to date has generally
involved highly exposed individuals,  such as smokers or workers4'7-1.  Specific research objectives
include discerning low from relatively high levels of exposure through the urinary elimination of MA
and to characterize the profile of MA elimination following a single acute exposure.
       The exposure and muconic acid data presented herein are partial and represent two components
of a multi-faceted study that also included measurements of dosimetry (respiratory and cardiac rate),
and blood and breath benzene.  The analysis of the full complement of data will be reported at a later
date.

METHODS

       The experimental design consisted of a short-term acute benzene exposure preceded and followed
by periods of low-level background  exposure.  The short-term acute  exposure was generated by an
individual taking a shower using ground water contaminated with gasoline. Therefore, a •bolus-lite"
dose of benzene was introduced by absorption through the lung and skin after a period of low level
background benzene exposure.  The level of contamination, and  the likely resulting exposure  was
characterized prior to, as well as  during the study10-".  The shower dermal and inhalation exposure
was limited to 20 minutes  followed by a 5 minute inhalation-only exposure period during drying off.
Background exposures resulted from normal activities within ambient, office,  in-transit, and home
microenvironments.  The identical shower exposure scenario was conducted three  times during the
summer of 1991 (June 11, 12, and 13) with  one  shower per day over  three consecutive days.
       The methods of collecting and analyzing water and microenvironmental air benzene levels are
described in a microenvironmental measurements/intersampler comparison investigation conducted in
conjunction with this biomarker validation experiment".  Integrated and grab samples were collected
throughout the study using Summa™ canisters, Tenax GC1*, and glass gas tight syringes.  Low-flow
personal sampling was conducted using the sorbent Tenax GC" to measure the shower and background
personal exposures. The pump (DuPont P4000) was operated at 10 cc/minute during the approximately
20 h background period which preceded and followed each shower exposure. Flow calibration was
conducted at the beginning and end  of each sampling period.  Personal sampling was delayed for
approximately 2 h following the shower exposure to minimize contamination of the Tenax GC1*  with
the elevated levels of exhaled  benzene.
       All urine passed during each of the three days of the shower plus approximately two days of
background samples was collected. Voids were collected at 1-lVi and 4 h intervals during day/evening
and  night-times respectively.   Each void was  collected  separately  in polypropylene (500 ml) or
polyethylene (100 ml) screw-cap bottle with exact time and date of collection recorded on the bottle
label.  Each sample was immediately placed into a freezer or dry-ice cooler and within 1-2 days all
samples were transferred to a -20°C laboratory freezer.
       Air  samples  collected on Tenax  GC™ were  thermally  desorbed  and  analyzed  by gas
chromatography/mass spectroscopy (GC/MS). Water samples were similarly analyzed by GC/MS using
a purge and trap technique.  Grab air samples were collected with syringes and analyzed  on-site by
GC/PID (photo-ionization detection).  Urinary  muconic acid was quantified by GC/MS (single ion
monitoring) after the addition of biosynthesized muconic Acid-13C internal standard and liquid extraction
(ethyl ether) according to methods described by Bechtold et a/.13
                                             982

-------
 RESULTS

 Dose Estimates

       MA data are currently available only for the June 13th shower exposure. Air and water benzene
 ^ncentrations and  quality assurance results are reported by Luidstrom et al.n The relevant data
 required for the biomarker assessment are specified here.
       Personal sampling yielded air concentrations of 1-2 pg/ms during the background periods. The
 benzene air concentration during the 20 minute shower and 5 minute dry-off period was 525 and 398
 Pg'tn3 as determined from the integrated Tenax GC~ and grab syringe samples (20 and 25.5 minute),
 respectively. From these measurements, dose was estimated using equation I.

                                           < *J x MV x F                         <*>
         i»w is the inhaled absorbed dose frig); Q is the benzene concentration in microenvironment
        ; MV is the minute ventilation rate (0.014 mVminute)1*; I, is the duration of exposure in
JJicroenvironment i (minute); and Fis the fraction of inhaled benzene that is available for gas exchange
(70%)". -jug fckkj dose d  .   ^ 25 ^yfc showef exposure was calculated to be 122 pg yielding
a dose rate of 334 pg/h  An inhaled dose of 29 pg is estimated over the 24 h background period giving
a dose rate of 1.2 ^g/h
      The dose delivered by dermal absorption is estimated from equation 2 to be 190 pg based on a
     *ater concentration at the shower head of 24? *g/L (1 85 and 309 ,ig/L, at times 5 and 18 minutes
    the shower, respectively).
                            D^  - CW x SA x Kf  x / x V                        <2)
         «« is the dose absorbed through the sfcifl G
-------
CONCLUSIONS

      These data relate to the relationship between benzene exposure and MA elimination for a single
individual during one of three repeated controlled exposure experiments. Data from the two unreported
experiments will be used to confirm these findings and to further investigate the validity of MA as an
exposure biomarker.
      The increased rate of MA elimination corresponded to an increased benzene exposure suggesting
that MA has some capacity as a biomarker for non-occupational exposures. Although the time metric
by which dose and MA elimination are reported are not directly comparable, it is noted that the benzene
dose increased 620 fold while MA elimination increased four-fold.  This suggests that large changes in
exposure are reflected by relatively small changes in MA elimination. Additional studies characterizing
MA response to varying levels of benzene exposures are required to more fully assess this relationship
and the sensitivity of MA resulting from  benzene exposures.
      Urinary  MA elimination resulting from a relatively high  short-term dermal and respiratory
exposure shows  two  minor peaks occurring  within the first three hours and  a dominant peak
approximately 11 hours following the exposure.  Interpretations of this time course will be made based
on these results,  and  the  confirming results from  the two previous exposures when they become
available.
                                             984

-------
REFERENCES

    1-      L.A. Wallace "The exposure of the general population to benzene," Cell Biol. Toxicol.. 5(3):297-314
           (1989).

    2-      International Agency for Research en Cancer, EvalUBtipp of the carcinogenic risk of chemicals to humans.
           IARC monograph no. 29, IARC, Lyon Prance (1982).

    3-      L. Drummond, R. Luck, A.S. Afacan, H.K. Wilson, "Biological monitoring of workers exposed to
           benzene in toe coke oven industry," BrT J. Ind. Med.. 45:256-261 (1988).

   4-      FJ. Jongeneelen, H.A.A.M, Dirven, C.-M. Leijdekkere, P.T. Henderson, R.M.E. Brouns, and  K. Halm,
           "S-phenyl-N-Acetylcysteine in urine of rats and workers after exposure to benzene, " L-A2SLt..Tw'\wlt*
           11:100-104 (1987).

   s-      P. Stommel, G. Muller, W. Stacker, C. Verkoyen, S. Schobel and K. Norpoth, "Determination of S- ^
           phenylmercapturic acid in the urine-an improvement in the biological monitoring of benzene exposure,"
           Carcinopeqesig. 10(2):279-282 (1989).

   6-      W.E, Bechtold, G. Lucier,  L.S. Bimbaum, S.N.  Yin, Ghim °T Maagure™nt °f TnTic Md ^"^ Air FoI|llUnte- AWMA, Pittsburgh,
          In Press.

  13-     W.E. Bechtold, G. Lucier, L-S. Birnbaum, S.N. Yin, G.L. Li, and R.F. Henderson, 'Muconic acid
          determinations in urine as a biologicd exposure index for workers occupahonally exposed to benzene,
          Am. Ind. HVE. Assoc. J.. 52(ll):473-478 (1991).
  W.     TJS EPA. ^-r^liTr^H.rv^ments. Federal Resister 45(23 1}:793 1 3-793 79,

  15-     A.C. Guyton, Tnt^Hf ftf M"««' ^iolo^ W.B. Saunders co., Philadelphia, (1971).

  16'     LH. Blank and D.J, McAuliffe, 'Penetration of benzene through human skin, ' LJbm
         85:522-526 (1985).
                                                  985

-------
Figure 1.
           20
           15
         Z
         UJ

         s10
         UJ
         oc
                                     n  ,  n  n
                                               J	1	L
               036 91215182124273033363942454851545760


                       MUCONIC ACID ELIMINATION RATE (ug/h)



                       H Background E 3 Post Shower

           Frequency distribution of MA elimination rate during background and post-exposure

           periods.
           MUCONIC ACID ELIMINATION RATE (ug/h)
                       Background

                        Exponir*
                                  2   2.5    3    3.5


                                  TIME (days)
                                                               4.5
                                                	  I	  Port-   I

                                                          Expo*ur*  |



Figure 2.    Time course of MA elimination during background and exposure periods.
                                      986

-------
               Session 22
 Measurement of Hazardous Waste Emissions
Richard Crume and Joseph Laznow, Chairmen

-------
       MERCURY IN AIR AND RAINWATER 'IN THE VICINITY OF A MUNICIPAL
          RESOURCE RECOVERY FACILITY IN NORTHWESTERN NEW JERSEY


          Arthur Greenberg**,  lubela Wo}tenkoa, Hsiu-Wan Cban*.
             Steven Xxivanek,  Janes P.  Butler0/ Joann Held0,
                   peddrick Wels* and Nathan K. Reiss*
 a- Department of  Environmental Sciences, Cook College, Rutgers
    University, New Brunswick, Hew  Jersey 08903 and Environmental
    and Occupational Health Sciences Institute, Piscataway, NJ 08855
 b- Columbia, New  Jersey 07832
 c- Division of Science and Research, New Jersey Department of
    Environmental  protection and Energy, Trenton, New Jersey 08625
 d* Air Quality Regulation Program, New Jersey Department of
    Environmental  Protection and Energy, Trenton, New Jersey 08625
 e. Department of Anatomy, New Jersey Medical School (UMDNJ) , Newark,
    New Jersey 07103                                 „ .
 f • Department of Meteorology, Cook College, Rutgers University,
    New Brunswick, New Jersey 08903
      sampling of ambient air for elemental mercury  [Hg(O)]  as well as
  oluble mercury in rainwater has been carried out at a number of sites
 in the  vicinity of  a municipal resource recovery  facility  (RRF)  in
 northwestern New Jersey.  This rural region appears to have a relatively
 low atmospheric  mercury  background.  The  predominant form  of mercury
 Bitted by a municipal RRF  is  anticipated to  be HgCl2,  thus producing
 higher local levels  of water-soluble  mercury compared to  background
 H<3(0) . The results of six rain events  suggest the contribution of the
 ***•  Analyses  of muscle  and   liver  tissues  of  eels  do not  indicate
 ynusual accumulation  of mercury. Conclusions concerning potential health
 impacts await future studies of atmospheric modeling as well  as human
 ai*J animal exposures.

 INTRODUCTION                                                     ,    f
     A renewed  and growing concern with ambient  atmospheric levels  or
 *ercury and the anthropogenic sources  of this toxic metal1"4 has  proyiaea
 impetus for  studies of mercury  emissions  in coal-fired power plants  as
 £U  as municrpal resource  recovery  facilities   (RRF) .  The .latter are
 expected,  in  the  absence  of  highly  efficient,   •P?t**l*Ie*aCl    a
 scrubbing  equipment,  to emit mercury largely  in the form P^JJoSibJ
 rather volatill salt.3 Thus, in the vicinity °f  an RRF, "gJLJ °£  ,£
             exceed the level of atmospheric Hg(0) '**J"l4kMWn  t0  be

                                    ^
                                                                  v
^icipar^F  The MtF chosen for study is a two-stack, 4 00- ton per day
Utlit in  rural northwestern  New Jersey.  This particular  facility is
e<3Uipped Jifh a dry fabric filtering system.  Its maximum allowable total
                   have Seen  set at  0.05  Ibs/hr/stack. Although the
                                  989

-------
overall RRF  study involves a  wide range of organics  and metals, the
present study  focuses on mercury  in three forms:  soluble mercury *n
rainwater, elemental airborne mercury  and total  mercury  in  eels as
bioaccumulators.
EXPERIMENTAL DESIGN

     The  initial  phase of  the mercury study  involved measurement of
airborne  elemental  mercury  [Hg(0)] at four air  sampling sites in the
vicinity  of  the  RRF. These  four  sites  (#1-4 below)  are at  a fa**
adjacent  to the facility  ("fencepost site"),  a farm upwind of the M*
(for  prevailing winds)  that  is  more distant and  behind a  hill,  *
condominium in the predicted moderate impact zone,  and  a water tower i"
the predicted high impact  zone. Rainwater samples were also collected at
these four sites with additional sites added (see below)  depending upon
the strategy employed. In the later phases of this  study access to Site
#1 was discontinued and a new  location, Site #5, was substituted.
     Elemental mercury was collected for  24-hour periods using a Jerome
422 dosimeter attached to  a  pump operating at either 500 cc/min or  1»0°°
cc/min.0 The dosimeters were attached to  a Jerome 411 mercury analyz«r'
the mercury  transferred into  the  latter and  analyzed  at the outdoor
sites. Control experiments performed in our laboratory  indicated little
variation of dosimeter efficiency as a function of  outdoor  temperature-
Backup dosimeter experiments indicated almost  quantitative recovery of
Hg(0)  in the first dosimeter at 500 cc/min with breakthrough of ca 25*
at a sampling rate of 1,000 cc/min.  Rainwater was collected according to
the protocols  of Glass et  al7 using 500-ml or  1,000-ml  polyethylene
bottles containing  oxidizing  solution and teflon funnels. The bottles
with oxidizer, funnels and distilled water for  rinsing  the  funnels were
supplied by Dr. Glass. Collected samples were  shipped overnight to or-
Glass within 24 hours of collection.
     The sites (Figures 1A-C)  employed in this  study are the following-'
1. "Fencepost site" on farm slightly >i km E of RRF.(AIR SITE)
2. Background site on farm ca  3.5 km NW of RRF.(AIR SITE)
3. Residential site, condominium development ca 2 km E of RRF. (AIR  SITE)
4. Water tower, predicted "high impact",  ca 1.5 km E of  RRF.(AIR  SITE)
5. New "fencepost site", farm  ca 1.5 km E (slightly N) of RRF (AIR  SITE)
6. Quarry SW,  site <0.5 km sw of RRF (6A and 6B  are  co-located samplers)
7. Quarry W,  site <0.5 km W of RRF
8. Quarry NW, site <0.5 km NW  of RRF
9. Farm site, <0.5 km N of RRF
10. Farm site, ca 1.5 km S  (slightly W)  of RRF
11. Farm site, ca 2 km SW of RRF
12. Farm site, ca 2 km NW of RRF
13. Farm site, ca 3 km SE of RRF
14. Farm site, ca 3.5 km W of RRF
15. Farm site, ca 3 km NW of RRF
16. Farm site, ca 2 km N of RRF
17. Farm site, ca 5 km NE of RRF
18. Farm site, ca 4 km SW of RRF
20. County property near road, ca 2 km NW of RRF
21. County property adjacent to road, ca 0.5 km NE of RRF
22. County property adjacent to road, ca 100-150 m N of  RRF
23. County property adjacent to road, ca <0.5 km NW of RRF
24. County property adjacent to road, ca 0.5 km NW of RRF
25. County property adjacent to road, ca >0.5 km NW of RRF
26. County property near road, ca 0.25 km SW of RRF
27. Farm site, ca <1 km N of RRF
28. County property- by road entering RRF, ca  1.5 km SE  of RRF       ,
    American eels (AnguiJJa rostrata), which are considered to be wei*
suited for mercury bioaccumulation studies,8 were collected at the  three


                               990

-------
  Figure .1.  Maps of area  (approximately 4 mile X 6 mile; in western New Jersey for A) January, 1991,




 B) Fall,  1991 and C) Spring,  1992 sampling periods. The identities of the air and rain sampling




sites (1-28)  and eel sampling  sites  (E1-E3) are described in the text  of this paper.
          •'•Vectors  represent wind direction

-------
sites shown in Figure  1  and the muscle and liver of each analyzed for
total mercury using  digestion  and cold vapor analysis. These eels are
bottom dwellers  and  ubiquitous in the  water bodies investigated. The
locations were chosen as follows: River  Site 1,  ca 1.5  km NE of RRF
considered to be close but  not  in the high impact zone of plume;  River
Site 2, control site, ca 6  km ENE from RRF; Brook Site 3, ca 2.5  km SE
of RRF in normal high impact zone of plume.
RESULTS
     The rainwater results are described first and are  listed  in Tables
1-3 which reflect  three different site location strategies. The first
two rain days  (1/15-1/16/91  and 1/19-1/20/91)  were monitored during «
six-day  State-mandated  stack  sampling  period  (1/14-1/19/91).  Stack
samples were collected during 2-hour periods (ca 10 AM-Noon)  for each of
these days. The data obtained from the NJDEPE  indicated that the stack
levels monitored  during this period  varied little  and  averaged just
under the permitted 0.05 Ibs/hr/stack. The eight sites monitored on each
of the two rain days included the four air monitoring  sites as well as
four other sites.  The four  air monitoring sites were chosen on  the basis
of atmospheric modeling using prevailing wind conditions. The additional
rain sites were chosen to reflect the  prevailing wind directions during
rain. Unfortunately, a small meteorological station located at Site 2
did  not  function during this period. However,  interpolation of wind
direction-speed data between Newark, NJ and Allentown, PA furnished data
useful for our study. Data for this first period are listed in Table 1-
The second period of rain sampling occurred during Fall, 1991. Here the
strategy involved adding to  the January network in a manner so as to
—————————_——-—	————————_________—	_.._.__—_———"—
Table 1. Hg concentrations in rainwater  (ng/L  or ppt), January,1991.
(NOTE:  These values  are  volume  corrected and differ  slightly from
earlier values). Below the  sampling date(s) are the wind direction/speed
from Newark Airport (N), Allentown Airport (A)  and the interpolated site
data (I) [090= winds from  E.; 180= winds from  S.]

DATE SITE #
1/15- 1
1/16/91 2
Ntl30/05 3
A:040/06 4
1:080/06 11
14
15
16
17
Field Blank

Detm
18
21
10
5
4
<2
5
10
__
<2
Hg Cone
l Detm
19
20
10
8
4
8
11
9
__
—
(PPt)
2 Avg
18.5
20.5
10
6.5
4
4.5
8
9.5
__
<2

DATE SITE #
1/19- 1
1/20/91 2
N:260/09 3
A:270/09 4
1:270/09 11
14
15
16
17
Field Blank

Detm
96
28
69
68
116
__
12
11
11
<2
Hg Cone
1 Detm 2
__
_-
—
—
—
— —
__
__
-_
— —
(ppt)
Avg
96
28
69
68
116
* —
12
11
11
<2
provide "concentric rings" of samplers biased toward the prevailing wind
direction  (easterly)  that  usually accompanied  rain.  These  data  are
listed in Table 2. In Table 3 we list rainwater mercury concentrations
obtained during  the Spring, 1992  sampling period. Here  the sampling
strategy was  changed.  Instead  of placing  "rings"  of  samplers with no
specific planning for plume direction, the strategy involved presetup or
some samplers based upon the previous day's knowledge of the anticipated
wind direction, with final placement of the remaining samplers under the
visible plume  or at least in the  observed prevailing wind direction.
This strategy was first attempted on March 26, 1992. While  the plume was
not  visible,  observations  at  the meteorological  station at the  RRF
indicated the^ prevailing  wind direction.  Shortly  after  five samplers
                                 992

-------
 were placed   it  was  discovered that the RRF had not been operational
 since  March  22. The  result of  this  unanticipated  event was  the
                .
 opportunity to collect rain next to the facility on one of th« rare days
 when  it  was shut down.  On April 9, 1992, this strategy was f?Pl°y;d
 While the RRF was in operation. Although no plume was visible, the wind
 direction was again obtained from the RRF
              ocenra                   (ng/L or ppt) for
 1991 and December,  1991 sampling periods  (also see heading of Table
DATE SITE #
9/24- 2
9/25/91 3
N: 180/07 4
*!130/09 5
IS150/Q7 6A








5B
7
8
9
10
11
12
13
14
16
*,, 18
pield Blank
Detm
22
8
11
3
192
175
16
13
16
24
11
— —
13
<2
Hg Cone
1 Detm
173
172
— ~
_•*•
-•~
25
11
~™*
^"*
—
(ppt)
2 Avg
22
&
11
8
182.5
173.5
16
• 1
13
•f f
16
A rf c
24.5
M «
11
•4 1
13
<2
DATE SITE #
12/2- 2
12/3/91 3
N:060/09 4
A:050/10 5
1:050/10 6A
6B
7
8
10

12
13
14
16
18
Field Blank
Detm
13
14
20
19
140
130
540
21
28
14
19
13
15
29
12
63
<2
Hg Cone
1 Detm 2
—
__
__
__
_—
— —
__
__

(PPt)
Avg
13
14
20
19
140
130
540
21
28
14
19
13
15
29
12
63
<2
^sults of th^se two sailing days are listed in Table 3. The ^pling

Wi 9rSS^S^f^^SS£^: {-fs ^S^pSK 3LS
          with the  rain
                              on that day.
DATE   SITE #
V26/92   4
!f:l30/12  20
A;060/08  21
i:09
     Hg Cone  (ppt)
Detm 1  Detm  2  Avg
 48
 33
 26
 38
 62
48
33
26
38
62

DATE SITE
4/9/92 4
N: 100/07 20
A:100/06 21
1:100/06 22
23
24
25
26
27
28
Field Blank
Hg
# Detm
32
606
87
56
24
—
107
27
307
25
1
Cone
1 Detm
—
53
^ ^
— ~
«
—
—
—

(PPt)
2 Avg
32
606
87
54.5
A 4
24
"•••
107
27
307
25
1
         22
         23
         24
         25
         26
         27
         28
      BlwnV
         "^«       *                         	^.^^•^••^— ' •••••••••  —*	
     ir7a;re"4";7TisT;;7oV-7haT^^^^                g^ ^
   PUng  sites (#1-4, January, i99li *2-*L°*Pll  site  #1 discontinued
   be  changed  to Site  #5  since Jhe owner 3 A dl  t  that no sample
   —•).  Whereas the blank spaces in J^1*8  1Ttb11",4^indicate that poor
     Won was attempted, the KAs^ations in Table ^indi ^ ^^^P^
     .oning or stoppage of the sampling p^P  ^ ^  invegtigati   ;f
                                          sensible. The present study
                                 993

-------
employed  American eels  (Anguilla rostrata)  which  represent bottom-
dwelling fish known to be a major dietary route for mercury in humans.
The very limited number of samples investigated  in the present protocol
study is  too small to draw scientific  conclusions.  Future studies of
this type, should  they  be called for,  might involve larger samples of
fish, grain, milk, meat, or human blood and urine.

Table 4.  Vapor-phase  elemental mercury [Hg(0)]  concentrations  (ng/m3)
obtained  at  the air monitoring sites #1-4  (1/91) and  #2-5 (9/91). NA
notation indicates invalid pump operation or pump stoppage. Samples ran
for about 24 hours, beginning at about 10 AH on start date.

START DATE
1/13/91




1/14/91




1/15/91




1/16/91




1/17/91




1/18/91




1/19/91



1/20/91




SITE #
1
2
3
4

1
2
3
4

1
2
3
4

1
2
3
4

1
2
3
4

1
2
3
4

1
2
3
4
1
2
3
4
Hg(o)
Cone (ng/nr)
1.35
NA
NA
1.74

5.08
3.99
4.04
2.30

3.70
2.13
2.40
1.45

2.73
2.85
NA
1.93

1.76
1.23
NA
NA

0.82
0.53
NA
NA

1.96
1.38
NA
0.28
3.50
0.70
NA
2.56

START DATE SITE #

9/9/91 2
3
4
5

9/10/91 2
3
4
5

9/11/91 2
3
4
5

9/12/91 2
3
4
5

9/13/91 2
3
4
5

9/24/91 2
3
4
5








Hg(0)
Cone (ng/mj)

1.73
NA
NA
0.08

24.69
0.25
NA
19.99

14.80
19.21
NA
7.25

NA
0.36
2.27
0.14

3.52
NA
1.60
3.73

2.96
2.44
2.40
1.96








     Table 5  lists the results  for  analysis of total mercury in the
muscles and livers of eels caught at the three sites in Figure 1A.

DISCUSSION OF RESULTS
     The Hg(0) data  in  Table  4  should not be readily interpretable in
terms of source since this pollutant comprises most of the background
mercury* and results  from a combination of atmospheric reactions. It is,
nonetheless,   interesting  that for six  of the eight sampling days in
                                 994

-------
January, 1991, the highest Hg<0) levels were observed at the "fencepost
site"  (site #1) and that the levels at Site #1 were close to the highest
for the next two days. As stated previously, the stack sampling which
occurred during this  period in January showed nearly <»n«tant *ercury
Missions.  It  is important,  however, consider the facts that  a)  the
stack sailing period was  2 hours and the Hg(0) collection
     and b) that the  predominant form of mercury
                                                           was 24

                                                         "    °
 Table 5. Data for total mercury analysis  of  ^"f10""^1"
 ^strata)  conducted at three locations (Figure 1A) on July 2' __  - •-
 November 20,  1991. The concentrations (ug/g or ppm) are the average  of

 triplicate Analyses                        November 20, 1991

 Site*  Eei YD  TissueCone (ppm)    Site t  Eel  ID Tissue  cone (ppm)
  ••^               _.     _ —. ^ •*         1*.^.       A
  El
  E2
          B
  E3
          E
          B
•uecle
liver
muscle
liver
muscle
liver
muscle
liver
muscle
liver
muscle
liver
muscle
liver
muscle
liver
muscle
liver
muscle
liver
muscle
liver
muscle
liver
muscle
liver
muscle
liver
muscle
liver
0.065
O.02O
0.120
0.103
0,090
0.111
0.114
0,078
0.078
0.109
0.031
0.010
0.097
0.124
0.021
0.011
0.039
0.019
0.076
0.077
0.066
0.018
0.068
0.069
0.280
0.181
0.098
0.044
0.235
0.130
                                             B
                                    E2
                                             6
                                     E3
                                             B
muscle
liver
muscle
liver
muscle
liver
muscle
liver
muscle
liver
muscle
liver
muscle
liver
muscle
liver
muscle
liver
muscle
liver
muscle
liver
muscle
liver
muscle
liver
muscle
liver
muscle
liver
O.OS7
0.067
0.06B
0.044
O.OB1
0.034
0.138
0.095
0.204
0.160
0*086
0.074
0.133
0.058
0.079
0.025
0*073
0.074
0.198
0.127
0.070
0.060
0.084
0.082
0.030
0.022
0.092
0.034
0.166
0.121

110 (126; 41); 3-11E  (427; 74).
SxSS«iSE£u^^^
                               995

-------
in summer and 3.7 ng/ra3 in winter.10 The  data may  also be compared with
the  Oct./Nov.,  1990  values  obtained over  the Atlantic Ocean in the
northern hemisphere  (mean, 2.25 ng/m3; range, 1.41-3.41 ng/m3).2
     Interpretation of the soluble mercury in rainwater  data is done in
qualitative terms here. Without direct wind information, the local data
were  interpolated using  Newark Airport  and Allentown  Airport, thus
adding uncertainty to wind data. The rainwater mercury data  clearly show
considerable site-to-site variation.  The prevailing wind direction on
1/15-1/16/91 was easterly and all levels  were low,  reflecting the facts
that the closest sites were upwind and the furthest sites were downwind.
However, the westerly wind on 1/19-1/20/91 raised  concentrations at the
nearby sites 1,3 and 4.  The explanation for the higher number at Site H
is not obvious.  The data on 9/24-9/25/91 and 12/2-12/3/91 are especially
striking.  Both  days were  characterized  by very  heavy  rainfalls.  The
levels at tne closest sites in the prevailing wind directions are 10-30
times  higher than  background.  The  particular  site values appear to
closely  reflect  prevailing  southeasterly  winds  on  9/24-9/25  and
prevailing northeasterly winds on 12/2-12/3. The relatively low levels
on 3/26, the day that the  RRF was not running, at locations  close to the
facility are striking. Nevertheless, explanation of the value at Site 24
is not easily done. Perhaps most interesting, from the point of view of
future modelling studies,  are the data of 4/9 in which very  high numbers
are seen in the general prevailing wind direction but not closest to the
facility. These data,  obtained  during a  moderate rainfall  suggest the
importance of the kinetic component of mercury  washout.
  f  For the sake of comparison, we note  that during the period 19B8-89
rainwater mercury concentrations in Duluth, MN  ranged from  0.9 ppt to a
singular value  of 100.9  ppt.9  A  value of  18  ppt is indicated as an
average in the  Minnesota rainwater  study, although an anomalous period
(Spring,  19BS>   occurred  in  which  thirteen  consecutive  rain  events
averaged  200 ppt  at Ely, MN.9  it was  felt that these  hiffh  numbers
betrayed the presence  of  a local  mercury source.9  The 18 ppt value
appears to be similar to background values in northwestern  New Jersey.
The  two  data points  in the present  study above 500 ppt  are  clearly
unusua1.
     The eel data presented in Table 5 yield no strong conclusions. Ifc
must be  emphasized  that  our main  purpose in  analyzing  eels was to
explore a bioaccuroulation assay protocol. Eels bioaccumulate mercury
thus providing integration over many years.  The  incinerator has been in
operation for  less than  four  years.  Not surprisingly, the older and
larger the eel, the  greater the potential for  bioaccumulation.8'9  The
small dataset does  not  indicate high mercury levels.  The  site-to-site
comparisons of  results  are confounded by the migration habits of the
eels, their different ages, sizes  and size distribution of  the catch at
a given site. For co^pa-riaott's sake, we note that levels of mercury i-n
Angullla  rostrata  collected  in  the St.  Lawrence  River  and  rivers
draining into it varied from 0,131 to 1.994 ug/g (ppm) with  the highest
levels found in the Savernay River, which is known  to  be polluted by
mercury from industrial operations.8


CONCLUSIONS
     The conclusions of this study may be briefly summarized as follows3
1. The thrust of the study has been  the development of protocols rather
   than a sample-intensive, statistics-generating approach.
2. Levels of water-soluble mercury in rainwater  show the greatest site-
   to-site variation of the three mercury analytes explored in this
   study. The highest values exceed 500 ppt.
3. The variation of  rainwater  mercury concentrations with site  location
   and wind direction are  conais.te.tvt with the RRF  as tne local source


                                    996

-------
   but do not prove it definitively.
4- Concentrations of elemental mercury in air also show
5.
    	"-— v^ «•>••* ^d*--* *^»»fc»fc.»-^™^ ^— —• —•	    •

   and their migration habits.               .         *,„«.-- =wa4t- the
6. Conclusions concerning health risks  to animals ^(jh«man^ua™lt the
   collection of more data and  the assessment of exposure routes.
       ceoa grant from the Division of *£»£*
N«w  Jerse?  Department  of  Environmental  P"^.0*""  *B5L, Jr  Avram






                                                *         °fP
5uSS^° - ^-^J^Lnirsss;  S!

chemistry o'f mercury.
                     ^^
   and  Corrective Methods ",  55:  (1991) .        atmospheric
   P. Slemr and E.  Langer,  "Increase in gl °JjJ^2g; "ver the
   concentrations of mercury inferred from measurements o

   Atlantic Ocean" ,  HfltoUCf'  35?}nliJ1ii ^chemical reactions of  mercury
   B. Hall,  P.  schager  and  0. Lindguist, ^JJJr8^,,    56:  3 (1991) .
   in combustion flSe gases", ttntnr .Mr * ^ff ^' determination of
   2- P. Xiao, j. Munthe  and  0. Lindguist,  s^PAi"9    using  gold-coated
   gaseous  and  particulate  mercury  in t*J.aJJ?!gJ:71S;i)T  9
   denuders", HUrr.  flir *  yU T  J^jd and J.  Waldman,  "Design of  an
   A. Greenberg,  J.P. Butler, J-L-Hel^""ce  recovery facility in  New
   environmental monitoring study at a re source^ cam ery
   J*-«y«,  Paper 91-132.3,  84th Annual Meeting,  Airj   ^^
   Managenent Association,  June 16-21, ^ wax, v            tfith  mercury
   C, Brosset and A. Iverfeldt,  "In^a5j-1,on 43.  147-i69 (1989).
   in ambient air",  Eitnr ,   ^ Vn  Mdt"ni  G.R! RaPP/ Jr. ,  New
   G.E. Glass,  J.A.  Sorensen, K.W. scnm^.^"_ ta  in the  Great Lakes",
   source identification of    ouc°
                                  Qo
                 Technol., 2T4;R1°"aux lourds comme  indicateurs

                           i                    (^ilja rostrata) '
                         Sci., 39: 1004
  Gass, T.A, Sorensen  K.W.  "*
Praser, "Mercury deposition and sources for
    . Praser, "Mercury deposton an
  region", wntnr. Mr ft ^M K^L^TOTT of  atmospheric mercury over
  ' A. Iverfeldt, "Occurrence and turnover or ^^^t-         (1991).

   the Kordic countries",               0** P0^4^'
                                  997

-------
POLYNUCLEAR  AROMATIC HYDROCARBON  CONCENTRATIONS IN
THE EMISSIONS FROM WASTE COMBUSTION AT SELECTED
MUNICIPAL, MEDICAL/MUNICIPAL, AND RESEARCH INCINERATORS

Lance Brooks, Ron Williams, and Jason Meares
Environmental Health Research and Testing, Inc.
P.O. Box 12199
Research Triangle Park, NC 27709

Randall R. Watts and David M. DeMarini
Health Effects Research Laboratory
Paul M. Lemieux
Air and Energy Engineering Research Laboratory
U.S, Environmental Protection Agency
Research Triangle Park, NC 27711

    The U.S. Environmental Protection Agency (EPA) is currently investigating the possible health
effects associated with the products of incomplete combustion (PICs) from municipal,
medical/municipal, and research incineration units.  Emission particles from the incineration of
municipal waste, mixed feeds of medical/municipal wastes, and a common plastic have been
extracted, fractionated, and analyzed  for the presence of 16 priority pollutant poly nuclear aromatic
hydrocarbons (PAHs).  A modification of  U.S. EPA Method 610 was utilized. This involved
selection of time-programmed excitation and emission wavelengths for high-pressure liquid
chromatography (HPLC) fluorescence detection of individual PAHs using a PAH-specific CIS
reverse-phase column.  Detector optimization and calibration, as well as chromatographic
conditions, are presented. Individual concentrations of PAHs in emission particles from municipal
and mixed waste feed incineration were found at levels up to 4 ng/mg particle.  Individual PAH
emissions as high as 4000 ng/mg particle were observed in the incineration of polyethylene plastic in
a rotary kiln research incinerator  operating at suboptimum conditions.  Little variation in PAH
particle concentrations was  observed  during two collection periods at the medical/municipal
incinerator.  Results obtained from periodic sampling at the municipal waste unit were found to vary
by PAH and concentration.  Particle  concentrations from the sampling locations for the 16 priority
PAHs are described.

INTRODUCTION

    Incineration technology is currently being used as one of the primary means to dispose of or
treat municipal, medical/pathological, and hazardous mixed  feed waste(l-3).  Although incineration
is often deemed the "best available technology" for waste treatment, little is actually known about
the PICs formed during the process.  This is especially true when "real world" sources such as
municipal and medical/pathological wastes that contain a variety of materials (plastics, biomass,
metals, fibers, etc) are incinerated. For this reason, the U.S. EPA is currently involved in a series
of studies evaluating the emission products from a number of incinerators(2-4). Permission was
received to collect stack particles from a municipal waste incinerator, a mixed waste incinerator
 (medical/municipal), and a research unit combusting a commercial plastic (polyethylene).
 Specialized sample collection systems consisting of either a Source Dilution Sampler (SDS) or a
 Baghouse Dilution Sampler (Baghouse) had been designed specifically for capture  of incineration
 emissions and were employed in  this study.  Details concerning the design and use of these stack
 samplers have been reported(4-6).
                                            998

-------
     Preliminary results from analysis of the dichloromethane (DCM) extracts of incineration samples
  indicated that some whole extracts were mutagenic(2,3)- Bioassay-directed fractionation was then
  conducted on these extracts using a previously reported ion exchange process that yielded
  base/neutral, polar, and acid ftactions(S). The base/neutral fraction contained significant mass and
  "iitagenicity from some incinerator extracts (2).  Based upon the known biological activity of some
  PAHs and their suspected presence in. this subtraction, quantitation of the 16 priority pollutant PAHs
  ^as performed using a modification of U.S. EPA Method 610(7). Method 610 utilizes a nonPAH-
  specific CIS reverse phase column with ultraviolet (UV) (254 nm) or fluorescence detection at one
  excitation/emission wavelength pair.  One modification of this HPLC method consisted of the use of
  a PAH-specific reverse phase LC column that contained highly uniform and PAH-selective silica
  chosen by the manufacturer prior to endcapping.  The advantages of specific PAH column packings
  over conventional CIS columns have been reported(8).  Another modification was the use of time-
  P^giammed excitation and emission wavelength selection that results in lower detection limits and
  Wgher specificity (elimination or reduction of fluorescence intensity from interfering analytes) for
  toe 16 priority pollutant PAHs. Due to the complexity of incinerator emissions, both modifications
  were needed for the 16 PAHs to be satisfactorily resolved at low detection limits with elimination or
 Deduction of chromatographic interferences.  This study reports the PAH particle concentrations
 determined from three incineration sources.


 EXPERIMENTAL

    A prototype SDS unit operating at 10 cfm (0.28 mVmin) was used to collect stack^missions of
 Particles at a municipal waste incinerator (Incinerator A) operating 24 hours/day,  having,two
 tientical 100 ton/day opacity boilers. Each  unit had its own ram piston  economizer, and
 electrostatic pfS^P) m* a single common stack. The SDS unit w*^^" *™&
 a medical/munid^[incinerator (Incinerator B) that consisted of two 50 ton/day Consumat
 farved-air bx>HeSngTShared ESP and stack. Only 3-5% of the waste <™b™£™V*"»S
 ^ility was medical/pathological waste based upon estimated mass.  A complete description  of the
     and samples collected has been reported eariier(2,5).
                              at 2.83 nWmin and designed to collect larger quantities of
                                w  «»« used tn collect the entire stack emissions at a pilot-
 --—-««» as wmparea 10 me DW a»eraDiy was, IK*** w         M—tino*ttbe>n
-------
emission extracts encountered in this study of incineration sources.  Acidic components have existed
to such an extent that upon occasion DCM extracts of incineration particles have corroded aluminum
weighing pans utilized in gravimetric determinations.  The procedure allowed for extract mass to be
fractionated into a base/neutral, polar, and acid subfractions.  Neutral PAHs have been shown to
essentially elute 100% into the base/neutral subfraction(3).  The mass concentration of each
subfraction was then determined through gravimetric analysis.  Dilution of the base/neutral
subtraction (in DCM) followed by solvent exchange into acetonitrile was performed for each sample
in preparation of HPLC analysis.

HPLC ANALYSIS

    HPLC analysis was performed using a Varian 5560 LC equipped with a Varian 604 Data Station
and a Perkin Elmer LS40 fluorescence detector.  Five microliter injections of each neutral
subfraction, as well as the quantitation standard (National Institute of Standards and
Technology-NIST PAH1647a) were utilized. Injections were made onto a 25 cm X 4.6 mm i.d., 5
tim Supelcosil LC-PAH column(#5-8229).  A Supelco CIS guard column (#5-9554, 2 cm X 4.6
mm) was utilized in line with the analytical column.  Both HPLC solvents (acetonitrile, water)  were
Burdick and Jackson HPLC grade, with only one lot of each used throughout the analysis.   Solvents
were degassed using helium sparging to eliminate possible oxygen quenching during fluorescence.
A solvent gradient of 65% water/35% acetonitrile was maintained initially for 2 min followed by a
linear gradient to 100% acetonitrile in 14 min.  A 9-min  hold at 100% acetonitrile completed the
LC program.  Flow rates were 1.5 mL/min throughout the analysis. The above LC conditions
allowed for adequate PAH resolution over the shortest analysis time.  Solvent blanks were analyzed
prior to incineration samples as part of quality  assurance  steps.  Linear response curves were
performed for each of the 16 PAHs using a minimum of three concentrations.  These standards
ranged  from 0.0 to 0.7 ng/mL  over three orders of magnitude.  PAH results were corrected for
blank interferences and quantitated using  data from a single point calibration standard utilized daily-
Excitation and emission wavelengths were selected that offered the best compromise between
compound specificity and fluorescence intensity that  allowed for use of longer excitation
wavelengths to reduce or eliminate detection of nonaromatic analytes.  Compromise wavelength and
attenuation factors were also used when adjacent peaks lacked 1.0 resolution factors and wavelengths
could not be changed.
 RESULTS

    Data concerning
 calibration results, limits of
 detection, wavelength and
 attenuation selection, and
 retention times of each PAH
 are presented in Tables  1 and
 2.  Calibration coefficients
 (r2) were found to exceed
 O.990 for all PAHs and in
 most cases exceeded 0.999.
 Limits of detection were
 calculated based upon an
 injection volume of 5 uL of
 NIST standard stock solution
 and using a 5 X Signal/Noise
PAH







fyrene





Dibenzo(* ,h)inlhnceiw


Detection Limit
ppb (ug/L)
0.06
0.04
0.03
.0.01
0.03
0.003
0.10
	 6,46 "
0.03
1 0.007
	 6.6i 	
0.003
6.663 ""
6.003
0.30

Calibration
(R1)
0.9951
0.9923
0.9904
0.9902
0.9949
0.9992
0.9991
0.9999
0.9996
0.9997
0.9999
0.9998
0.9999
' 6.9994
0.9970
0.9999
(min) _
^To!S^
— 10>
— ilJir
" 12.76 	
- iT35
" iS37
- 14.70
- 103
TJ.61 _
. 9
— 101
— i*7J3
l£2S
- ioxn.
*v«y*
— 21.55
Table  1.   HPLC Analysis  Conditions
                                          1000

-------
         PAH
                     Excitation
                                                         (S/N) ratio.  Pyrene was found to
                                                         have the highest detection limit (0.40
                                                         ug/L) with anthracene,
                                                         benzo(k)fluoranthene,
                                                         benzo(a)pyrene, and
                                                         dibenzo(a,h)anthiacene the lowest
                                                         (0.003 ug/L) under the test
                                                         conditions. Specific wavelengths
                                                         were used when possible.
                                                         Compromise wavelengths were used
                                                         for analyte pairs failing to
                                                         completely resolve.  These pairs
                                                         included acenaphthylene and
                                                         fluorene, benzo(a)anthracene and
                                                         chrysene, benzo(b)fluoranthene and
                                                         benzo(k)fluoranthene, and
                                                         benzo(ghi)perylene and
                                                         indeno(l,2,3-cd)pyrene. Attenuation
                                                         factors at each wavelength change
                                                         were determined through
experimentation so that acceptable noise and sensitivity levels were achieved. Retention times were
found to average within 0.09% RSD as evidenced by the retentions obtained from triplicate
analyses of the NIST standard.
 Table 2.   Detector Conditions
                                              HI 51 PMI SID
    Chromatograms of the NIST standard and neutral fraction extract from incinerator
 in Figure 1 and are representative of those obtained for the other
 Etta pe* not labeled in the NIST standard chromatogram are
 in their mixture. The NIST standard chromatographed satisfactory as
 as well as the resolution between near eluting peaks.  As seen in the lower chromatogram, the peak
 shapes in the incineration extracts are
 sometimes affected by interfering species.

 Comparison  of the calculated particle
 concentration (Table 3) of each PAH(ng
 PAH/mg particle) reveals observable
 differences between the various incinerators.
 Benzo(a)pyrene, for example,  was found  to
 range from 0.004 to 875 ng/mg particle.
 Further comparison reveals that emissions from
 Incinerator B, a unit combusting mixed
 municipal/medical-pathological waste, had the
 lowest overall particle concentrations of PAHs.
Particle concentrations from the samples at this
incinerator ranged from below detectable
quantities to only 0.2 ng/mg
(Benzo(a)anthracene-Sample 2), for example.
Whole particle concentrations found in samples
from Incinerator A were  slightly higher than
those from Incinerator B  and also more          Fiaure l  chromatographs of Modified
variable. The Incinerator A sample was found   Figure l . cEftprAOI^th9od P610
to have nondetectable levels of the early eluting
                                          1001

-------
                                                               (low molecular weight) PAHs
                                                               with compounds phenanthrene
                                                               through
                                                               indeno(I,2,3-cd)pyrene found
                                                               to be in a narrow range of
                                                               0.1-4.0 ng/mg.  Differences
                                                               observed between the two
                                                               samples at this site may well
                                                               have been due to composition
                                                               of the waste feeds, but
                                                               weather may have played a
                                                               part (there was heavy rain
                                                               just prior to the loading of
                                                               waste in Incinerator A). The
                                                               municipal waste  at Incinerator
                                                               A is unprotected from the
                                                               elements and,  therefore, was
                                                               saturated with rain water.
                                                               During incineration, water
                                                               vapor exiting the stack was so
                                                               prevalent that  the sampler
attached to the unit to capture emissions had to be turned off due to large intakes of condensing
water.  The temperature quenching effect of high-moisture content may very well have  reduced
conditions necessary for PAHs to be formed or acted as a water spray like those used in emission-
control devices.

    Particle stack emissions (Table 3) from the incineration of PE (Incinerator C) were found to
have the highest levels of all PAHs. Concentrations found in the PE  sample combusted without an
afterburner (Sample #2) were found to range up to 4007 ng/mg particle (pyrene).  PAH formation
from combustion of PE with an afterburner (Sample #1) was reduced  10 to 1000 fold as seen in
table 3.
PAH
Naphthalene
Acenaphthene
Acenaphthylene
Fluorcne
Phcnanthrene
Anthracene
Pluoranihene
Pyrene
Benzo(b)u)thncene
Chryaene
Benzo(b)Quonnlhcne
Benzo(k)fluonnlbene
Benzo(t)pyrene
Dibenzo(a>h)anlhnceiM
BenzodJi,i)p«ryl«n*
Indeoo(l ,2,3-cd)pyrene
Incinerator A
Simple* 1
0.11
*#*
*++
0.10
1.08
0.01
0.25
0.17
0.48
1.10
0.01
0.08
0.04
0.02
***
•*•
Samplc*2
*•*
+**
++*
*»•
0.11
***
2.33
0.38
0.73
1.61
3.97
1.32
0.34
0.84
3.36
3.11
Incinerator B
Simple* 1
0.02)
0.009
+++
0.028
0.042
0.001
0.021
***
0.007
0.004
0.031
0.008
0.004
0.001
0.092
0.030
Simplefl
0.060
0.007
***
0.014
0.051
0.012
0.084
*»*
0.204
0.111
0.091
0.038
0.015
0.014
0.016
0.060
Incinerator C
Sample*!
5.80
0.50
»**
0.70
18.70
0.50
11.30
29.60
0.80
0.10
0.10
0.03
0.20
0.01
0.70
0.10
Sample*!
15.20
108.00
**•
*#•
2037.50
231.10
2193.60
4006.80
349.20
301.10
350.00
230.20
874.60
12,70
*•*
797.00
(***) not detected
Table  3.   Particle  Concentrations of  PAHs
             (ng PAH/mg Particle,  ppm)
DISCUSSION

    This study demonstrates that measurable quantities of condensable PAHs can be emitted from
incinerators and quantified.  A modification of EPA Method 610 HPLC permitted low limits of
detection with high specificity to be employed during quantitation using programmed wavelength
fluorescence and a PAH-specific CIS column.  Variations  were shown to exist between two
incinerators (A,B) where over 95% of the refuse combusted was municipal waste.  Differences were
expected due to differences in operating conditions and variability of waste feed streams.  Results
from the incineration of PE indicated that the use of an afterburner reduced individual PAH
emission 10 to 1000 fold. The incineration of this type of plastic (and presumably others) may
result in the  formation of PAHs at a much higher rate than those encountered from municipal waste.
This also was expected due to the organic-rich nature of PE.  Further investigation of pollution
control technology and combustion conditions could further safeguard the use of incinerators to
handle the growing problem of refuse treatment.
                                             1002

-------
  ACKNOWLEDGEMENTS

  This work was supported by U.S. EPA contract 68D10148. This document has been subjected to
  the Agency's peer and administrative reviews and has been approved for publication. This does not
  signify that the contents necessarily reflect the views and policies of the Agency nor does mention of
  trade names or commercial products constitute endorsement or recommendation for use.


  REFERENCES

     1.  E. Steverson, "Provoking a firestorm: waste incineration", Environ. Sci. Technol. 25:1808
  (1991).

     2.  R. Watts, P. Lemieux, R. Grote, R. Williams, L. Brooks, D. Bell, S. Warren, and D.
  DeMarini, "Development of stack testing, analytical and mutagenicity bioassay procedures for
  evaluating emissions from municipal waste combustors,"  In press, Environmental Health
  Perspectives (1992).

     3.  R. Williams, L. Brooks,  M. Taylor, D. Thompson,  D.  Bell, D. DeMarini, and R. Watts,
  "Fractionation of complex combustion mixtures using an ion-exchange methodology,* Proceedings
 of the 1991 EPA/A&WMA symposium  on measurement of toxic and related air pollutants, May 7,
  1991, Durham, NC, 849-854, EPA-600/9-91-018.

     4.  D. DeMarini, R.  Williams, E. Perry, P. Lemieux, and W. Linak, "Bioassay directed
 chemical analysis of organic extracts of  emissions from a laboratory-scale incinerator: combustion of
 surrogate compounds," Combust. Sci. Technol., in press, (1992).

     5.  W. Sieele, A. Williamson, and J. McCain,  "Construction and operation of a 10 CFM
 sampling system with a 10:1 dilution ratio for measuring  condensable emissions,"
 EPA-600/8-88-069, (NTIS PB88-198551), RTP, NC, April 1988.

     6. P. Lemieux, J. McSorely, and W. Linak," A prototype baghouse/dilution tunnel system for
 Paniculate sampling of hazardous and municipal waste incinerators," Presented at the 15th annual
 EPA research symposium on remedial actions, treatment and disposal of hazardous waste,
 Cincinnati, OH, April 10-12, 1989.

    7.  Method 610, 40 CFR, Pt  136, App.  A. 413-426, 1990.

    8.  R. Majors, "New chromatography columns and accessories at the 1991 Pittsburgh
conference, part II, LC-GC 9:256 (1991).

    9.  R Williams T  Pasley, S. Warren, R. Zweidinger, R. Watts,  A. Stead, and L. Claxton,
"Selection of a suitable extraction  method for woodsmoke-impacted air particles, Intern. J. Environ.
Anal. Chem. 34: 137 (1988).
                                          1003

-------
                 CHARACTERIZATION OF THE AIR POLLUTANTS EMITTED

        FROM THE SIMULATED OPEN BURNING OF AUTOMOBILE RECYCLING FLUFF
                           Jeffrey V. Ryan and Christopher C. Lutes
                              Acurex Environmental Corporation
                               Environmental Systems Division
                                      P. O. Box 13109
                              Research Triangle Park, NC 27709

                                      Paul M. Lemieux
                             U.S. Environmental Protection Agency
                        Air and Energy Engineering Research Laboratory
                              Research Triangle Park, NC 27711
ABSTRACT
   The reclamation process for retrieving recyclable ferrous and non-ferrous metals from scrap
automobiles generates a non-metallic waste product called "fluff," consisting of a combination of
plastics, rubber, glass, wood products, and electrical wiring. The waste product is often stockpiled or
landfilled.  A number of stockpiles have caught on fire, resulting In the emission of numerous air
pollutants. To gain insight into the types and quantities of these air pollutants, a study was conducted
in which the open combustion of fluff was  simulated and the  resulting emissions collected and
characterized.  Samples were collected and analyzed for volatile and semivolatile organic*/
particulate, and metal aerosols. Typical combustion exhaust gases carbon dioxide (CO2)/ carbon
monoxide (CO), nitric oxide (NO;  NO2 was not monitored), oxygen (O2>, and unburned tot*1
hydrocarbons (THCs) were monitored continuously. The respective samples were analyzed using
GC/MS, GC/FID, gravimetric, and atomic absorption/emission methodologies to identify and quantity
the types of compounds present In the open combustion process emissions. The resulting mass/volume
concentrations were related to the measured net mass of material consumed through combustion an
known dilution air volume to derive an estimate of overall mass emissions. Volatile and semivolati e
organics characterized included mono- and  polyaromatic hydrocarbons, substituted alkanes an
alkenes, aldehydes, nitriles, phenols,  chlorinated aromatics, heterocycles,  and polychlorinate
dibenzodioxins  and furans.  Of the 11 metal aerosols characterized, cadmium, copper, lead, and zin
were found in significant quantities.   The emission characterizations performed indicate tha
substantial quantities of air pollutants were emitted.  For the organic pollutants alone, the emission o
over 200 g/kg of fluff combusted was observed.

INTRODUCTION
   The reclamation process for retrieving recyclable ferrous and non-ferrous metals  from scrap
automobiles generates a non-metallic waste product called "fluff."  For the most part, fluff consists o ^
combination of plastics such  as  polyethylene (PE), polypropylene (PP), acrylonitrile-butadiene-styren^
(ABS), polyurethane foam (PUF), polyvinylchloride (PVC), rubber, glass, wood products, cloth, P*P*.'
dirt, and electrical wiring.1'2'3  Conservatively, it can be estimated that roughly 2 billion Ib of flu" l
produced annually.1'^
   The resulting automobile fluff waste is discarded at landfills or, more commonly, stockpiled on si ^
At several automobile reclamation facilities,  these stockpiles have, for whatever reason, caugn
                                     1004

-------
  fire. One such stockpile fire, in Montvale, Virginia, burned for 38 days emitting unknown quantities of
  potentially harmful air pollutants.6  It was estimated that between 13,000 and 16,000 bales of fluff,
  weighing 3,000 Ib each, were burned in the fire.6 Over the course of the fire, several attempts were
  made to extinguish the fire  as well as accelerate combustion.  The Commonwealth of Virginia's
  Department of Air Pollution Control contacted the EPA's Control Technology Center (CTQ requesting
  emissions data on the combustion of this material. Unfortunately, data pertaining to the open burning
  of fluff or any similar material were extremely limited.  As a  result, the CTC felt that a  study
  characterizing the emissions resulting from the open combustion of fluff was warranted. Through the
  guidance of the Combustion Research Branch (CRB) of EPA's Air and Energy Engineering Research
  Laboratory (AEERU, Acurex Environmental performed a study which identified and quantified organic
  and inorganic emission products produced during the simulated open combustion of fluff. Specifically,
  this study was designed to determine rough order of magnitude (ROM) emissions rates for volatile and
  semivolatile organics, particulate, and selected metal aerosols identified in combustion emissions.
  Emphasis was placed on gaining a better understanding of the emissions produced from the open
  combustion of fluff.

  EXPERIMENTAL
    The project consisted of replicate tests to collect and qualitatively and quantitatively characterize
 organic and inorganic emissions resulting from the simulated open combustion of actual automobile fluff
 waste. Small quantities <20-25 Ib, 9-11 kg) of actual fluff, obtained from an automobile reclamation
 facility, weie combusted in a test facility specifically designed for simulation of open combustion
 conditions (see Figure 1). The test material was combusted in a 22 x 22-in. (0.56 x 0.56 m) diameter steel
 cylindrical vessel located on a platform scale used to continuously monitor weight differential.  A
 known, constant volume of conditioned air is added to the bum to simulate open combustion conditions.
 A representative air sample from the bum hut environment is delivered to a sampling facility located
 adjacent to the burn hut through an 8-in. (0.2 m) sample duct via an Induced draft fan.
    The sample shed contains most  of the associated sampling equipment:  the volatile organic
 sampling train (VOST) system, the semivolatile organlcs/particulate sample collection systems, and
 the particulate removal  system for the continuous emission monitors (CEMs). The  digital readout for
 the platform scale is remotely operated from  the sample shed.  All samples were extracted from a
 sampling manifold within the duct using 3/8-in. O.D. (9.5-mm) stainless-steel probes located at the
 same axial and radial locations.
    Fixed combustion gases (CO, COfc NO, ©2, THO were measured continuously using on-hne process
 analyzers.  Volatile organics were collected using an unmodified VOST system.7 Semivolatile organics
 and particulate were collected  using a sample system modified  for use in this study consisting of a
 particulate filter holder, followed by an XAD-2 canister, a vacuum pump, and a dry gas meter.  Two
 separate semivolatile organic/particulate collection systems were operated simultaneously during the
 test period  One sample system was used for the collection of samples for the purpose of general
 semivolatile organic and particulate characterization while the remaining system was used to collect
 samples for polychlorinated dibenzodioxin (PCDD) and polychlorinated dibenzofuran (PCDF)
 analyses. A separate particulate sampling system was used to collect metal aerosols. A Texas A &M
 medium volume ambient particulate sampler, similar to the  Andersen Series 254  medium  flow a«
 sampler, was used to collect particulate 10-jim in diameter and less.8
   The VOST samples were analyzed by GC/MS/FID on a purge-and-trap thermal desorption system.
The effluent of the chromatographic column was split to each of the GC detectors for simultaneous
detection of eluting analytes.  Compounds were identified using multKomponent Ration standard
comparisons, mass special library searches, and investigator interpretation.  Identified analytes were
quantified using a combination of GC/MS and GC/FID system responses based on the characteristics of
the compound identified.
                                          1Q05

-------
     The semivolatile organics from the general organics samples were retrieved from the collo lu.n
 media  by soxhlet extraction using dichloromethane.  The  XAD-2 w<>* extract.-.1 separately Imm the
 paniculate  fraction.   Both the paniculate  extracts and  the  XAD-2 extract-,  were anal-
 individually for total chromatographable organics (TCO)	(organic compounds with boiling points
 botwecn  100 and 300 'O and total gravimetric organics (GRAV)	(organic compounds with boiling
 points greater than 300 'O.9
                           Sample Duct
                                      Fluff Combustion
                                      Container
                    Air Inlet
                                                                 Air Inlet
                                       Weighing Platform
                                 Figure 1. Diagram of Burn Hut.
    Individual  semivolatile  organic compounds were identified and quantified using an approach
similar to that used for the volatile organics.  The XAD-2 and paniculate extracts were analyzed
separately by GC/MS to obtain mass spectral information.  The mass spectra of acquired data were
compared to those of multicomponent standard mixes as well as the mass spectral data base to identify
compounds.  Identified analytes were quantified using a combination of GC/MS and GC/FID system
responses based on the characteristics of the compound identified.
    The  PCDD/PCDF  samples were analyzed by  low resolution GC/MS.  Isotopically  labeled
homologues for all congeners were used for qualitative and quantitative purposes.1^1 1
    Metals potentially present  in fluff were chosen for characterization. The samples were analyzed
by inducbvely coupled argon plasma (ICAP) - atomic emission for barium, cadmium, total chromium,
copper, and zinc.  The samples were analyzed by Graphite Furnace Atomic Absorption (( ,1  \.\) for
.irsenic, lead, and selenium
    For purposes of conciseness, the descriptions of the methods and techniques employed during tlm
study have been generalized

RESULTS AND DISCUSSION
    Table 1 summarizes the  data pertaining to combustion performance over the course ul the three
combustion  tests.  Nominally, 25-lb (11-kj.) ,.i  Huff was evaluated for each test.  As Table 1  indicates,
not all of the material  tested was actually combusted within the duration  nf testing   Indeed, only
                                             1006

-------
approximately 45% of the mass of fluff placed in the combustion apparatus was actually combusted
over the course of the 200 min test.  The remaining ash and incombustible material  were not
characterized.
    Figure 2 represents the burn rates as a function of elapsed time for each of the three tests. Maximum
burn rates were observed within 20 min of material ignition.  After this time, bum rates  gradually
decreased throughout the duration of the burn.  Peak temperatures, observed by a thermocouple placed
directly over  the combustion apparatus,  correlate well  with peak bum rates.   Similarly,  peak
concentrations for CO, CC>2, and  NO emissions, correlate reasonably well with peak burn rates.  The
THC data reveal peak emissions at periods slightly longer into the  test (-30 min) than the observed
peak burn rates. Over the course of the burns, ©2 concentrations remained greater than 19%.

    	Table 1 : Mass Combustion Summary
                                                           Day 1
Day 2
Day 3
Mass Fluff At Start (kg)
Weight After 200 Min Of Combustion (kg)
Fluff Mass Lost Due To Combustion In 200 Min (%)
Burn Rate Over 200 Minute Test (kg/min)
Burn Rate Over Sampling Period
11.3
5.8
48.8
0.028
0.026
10.7
5.8
45.8
0.024
0.025
11.2
6.2
44.7
0.025
0.025
               0.16
                                                              First Test

                                                              Second Test

                                                              Third Test
                          20   40   60    80   100   120   140  160  180  200
                                 Elapsed Time Since Ignition (min)
                              Figure 2. Combustion Rate vs. Time
   GC/MS analysis of the VOST samples collected yielded the identification of over 50 compounds.
However, for the range  of volatile compounds characterized (retention times up to and including
benzaldehyde), over 100 peaks were evident in the GC/F1D chromatograms.  The majority of the
compounds identified were alkanes, alkenes, cycloalkanes, and alkyl substituted aromatics.  However,
aldehydes, ketones, nitrites, and  chlorinated  aromatics were also identified.  The types of volatile
compounds identified  are consistent with those identified during thermal decomposition  studies of
individual plastics.12'15 Because of the diversity of the plastics present in fluff, it is not possible to
attribute the products of incomplete combustion (PICs) identified in this study to any  one type of
plastic.
                                           1007

-------
   The mass of volatile organic emissions was characterized in several ways.  The mass of volatile
organic compounds (VOCs)  with  boiling points less than 110 X! was estimated by summing the
integrated areas of peaks eluting prior to toluene and applying the toluene response factor. Figure 3
plots total volatile organic emissions as a function of burn rate. As bum rates decreased, the estimated
mass emissions of volatile organics increased. The estimated emissions presented are based on several
variables. They were calculated by assuming that the dilution air flow added to the bum hut was
constant at the measured  rate and  that the volume of air added to the bum hut equaled the volume
exiting the hut. It was also assumed that the gas mixture collected in the sample duct was well mixed
and representative of the gas mixture found throughout the bum hut. The average volatile organic
gaseous concentration, determined by dividing (he mass collected by the volume sampled, was
multiplied by the volume of air added to the burn hut per unit time. This represents the mass of organic
material emitted per unit time.  Dividing by the average fluff burn rate yields the mass of volatile
organics emitted relative to the mass of fluff consumed through combustion.
                                      0.04     0.06
                                       Burn Rate (kg/min)
0.12
                            Figure 3. Total Volatiles vs. Burn Rate.
    Figure 4 graphically depicts estimated emissions for VOCs which are included in the Clean Air Act
Amendments' (CAAA) Hazardous Air Pollutants (HAP) list. Benzene represents the single largest
VOC emitted, generating nearly 10 g for every kg of fluff consumed in combustion.                    .
    The characterization of  semivolatlle  organic  emissions collected on both the  XAD-2 an
paniculate filters used an approach similar to that used  during  the characterization of the v°^f
organics emissions. Table 2 summarizes TCO and GRAY data for these fractions. As would be expectea,
the XAD-2 sample fractions contained more (985%) TCO mass than did the particulate filter
Conversely, the particulate filter fractions  contained more (85%) GRAY mass than did the
fractions.  The compounds identified  in the XAD-2 and particulate fractions are similar to
identified in the YOST samples.  In addition, phenols,  PAHs,  phthalates, and heterocycles were
identified. Again, the types of compounds identified were consistent with those identified in vari°
studies of the thermal decomposition of plastics.12'15  Many of the compounds Identified common to tne
HAP list were PAHs.
                                           1008

-------
                 16

                 14
               o
              2 10
             •i
              f>   n
             W
              (A
             UU
 Note: Only samples analyzed to date are presented
• Sample 1-1        Q  Sample 2-1
                             Q]  Sample 1-3
                           Sample 2-2
                                                         m
            1
                                                     S
                                                     8

                                           >•>
                                                                        o
                                                                        u
                              Figure 4.  Hazardous Air Pollutants.

    Table 3 presents estimated emissions data for selected individual compounds present in the XAD-2
and particulate fractions.  Particularly good agreement exists between emission rates of ethyl benzene
and m-/p-xylene, compounds identified in both the VOST (see Figure 4) and XAD-2 sample fractions.
Because of the complexity of the sample and its components, identification of all compounds present i
the organic fractions was not within the scope of this study.
    Separate samples were also collected specifically for characterization of PCDD/PCDF emissions.
Separate analyses were performed on  the  XAD-2 and  particulate filter samples.  The total
PCDD/PCDF emission results are summarized in Figure 5. It is important to point out that the analyses
performed do not determine specific isomers, and only present the total mass for each congener group.
Therefore it is not possible to determine dioxin toxic equivalency factors for these samples, because the
2,3,7,8 substituted isomers  (with  the exception of OCDD/OCDF)  were not positively confirmed.
However, these more toxic isomers may indeed be present.
    Overall  the  resulting  emissions favored  the formation  of the less-substituted  chlorinate
dibenzofura'ns. The tetrachloro and pentachloro dibenzofurans (TCDF/PeCDF) were roughly an order
of magnitude greater in concentration than the dioxin homologues. These profiles are similar to  hose
observed from soil samples  collected from scrap automobile incineration sites in the Netherlands.
The congener profile, although not tyoical of most municipal waste combust
similar to those seen in some  MWCs.17'*8
                                          1009

-------
                Table 2: Estimated Emissions for Classes of Pollutants (g/kg)
                                             Day 1
          Day 2
          Day 3    Average
Volatile*:
       Early In Test
       Mid-test
       Late In Test

Semivolatiles:
       XAD-2 TCO
       XAD-2 GRAV
       Particulate TCO
       Particulate GRAV
5.93
43.06
25.73
56.99
6.68
0.61
53.78
17.28
69.16
70.87
50.05
10.12
 1.27
69.11
62.54
 NA
80.94
90.72
23.58
 0.85
113.71
28.58
56.11
59.18
65.92
13.46
 0.91
78.87
Particulates:




PM10
General Organic Train
Dioxin Train
Metals Train
Average - 3 Trains

91.25
85.82
81.55
86.20
66.03
116.17
115.68
89.93
107.26
NA
183.44
188.63
174.49
182.19
41.11
130.29
130.04
115.32
125.22
53.57
                 Table 3: Estimated Emissions for Selected Pollutants (g/kg)1
Compound
Ethyl Benzene
m- or p-Xylene
Ethynyl Benzene
Styrene
Benzaldehyde
Phenol
1,2-Dichlorobenzene
Naphthalene
Methylethylphenol
Biphenyl
Acenaphthylene
Caprolactam
Phenanthrene
Fluoranthene
Pyrene
Terphenyl
bis(2-Ethylhexyl)
Phthalate
XAD
Testl
2.26
1.03
0.38
6.27
1.20
1.39
N.D.
0.90
0.49
0.29
0.20
N.D.
0.211
N.D.
N.D.
N.D.
N.D.

XAD
Test 2
2.05
1.11
0.39
6.49
1.53
1.59
0.17
0.95
N.D.
0.30
0.18
N.D.
0.177
N.D.
N.D.
N.D.
N.D.

XAD
Average
2.16
1.07
0.38
6.38
1.36
1.49
0.09
0.92
0.24
0.29
0.19
0.000
0.194
0.000
0.000
0.000
0.000

Particulate
Testl
N.D.
N.D.
N.D.
N.D.
N.D.
N.D.
N.D.
N.D.
N.D.
N.D.
N.D.
N.D.
0.068
N.D.
0.110
0.050
0.761

Particulate
Test 2
N.D.
N.D.
N.D.
N.D.
N.D.
N.D.
N.D.
N.D.
N.D.
N.D.
N.D.
0.380
0.129
0.109
0.118
0.070
1.995

Particulate
Average _
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.190
0.099
0.055
0.114
0,060
1.378

1 Compounds Listed In Order Of Retention Time, N.D. = Not Detected
                                        1010

-------
                 0.004
             Figure 5. Total PCDD/PCDF by Congener; Vapor and Partiadate Summed.
    The majority of PCDD/PCDF material was found on the particulate filters. Nearly 30 times more
total PCDD/PCDF material was contained on this fraction relative to the XAD-2 fraction.  Similar
congener profiles were observed in the particulate and XAD-2 fractions.
    Of the 11 metals targeted, only cadmium, copper, lead, and zinc were detected in the samples
collected.  Figure 6 presents the estimated mass emissions for these metals.  It is interesting that copper
is present in relatively large concentrations: Copper compounds have been suggested as catalysts in the
low temperature formation of PCDDs/PCDFs in municipal waste incineration processes.^'2" An open
burning environment provides relatively long residence times at the proposed optimal PCDD/PCDF
formation  temperatures.
    Particulate matter was collected, by using several sampling systems: the semivolatile organics
systems, the metal aerosol system, and the PMjQ ambient sampler.  The estimated particulate matter
emission rates for these systems are also presented in Table 2. For the sampling systems operated in the
sample shed and connected to the sampling manifold, excellent agreement exists between sampling
systems when comparing the emission  rates for a given test day.  Greater variation exists when
comparing the emission rates of different test days.  A comparison of the PMiQ to total particulate,
based on total averaged values, indicates  that the PMjQ comprises roughly 40% of the total particulate
matter collected.
                                          1011

-------
                                 First Test

                                 Second Test
                       Cadmium     Copper
    Third Test

    Average
Lead
Zinc
                                  Figure 6. Metals Emissions
   To assess the overall organic emissions, the volatile and semivolatile organics emission data were
summarized. The total organics emitted, volatile, vapor-phase semivolatile, and  particulate-bound
semivolatile, averaged over 200 g/kg fluff combusted. The actual mass contribution from each fraction
is summarized in Table 2.
   The particulate collected was also characterized to the greatest extent possible.  The total mass of
organic extractables was determined. On average, nearly 60% of the total particulate  mass was found to
be dichloromethane-extractable.  An additional 1.2% of the total particulate mass  was accounted for
by the metals analyses.  The remaining particulate matter may be comprised of organic compounds not
extracted by dichloromethane; e.g., strongly polar organics, non-analyzed inorganics, and carbonaceous
matter.
   As a measure of the quality of estimated mass emissions, a total mass balance was performed. The
diversity  of the  measurements  performed during testing was  felt  to sufficiently  enable the
determination of total mass emissions since they included most classes of observed PICs as well as
several common gaseous products of complete combustion. The actual mass balances, based on individual
and overall test average mass emissions  values, are presented in Table 4.  The  result of the  mass
balances reveals an over estimate of roughly 20%.  Given the semiquantitative nature  of the tests
performed, this result appears well within reason.
                                             1012

-------
                   Table 4: Mass Balance For Combustion Emissions, All Data as g/kg

Volatiles
Vapor-Phase Semivolatiles
Particulate
{Average Of 3 Trains)
COAsC
CO2 AsC
NOAsN
Sum
Day 1
28.58
63.67
86.20

67.93
915.71
NA
1162.09
Day 2
56.11
60.17
10726

71.54
74630
2.54
1043.92
Day 3
59.18
114.30
182.19

72.09
771.93
2.43
1202.12
Average
47.96
79.38
125.22

70.52
811.31
2.49
1136.87
 SUMMARY AND CONCLUSIONS
    To  re-emphasize, the primary objective of this study was to characterize, as completely as
 possible, the emissions resulting from the simulated open combustion of fluff.  This necessitated an
 approach where qualitative information was given greater emphasis than quantitative information.
 It was hoped that this approach would provide the data and insight to direct subsequent, specialized,
 and more quantitatively detailed investigations.  An attempt was made to characterize the diversity
 of the emissions as efficiently as possible.
    The data produced from this study are sufficiently comprehensive to provide a semiquantitative
 characterization of the emissions resulting from the simulated open combustion of automobile recycling
 fluff. While the  data may be adequate from a physical and chemical characterization standpoint,
 data are lacking on the toxic effects of these emissions.  However, the substantial emissions of many
 compounds with known, deleterious health effects (e.g., benzene, acrolein, PAHs, PCDDs, PCDFs)
 should be cause for concern. Risk/exposure assessment studies would be merited.
    The PCDD/PCDF analyses revealed that significant quantities of PCDDs and PCDFs are produced
 as a result of the open combustion of fluff. Because these compounds are present, the presence of
 polybrominated dibenzodioxins (PBDDs) and furans (PBDFs) seems likely as well.  Polybrommated
 diphenyl ethers are commonly used as flame retardanls in polyurethane foams. The formation of
 PBDDs  and PBDFs from the thermal  decomposition of polybrominated dipheny! ethers has been
 observed.21/22  These compounds merit investigation if further fluff studies are performed.

 ACKNOWLEDGMENTS
    The work described in this paper has been performed by Acurex Environmental Corporation under
 EPA contract 68-DO-0141.  The authors wish to gratefully acknowledge the valuable contributions of
 Tom Henderson and Jed Brown (The Commonwealth of Virginia - Department of Air Pollution Control)
 and Chris Ralph (Washoe County, Nevada - District Health Department) to the success of this study.

REFERENCES

    1. p T  VnTrtrr. ft r'  F«™"rpff Pa»vureth*m«. Fnam and Other Plastics from AutQ-shredcier
      Report of Investigations 8091, U.S. Bureau of Mines, Washington, DC, 1975.
    2. K. C Dean, etal., B"*ff » at Mine? m***"* on Raveling Scrapped Autpmpbile?, Bulletin 684,
U.S. Bureau of Mines, Washington, DC, 1985.

    3, M. Rousseau, A. Melin, 'The processing of non-nnagnetic fractions from shredded automobile
scrap: a review," R^urrps. Cor^vation and Recycling, 2: 139-15* (1*8*).
                                           1013

-------
   4.  L. R. Mahoney, et al., "Hydrolysis of polyurethane foam waste," Environmental Science  and
Technology. 8(2): 135-139 (1974).

   5. A. Wrigley, "Automotive use of plastics expands," American Metal Market. 94(163): 1 (1986).

   6. T. L. Henderson, Commonwealth of Virginia, Department of Air Pollution Control, Lynchburg,
VA., personal communication, 1992.

   7.  E. M. Hansen, Protocol for the Collection and Analysis of Volatile PQHCa Using VOST. EPA-
600-8-84-007 (NTIS PB84-170042), US. Environmental Protection Agency, Research Triangle Park, NC
 "
    8.  A. R. McFarland, C. A. Cortiz, "A 10 um cutpoint ambient aerosol sampling inlet,"
Environment. 16(12): 2959-2965. 1
15(7): 901-915, 1986.
                                            1014

-------
    18.  R. M. Smith, et al.. Chlorinated Pioxins and Dibenzofurans in Perspective; C. Rappe, et al.,
Eds. Lewis Publishers Tnr. Chelsea, 1986, pp 93-108.

    19.  B. K. Gullett, et al., 'The effect of metal catalysts on the formation of polychlorinated dibenzo-
p-dioxin and polychlorinated dibenzofuran precursors," Chemosphere. 20(10-12): 1945-1952,1990.

    20.  K. R. Bruce, et al, The role of gas-phase CI2 in the formation of PCDD/PCDF during waste
combustion," Waste Management. 11:97-102,1991.

    21.  H. R. Buser, "Polybrominated dibenzofurans and dibenzo-p-dioxins; thermal reaction products
of polybrominated diphenyl ether flame retardants," Environmental Science and Technology. 20: 404-
408,1986.

    22. H. Thoma, et aL, "Polybrominated dibenzofurans and dibenzodioxins from the pyrolysis of neat
brominated diphenyl ethers, biphenyls and plastic mixtures of these compounds," Chemosphere. 16:
277-285, 1987.
                                          1015

-------
AIR EMISSION RATE MEASUREMENTS OF VOCs AND
             SVOCs EMITTED FROM AN IN-SITU
BIOREMEDIATION PILOT-SCALE TEST ON SURFACE
                     IMPOUNDMENT SLUDGE
                               William A. Butler
                  Du Pont Environmental Remediation Services, Inc.
                         300 Bellcvue Parkway, Suite 390
                        Wilmington, Delaware 19809-3722
 ABSTRACT
 An in-situ bioremediation pilot-scale test was completed to demonstrate the effectiveness of this
 technology  to reduce the concentrations of VOCs and SVOCs contained within a surface
 impoundment sludge. A 5,600 sqft bioremediation pilot cell was constructed within the surface
 impoundment and consisted of mixers and aerators. The air emission rates of VOCs and SVOCs
 from the pilot cell were measured with floating emission isolation flux chambers. The basis for
 the measurement procedures and flux chamber design were obtained from the Measurement of
 Gaseous Emissions from Land Surfaces Using an Emission Isolation Flux Chamber - User's
 Guide (EPA 600 8-86-008). Measurements were performed on the mixed and aerated zones of
 the pilot cell surface and on the quiescent water surface outside of the pilot cell. The aerated
 zone was distinguished from the mixed zone by the turbulent, bubbling surface caused by
 aeration. Measurements were conducted on the mixed and aerated zones throughout the test to
 depict the change in air emission  rates over time.  The results were used to determine the
 effectiveness of bioremediation by providing input to an overall mass balance calculation. The
 mass balance calculation enabled the determination of the total mass of VOCs and SVOCs
 biodegraded versus that which was air stripped.


 INTRODUCTION

 A chemical manufacturing facility located in southern New Jersey has an agreement with the
 New Jersey Department of Environmental Protection and Energy (NJDEPE) in the form of an
 Administrative  Consent Order  to close two large surface  impoundments.   The surface
 impoundments contain approximately 400,000 cubic yards of process wastewater sludge which
 accumulated over many decades of operation.  The sludge contains an average total solids
 concentration of 30% and a wide variety of volatile organic compounds (VOCs), semivolatile
 organic compounds (SVOCs), and metals with  the predominant compound from each group
 being chlorobenzene, 1,2-dichlorobenzene, and lead,  respectively.  The conclusions of a
 feasibility study identified in-situ  bioremediation as a potential treatment technology for the
                                       1016

-------
  sludge.  A series of laboratory-scale treatability studies were completed, and the results indicated
  that the VOCs  and  SVOCs contained within the sludge could be biodegraded by indigenous
  microorganisms with the addition of oxygen, nutrients, and pH-adjusting materials.

  With the results of the laboratory-scale studies, an in-situ bioremediation pilot-scale test was
  developed and successfully implemented in the field.  One concern of the NJDEPE was the
  potential for air emissions  from a full-scale operation.  An  air monitoring program  was
  developed and implemented as part of the pilot-scale test, and it provided  sufficient data to
  quantify the air emission rates of VOCs and SVOCs. The objectives of the program were as
  follows:

        •     Determine whether the NJDEPE air emission rate standards would be exceeded
               for a full-scale operation.

        •     Determine whether air pollution control equipment would be required for a full-
               scale operation and provide emission rate data for design.

        •      Determine whether a full-scale operation would impact the local ambient air
               quality and present a risk to human health and the environment.

        •      Provide data to complete a mass  balance of  the system  to determine what
               percentage of  the  VOCs and SVOCs removed  was  by air stripping and
               biodegradation, respectively.
 BIOREMEDIATION PILOT CELL

 The Bioremediation Pilot Cell (pilot cell) was a 5,600 sqft cell constructed within the surface
 impoundment.  A custom-designed floating baffle was used to segregate the pilot cell from the
 remaining surface  impoundment sludge  and surface water.  The pilot cell  contained six
 submersible mixers, one vertical mixer, and two surface aerators, which were all  mounted on
 independent flotation units.  An array of deadmen and cables provided support for the floating
 baffle, mixers, and aerators.  Figure 1 depicts the layout of the pilot cell. The pilot cell was
 operated for seven  weeks.   The first week consisted of uplifting and completely mixing the
 sludge. Aeration was started at the beginning of the second week. Nutrients and pH-adjusting
 materials were added periodically throughout  the remaining six weeks of operation.


 AIR MONITORING PROGRAM

The air monitoring program consisted of performing direct air emission rate measurements with
a floating emission isolation flux chamber  (flux chamber).  Figure 2 depicts the  flux chamber
and support equipment.  Air emission rate measurements were completed by placing the flux
chamber on the water surface at the desired locations.  The flux chamber was placed within a
                                          1017

-------
                                                .TANK
c
I—
DC
                                                                                                                                                SCSI
                                                                                                                                                NO SCALE
                                                                                                                                                         BIOREMED1ATION PILOT CEU,
                                                                                                                                                   OBSERVED ZONE DELINEATION & EMISSION
                                                                                                                                                     ISOLATION FLUX CHAMBER LOCATIONS
                                                                                                                                                Du Ponl  Environmental  Remediation Services

-------
o
H-
VO
                                                         TEMPERATURE
                                                           READOUT
                    CARRIER
                      GAS
THERMOCOUPLE
                                                                                    16*
                                                                                                                                 SAWLE  OUTLET
                                      STAINLESS STEEL
                                      OR PLEXIGLASS
                                                                                                                        DIAGRAM  OF THE EMISSION  ISOLATION
                                                                                                                        fLUX CHAMBER i. SUPPORT  EQUIPMENT
                                                                                                                        KI-
                                                                                                                       ND SCALE
                                                                                                                               H5B
                                                                                                                                                1085-IE
                                                                                                                       Du Pont Enviroiimental Remediation Seryices

-------
16-inch inner tube that enabled it to float on the water surface only submersed one to two inches.
A  high purity air (<0.1 ppm total hydrocarbons) carrier gas was introduced into the flux
chamber at a constant flow rate of 5 Lpm. The carrier gas entered the flux chamber at several
points to facilitate complete mixing with the gaseous emissions from the enclosed surface. The
carrier gas creates a slight positive pressure within the flux chamber, which prevents external
air from  entering  and possibly  contaminating or diluting  the  flux chamber exhaust gas.
However, the slight positive pressure was not enough to suppress the air emissions from entering
the flux chamber, because the pressure was constantly relieved through a 3/4-inch vent on top
of the flux chamber.    A portable  organic  vapor  analyzer was  utilized  to  measure the
concentration of total hydrocarbons in the exhaust gas from the sample outlet,  and to purge the
sample outlet prior to sample collection. After five theoretical residence times, samples were
collected from the sample outlet and analyzed for individual VOCs and SVOCs  utilizing ambient
air method TO-14, which consists of collecting samples  in evacuated  Summa® canisters and
subsequent analysis by GC/MS. Method TO-14 can detect low ppbv concentrations of VOCs and
SVOCs with saturation vapor pressures at 25°C between 10"1 to 10"7 mmHg.  The samples were
collected  at a flow rate of 0.5 Lpm, because at a flow rate of 2 Lpm or greater a negative
pressure could result in the flux chamber. The basis for the  measurement procedures and flux
chamber design was obtained  from the Measurement of Gaseous Emissions from Land Surfaces
 Using an  Emission Isolation Flux Chamber - User's Guide (EPA 600 8-86-008).

The theoretical residence time for the flux chambers utilized was six minutes and was calculated
with the following equation:

       tr  = VFC/Q

              where:       t,     =     theoretical residence time (min)
                           Vrc   =     flux chamber  volume (m3)
                           Q    =     total gas  flow rate (carrier gas plus air emission
                                        rate) (m'/min)

 Vrc for the flux chambers utilized was 0.03 m3. For the quiescent and mixed water surfaces,
 Q was the same as the carrier gas flow rate (5 Lpm) because the air emission flow rate was
 negligible.  For aerated surfaces  of the pilot cell, the air emission flow rate was measured and
 determined  to be an  additional 6.7 Lpm into the flux chamber.

 The plan  initially assumed that the pilot cell surface was symmetrical, and that each half could
 be segregated into three distinct surfaces as follows:

       •     Open  Zone (smooth but moving surface)

       •     Mixed Zone (turbulent surface)

       •     Aerated Zone (turbulent, bubbling surface)
                                           1020

-------
  After observing the pilot cell in operation, it was determined that the pilot cell surface only
  consisted of two distinct zones. The open and mixed zones were the same and consisted of 75%
  of the pilot cell surface.   The aerated zone consisted of the remaining 25%.   Three flux
  chambers were placed at  fixed locations in  the pilot cell to make the  air emission rate
  measurements and included two in the open/mixed zone and one in the aerated zone.  Figure 1
  depicts  the zone delineation of the pilot cell and  flux chamber locations.  Ideally, the flux
  chambers should have been moved around in order to take measurements from several locations,
  but this could  not be done safely or without hindering the operation.

  Measurements were completed during mixing only, aeration start-up, week two of aeration, and
  week four of aeration. During mixing only, a single grab sample was collected from each flux
  chamber. During start-up and week four of aeration, two grab samples were collected from each
  flux chamber.  During week two of aeration, three grab samples were collected from each flux
 chamber because extra SUMMA canisters were available.   Two quiescent water surface
 measurements  were completed on the surface impoundment prior to the start of the pilot-scale
 test. Two field blanks were completed by setting the flux chamber on a clean inert surface and
 performing the measurement procedure.  The sample collected should only contain carrier gas;
 but if contaminants are present in the flux chamber, they will be detected by the analysis.
 RESULTS

 With the analytical data, the air emission rate of VOCs or SVOCs from each measurement was
 calculated with the following equation:

       E,
             where:       Ei     -  ,'  emission rate of component i (ug/ml-min)
                          Q     =     concentration of component i in the sample (ug/m3)
                          Ape    =     surface area enclosed by the flux chamber (m5)

The Apc for the flux chambers utilized is 0.13 m2.

The overall emission rate from each sampling period was calculated utilizing the following
procedure:

       1.     Average  the emission rates determined for each measurement made in  the
             open/mixed zone.

      2.     Average the emission rates determined for each measurement made in the aerated
             zone.

      3.     Calculate a weighted average emission rate based on  the area of the respective
             zones.
                                        1021

-------
      4.     Multiply the weighted average by the entire surface area of the pilot cell to obtain
             the total Ib/hr of VOCs and SVOCs emitted.

Table 1  presents the initial average concentrations, emission rates of average total VOCs and
SVOCs  for each measurement period, and air emission rates of individual VOCs and SVOCs
for each measurement period.  Figure 3 is a graphic representation of the average air emission
rate of  total VOCs and SVOCs,  chlorobenzene,  and 1,2-dichlorobenzene versus time.  The
average air emission rate of total VOCs and SVOCs from each measurement period ranged from
9.25 Ib/hr after mixing/aeration start-up to 1.19 Ib/hr during week four of mixing/aeration. The
overall average air emission rate of VOCs and SVOCs was 3.63 Ib/hr throughout the pilot-scale
test. No significant concentrations of VOCs or SVOCs were detected in the field blank samples.
DISCUSSION OF RESULTS

The results indicated that the NJDEPE air emission rate standard of 0.5 Ib/hr total volatile
organic substances was exceeded, and air pollution control equipment would be required for a
full-scale operation. The NJDEPE air emission rate standard of 0.1 Ib/hr of an individual toxic
volatile organic substance was not exceeded. Benzene-was the only compound detected that is
defined by the NJDEPE regulations as a toxic volatile organic substance, but  was only detected
in the measurements completed immediately following aeration startup. The air emission rate
measurements of individual VOCs and SVOCs and flow rate measurements provided sufficient
information to design an air pollution control device.  An air dispersion model (ISCLT) was
completed with this data for a full-scale operation without air pollution control equipment.  The
results indicated that a risk to human health was not a concern beyond the site boundaries, but
would cause an odor problem.  Since air pollution control would be required for a full-scale
operation  to  meet NJDEPE air emission rate standards, the risk to site workers and odor
problem would be eliminated,

A mass balance was completed on the pilot cell data to determine what percentage of the VOCs
and SVOCs removed was by air stripping and biodegradation, respectively.  The results were
as follows:

             Initial Mass of VOCs/SVOCs            7,746 Ib

             Final Mass of VOCs/SVOCs             377 Ib

             Difference                             7,369 Ib removed

             Total Mass Emitted to Air               4,234 Ib

             Total Mass Biodegraded                 3,135 Ib
                                         1022

-------
o
to
                                                       TABLE 1
                                  AVERAGE AIR EMISSION RATES OF VOCs AND SVOCs
                                       FROM THE BIOREMEDIATIONPILOTCELL
I Parameter
Benzene
IjChlorobenzene
1 1 ,2-dichlorobenzene
|Ethylbenzene
Freon113
IjToluene
1 1 ,2,4-trichIorobenzen
[Xylene, total
iTotalVOC/SVOC
Initial
Sludge
Cone.
mg/kg dfwtj
8.90
2,734.00
7,895.00
27.70
NA
293.00
677.00
176.00
11,811.60
Quiescent
Surface
Rate
(Ib/hr)
1.99E-05
1.77E-03
5.77E-03
2.70E-05
1.31E-04
1.40E-04
1.12E-03
1.05E-04
9.08E-03
Mixing
Only
Rate
(Ib/hr*
0.00
0.86
0.66
0.01
0.00
0.09
0.05
0.04
1.71
Aeration
Startup ^
Rate
(ib/hr)
0.02
4.36
3.54
0.03
0.12
0.55
0.34
0.24
9.25
Aeration
Week 2
Rate
(Ib/hr)
0.00
0.74
1.36
0.01
0.00
0.06
0.14
0.05
2.36
Aeration
Week 4
Rate
Ob/hr)
0.00
0.16
0.85
0.00
0.00
0.02
0.14
0.02
1.19
Overall
Average
Rate
(Ib/hr)
0.01
1.53
1.60
0.03
0.03
0.18
0.17
0.09
3.63
            Notes:
            (1) - Initial sludge concentration based upon 15 grab samples collected from within the pitot cell.
            (2) - Each air emission rate value is an average of each of the measurements conducted during that period.
            (3) - The overall average represents the average air emission rate throughout the pilot cell operation, but does not
                 include the quiescent surface air emission rate.
            (4) - NA (not analyzed)

-------
                                    FIGURE 3
                            AIR EMISSION RATE vs. TIME
UJ
                                               Aeration-Week 2
             Total VOC/SVOC
   10          15          20
Time (days since start of mixing)

         _ 1,2-Dichlorobenzene
Chlorobenzene

-------
 The initial and final mass of VOCs and SVOCs was based on average concentrations of all the
 VOCs and SVOCs detected in the initial and final sludge samples.  Table 1 only presents the
 compounds detected in the air samples collected as part of the air emission rate measurements.
 The total mass emitted to the air was based on the average air emission rate throughout the seven
 week operation.  For the total mass of VOCs and SVOCs, 5796 of the removal was due to air
 stripping, and 43% was due to biodegradation.  A mass balance for  chlorobenzene,  1,2-
 dichlorobenzene, and 1,2,4-trichlorobenzene was also completed.  All of the chlorobenzene
 removal was due to air stripping, as was the case for  1,2,4-trichlorobenzene and the other
 VOCs, A mass balance around Freon* 113 could not be completed, because it was not detected
 in the initial or final sludge samples.  It is assumed that it was completely  air stripped with the
 other VOCs.  For 1,2-dichlorobenzene,  41 % of the removal was due to air stripping, and 59%
 was due to biodegradation.  The removal of other SVOCs detected in the  sludge  was assumed
 to be  due to biodegradation since these compounds have relatively low vapor pressures  and
 Henry's Law constants.
 CONCLUSION
 The air monitoring program provided all of the necessary information to meet the objectives of
 the program  Air pollution control equipment will be required for a full-scale operation, since
 the estimated air emission rates exceeded the NJDEPE standards.  A full-scale operation without
 air pollution control would impact the  local ambient air quality by causing off-site odor
 problems so air pollution control would be required to prevent an odor problem.  A mass
 balance was completed, and indicated that air stripping was responsible for 57% of the VOC and
 SVOC removal from the pilot cell.  Although, biodegradation was still a significant removal
 mechanism.  With the information provided by the  air monitonng program, a full-scale
 bioremediation operation was designed to control air emissions.

 The procedures used for the air monitoring program were not without some degree of error.
 FOT  eSrthe measurements were conducted  from fixed locations rathei : than multiple
                the oilot cell which would have been more representative.  Fixed locations
              if ^mptete mixing is achieved, but this  is unlikely.  If air emission rate
                            once or more a week throughout the operation, toe results would
                              Additional error may have resulted  from the samphng and
tata ™*n*ve.
SvSSS  which is  common for all sampling and analytical techniques   The



operations associated with remediation and industrial processes.
                                       1025

-------
        Session 23
          General
William Gutknecht, Chairman

-------
        GEOGRAPHICAL DISTRIBUTION AND SOURCE
        TYPE ANALYSIS OF TOXIC METAL  EMISSIONS

                      William G. Beqjey* and Dale H. Coventry*
                        Atmospheric Sciences Modeling Division
                              Air Resources Laboratory
                    National Oceanic and Atmospheric Administration
                     Research Triangle Park, North Carolina  27711

  ABSTRACT
        An interim toxic emission inventory has been developed for the conterminous United
  States. Seven toxic metals found in lake and coastal waters are included: arsenic, cadmium,
  chromium, lead,  mercury, nickel and selenium.  The emissions are large relative to some
  estimates and demonstrate the importance of metal production in toxic metal emissions.  In the
  absence of regional inventories dedicated to toxic emissions, there is a need for improvement of
  emission factors and speciation profiles for use with particulate emission inventories.
       This paper has been reviewed in accordance with the U.  S.  Environmental Protection
  Agency's peer and administrative review policies and approved for presentation and publication.
  Mention of  trade names or commercial products does  not constitute  endorsement  or
 recommendation for use.

 INTRODUCTION
       Title HI of the Clean  Air Act Amendments of 1990 requires several studies to help
 determine whether toxic air emissions should be regulated.  These requirements include Sections
 112(c)(3) and 112(k) (Urban Area Source Program), 112(c)(6) (regulation of seven classes of
 toxic emissions), and 112(m) (Great Waters Toxic Deposition Program).  In order to accomplish
 these studies,  modeling of transport and deposition of toxic emissions are needed in conjunction
 with source and location data (a toxic emission inventory).  Consequently, an interim inventory
 suitable for modeling anthropogenic sources was compiled for 28 compounds based on the 1985
 National Acid Pollution Assessment Program (NAPAP) inventory1.

 \TI t' HTI TfYIWT f\f* V
       This paper presents the general geographical distribution and source classificationsof
 mercury, cadmium, chromium, arsenic, lead, nickel, and selenium  ftom the inventory.  The
 methodology for estimating emissions applied speciation and emission factors to the volatile
 organic hydrocarbon and total particulate matter portions of the NAPAP «^™£^?
 pomt, area, and mobile sources.  The factors were selected  from  the U. S. Environmental
 Protection Agency's "Speciate2" and "Xatef3" databases, reflecting the experience of the
 Detroit-Windsor area Transboundary Air Toxic Study4 for emission factors. Speciation factors
 were smniied first and emission factors were used where no speciation factors were available.
     ap!ttv^^
and source type <*tegory for the selected toxic chemicals. The information is more complete for

*0n assignment to the Atmospheric Research and Exposure  Assessment Laboratory, U. S.
Environmental Protection Agency
                                     1029

-------
toxic metals than for many organic toxic chemicals.  The methodology has the advantages of
good spatial coverage and the wide range of source types in the NAPAP inventory and spatially-
consistent emission estimation  procedures.  The emission data are easily gridded using a
geographic information system to any spatial scale used in a regional transport model. The Toxic
Chemical Release Inventory (TRI)3, which is often a basic information  source for the  United
States, lacks the spatial location accuracy or complete range of source types needed for modeling.
       The disadvantages of this methodology include the age of the NAPAP data, the use of
factors rather than a direct "bottom-up" inventory, the variable quality of the speciation and
emission factors and limited natural emissions data.  Natural emissions may account for more
than half of mercury emissions6, while this approach addresses anthropogenic sources, with the
exception of rough estimates for dust devils.  Neither our inventory nor TRI contain emissions
from pesticide applications or banned toxic chemicals.  These chemicals will require a separate
approach to address residual sources.  Many chemicals remain to be added to the inventory. For
these reasons it is described as an interim inventory.

DISCUSSION
Geographic Distribution of Toxic Metal Emissions
       The general  emission distribution pattern for most metals shows that more populous
industrial states tend to have more total emissions, as expected.  However, the relative ranking
of states by total emissions does not hold for all metals examined (Table I), reflecting different
mixes of source categories. National total lead emissions are an order of magnitude larger than
the contribution from all other examined metals.
       Three general characteristics appear.  First, states with concentrations of primary and/or
secondary metal refining have significant emissions, along with states with large amounts of
industrial and residential combustion. Second, point sources dominate over area sources for each
metal  except lead and mercury (Figure I). However, the mercury point source emissions may
be greater because emissions from the mineral products industry were omitted.  The speciation
and emission factors for mercury for mineral products require additional investigation. Existing
 mineral  products factors for mercury yielded emissions at least an order of magnitude greater
 than for other sources combined.  Third, for all metals examined, our emission estimates are at
 least one order of magnitude larger than estimates based on approximate emissions from general
 source categories".   The  differences may be because the interim inventory addresses all known
 sources  specifically rather than by estimates of general categories; and partly because of the
 substantial uncertainty inherent in many speciation and emission factors.

 Source  Categories
       The  toxic  metal  emission sources appear to be heavily influenced  by  primary and
 secondary metal production, including sources of arsenic, cadmium, lead, chromium, nickel and
 selenium (Table II).  Mobile sources are an  important contributor  of lead;  incineration and
 natural  sources are key to mercury emissions, and chemical  manufacturing is important to
 selenium  emissions.  Table II is not intended to be a detailed or complete list of source
 categories.  It presents only those source categories with the greatest toxic metals contributions.
 These categories account  for at least sixty percent of emissions in each  case.  The source
 category listing will be made more detailed and will be refined as additional data  become
                                         1030

-------
  available.  Future work must address missing sources, emission factors and incomplete speciation
  profiles, particularly with respect to mercury.  Ultimately, modeling results based on the interim
  toxic emission inventory will be a part of model validation with field measurements of air
  concentrations of metals.

  CONCLUSIONS
        Development of toxic metals emission  estimates resulted in several observations
  concerning the emissions sources and data needs.
        1 . A speciation approach to a toxic emission inventory results in relatively large emission
  estimates.  These estimates will probably change significantly with new ^formation
        2. Although there are many source categories emitting metals, metal production is the
               :^

  factors for  toxic metals from anthropogenic and natural sources.
                 L  Langstaff,  R. Walters, L. Modica, D.  Zimmerman, D.
 EPA-SooVsg'-oSSaT1^                             ^"^ LllTrlh
 Triangle  Park,  1989,  692 pp.
                                                         Factor Data Base
 4. Engineering science,
5.   D.   S.  Environmental   Protection  Agency^Offi^  of   Toxic
Substances, T??Fic ch.fffli'cai  Pp'ft^s^a An^
Instructions.  EPA 560/4-90-007,  0.  S.
Agency,  Washington,  D.C., 85 pp.
                      *  T   CTTiHt-h   pr^'T^frlonf Psqge  and  Atmospheric
6.  B.C.  Voldner  and  L.  sinicn,  rr''MM^vi"m ^^,     ^  2  tQ  ^&



Commission, Windsor,  Ontario,  1986,  94 pp.
                                 1031

-------
  Table I.  Total Annual Toxic Metal Emissions by State (Tons per Year) Based on 1985
           NAPAP Emissions Inventory1.

AL
AZ
AR
CA
CO
CT
DE
DC
FL
GA
ID
IL
IN
IA
KS
KY
LA
ME
HD
KA
HI
KN
MS
MO
MT
ME
NV
NH
NJ
MM
NY
NC
ND
OH
OK
OR
?A
RI
SC
SD
TN
TX
UT
VT
VA
WA
W
WI


300.4
261.9
71,6
435.4
81.6
13.4
10. B
1.6
184.9
138.1
99.7
3390.3
673.3
172.2
190.6
100.5
387.7
31.9
785.1
52. 6
773.5
213.0
87.2
553.3
248.4
80.4
283,6
7.7
30.8
219.5
199.0
62.2
74.2
679.5
173.2
196.6
464.0
6.5
42.4
34.8
95.7
1405.8
249.6
13.0
94.3
£3.9
3063.1
68.8


138.9
489.9
63,8
1527.2
228.0
64.9
5.3
26.3
66.6
37.8
122,0
465.*
263.2
204.8
172.6
36.4
119.5
47.0
86.2
214.1
426.1
218. 6
96.9
369.7
350.1
95.1
501.8
30.7
284.4
395.0
303.2
89.5
115.9
514.4
116.1
284,5
84. B
32.3
95,2
62.8
150.1
1074.0
360.2
17.6
41,5
217.8
10.5
257.1


209.9
162.7
109.6
810.8
56.9
131.5
61.0
11.4
403.3
146.0
41.4
1159.9
188.7
45.1
53.2
79.2
796,8
219.6
192,5
322.4
143.0
139,6
48.0
161.6
151.4
17.6
163.7
58.8
354.3
198.1
657.3
188.3
45.4
153.8
77.6
84.7
350.7
32.4
83.0
12.5
116.1
1562.4
145.9
14.2
172. B
190.6
51.9
71.9
90.4

29,3
293.7
11.0
61.7
7,3
l.B
3.6
0.7
32.2
23.7
4.7
77.7
44.4
9.2
7.7
18,1
1958.6
0.7
19.7
7.3
30.4
29.0
9.1
70.9
6.6
2.1
5.0
1.1
8.61
737.6
29.2
23.0
7,0
31.8
19.2
7.1
36.9
0.5
6.8
0.6
58.5
242.8
5,6
0.3
15.3
16.5
13.1
10.9
3,1 	

441.3
40878.2
170,4
338.0
51.0
5,7
16.5
1.3
232.2
260.4
36.1
944.8
326.8
108.2
53.3
254.4
5063.2
10.4
201.3
21.0
314.7
954.6
44.1
2834.5
72.7
26.6
71.1
5.8
32.0
630.2
309.0
270.5
14.1
432.5
226.9
21.6
404.9
0.9
76.6
8.4
196,5
2086.2
236.1
2,3
129.1
106.0
131.8
108.2
*6 *

122.3
68.3
50.1
159. *
25.3
2.3
4.3
0.9
118.1
54.8
12.7
377. 9
135.7
46.1
24.3
73,2
1436,4
3.9
155.7
10.4
180.8
288.1
13,0
10890. 5
74.9
11.5
66.1
1.9
13.4
87.3
92.9
£2.1
9.9
152.5
73.9
22.7
109.6
0,9
22.4
5,2
43.3
565.9
41.4
0,9
41,2
35.4
37.7
36.3
"-»

3026.5
2973,5
1707.1
15734.6
2307,7
1126,2
356.6
151.9
9105.9
3816.5
911.1
6336.4
4«57.9
2113.7
206&4
2183.7
9781.4
654.6
6640.0
2144.9
6801 .6
4530.4
1575.8
16945.4
1708.3
1168.7
1663.6
493.0
3088.4
2206,7
5495 ,0
3647.2
742.0
7419.9
2249.7
2362.1
M32.9
281.3
1762.5
643.9
3136.2
18136.7
2021. 8
4* • * ^
355.7
2*76.6
2459.2
1245-8
2715.7
89LQ
TOTAL   17037.7      11143.6    10941.9     4041,7

1 Mercury emissions without mineral procewiog industry lourw*.
59188.9
15902.6    183955.9
                                            1032

-------
Table II. General source category codes  associated with the greatest portion of toxic
        metal emissions.
               Percentage of Known Total U. S. Emissions for each Metal
      ARSENIC
CADMIUM
CHROMIUM
                                                               LEAD
sec
303
305
46
99
302
SL
93.0
3.0
1.0
1.0
1.0
sec
303
305
46
903
302
&
85.1
4.1
1.9
1.8
1.2
sec
303
901
305
903
902
%.
54.5
15.2
8.1
7.4
3.6
sec
27
303
21
903
304
3L
59.2
20.0
5.3
2.7
2.6
           MERCURY
             NICKEL
                                                             SELENIUM
sec
21
903
902
501
102
&
57.2
22.8
11.0
2.9
1.9
sec
102
303
13
101
7
%.
23.3
11.2
10.4
8.6
8.0
sec
301
303
305
101
102
%.
46.0
30.1
5.2
4.9
4.5

                General Source Classification Code (SCC)* Definitions

       7 - Commercial Institutional Fuel - Anthracite Coal
      13 - Industrial Fuel - Anthracite Coal
      21 - On-Site Incineration - Residential
      27 - Light Duty Gasoline Vehicles - Limited Access Roads
      46 - Aircraft LTO's - Military
      99 - Minor Point Sources
     101 - External Combustion Boilers - Electric Generation
     102 - External Combustion Boilers - Industrial
     301 - Chemical Manufacturing
     302 - Food and Agriculture
     303 - Primary Metal Production
     304 - Secondary Metal Production
     305 - Mineral Products
     901 - Unpaved Road Travel
     902 - Wind Erosion and Agricultural Lands
     903 - Dust Devils
                                         1033

-------
K
<
U
a. 3
sl
0s--
u •
0- 3
            CADMIUM
                         CHROMIUM
                                       MERCURY
                                                     NICKEL
                                                                  SELENIUM
      140
                    LEAD


            1771  AREA SOURCES
                                                           ARSENIC
                                               POINT SOURCES
 Figure I.  Estimated national total point and  area  source emissions for toxic
           metals, based on speciation  of the  1985 NAPAP paniculate  matter
           emission inventory.
                                        1034

-------
   FIELD-SCREENING FILTERS USED IN MONITORING AIR
       QUALITY FOR METALS WITH A FIELD-PORTABLE
             X-RAY FLUORESCENCE SPECTROMETER
                             Mark B. Bernick, Jon Corcoran
                            Roy P. Western, Inc., REAC Project
                GSA Raritan Depot, 2890 Woodbridge Ave., Building 209 Annex
                                   Edison, NJ 08837

                                  Philip R. Campagna
                       United States Environmental Protection Agency
                              Environmental Response Team
                             GSA Raritan Depot, Building 18
                                   Edison, NJ 08837

                                Stanislaw Piorek, Ph.D.
                               Outokumpu Electronics, Inc.
                                 Langhorne, PA 19047

                             Peter F.  Berry, Scott R. Little
                                 TN Technologies, Inc.
                                Round Rock, TX 78664
 ABSTRACT
       Field portable X-Ray Fluorescence (FPXRF) spectrometers are presently used for on-site rapid
 screening of hazardous metallic wastes. The Outokumpu Electronics, Inc. (OEI), X-MET 880 and the
 Spectrace Instruments, Inc., Spectrace 9000 FPXRF spectrometers were adapted to perform analysis of
 filters used in monitoring air quality.  The instruments differ in their energy resolving  power and
 calibration methodology. Both instruments, representing two different analytical techniques, performed
 similarly.  Examples of typical method detection and quantitation limits, results of an accuracy check
 and results of a blind performance evaluation are presented.

 INTRODUCTION                                                   .
      The objective was to develop a method to provide a rapid, nondestructive, on-site alternative for
 analysis of membrane filters used in National Institute for Occupational Safety and Health (NIOSH)
 Method 7300 for metals using FPXRF spectrometers.15  NIOSH Method 7300 may be used  to  monitor
 or identify off-site migration, sources, indoor air quality, and personnel sampling. Additionally, filters
 and thin films used in Hi-Vol sampling or performing wipe tests could be analyzed with this method.
 The United States Environmental Protection Agency (U.S. EPA) Environmental Response Team has been
 using the OEI X-MET 880 and the Spectrace 9000 FPXRF spectrometers to characterize soil and
sediment metal contamination  at  hazardous  waste sites.3-4-*   The analytical capability of these
spectrometers can be adapted to include analysis of membrane filters used to quantify metals in air.

METHODOLOGY
                                     1035

-------
Introduction
      The following target list of metals was used in evaluating the FPXRF methods:

             Arsenic (As)        Iron (Fe)            Selenium (Se)       Cadmium (Cd)
             Lead (Pb)           Tin (Sn)             Chromium (Cr)      Manganese (Mn)
             Zinc (Zn)           Copper (Cu)         Nickel (Ni)

       N1OSH  Method 7300 uses a 37-millimeter (mm) diameter, 0.8-micron pore, cellulose ester-
membrane filter in a sampler connected to a pump with a flow rate of 1  to 4 liters per minute for
sampling volumes of .5 to 2 cubic meters (m3) over 8 hours.  The method calls for chemical ashing of
the filter, followed by atomic emission, atomic absorption or inductively coupled argon plasma analysis.
The 37-mm filters are prepared for XRF analysis by mounting them on a 40-mm double open-ended X-
ray sample cups between two layers of 0.2 mil polypropylene X-ray film.
       The FPXRF instruments  evaluated employ radioisotope source excitation  and X-ray energy
spectrum,  based on the  detection process,  to  analyze fluorescent spectrum.   X-ray excitation  was
provided in each case by the radioisotopes; Cd-109 and Am-241. The Am-241 source was used for a
measurement time of 800 seconds for the elements Cd and Sn. Cd-109 was used for the other elements
with a measurement time of 200 seconds.  A third source, Fe-55, was  also used by  the Spectracc 9000
for a measurement time of 200 seconds for a second analysis of the element Cr. In each case, all of the
elements excited with a given source are effectively determined  in a simultaneous fashion.
       Both spectrometer designs provide lightweight, battery-powered, hand-held operation, for practical
application to in-situ measurement of soils. The instruments differ in their energy resolving power and
calibration methodology. The adaption of each to filter measurement  is relatively simple, as described
below.

Outokumpu Electronics, Inc., X-MET 880 HEPS Probe Description and Methodology
       The OEI X-MET 880 can be adapted to perform  filter measurement by mounting the surface-
analysis probe (SAPS) or the double-source surface (DOPS) probe in the upright geometry and attaching
the  safety shield.  A heavy element powder/liquid (HEPS) probe was used in this evaluation.  This
eliminates the need to hold the DOPS  or SAPS trigger for the 200 to  800 second measuring times  and
provides better sensitivity and sample presentation.  Two HEPS probes were required, because each
 probe can be fitted with only one excitation radioisotope. The  probes are temperature-sensitive. The
 operator activates a software-controlled gain-control circuit for five minutes for every 5-degree farenheit
 change in the ambient operating temperature to prevent possiable error due to gain shifts.
       The OEI HEPS probe employs  a gas proportional detector with  a typical energy resolution of 83U
 electron volts (eV) at the full width at half of the maximum (FWHM) of the manganese (Mn) K X-ray
 line. The resolution  of the detector does not allow for universal  and efficient use of a fundamental
 parameters (FP)-based program to calculate elemental concentrations.  Elemental standards and certified
 thin-film standards are used for an empirical instrument calibration. This provides the operator with the
 flexibility to configure the instrument to analyze for any element from aluminum (Al) to uranium  (U).
        Two sets of gravimetrically prepared thin-film standards were purchased from OEI for target
 element model calibration. The  standards  were  fabricated  using  37-mm  diameter, 0.8-micron po«.
 cellulose-ester filters.   The single element standards were quoted as +/-  5 percent accurate and the
 multielement standards as +/- 10 percent accurate. A thick (approximately 6-mm)  piece of high-puntv
 aluminum was placed directly behind all samples and standards prior to analysis, to provide a constan
 background/backscatter radiation profile and eliminate possible background from impurities in the probe
 shield material.                                                                            .
        The electronic unit of the OEI X-MET 880 FPXRF is capable of holding 32 calibration models.
 Each model can  be calibrated to analyze for six target elements.  The OEI standards were used  to
                                            1036

-------
develop three calibration models. The electronic unit does not provide internal storage for spectrum and
analytical results.  An RS-232 serial port is provided for downloading data and spectra to a peripheral

device.

Spectrace 90W Description and Methodology                            .     .      .   .  .
       The Spectrace 9000 is adapted to perform filter measurement by placing the surface probe in its
lab stand and mounting the safety shield. An adaptor ring locates the sample cup in the center of the
apaturc. Three excitation sources, Fe-55, Cd-109 and Am-241, are contained in the probe providing an
elemental analytical range of S through U. Calibration is not necessary; only selection of a thin-film
FP-based application from a menu is required.  A spectrum energy calibration is performed automatically
with each analysis to prevent error due to gain shifts.
       The Spectrace 9000 utilizes a mercuric iodide (Hgy semiconductor detector with an energy
resolution of less than 300 eV at the FWHM of the M* K X-ray line. The higher energy resolution of
the detector allows for efficient use of a FP-based program to calculate elementalconcentrattpiM.  For
thin-film samples such as filters, element concentrations are computed using FP-denved coefficients in
            P                                                            sure  analteX-
    -                         ,
 an algorithm of the form: CONCENTRATION = R x S; where, R « fte measured
 intensity relative to the pure element and S is a calculated sensitivity coefficjent  A more complex FP
 based program is used for soils applications.
 for any or all of these elements without developing a calibration model.  Additionally, the thin-film
 application calculates and reports Cr results for both Fe-55 and Cd-109 specuu
       The  probe shield design  utilizes a high-purity aluminum metal over the tead in *' shield to
 prevent excitation and analysis of the lead during thin-fUm measurements. Therefore .the g"??"™
 thin film analysis method did not require placement of a high-punty piece of aluminum chrectly behind

 the thin films prior to analysis.
to a peripheral device.  The miilti- element analytical reports and the 2000-channel spectra can be

displayed on the instrument's LCD panel.
                              standards purchased from MicroMatter Co. The standards were quoted

                                                                by performing 10 —-
of the approximte 10 wfcm* (2o        *>r Cd and Sn) per
method detection and quantitation limits, shown in Table HI, were calculated as
the standard deviation of the measurements and are quoted in ^I0^s.of
deposit area is 10.75 cm2 (area of a 37mm filter). These units are equivalent to the concentration in air
expressed as ug/m3 if 1 mj of air is sampled through a 37-mm diameter filter.


Performance Evaluation Sample Methodology                         .  „ f       rf hv nm fnr
       Two cellulose-ester thin-film multi-element standards were gravimetncally prepared t by OEI for
use as performance evaluation standards.  Sample 1  was loaded with «!»>""•** !° . «^  ^
Ni, and Zn. Sample 2 was loaded with approximately 10 ^cm1 Co. As, Pb  OK ICd- ^The  ^
certified values were multiplied by 10.75 for units  bi ug/10.75 cm1 (area of a 37mm filter).   These
                                         1037

-------
standards were used to evaluate the performance of both FPXRF instruments and the chemical ashing
metal analysis methodology. The standards were first analyzed by both instruments and then sent to the
Spectrace Instruments Inc., laboratory for independent XRF analysis by a high resolution tube excited
Spcctrace 6000 instrument. Quantitative analysis was performed by the 6000 using a Fundamental
Parameters model that was calibrated using MicroMatter Co. standards numbered 6304, 6308, 6310 ,
6311, and 6314.  The certified values for these standards can be found in Tables I or II.  The cellulose-
ester standards were then sent blind (with a set of 16 site samples) to a contract laboratory for ashing
and chemical analysis.  The results of all four analyses are in Table IV.

DISCUSSION OF RESULTS

OEI X-MET 880 HEPS Probe
       The OEI X-MET 880 HEPS probe model Se calibration was  not checked because the Se
calibration  standard provided by OEI was unstable, invalidating the Se calibration. Additionally, the
Americium 241 HEPS probe was unavailable when the performance evaluation samples were analyzed,
so Cd analysis was not performed on these samples. The method detection-limit range was from 12.9
to 67.7 ug/10.75 cm2 (Table III).  The error of the accuracy check ranged  from  -27.6 to 35.5 percent
(Table I).  The error of the performance evaluation check ranged from -41.7  to 30.3 percent (Table IV).

Spectrace 9000
       The method detection-limit range was from 12.9 to 35.5 ng/10.75 cm2 (Table ID). The error of
the accuracy check ranged was from -18.8 to 33.3 percent (Table II).  The error of the performance
evaluation check ranged from -40.2 to 37.0 percent (Table IV).

Spectrace 6000
       The error of the performance evaluation check ranged from -1.4 to  -40.8  percent (Table IV).

Chemical Ashing and Metal Analysis
       The error of the performance evaluation check ranged from -69.7 to 30.5 percent  (Table IV).
Additionally, half of the errors were both negative and greater than 60 percent

CONCLUSIONS
       All of the elements evaluated (with  the exception of As) by both FPXRF spectrometers had
detection limits (assuming a 1 mj sample air volume for a 37-mm diameter filter) below the exposure
limits (as the element, i.e., lead dust as Pb) published in the NIOSH Pocket Guide To Chemical Hazards.
U.S. Department of Health and Human Services, September, 1985.
       Generally, the XRF performance-evaluation results agreed well and had similar differences with
the certified gravametric values.  The larger negative metal-analysis  performance-evaluation errors of
up to 70 % indicate a loss during the analytical procedure. Blind-performance evaluation samples should
be included in samples submitted for chemical ashing and metal analysis.
       FPXRF analysis provides  a rapid nondestructive on-site technique  for prescreening filters and
wipes. This technique could be adapted by the users of the OEI X-MET 880 FPXRF unit by using the
appropriate HEPS probe and standards for the metal(s) of interest. This technique could be adapted by
the present users of the Spectrace 9000 through use of the thin-film application model provided with the
unit  Both instruments, representing two different calibration approaches, performed similarly.
       The reported method detection limits are based on repetitive measurements of filters loaded with
 10 ug/cm2 (20 ug/cm2 for Cd and Sn)  of the target element(s).  Lower method detection limits,  by
generally a factor of 2, could be  calculated by measurement of a blank filter reducing the counting
statistical error.
                                           1038

-------
 REFERENCES
 1. NIOSH Manual of Analytical Methods, third edition, National Institute for Occupational Safety and
 Health, Section A, Method 7300.

 2. J. Rhodes, J. Stout, J. Schindler, and S. Piorek, "Portable X-ray survey meters for in-situ trace element
 monitoring of air particulates," in Special ASTM Technical Publication 786. Toxic Materials in tha
 Atmosphere. American Society for Testing and Materials, 1982, pp 70-82.

 3, M. Bernick, M. Sprenger, G. Prince et al., "An evaluation of field portable  XRF soil preparation
 methods," in Proceedings of the Second International Symposium on Field Screening Methods for
 Hazardous Wastes and Toxic Chemicals. U.S. Environmental Protection Agency, EMSL, Las Vegas, NV,
 1991, pp 603-607.

4. M. Bernick, P. Berry, G. Prince et al., "A high resolution portable XRF Hglj spectrometer for field
screening of hazardous metal wastes," in Proceedings of the Pacific-International Congress on X-ray
Analytical Methods. University of Denver, Denver, CO, 1991.

5. W. Cole HI, R. Enwall, G. Raab and C. Kuharic, "Rapid assessment of superfund sites for hazardous
materials with X-ray fluorescence spectrometry," in Proceedings of the Second International Symposium
on Field Screening Methods for Hazardous Wastes and Toxic Chemicals. U.S. Environmental Protection
Agency, EMSL, Las Vegas, NV; 1991, pp 497-505.
                                          1039

-------
                               TABLE I
OBI X-MET 880 HEPS PROBE MODELS 30, 31, AND 32 ACCURACY CHECK RESULTS
                   USING HICROMATTBR CO. STANDARDS
STANDARD I TARGET (DENSITY) ISOTOPE (ANALYSIS I INSTRUMENT I
NUMBER (ELEMENT (DEPOSIT) SOURCE I TIME IN (READING 1% ERROR
1 Ing/cm2 | (SECONDS I|ig/cm2
6301
6302
6303
6304
6305
6306
6311
6307
6308

6313



6314






6309


6310

6312





RTiANK£
Fijir™ r


ICr
|Mn
(Fe
INi
ICu
(Zn
(Pb
IAS
ISe
1
(Pb
IAS
ISe
1
ICr
|Mn
iFe
INi
ICu
|Zn
1
ICd
ISe
1
|Sn
1
ICd
ISe
ISn
1
1
ICr,
INi
1 *™ ™ f
ISe,
ICd,
1
121.0
117.0
120.4
[18.5
120.0
119.2
121.9
(34.2
(18.6
1
121.4
134.4
119.7
1
118.6
116.1
(19.0
(18.2
119.7
(18.7
1
118.9
113.2
1
(18.8
1
121.0
(14.7
118.2
1
1
Mn, Pe 1 0
Cu . Zn 1 0
^ v / ••• • l *•
Pb,As|0
Sn 10
1
ICd-109 1200
ICd-109 (200
ICd-109 1200
ICd-109 1200
ICd-109 1200
ICd-109 1200
ICd-109 1200
ICd-109 1200
ICd-109 1200
1 1
ICd-109 1200
ICd-109 1200
ICd-109 (200
1 1
ICd-109 1200
ICd-109 1200
ICd-109 1200
ICd-109 1200
ICd-109 1200
ICd-109 1200
1 1
|Am-241 |800
ICd-109 1200
1 1
|Am-241 1800
1 1
I Am- 241 |800
ICd-109 1200
|Am-241 (800
1 1
1 1
ICd-109 1200
ICd-109 1200
ICd-109 1200
|Am-241 1800
1 1
120.7
116.0
119.4
121.0
118.1
119.9
126.7
140.4
I NOT ANAI
1
115.5
141.0
1 NOT ANAI
1
125.2
119.2
122.8
121.9
118.3
119.9
1
120.3
1 NOT ANA]
1
121.8
1
127.8 *
1 NOT ANA]
117.2 *
1
(ALL RESULTS
IWBRB BELOW
I THE ELEMENT
(DETECTION
(LIMITS
1
-1.4
-5.9
-4.9
13.5
-9.5
3.6
21.9
18.1
YZBD

-27.6
19.2
YZBD

35.5
19.3
20.0
20.3
-7.1
6.4

7.4
pYZBD

16.0

32.4
LYZBD
-5.5







                                                   taken to
|ig/cm2-denotes micrograms per square centimeter
*-denotes  reported average  of  ten measurements
detection limit
% error= ([instrument reading-certified value]  /  certified value)
calculate
                                 1040

-------
                          TABLE II
SPECTRACE 9000 THIN FILM APPLICATION ACCURACY CHECK REStJLTS
              USING MICROMATTER CO. STANDARDS
STANDARD | TARGET 1 DENSITY I ISOTOPE I ANALYSIS I INSTRUMENT I
NUMBER (ELEMENT I DEPOSIT 1 SOURCE (TIME IN I READING 1% ERROR
| mg/cm2 1 (SECONDS )ng/cm2 1
6301
6301
6302
6303
6304
6305
6306
6311
6307
6308
6313


6314


6309
6310
6312
BLANKS
ICr
ICr
IMn
IFe
INi
(Cu
IZn
IPb
|As
ISe
1
IPb
IAS
ISe
1
ICr
ICr
l ^^™
IMn
IFe
INi
J *1*
ICu
fZn
1
led
ISe
1
ISn
1
(Cd
ISe
ISn
1
ICr
|Cr,M»,
|Ni,Cu,
ISe, Ft,
1 Cd, Sn
(21.0
121.0
117.0
120.4
118.5
120.0
119.2
(21.9
134. 2
118.6
1
121.4
134.4
119.7
1
[18.6
118.6
116.1
119.0
118.2
119.7
{18.7
1
(18.9
113.2
1
118.8
1
121.0
114.7
118.2
1
10
FelO
ZnIO
ABlO
10
|Fe-55 1200
|Cd-109 1200
|Cd-109 1200
|Cd-109 1200
|Cd-109 1200
ICd-109 1200
ICd-109 1200
|Cd-109 1200
|Cd-109 1200
ICd-109 1200
1 1
ICd-109 1200
|Cd-109 1200
ICd-109 1200
1 1
IFe -55 1200
ICd-109 1200
ICd-109 1200
|Cd-109 1200
ICd-109 1200
ICd-109 1200
ICd-109 1200
I 1
|Am-241 1800
JCd-109 1200
1 1
|Am-241 1800
1
I 1
|Am-241 1800
ICd-109 1200
|Am-241 1800
1
1 1
|Fe-55 1200
|Cd-109 1200
ICd-109 1200
ICd-109 (200
|Am-241 1800
[18.2
120.5
118.4
122.2
123.2
121.8
120.0
124.1
136.9
122.4
1
122.2
140.3
(23.8
f
115.1
122.2
116.4
121.7
(22.0
(19.4
117.9
1
125.2
115.4
I
123.5
1
J25.7 *
117.2 *
121.9 *
1
(ALL RESULTS
(HERE BELOW
JTHE ELEMENT
| DETECTION
(LIMITS
-13.3
-2.4
8.2
8.8
25.4
9f*
.0
4 A
.2
10.0
rt A p*
13.7
A. A A
20.4
3.7
•4 H M
17 .2
20.8
-18.8
19.4
1A
,9
14.2
20.9
If
,5
-4.3
33.3
16.7
25.0
22.4
17.0
20.3

                                                           doc,
                            1041

-------
                               TABLE III
              OBI X-MBT  880  RBPS PROBB & SPBCTRACB 9000
                  DETBCTION  AND QUANTITATION LIMITS


        SPBCTRACB 9000 DETECTION AMD QUANTITATION LIMITS
                    ™ — '*"' ™ — — •• ^''^^^'^'^^•••"••^••••^••.^^IM^^^^^^^^^^^ 4P» «M ^ ^W ^ •»*
STANDARDITARGET  (STANDARD 1ISOTOPB|ANALYSIS IDBTBCTIONIQUANTITA-  I
NUMBER  1ELEMENT IDEVIATIONI SOURCE  [TIME  IN  ILIMIT     |TION LIMITI
        I        lmr/cm2   I        (SECONDS  I   ng/10.75 cm2      '
B-l-031
B-l-031
B-l-048
B-l-031
B-l-031
B-l-048
B-l-031
B-l-048
B-l-048
B-l-031
6312
6312
ICr
ICr
IMn
|Fe
INi
ICu
IZn
IPb
IAS
iSe
(Cd
ISn
10
10
10
to
10
10
10
10
10
10
11
11
.4
.6
.8
.8
.5
.5
.5
.5
.8
.4
.1
.1
|Fe-55
ICd-109
ICd-109
ICd-109
ICd-109
ICd-109
ICd-109
ICd-109
ICd-109
ICd-109
tAm-241
tAm-241
1200
1200
1200
1200
1200
1200
1200
1200
1200
1200
1800
1800
112
119
125
125
116
116
116
116
125
112
135
135
.9
.4
.8
,0
.1
.1
.1
.1
.8
.9
.5
.5
"ii.
64.
86.
86,
53.
53.
53.
53.
86.
43.
118.
118.
0
5
0
0
8
8
8
8
0
0
3
3
    OBI X-MBT 880 HEPS PROBE DETECTION AND QUANTITATION LIMITS
NUMBER
IELEMENT IDEVIATION|SOURCE (TIME IN |LIMIT    ITION LIMIT I
I         IMT/C»2   t        (SECONDS |    jig/10.75 C»2     I
B-l-031
B-l-048
B-l-031
B-l-031
B-l-048
B-l-031
B-l-048
B-l-048
B-l-031
6312
6312
ICr
IMn
ire
INi
ICu
IZn
IPb
IAS
ISe
ICd
ISn
10
10
10
10
10
10
10
10
1
12
11
.7
.9
.5
.5
.5
.4
.6
.4

.1
.8
ICd-109
ICd-109
ICd-109
ICd-109
ICd-109
ICd-109
ICd-109
ICd-109
ICd-109
lAm-241
IAm-241
1200
1200
1200
1200
1200
1200
1200
1200
1200
1800
1800
122
| • •*•
129
1 *«*
116
1 ••»*
116
1 *v
116
} W V
112
119
112

167
158
.6 7S-
• V
n
* V
.1
1
• A
.1
.9
.4
.9
96.
53.
53.
S3.
43.
64.
43.
3
8
8
8
8
0
5
0
NOT ANALYZED
.7 1225.
.1
193.
8
5
Hff/cm2-d»nots» microcrrama per »
-------
                                 TABLE IV
              PERFORMANCE EVALUATION SAMPLE ANALYSIS RESULTS
1 ID 1 Ell CERTIFIED | ANALYTICAL RESULTS 110/10. 75 Ctt2 J
l# 1 |ua/10.75 cm21 AA |SPC 6000IX-MET 880ISFC 90001
11 lCr|
ii I r
11 iPel

11 (Nil
12 1 Cu|
1 — I — j 	
11 IZnl
— 1 — \ 	
12 IAS)
--I — 1 	
12 IFUI
— \ — 1 	
12 ICdl
1 	
131.2)
1
118.31

122 . 6 1
107.51
127.91
98. 9f
123.61
114.01
1401
1
1101

1601
371
1301
301
431
421
126.31
1
116.61

117.71
74.41
119.21
67. 5J
84.71
67.51
167.71$ 159.5)
l# 179.81
145.81 134.7 |

159.7
62.'
157.4
84.4

153.51
I 91.31
148.21
	 j
80.0)
	 1
81.51 98.41
	 I 	 1
NAI 68.21
1 ID1 Ell
PBRC2HT
ERROR

0 ] AA ISPC 6000IX-MET 880ISPC 9000
1 Crl 6.71
1 1 1
	 1-
1 |Fe| -7.01
11 mil 30.51
I--I--I 	 1-
2 ICul-65,61
— 1 — 1 	 1-
1 IZnl 1.61
2 IAsl-69.71
--I — 1 	 1 —
2 |Pb|-65,2|
— I 	 1_.
2 |Cd|-63,2|
-3.7)
1
-1.41
-4.01
-30.81
-6.8|
-31.71
-31.51
-40.81
27. SIS

23.21
30.31
-41.71
23.11
-14.71
	 	 — f —
-34.11
	 i —

21.6
37.0
13.9
25.2
-15.1
15.9
-19.1
-20.41
i
-40.21
	 f
             -55  excitation,   #-denot«s Cd-109 excitation,  ND-denotes
               \£Sm***m Mot Analysed,  AA-denotea Atomic Abeorptlon,
                                      -  ce^ied value]  /  certified
    e      fl 0     Uff/10.75  cm2-denotes   nicrograms  per  10.75  sgjuare




diameter filter.
                                   1043

-------
           OVERALL EFFICIENCY OF INLETS SAMPLING AT SMALL
           ANGLES IN THE YAW AND PITCH ORIENTATIONS FROM
                       HORIZONTAL AEROSOL FLOWS
Sunil Hangal
RTF Environmental Associates, Inc.
239 U.S. Highway 22, East
Green Brook, New Jersey 08812

and

Klaus Willeke
Aerosol Research Laboratory
Department of Environmental Health
University of Cincinnati
Cincinnati, Ohio  45267-0056
                                  ABSTRACT
We have developed a model for the overall sampling efficiency at yaw and pitch based
on our experimental data obtained for tubular sharp-edged inlets at 0 to 20 degrees from
horizontal aerosol flows in a wind tunnel facility. In our model, the difference between yaw
and pitch is expressed by the effect of gravity on the wall impaction  process of the
aerosols inside the inlet. At yaw, the gravity effect on the wall impaction process does
not change with sampling angle.  At pitch, the gravity effect on the impaction process
results in particle loss increase for upward and decrease for downward  sampling.

Using our model, we have developed graphical representations for aerosol sampling at
small angles. These can be used in the field to determine the overall sampling efficiency
of inlets at several operating conditions and the operating conditions that result in an
acceptable sampling error. Pitch and diameter factors have been introduced for relating
the efficiency values over a wide range of operating conditions to those of a reference
condition.  The pitch factor determines the overall sampling efficiency at pitch from yaw
values, and the diameter factor determines the overall sampling efficiency at different inlet
diameters.
                               INTRODUCTION

Several processes, schematically shown in Figure 1, may affect the  overall aerosol
sampling efficiency, E,, of an inlet:
      1)   Aspiration to the face of the inlet (aspiration efficiency, EJ.
      2)   Bounce from the front edge of the Inlet (entry efficiency, Er).
      3}   Transmission loss in the inlet (transmission efficiency,  E,) due to gravitational
           settling, direct wall impaction and turbulence in the vena contracta which is
           formed when the inlet velocity (U,) exceeds the ambient wind velocity
                                      1044

-------
  For a sharp-edged inlet, particle bounce is negligible (E, = 1) and
                                     E,  = E. E,                                (1)

  We have developed models for aspiration (Hangal and Witleke1) and transmission (Hangal
  and Willeke2) efficiencies based on a large set of sampling efficiency data that has been
  obtained in our wind tunnel facility for inlets oriented in the vertical plan (pitch) (Tufto and
  Willeke3-4; Okazaki et al.w>e; Wiener et al.9).

  (n  ambient and industrial environments  the  wind direction may also change in the
  horizontal plane (yaw).  We have performed experiments in our wind tunnel system at
  several pitch angles between 0 to 20 degrees from horizontal aerosol flows, and have
  added to these experiments at several yaw angles10.  Based on these data we have
  extended our overall sampling efficiency model for pitch to yaw and have developed from
  this model graphical representations for sampling aerosols at small angles that can be
  used in the field to determine the overall sampling efficiency of inlets at several operating
  conditions and the range of operating conditions that results in an acceptable sampling
  error.
                  EXPERIMENTAL SYSTEM AND PROCEDURES

  In the wind tunnel, test aerosols - monodisperse oteic acid particles for this study - are
  produced by a vibrating orifice generator, followed by a charge neutralizer.  A mixing fan
 placed upstream of the generator disperses the  aerosol before it is accelerated to the
 desired wind velocity in the test section. The test inlet is' integrated into a modified optical
 single particle counter which permits fast data acquisition and analysis at high statisttcal
 counting efficiency.  The inlets are round brass tubes that meet the Belyaev and Levin
 criteria for sharp-edged inlets. The air exiting from the inlet is surrounded by clean sheath
 air in order to eliminate  particle deposition inside the optical  partide counter which
 dynamically records the sampled aerosols.  The overall sampling efficiency of three 20 cm
 long (L) inlets have been determined with inner diameters of 0.32,0.56 and 1.03 cm, at
 a wind  velocity (UJ of 500 cm s'1, inlet velocities of 250 to 1000  cm s'1, particle sizes
 (aerodynamic diameter, dj of 10 to 40^m, and sampling angles of 5 to  20° in the pitch
 and yaw orientations.                                  ._.„
                     RESULTS AND MflPFL DgVELOPMENT

 The overall sampling efficiency, E,, decreases wrthincrease Article size. The E, values
 for pitch upward sampling are lower than for pitch downward sampling. The E^ values
 for yaw sampling  are in  between the  upward and downward pitch values and the
 difference between yaw and pitch values increases with increase in samplmg angle.  In
 ouru^^^^^^e transmission efficiency is separated into a gravitational
 settling component, E,., and an impaction component,  E,,

                                  E^E,.                                (2)

The impaction component is expressed as a function of the wall impaction parameter, L,

                    I  = StK, R05 sin (6 ±  or) sin  ((9 ± a)/2}                  (3)
                                     1045

-------
where Stk* is the Stokes number, 6 is the physical sampling angle, and R is the velocity
ratio.
                                  R  = UJU,                                (4)

For pitch sampling, gravity effect angle, a, represents the effect of gravity on the particle
impacting onto the wall. For pitch upward sampling, inertia Impacts the partide towards
the lower inside wall and gravity pulls them towards the same wall [represented by a
positive sign in equation (3)].  Conversely, for pitch downward sampling, gravity opposes
the particle motion towards the wall [represented by a negative sign in equation (3)].

During yaw sampling in the horizontal plane, the effect of gravity on the motion of the
particles is the same for all yaw sampling angles. Therefore, the gravity effect angle, or,
which differentiates upward from downward sampling, is zero for yaw.

  THE OVERALL SAMPLING EFFICIENCY AT YAW AND PITCH ORIENTATIONS

Using the equations in our model we have developed Figures 2 to 4 as convenience
graphs for use in the field as a first step assessment of the overall sampling efficiency of
inlets under several field operating conditions.  A more detailed  assessment of the
sampling error can be done with the use of model equations.  These figures are based
on a reference inlet size of 1 cm inner diameter.  Figure 2 shows the overall sampling
efficiency at several yaw orientations, Etyiw of a 20 cm long reference inlet as a function
of Stk*.  The aerodynamic diameter (dM) scales can be used under any  of the Stk*
scales.

We have developed a new  factor, Pitch Factor (PF),  which is used to determine the
overall sampling efficiency at pitch orientation, Eiiplteh from E, yaw. PF is independent of inlet
diameter and is, therefore, valid for alt D,.

                               PF -  E.,pdch (Ei>yJ-1                            (5)

 Figure 3 gives  the PF as a function of Stokes number at R -  2,  1  and 0.5 for 5 to 30
 degrees downward and upward sampling angles.

 We have also developed a Diameter Factor (DF), for determining the overall sampling
 efficiency of inlets larger or smaller than the reference inlet, D, = 1 cm, used in Rgure 2

                              DF-E^E,^.^)-'                           (6)

 for all yaw sampling angles.

 Figure 4 gives the DF as a function of Stokes number for D, = 2 and 0.5 cm at Uw » 125
 to 1000 cm s"1 and R = 2,  1, and 0.5.
                                        1046

-------
                                  REFERENCES
  1.  Hangal, S. and  K. Willeke (1990a).  Aspiration Efficiency:   Unified Model for ail
     Forward Sampling Angles.  Environ. Sci. Techno!., 24, 688-691.
  2.  Hangal, S. and K. Willeke (1990b). Overall Efficiency of Tubular Inlets
     Sampling  at 0 to 90 Degrees from Horizontal Aerosol Flows.  Atmos. Environ.,
     24, 2379-2386.
 3.  Tufto, P.A. and K. Willeke (1982a),  Dependence of Particle Sampling Efficiency on
     Inlet Orientation and Flow Velocity. Am. Ind. Hyg. Assoc. J., 43_, 436-442.
 4.  Tufto, P.A. and K, Willeke (1982b).  Dynamic Evaluation of Aerosol Sampling Inlets.
     Environ. Sci. Technol., Ifi, 607-609.
 5.  Okazaki,  K.,  R.W.  Wiener  and  K.  Willeke  (1987a).     Isoaxial   Sampling:
     Nondimensional  Representation of Overall  Sampling  Efficiency.   Environ. Set.
     Technol., 21, 178-182.
 6.  Okazaki, K.f R.W. Wiener and K. Willeke (1987b). The Combined Effect of Aspiration
     and Transmission on Aerosol Sampling Accuracy for Horizontal Isoaxial Sampling.
     Atmos. Environ., 21,  1181-1185.
 7.  Okazaki, K.,  R.W.  Wiener  and  K.  Willeke (1987c).  Non-isoaxial  Sampling:
     Mechanisms'Controlling Overall Sampling Efficiency. Environ. Sci. Techno!., L 183-
     187.
 8.   Okazaki, K.  and K.  Willeke (1987).  Transmission and Depos
     Aerosols in Sampling Inlets. Aerosol Sci. and Technol., 7, 275-283.
 9.   Wiener, R.W., K. Okazaki and K. Willeke (1988). Influence of Turbulence on Aerosol
     Sampling Efficiency.  Atmos. Environ., 22, 917-928.
10.  Hangal, S.  and K. Willeke (1992). Aerosol Sampling at Small Forward-Facing Angles:
     Differentiation of Yaw from Pitch.  Atmos, Environ.  (In print).
11.,  Belyaev, S.P, and LM. Levin (1974).  Techniques for Collection of Repres
   '  AerosolSamples.  J. Aerosol Sci., 5, 325-338.
                  Limiting Streamline
                   of Aspirated Air
            Boundary
             Layer
Non-Aspirated

Inward Bounced



Wall Impacted


Sampled
                                                    Gravitationally Settled
                                                    Vena Comracta Lost
                                                    Outward Souncad
                                                    Non-Aspirated
                   Figure 1.  Schematic representation of the rne^anisms that
                   affect the overall efficiency of a sampling inlet.
                                     1047

-------
 M

LU  0.1  -
U

I 0.01
LJ

CT


lo,
re
CTj
£0.01
                   Yaw  Samplins. D . • 1  cm, L. - 20 cm
          U ,i
                       	500
        R-2
        6«0
                    e-o
                         \
                                       R-0.5
•R-2
••. \\\
 \M
  •. »
   ', V
      •e-is
         : R-1
                                           JR-0.5  "^
                         o      - * 3 :        e      ;•!  .
                   e-is       •.;!] :  0-15
                   	.	ill I	  .	"A...
a
O«
i



0.1
n n 1
...... n^
~ • --. ^""^s.
E R • 2 "••"•?X
*" * A
'» I

r U
ie-3o° I
, . ..flJ 	 ^ 	 i,i
J
-

-

-
-.
         0.01 0.1
                10   0.01 0.1   1   10   0.01 0.1  1   10

                Stokes  Number,  Stkw

(Cf
tor
1
5 1
u •
i
5
U *
•
I
0
125
i
10
253
. .1 	
50
cm s
. , . I ..
i
150
for U
•
..i
50 100
• i
cm i
Aerodynamic
I I ,.,!,. 1
5 10 50 1
• 500 cm i" tar \j •
•
Diameter, dae pm
i i , , . i
5 10 50
• i
1000 cm s
        Figure 2. Overall sampling efficiency for several yaw angles.
                             1048

-------
 G


 15

 I—
 o
>
a
      0.01
                    & -JG".V|S' '•
                        -la*   -ioa
  a
  gi
LU
U.
Q.
      a.*  a-
     O.QL
      I CO =
    0.0!
        G.l            l            10
            Stokes  Number.  Stk
                                                     Reference,  D; * "I  Cm
                                               0.01     0.1       1       10

                                                    Stokes Number,  Stk
       Figure 3. Pitch factor for determining       Figure 4. Diameter Factor for
       the sampling efficiency from yaw values.    inlet diameters D,">1 cm.
                                      1049

-------
               COMPARISON   OF  AEROSOL  ACIDITY   IN  URBAN
                        AND SEMI-RURAL  ENVIRONMENTS
                      Robert M.  Burton and William E. Wilson
                      U. S. Environmental Protection Agency
                         Research Triangle Park, NO 27711

                     Petros Koutrafcis and Lee-Jane Sally Liu
                         Harvard School of Public Health
                              665 Huntington Avenue
                                 Boston, HA 02115
  ABSTRACT

       During the summer of 1990, acid aerosol, acid gas, and ammonia measurements

  were  conducted  simultaneously  at  three  locations in  central  and  western

  Pennsylvania where population  levels were  large  (metropolitan Pittsburgh) and

  small (semi-rural communities of Uniontown  and State College) .  Aerosol  acidity

 was found to be lower  in the urban  area than in  the  two semi-rural  locations.

 In contrast, ammonia levels were higher  In the urban environment than in the

 semi-rural environments.   Possible  sources of ammonia In  Pittsburgh are the

 people residing  in the city  or  the  two  coke plants  located upwind  of the

 Pittsburgh sampling  site.   A mixture of  totally and partially neutralized

 sul fates, i.e., (NH4)2S04 and NH4HS04,  were the  dominating  sulfur species  in

 Pittsburgh while in State College and Uniontown,  the primary  sulfur species were

      and N
Keywords: acid aerosols, ammonia neutralization, regional transport.



INTRODUCTION

      Acid sulfates and nitrates are secondary air pollutants formed through the

heterogeneous or homogeneous oxidation of S02 and NOX in the atmosphere.  During

a major  summertime acid  aerosol episode,  ambient exposures  of 100  to 900
                                     1051

-------
(Mg/ms)-hr of sulfates were shown to be possible.1  The actual exposure nay be



confounded by variable levels of outdoor activity In the summer and by the degree



of penetration of the acidic sulfate Into the home.2  Epldemlologlc studies have



suggested that morbidity and mortality rates are associated with  total sulfate,



hydrogen ion, or acid mint concentrations.''4 Animal and human exposure studies



in  the laboratory have demonstrated  that  acidic sulfate  particles  produced



functional changes In  the respiratory tract at  levels  as  low as 40 (ig/m3.*'*  In



a  more recent paper,  Schlesinger  et »1.7 indicated  that  identical levels of



hydrogen  ion  (H+) produced different degrees of response depending upon whether




exposure  was  to  H2S04 or NH4HS04.








       It  is  thought  that  acidity may  be higher in rural areas than  urban areas



because of higher NH,  emissions in the urban areas.   These higher NHj emissions



result in more  neutralization  of the  acidic  sulfate.   This  hypothesis is




supported by  results from the New York metropolitan area summer aerosol study. '




In a  more recent study,  Waldman  et al.10  reported  levels  of   acidic sulfate



species measured simultaneously at three nearby sites.  It was  found that  the



degree of sulfate neutralization was highest at the urban downtown site as



compared  to   two  more remote  sites located  30 km of downtown.    Nevertheless,




simultaneous measurements of acidic  aerosols  as  well as  NH}  concentrations  in




large cities have been sparse.  Very little Is known  about the  relationship of




acid levels   in  neighboring smaller cities.   The purpose  of our study was to



characterize the regional  transport of acid  particles  and  ammonia levels  in



adjoining urban (Pittsburgh,  PA)  and semi-rural areas  (Unlontown and  State



College,  PA) and to  examine the extent of neutralization In each location.
                                       1052

-------
  ANALYTICAL APPROACH




        During the  summer of 1990,  acid aerosol concentrations  in central and



  western Pennsylvania were measured.  This region was chosen because it has the




  highest concentrations  of acid aerosols  and  sulfate particles  in  the United




  States.11'12      Monitoring   was   conducted  simultaneously   in   Pittsburgh




  (population-2,000,000) and two semi-rural towns surrounding Pittsburgh, including




  Uniontown  (pop-15,000),  located 97  km  south of Pittsburgh, and  State  College




  (pop-36,000), located 240  km east  of Pittsburgh.








       Fine-fraction aerosol (<2.5 |im) was collected using the Harvard-EPA Annular




 Denuder System  (HEADS) and analyzed  for total  particulate strong  acidity (H*),




 ammonia  (NH3),  ammonium (NH^*),  nitric acid  (HNO,),  nitrous  acid (HN02) and




 sulfate (S042").   The HEADS  consists of a borosilicate  glass  impactor, two glass




 annular denuders,  and a teflon  filter pack.   The glass impactor has  a 50%




 aerodynamic cutoff  of  2.1 (im at a flow rate of 10 L/min and allows gases and fine




 particles  to  pass into the annular  denuder and filter pack components.13  The




 series  of annular  denuders collect acidic gases  and  ammonia.   Following the




 annular  denuders is a filter pack  containing  three filters.   The first  is  a




 Teflon  membrane  used  to collect fine  particles  for  particle mass,  aerosol




 acidity, ammonium, sulfate,  nitrate,  and  nitrite determinations.  The second and




 the  third  coated  glass  fiber  filters  are  used  to  collect  HN03  and  NH,,




respectively,  generated by  the dissociation of NH4NOj.   The Teflon  filters were




analyzed for  aerosol  acidity using  a pH-meter with a microelectrode and for




inorganic ions using ion chromatography.
                                     10S3

-------
      HEADS samples war*  collected over  24 h, 12  h,  and  6  h periods.   The



sampling schedule for  the three sites is briefly described in Table I.  Six-hour



integrated concentrations were collected every other d»y  and were considered to



be sufficient to catch high acid periods14.  Particular aerosol concentrations



reported  in the  results  section are  in units of  nanonoles per  cubic mater



(nmol/m*), while gaseous components (e.g., HNOj and KHj) are in parts per billion




(ppb).







RESULTS



      The  study results  are summarized in Table  II.   The 6 h integrated mean



gaseous  HNOj concentrations were 3.65 ppb in Unlontovm,  3.60 ppb  in Pittsburgh.



and 2.83 ppb in State College.  However, these acid gases did not contribute  to



the aerosol acidity levels.  Concentrations of HN02 were negligible in all three



cities.  Hence,  atmospheric aerosol acidity in these cities was associated with



the presence of acidic sulfates.  The highest levels of aerosol acidity observed



were 628 nmol/m3 on  August  12 in Uniontown,  725 nmol/m5 on July 20  in State



College, and  308 nmol/m3 on July 30 in Pittsburgh.  Acid episodes occurred nore



often in August than June or July and usually lasted  three to four  days.   The



mean 6  h integrated [H*J  concentrations in Uniontown were significantly higher



 than those in Pittsburgh, but only moderately higher than those in State College.



Differences in mean total sulfate concentrations among the three  cities were not



 significant at a 0.05 significance level using analysis of variance techniques.








       The acidic fraction of sulfates,  i.e.,  the  [H*]/[S042'] molar ratio, never



 exceeded 1.6 in these three sites indicating that neutralization of acid  sulf't'



 has  occurred  to some extent.   Sulfates  were less acidic  in Pittsburgh.   The
                                       1054

-------
   ratios  of IH*]/[S042-] averaged 0.59+0.26 In Pittsburgh. 0.97±0.40 in Uniontown.



   and 0.8410.34 in State College.  Six-hour integrated ratios of [H*]/[S042']  were



   proportional to  the corresponding sulfate levels with a Pearson'*  correlation



   coefficient  (r)  of 0.79 in  Pittsburgh,  0.55 In Uniontown,  and 0.68 in State



   College.








        Ammonia levels were highest in Pittsburgh and lowest in Uniontown.  The two



  Pittsburgh coke ovens were upwind of the sampling site and could have influenced



  the city  ammonia  levels.   In State  College,  where the population  size  falls



  between Pittsburgh and Uniontown, the ammonia levels also ranged in between the



  two other cities.   This,  along with the previous findings  that aerosol  acidity



  was highest in Uniontown  and comes primarily from acidic sulfates, strongly



  suggests that acidic sulfates  are mainly neutralized by ammonia. The correlation



  coefficient  for  6  h  integrated  [H*]/[S042*]  ratios  and  ammonia  levels  in



  Pittsburgh was as  high as  -0.71,  suggesting that ammonia generated within big



  cities depletes a  portion of the acidic aerosols.   Although the large cities




 provide more ammonia for  acid  neutralization, aerosol acidity will still remain




 high when the levels of acidic sulfates exceed the buffer capacity of ammonia15.








      The differences in aerosol acidity and ammonia levels in these three cities



 became particularly distinct during high acid aerosol periods. The episode which



 started  on July 16  and ended on July  20 provides sufficient  information  for



 analysis.  During this episode, the 6 h integrated acid level  reached 531 nmol/m3



 in Uniontown, 725 nmol/m3 in State College,  and 181 nmol/m3  in  Pittsburgh.  The



 6  h  integrated acid concentrations in Uniontown and State College were always



higher than those in Pittsburgh.  On the contrary,  the 24 h total ammonia levels,
                                     1055

-------
Including gaseous NH, and partlculate  NH4*. were higher  In Pittsburgh than  In



Unlontown and State College.  The [H*]/[S042'] ratio reached 1,52 on July  18  In



Unlontown,  and  1.50 on July 20 In  State  College.   The [H*]/[S042-]  ratio  In



Pittsburgh  remained well below 1.0  during this period.  Therefore, during the



episode, the Pittsburgh aerosol consisted of primarily neutralized and  partially



neutralized sulfates,  i.e.,  (NH4)2SOi and NH4HS04,  while  In Unlontown  and State



College  the aerosol was mainly sulfurlc acid and partially neutralized sulfate,



 I.e.,  HjS04 and NH4HS04.  The lower ratio of 1.0 for Pittsburgh Indicated a more



neutral  species.







       Although there were substantial differences In the degree of neutralization



 among the cities,  aerosol acidity was  found to be highly correlated between the



 urban and  the  semi-rural sites.  The  Pearson's r was as  high  as  0.85 for 6 h



 Pittsburgh versus  12 h Unlontown measurements  and 0.64 for 24 h Pittsburgh versus



 6 h State  College measurements.  Similarly, between city sulfate levels were



 highly  correlated.  Both  6 h and 12  h  sulfate measurements  In Unlontown were



 highly  correlated  with 6 h Pittsburgh measurements (r-0.83).   Six-hour sulfate



 measurements  in  State College also were  correlated  with  measurements  at



 Pittsburgh (r-0.68).    The high  sulfate correlations  between sites  imply •



 regional transport.







       Diurnal variation of acid was  demonstrated by the fact that 24 h integrated



  [H*] was significantly lower than the  6  h  integrated daytime  [H*].  This finding



  Is consistent  with the previous studies'*'17'18'19 and  was explained by Vilson et



  al.29, who proposed atmospheric dynamics involving vertical convection  in the



  mixing  layer as the major  cause of diurnal variation In aerosol acidity.
                                        1056

-------
  CONCLUSIONS




        Our results indicate that aerosol acidity was lower In an urban area than



  the surrounding semi*rural environments.  As expected, ammonia levels were higher



  in a large city than smaller,  semi-rural towns.  The dominate sulfur species in



  Pittsburgh were found  to be the mixture of totally and partially neutralized



  sulfates,  i.e., (NH4)2S04 and NH4HS04,  while sulfur species in semi-rural areas



  such  as  Uniontown and  State  College  were  primarily  H2S04  and  NH4HS04.



  Accordingly,  the higher Pittsburgh ammonia levels resulted in lower [H*]/[S04Z'J



  ratios.  Possible sources of NHj in Pittsburgh may be associated with the people



  residing in the  city and perhaps two upwind two coke plants.   If,  in fact, coke



  oven plants were the major source of ammonia, Pittsburgh could be a special case



  of a large amount of ammonia  in an urban area.  Further  characterization of acid



  aerosols and  ammonia in large  cities  and their neighboring cities is needed.



 This can be achieved by conducting year-long, every-other-day measurements with



 more intensive  sampling during episodes.   In  spite of  the  greater degree  of



 neutralization,  the Pittsburgh acid levels are  still high  enough to result in a



 health concern,  especially considering the  substantial population that nay  be




 exposed to  acid  aerosols in  large urban cities.








 DISCLAIMER



      The information in this document has been funded wholly or in part by the



United States Environmental Protection Agency under EPA Cooperative agreement CR



816740  to Harvard School of  Public Health.   It has been subjected to Agency



review  and  approved for publication.   Mention of trade  names  or commercial



products does not constitute endorsement or recommendation for use.
                                     1057

-------
                                  REFERENCES


(1)   P.J. Lioy and J.M. Waldman, Environ. Health Parspect. 79: 15-34 (1989).

(2)   H.H. Suh,  J.D.  Spengler, P. Koutrakia, submitted to Enyjlron.  Scl. & Tech^.
      April (1992).

(3)   Ministry of Health,  "Mortality and morbidity during London Fog." December
      1952.  Reports  on public health and medical subjects.  No. 95, Her Majesty's
      Stationary Office, London, 1954.
(4)   H. Ozkaynak and J.D. Spengler, Environ. Health Perspest^ 63: 45-55 (1985).

(5)   R.F. Wolfe, Environ. Health PerapecJ^ 66: 223-237 (1986).

(6)   M. Lippmann, Environ. Health Peraoeet. 79: 3-6 (1989).

(7)   R.B. Schleslnger, L.C. Chen, I. Flnkelsteln, and J.T. Zelikoff, Jfrwlron^
      Res. 52: 210-224 (1990).

(8)   P.J. Lioy, P.J. Samson,  R.L.  Tanner, B.P.  Leaderer, T. Mlnnlch, W. Lyons,
      Atmoa. Environ. 14: 1391-1407 (1980).

(9)   R.L. Tanner, R. Carber, W. Marlow, B.P.  Leaderer,  M.A.  Leyko, nmv  M.Y^
      Acad. Sei. 332: 99-114 (1979).

(10)  J.M. Waldman,  P.J. Lioy,  G.D.  Thurston, M.  Lippmann,  Atnoa.
      24B(1):115-126 (1990).
(11)  A. P. Altshuller, Environ. Set.  Technol.  14,  1337-1349 (1980).

(12)  V.R. Pierson, V.V. Brachaczek, T.J. Truex, J.V. Butler, T.J. Komiski, Ann
      N. Y. Acad.  Sel. 338:  145-173 (1987).

(13)  P. Koutrakis,  J.M. Volfson, J.L.  Slater,  M.  Brauer,  J.D.  Spengler,  R.K.
      Stevens,  C.L.  Stone,   Environ.  Sci. TechnoL 22:  1463-1468 (1988).

(14)  K. Thompson, P.  Koutrakis, M. Brauer, J.D. Spengler, V.E. Wilson, and R.M.
      Burton,   Proceeding of the 1991 U.S. EPA/A&WMA International Svmnosiutt PD
      Measurement  of Toxic  and Related. A^r pflMu^aqtB ." (1991).
(15)  P.  Koutrakis and B.  Aurian-Blajeni,  submitted to J.  Cepphys. Res.
      April 1992.

(16)  V.G.  Cobourn,  R.B. Husar,  Atnoa.  Environ.  16: 1441-1450 (1982).

(17)  A. P.  Waggoner,  R.E.  Weiss,  T.V. Larson,  Atnos. Environ.  17:  1723-1731
      (1983).
                                     1058

-------
(18)  J.D.  Spongier,  G.A.  Allen,  S.  Foster,  P.  Severance,  B.  Ferris,  Jr.,
      Proceedings of  the  ^nd annual  U.S.-Dutch International  Symposium  on
      Aerosols.  S.D.  Lee et al.,  Eds.;  Lewis Publishers:  Chelsea,  MI,  pp.  107-
      120 (1986).

(19)  tf.E,  Wilson, P.  Koutrakls, J.D.  Spengler,  In Proceedings  of the  1991
      U.S.EPA/A&WMA International Synroosi^™ on Measurement of Toxic and Related
      Air pollutants." (1991).
                                     1059

-------
Table I. Sampling schedule for Pittsburgh, Unlontown, and State Collage.
Site Name
Pittsburgh

Unlontown


State College


Sampling Tine
10am - 4pm
7: 30am - 7: 30am
10am - 4pm
7am-7pm; 7pm-7am
7: 30am - 7: 30am
10am - 4pm
7am- 7pm; 7pm- 7am
7: 30am - 7: 30am
Sampling Frequency
•very other day
•very other day
daily
twice per 24 hours
daily
every other day
twice per 24 hours
dally (for H* only)
Sampling Period
7/2/90 - 8/11/90
7/2/90 - 8/11/90
6/23/90 - 8/19/90
6/22/90 - 8/20/90
6/22/90 - 8/20/90
6/24/90 - 8/21/90
6/22/90 - 8/20/90
6/22/90 - 8/20/90
                                         1060

-------
Table II. Summary of the samples collected in Uniontown, Pittsburgh, and State College,
Soecies
H+
(nmol/m3)





so,2-
•1 ,_
(nmol/m3)




HVSCX2-
f ^




NH/
(nmol/m3)
v t /



NH,
3
(Ppb)
\rr f



Location & Duration
Uniontown 6-h
Uniontown 12-h
Uniontown 24-h
Pittsburgh 6-h
Pittsburgh 24-h
State College 6-h
State College 24-h
Uniontown 6-h
Uniontown 12-h
Uniontown 24-h
Pittsburgh 6-h
Pittsburgh 24-h
State College 6-h
Uniontown 6-h
Uniontown 12-h
Uniontown 24-h
Pittsburgh 6-h
Pittsburgh 24-h
State College 6-h
Uniontown 6-h
Uniontown 12-h
Uniontown 24-h
Pittsburgh 6-h
Pittsburgh 24-h
State College 6-h
Uniontown 6-h
Uniontown 12-h
Uniontown 24-h
Pittsburgh 6-h
Pittsburgh 24-h
State College 6-h 	
N
52
59
53
19
17
27
24
59
59
53
18
19
27
50
56
51
16
16
23
52
59
61
20
20
28
55
61
62
20
20
2?
Mean
173.3
148.6
118.5
81.2
48.8
120.1
85.8
151.2
149.0
148.5
123.1
121.2
118.6
0.97
0.89
0.72
0.59
0.35
0.84
157.9
138.6
159.4
147.0
212.9
146.2
0.50
0.45
0.49
1.88
1.64
0.73
SD
146.2
132.8
106.4
79.8
51.7
155.7
86.5
100.3
101.3
97.9
76.4
75.4
107.4
0.40
0.25
0.22
0.26
0.22
0.34
81.8
80.9
100.6
96.5
156.2
156.3
1.06
0.35
0.40
1.57
0.96
U3
Min
-53.5
4.4
14.2
0.5
-2.7
-7.5
7.4
0.0
0.0
29.4
0.0
8.4
0.0
-0.83
0.41
0.31
0.09
0.09
0.10
0.0
5.7
2.8
0.0
0.0
0.0
-0.83
-0.43
-0.42
-0.74
0.42
-Q.88
Max
628.0
676.5
511.0
307.5
148.6
725.3
340.8
422.1
467.5
456.6
281.1
259.6
484.9
1.52
1.46
1.27
1.09
0.78
1.50
347.1
333.3
458.2
317.1
665.0
797.1
5.21
1.32
1.93
6.73
4.21
3-66
Median
129.9
121.6
93.7
64.0
28.2
77.6
43.7
131.2
125.9
126.5
134.6
122.9
112.1
1.02
0.89
0.68
0.63
0.27
0.82
154.2
131.1
145.6
176.7
194.5
121 A
0.20
0.49
0.40
1.79
1.53
Q,61
      N - Number of samples
      Min - Minimum
SD - Standard Deviation
Max - Maximum
                                      1061

-------
AEROSOL ACIDITY CHARACTERIZATION OF LARGE METROPOLITAN AREAS:
PILOT AND PLANNING FOR PHILADELPHIA.
Jed M. Waldman   Robert Wood Johnson Medical School

Petros Koutrakis   Harvard School of Public Health

Robert Burton, William E. Wilson, Larry J. Purdue and Dale Pahl
     U.S. Environmental Protection Agency.
ABSTRACT

The majority of data on atmospheric levels of acidic particles has
been produced  in just  the  past  few years.   While it is now known
that acidic sulfate concentrations  (24-h) can be as high as 25 M9
m"3  in the  rural  and  suburban  regions  of  the eastern  U.S.  and
Canada, few measurements have been performed in urban centers.  In
order to determine the potential effects on the total population,
accurate exposure determinations are needed, especially where the
highest density of people occur.  In these populated areas, it is
hypothesized that acidic particle exposures  would be attenuated by
anthropogenic ammonia.

The U.S.  Environmental Protection Agency, Harvard School of Public
Health and  Robert  Wood  Johnson  Medical School have  developed a
multi-year program  to investigate the  specific  issues affecting
human exposures to  aerosol acidity.   The program —  called  the
Aerosol Acidity Characterization of Large  Metropolitan  Areas —
will include ambient measurements for a network of sites overlaying
a  metropolitan area,  indoor monitoring in homes,  offices  and
schools,  samplers for  roadway/vehicle  exposures,  plus studies of
aerosol neutralization potential in human microenvironments.

Philadelphia has been chosen as  the first city in the program.  It
is a  large metropolitan area in  the  heart of  the  northeastern
seaboard afflicted  with photochemical  regional  smog  during  the
summertime.  A pilot study  of  ambient concentrations was performed
in July 1991.   An annular denuder system (ADS) sampler was operated
for two  weeks  near downtown Philadelphia, with  a second  unit
operated in  central,  suburban New Jersey,  the same  location of
measurements in past  years.   The  Philadelphia site was  found to
have higher concentrations of most major aerosol species, ammonia
and acidic particles than in New Jersey.  Hence,  these early data
do not support speculation that aerosol neutralization within the
urban center will  necessarily totally  eliminate  acidic  particle
exposures.
                               1063

-------
OBJBCTIVB8

The Clean  Air  Scientific  Advisory Committee  of the  U.S.  EPA's
Science Advisory Board recommended that the requisite research be
reviewed  and/or conducted to  address  health  effects  directly
associated with acidic aerosol and the possibility of listing it as
a separate criteria pollutant (U.S. EPA, 1989).  The acid aerosol
research program of U.S.  EPA's  Atmospheric Research and Exposure
Assessment  Laboratory  (AREAL)  supports setting an air quality
standard  based  on human  exposure  levels  rather   than ambient
concentrations.  Following  U.S. EPA-sponsored projects to  establish
standard measurement  protocols, the  current  planning  calls  for
full-scale  urban  air characterization studies to document human
exposure levels.

The U.S. EPA/AREAL Aerosol Acidity  Characterization  Study is being
planned  with  the  following  objectivest   1)  to  ascertain  the
significance of acidic aerosol levels  in  major  metropolitan  areas;
2) to  characterize the acidic  aerosol  chemistry during episodic
events; 3)  to estimate human exposures to acidic aerosol within the
metropolitan  area;  and  4)   to assist  in  the ep idem io logical
investigations  of  acute  respiratory  illness  related  to »»og
components, notably ozone  and acidic aerosols.

BACKOROUWD

The assessment  of  acidic aerosol exposure has  increased  in  recent
years  due  to  a growing body of  evidence  of  its adverse  health
effects.   The database on ambient  concentrations has  shown that
outdoor  concentrations  in  the range  of  20  to  200   nmole  •
(equivalent to  1 to 10 ng m'5 HZS04)  a  for 24 h  period are commonly
monitored in regions in the northeastern U.S.  and Canada  (Lioy and
Waldman, 1989).  summertime levels  are markedly  higher than those
measured  during the  other months   (Thompson ejt  &!•).    Multi-day
stagnation periods can lead to widespread episodes impacting sites
100's  of kilometers apart  (Stevens  et al., 1980;  Thurston et al.<
1991).

Summertime  studies in the  northeastern U.S. have chiefly provided
data for small  cities and  suburban  sites.  The early measurements
in  metropolitan  New  York City  suggested  that acidic aerosol
concentrations  in urban  areas  were much  lower  (o
-------
 10 km of a central site have been shown to agree with small (<20%)
 bias (Thompson et al., 1991;  Liang and Waldman,  1993b).

 No indoor measurements  of acidic aerosol were available prior to
 1988, and  only a limited number  of studies have  addressed  this
 phenomenon since then.  The emerging data to date show a consistent
 pattern  for  acidic  particles;  like  ozone  (another  reactive
 pollutant produced  in  smog),  sharply lower levels  are  generally
 found indoors than outdoors (Li  and Harrison, 1990; Brauer et al.,
 1991; Liang and Waldman, 1993a;  Sun et al.,  1993).

 A number of other important factors are consistently observed.
 1)  Particle acidity is  singularly associated with sulfate aerosol.
 2)  The penetration of ambient sulfate aerosols to  the indoors  is
 generally high, often >70%.   Since these particles  are  in the 0.2
 to  1  micron  (aero,  dia.)   range  (Koutrakis   et  al.,   1989),
 depositional losses (both impaction and diffusion)  are relatively
 minimum.   3)  Indoor levels of ammonia are much higher than outdoor
 levels.   Humans (and pets)  are the  principal  cause  of high levels
 of ammonia  in  occupied  spaces;   breath  and  sweat  are  highly
 concentrated NH5 sources. 4)  The  use of ammonia-containing cleans-
 ers can also  contribute in some settings.   The contact  between
 infiltrated acidic sulfate aerosols and high ammonia levels indoors
 gives ample time for the neutralization reaction to occur.   Data
 from  indoor studies indicate  the reactions occur within 15 to  90
 min,  far longer than laboratory  data for pure components  suggest .
 (Huntzicker et al.,  1980).

 PHILADELPHIA AEROSOL ACIDITY CHARACTERIZATION STUDY

 The U.S. EPA,  Harvard School of  Public  Health  and Robert  Wood
 Johnson  Medical  School  have  developed  a  multi-year  program  to
 investigate the specific issues affecting human  exposures.  The
 program,  called  the Aerosol  Acidity Characterization  of Large
 Metropolitan Areas, will include  ambient measurements for a network
 of sites overlaying metropolitan  areas, indoor monitoring  in homes,
 offices  and schools,  samplers  for roadway/vehicle exposures,  plus
 studies of aerosol neutralization potential in human microenviron-
 ments.  The question motivating the research is the following:  Are
 acidic  aerosol  exposures in  large urban areas  high—enough  to
 Justify expanded  study  of human  exposure, governmental regulation
 and/or strategies to protect public health?   Philadelphia has  been
 chosen  as  the  first  city  in  the  program.    It  is  a large
 metropolitan  area  in  the  heart  of  the  northeastern  seaboard
 afflicted with photochemical regional smog during the summertime.

 Pilot Study.   In August  1991,  we conducted a two-week field study
 of acidic aerosol measurements  in Philadelphia. An annular  denuder
 system  (ADS)  sampler was located very  close  to  downtown  (Drexel
University campus).  Simultaneous measurements were made at a New
Jersey site «100 km north. Data  from  other New Jersey sites close
to Philadelphia were are also available for previous summers (Liang
and Waldman,  1993b) .  Comparison of  results for the  1991 pilot
period and  summer  1989  data are  given in Figure  1.   For the  same
                               1065

-------
period,  the   Philadelphia  site   was  found   to  have  higher
concentrations of  roost major aerosol  species,  acidic particles,
sulfur dioxide and ammonia than in New Jersey.  The concentrations
of aerosol sulfate and acidity measured at  both sites are below
levels reported for cities closer to the Ohio River valley,  such as
Pittsburgh (Burton et al.,  1992) or Toronto (Waldman et al., 1990).
However, concentrations  at all urban sites were  high- enough  to
counter speculation that aerosol neutralization within an urban
center will reduce acidic particle exposures.	
     toe
       ACIDIC AND SULFATE AEROSOL

       nM/m3
SULFUR DIOXIDE AND AMMONIA
     MO
p/





V91





NJ91




II
NJ89
i










S02(ppb>
NH3 (ppb)
                                    PA91
         NJ91
  NJ89
                                       If
                                            :
                                                          to
                                                          IX
       H+ 804*   H+ 804"   H+ 8O4*
8O2 NH3  802 NH3  8O2 NH3
Figure 1.     Aerosol   and  gaseous   concentration   data   for
Philadelphia and New Jersey sites for 2 weeks in 1991, plus data
for New Jersey in 1989  (6 weeks).  The 75 to 25% ranges with the
mean  (x) are shown.
Characterization  Study.   The  study  in Philadelphia will  include
yearlong measurements of atmospheric components at several suburban
and  one center city site.   For an  intensive monitoring  period
including the  summer months (June to August), daily measurements
will  be made  at  up  to eight  outdoor sampling  sites.   Annular
denuder technology will be employed to measure aerosol  acidity and
other components.  The sites will be chosen to maximize the benefit
of the prevalent wind in establishing both background and downwind
areas  relative to  the City  of Philadelphia  to the  predominant
upwind  and  downwind areas.   At  one  site   (Northeast  Airport),
additional  measurements will be made,  including  particle sizing,
visibility,  organic  acids,   elemental  carbon,   and   continuous
H2S04/S04' (thermal speciation).
                                1066

-------
                QROX
                                Camden
                                        SITES
                                        VAL-Valley Forge
                                        ROX-Roxborough
                                        N/E-Northeast Airport
                                        LAB-City Air Mgmt Lab
                                        TEM-Temple Univ.
                                        FRI-Franklin  Inst.
                                        600-So.Broad St,
                                         PBY-Presbyterlan Hosp
                                         CYC-Camden Youth  Ctr
                                         CAL-Camden Air Lab
Figure 2.  Philadelphia area site locations proposed for ]   > program
Another  focus  of the  Philadelphia 1992  program is  the direct
monitoring of human exposures at indoor institutional environments,
such as schools,  offices and other public buildings.  ADS  samplers
will also  be  used  to make  measurements  of  particle  acidity
sulfate, gaseous ammonia, sulfur dioxide, nitric and nitrous acids.
Simultaneous measurements  of outdoor concentrations  wil  be made
                               1067

-------
for matched analyses with indoor data.  Infiltration rates will be
monitored  using  a  perfluorocarbon  tracer  (PFT)  technique.
Infiltration of acidic sulfate particles, plus the neutralization
by indoor ammonia will be determined with this schedule of daily
monitoring  (12-h day and nighttime periods).   Surveys of indoor
ammonia and  ozone  levels, both  in  institutional  and residential
settings, will be performed.  Exploratory measurements of organic
acids will be conducted indoors and outdoors.

The potential for human exposures in work, school and residential
environments will  be determined using these data and  models of
acidic aerosol  neutralization and  human time use  and activity.
Datasets of  daily  acidic particle  and peak ozone concentrations
will be  collected  for the  "high11  season  (June to  September) to
serve  as  an  exposure database  in  a  retrospective analysis of
adverse human respiratory health effects  in metropolitan Philadel-
phia .
                               1068

-------
Disclaimer

The information in this document has been funded wholly or in part
by the  United States  Environmental  Protection Agency  under EPA
Cooperative Agreement 816740 with Harvard School of Public Health
and EPA Cooperative Agreement  with  Robert Wood  Johnson Medical
School.    It  has  been  subjected  to  the  Agency's  peer  and
administrative review,  and it has been approved for publication as
an EPA  document.   Mention of trade names  or  commercial products
does not constitute endorsement or recommendation for use.
                               1069

-------
REFERENCES

Brauer M, Koutrakis P, Keeler GJ and Spengler JD, 1991.  Indoor and
      outdoor concentrations of acidic aerosols  and gases.  J. Air
      Waste  Manage.  Assoc.  41; 171-181.
Burton KM,  Wilson WE, Koutrakis P and Liu S,  1992.  A pilot study
      for comparison of aerosol acidity in urban  (metropolitan) and
      semi-rural environments.  Presented at Measurement of Toxic
      and Related Air  Pollutants. Durham, NC,  May 1992.
Huntzicker  JJ,   Gary  RA and  Ling  CS,  1980.    Neutralization of
      sulfuric acid  aerosol by ammonia.   Enyj.ronT Sci.  Technol. 14;
      819-824.
Keeler GJ,  Spengler JO,  Koutrakis P, Allen GA,  Raizenne M and Stern
      B,  1990.   Transported  acid  aerosols measured  in southern
      Ontario.   Atmos. Environ. 24A: 2935-2950.
Kopstein, J., Wong, O.M. "The Orgin and  Fate of  Salivary, Urea and
      Ammonia in Man".   Clin.  Sci. Mol.  Med.,  Vol 52,  9-47, 1977.
Koutrakis P,  Wolfson JM,  Spengler  JD,  Stern B and Franklin CA,
      1989.   Equilibrium size  of atmospheric aerosol sulfates as a
      function of the relative humidity.  J. geophys. Res.  94D; 6442-
      6448.
Li Y and Harrison RM,  1990.  Comparison of indoor and outdoor  con-
      centrations of acid gases, ammonia and their associated salts.
      Environ. Tech. 11;  315-326.
Liang CSK   and  Waldman JM,  1993a.    Indoor exposures  to  acidic
      aerosol at child and elderly care  facilities.  Indoor Air (in
      press).
Liang  CSK   and   Waldman  JM,  I993b.    Estimating  acidic aerosol
      exposures  on a regional  scale Atmos. Environ,  (submitted).
Lioy  PJ  and Waldman JM, 1989.  Acidic  sulfate  aerosols: Charac-
      terization and exposure. Environ. Health Per spectjlyes 79; 15-
      34.
Stevens RK,  Dzubay  TG,  Shaw RW, McClenny WA,  Lewis CW and Wilson
      WE, 1980.   Characterization of the  aerosol  in the Great Smoky
      Mountains.  Environ.  Sci. Technol.  14: 1491-1498.
Suh HH,  Spengler SJ and Koutrakis P, 1993.   Personal  exposures to
      aid aerosols and ammonia. Environ.  Sci. Technol.  (submitted).
Tanner RL,  Leaderer BP and Spengler JD, 1981.   Acidity of atmo-
      spheric aerosols:  A summary of data concerning their chemical
      nature and  amounts of acid.  Environ. Sci.  Technol.  15; 1150-
      1153.
Thompson KM,  Koutrakis P,   Brauer M,  Spengler  JD,  Wilson  WE and
      Burton RM,  1991.   Measurements of  aerosol  acidity: Sampling
      frequency,  seasonal   variability   and  spatial  variation.
      Presented  at  Air  &  Waste  Management Association Meeting.
      Vancouver  BC.
Thurston GD,  Gorczynski J,  Jaques  P,   Currie J and  He  D,  1991.
      Daily  acid  aerosol  monitoring  the  three  New  York  State
      metropolitan   areas:    Sampling   techniques   and  results.
      Presented  at  Air  &  Waste  Management Association Meeting.
      Vancouver  BC,  June  1992.
U.S Environmental Protection Agency, 1989.  An Acid Aerosols Issue
      Paper;  Health Effects  and  Aerometrics.    Report EPA/600/8-
                               1070

-------
     88/005F,  Office  of  Health  and Environmental  Assessment,
     Washington  DC.
Waldman JM,  Liang  CSK,  Stevens RK,  Vossler T,  Baugh J and Wilson
     WE,  1991.   Summertime patterns  of atmospheric  acidity in
     metropolitan  Atlanta.   Presented at Air  & Waste Management
     Association Meej; jypg, Vancouver BC.
Waldman JM, Lioy PJ,  Thurston GD and Lippmann M,  1990.  Spatial and
     temporal  patterns  in summertime sulfate aerosol acidity and
     neutralization  within  a  metropolitan area.  Atmos. Environ.
     24B:  115-126.
                               1071

-------
                                    Subject Index
 accuracy assessment, 463
 acetaldehyde, 725
 acetic acid, 295
 acetone, 725
 Acid Aerosols and Related Pollutants, 170,
       257,379
 acid deposition, 129,141
 acid pollutants and automotive finishes, 135
 acid precipitation, 123,271,559
 acidity, 282
 active nitrogen, 750
 adsorption, 45,51,857
 aerosol strong acidity, 170,379
 aerosols, 559,1044
 airborne lidar, 628
 airborne paniculate monitoring, 730
 airborne remote sensing, 628
 airborne VOCs, 176
 air cleaners, 77
 air contaminants, 407
 air monitoring filters, 1035
 air pollutants, 675,895
 air sampling, 153,244,282,401
 air toxics, 244,506,532,607,933
 alternative analytical method, 481
 aluminum rolling mill emissions, 228
Ambient Air Measurements, 395,401,454,
       499,506,539,734,803,905,927
 ambient air monitoring, 373,407,445,
       915,933
ambient concentrations and LIDAR, 641
Ambient Monitoring Technology Information
   Center (AMTIQ, 811
amines, 506
ammonia, 264,827
ammonium sulfate, 264,770
analytical methods and QC, 499
analytical performance, 282
analytical systems, 65
anions, 827
annular denuder systems, 165,288,295,827
anodizers, emissions standard, 209
AREAL Acid Aerosol Research Program, 259
argon ionization detector, 762
arsenic, 1029
atmospheric acidity, 321,379
Atmospheric Chemistry, 551
atmospheric corrosion, HI, 117
atmospheric deposition, 516,681
Atmospheric Oxidation Program (AOP), 565
audits, 469,516
automated gas chromatography system, 427
automobile fluff, 1004
automotive finishes, 135,141

                   B
backflush method and GC, 427
background spectra, 582
benzene, 39,413,445,669,915,968,
       981,1016
benzo(a)pyrene, 915
biogenic emissions, 571
biomarker studies, 188,981
biorcmediation, 615,1016
biosensors, 730
breast milk and PQB exposure, 975
bronze, corrosion of, 123
building wake effects, 663
burning of pesticide bags, 481
cadmium, 1029
calcium, 129,386,475
canisters, 527,607
capillary SFC, 433
CARS Methods 429 and 436,203
carbon monoxide, 488,968
                                        1072

-------
 carbonyl compounds, 361,725
 catalytic flame ionization detector
    (CFID),236
 cement plant plume analysis, 770
 CFCs,469
 chemical microsensors, 647
 chemiluminescence, 745,750
 Chemometrics, 95
 chlorinated benzenes, 506
 chlorinated dioxins and furans, 694
 chlorinated hydrocarbons, 762
 chlorinated organic compounds, 197
 chlorofluorocarbons, 469
 chromium, 1029
 cleaning solvents, industrial, 895
 cleaning Summa canisters, 527
 cloud chemistry model (CCM), 559
 coarse particles, 386
 coatings, interior architectural, 71
 coke and coke by-product emissions, 915
 cold trap freezing, 532
 combustion exhaust gases, 1004
 communication and QA, 520
 composites, 779
 compressed gas standards, 463
 computer programs, 103,565
 concentrators, 65
 constant-condition meteorological data, 675
 contaminant dispersion, 669
 continuous emissions monitoring, 214,454
 continuous sulfate/thermal speciation
    (CSTS) monitor, 288
 conversion factors, 663
 copper, 111
 correlation chromatography, 445
corrosion, 111, 123
cresols, 719
 CSTS monitor, 288
"Cylinder Audit No. 8," 463
cylinder mixture stability, 545
                    D
 Dasibi 1008,745
 Data Analysis, 95,488,805,815,821,915
 databases, 103
 data quality, 475
 data validation, 499
 delta ozone analysis, 97
 deposition, 111, 117,123
    and acid fog, 271
    and marble deterioration, 153
    of mercury in the Great Lakes Basin, 367
    modeling, 694
 dermal exposure, 981
 desorption, 45
 detectors used in GC, 762
 DIAL (differential absorption lidar), 628
 dichloromethane (DCM), 832
 dioxin/furan emission profile, 940
 dioxins, 214,694,905,927
 directory of sampling and analysis
    methods, 103
 Dispersion Modeling, 182,661
 diurnal variation, 288,553
 DNPH impinger method, 725
 DOAS (differential optical absorption
    spectrometer) system, 654
 dose impact, 77,981
 dry deposition, 111, 386,516
 dust, 785,791,796
 dynamic sink model, 45

                   E
 BCD (electron capture detectors), 407
 ecological resources, baseline of, 957
 effective plates and fast GC, 407
Effects of Pollution on Materials, 109
electroplaters, emission standard, 209
ELISAs.730
emissions monitoring, 214,454
emissions quantification, 895
                                        1073

-------
 emissions, types of
    biogenic, 571
    hazardous and medical waste, 57,987
    industrial, 209,228,915
    motor vehicle, 883
    organic vapor, 45,71
    toxic metal, 1029
 environmental impact assessment, 989
 environmental management, 895
 Environmental Monitoring and Assessment
    Program (EMAP), 957
 EosinY,745
 EPA Air Program, 516
 EPA Methods
    Method 25 and 25A, 228
    Method 54 modification, 864
    Method 306-A, 209
    Method 610,998
    Method TO-l.TO-2,539
    Method TO-1, TO-2, TO-3, TO-14,499
    Method TO-8,719
    Method TO-14,25,734,889
 EPA protocol gases, 463
 estimation methods, 565,601,687,700
ethane, 762
ethers, 506
ethylbenzene, 45,51
ethylene monitoring, 745,877
experimental error variance, 475
Exposure Assessment, 39,57,77,565,
       694,955
extraction, 282
extractive FITR, 57

                   F
fastGC.407
Fate of Atmospheric Pollutants (PAP)
    Program, 565
Federal Reference Method for lead, 779
Pick's Law of Diffusion, 71
 field portable instrumentation, 445,756,1035
 field procedures, 176,203,494
 fill soil, 83
 filters, 779,1035
 flame ionization detector (FED), 407
 flow-through chamber design, 45
 fluff, 1004
 fluorescence detector, 998
 flux, 386,911
 forest fires, 927
 formaldehyde, 454,725,968
 formic acid, 295
 FPGC (field portable gas chromatograph), 445
 FTIR spectroscopy, 57,579,595,615
 fugitive emissions, 445,615,641
 furans, 214,694,905
gas chromatography (GC), 407,413,445
    -AED (atomic emission detector), 395
    -EDO (electron capture detector), 427
    -FID, 228,419
    -MSD (mass selective detection), 419
GC-MS,19,481,499,506
    GC-Ion trap MS system, 734
gas exchange, 911
gas phase ammonia, 333
gas phase nitric acid, 333
geographical distribution of toxic metal
    emissions, 1029
Great Lakes, 367,911
ground water, 39

                   H
halocarbons, 401
haloethanes, 762
halogenated hydrocarbons, 762
halomethanes, 762
hazardous materials, 730,1035
Hazardous Waste Emissions, 987
                                       1074

-------
 HCFC-22,469
 HEADS (Harvard/EPA annual denuder
    sampler) data, 288
 health assessment, 3,321
 hexachlorocyclohexane, 911
 hexavalent chromium emissions, 209
 high pressure liquid chromatography, 998
 high resolution mass spectrometry, 905
 high-speed GC, 407
 HPLC analysis, 719
 human exposure and the sink effect, 51
 HVAC systems, 333
 hydrocarbons, 228,419,805,857
 hydrogen peroxide concentrations, 553
 hydrogen sulfide, 3
 hydroxyl radicals, 565
immuno-based methods, 730
impact assessment, 3,933
incinerators, 57,933,998
index pollutants, 321
Indoor Air Measurements, 19,37,182,
       333,344,454,669
industrial cleanup solvents, 895
information management, 811
infrared DIAL, 641
inhalation dose, 981
inlets sampling, 1044
in-situ emissions monitoring, 214
in-stack/in-plume sampling, 770
integral methods, 264
integrated systems, 419,734
interactive air transport model, 700
intercompaiison of methods, 607
interlaboratory precision, 282
inventory, 1029
isopentane, 805
isoprene emissions from willow oak trees, 571
iterative IQ technique, 582
 Kodak Park Ambient Air Monitoring
    Network, 832
 Kuwaiti Oil Fires, 3
 laboratory procedures, 176
 Lake Michigan, 681
 Lake Michigan Ozone Study, 361,628
 Lake Michigan Urban Air Toxics Study, 353
 laser-induced fluorescence (LIF), 214
 Lead in the Environment, 386,681,777,1029
 library air quality, 333
 lidar system, 641
 low-level monitoring, 762
 LOZ performance, 745
 luminol, 750

                   M
 MAID (micro argon ionization detector), 762
 management tools, 520
 marble deterioration/weathering, 153
 Massachusetts 1991NMOC Monitoring
   Program, 844
 mass balance models, 669
 mass spectrometry, 838
 mass transfer models, 71
 material balance, 895
 materials screening, 45
 MAXOZ (daily maximum ozone
   concentration distributions), 821
 measurement, 83
 measurement error variability, 475
 Measurement Methods Development, 711
 medical waste incinerator emissions, 57
 mercaptan detector, 756
 mercury, 367,989,1029
 metal aerosols, 1004
metals, 386,1029
metals damage, 111, 117,123
                                        1075

-------
meteorological variability and acid aerosol
   levels, 306
methane, 762
method detection limits (MDLs), 506
method evaluation, 539
methodology, 811
methods comparison, 282
methods development, 373,393
methods directory, 103
methylethyl ketone, 725
methylphenols, 719
microbial VOCs, 19
microchip FPGC, 445
micro-climate measurements, 153
microenvironments, 170,968'
microsuspension mutagenicity assay, 433
minimum detection limits and FUR, 595
mitigation systems for radon, 83
MMS (moisture management system), 25
mobile monitoring, 838
model development, 288,361,488,559
model identification, 647
models, 45,71,170,271,559,663,669,
       681,700
modified volatile organic sampling train
   (MVOST), 197
modular personal sampler, 188
moisture management, 25,889
monuments, corrosion of, 123
motor vehicle emissions, 883
muconic acid, 981
multicomponent gaseous VOC standards, 545
multisorbent traps, 65
multizonal models, 669
municipal waste incinerators, 933,940

                    N
nation dryers, 532
National Dry Deposition Network (NDDN),
       312,516
natural gas odorants, 756
n-butane, 805
NIOSH Method 7300,1035
nitric acid, 312,379
nitro benzenes, 506
nitrogen oxides, 333,361,488
nitrous acid, 344
nitrous oxide, 427
NMOC data, 805,815,821
NMOC Monitoring Program in
   Massachusetts, 844
NO, 463,654
NO2,654,750
non-cryogenic concentration of
   hydrocarbons, 857
NOx,750,821
NOy,750

                   O
observation-based analysis, 97,488
odd nitrogen, 750
odorant analysis, 756
oil, 228
oil fires in Kuwait, 3
on-line monitoring, 427
on-site analysis, 445,756
open path ambient measurements, 654
open-path FUR, 582,595,601,607
optical sensing techniques, 214
organic compounds, 65,565
organic vapors, 45,407,968
oxidation technique, 228
ozone, 97,361,488,654,745,821,844
   chemistry, 628
   field studies, 628
   and hydrogen peroxide, 553
   and isoprene emissions, 571
   in library air, 333
   measurement, 628,962
   monitors, 165,745
                                    1076

-------
    and NMOC data, 815
    and organic compounds, 565
    precursors, 401
    scrubber, 750
PAHs, 31,214,373,506,915,927,998
paint, 71,129,147
parameter estimation, 647
partial vapor pressure, 264
particle mass, 386
particle size distribution, 386
particulates,3, 111,333,915,1004,1035
passive methods, 264
passive samplers, 165,176,962
path-integrated concentration, 601
PCBs.506,870
PCDD/PCDF, 905,933,940,1004
PCE (perchloroethane) in breast milk, 975
PCFAP, 565
pentachlorophenol (PGP), 838
perchlorination of PCBs, 870
performance assessment, 745,827
performance evaluation audit (PEA)
    samples, 469,506
Persian Gulf, 3
personal computer programs, 103,565,700
personal exposure models, 170
Personal Samplers, 163
pesticides, 481,506,730,864
phase distribution of PAHs, 31
phenols, 506,719
phthalates, 506
physical modeling, 687
physiologically-based pharmacokinetic
    (PBPK) modeling, 975
pitch, 1044
PM10,3,915
point measurements (Federal Reference
    Method), 654
Polar Volatile Organics, 17,395
pollution prevention, 895
polychlorobiphenyls (PCBs), 506,870
polyurethane foam (PUP), 506
porosity and removal efficiencies, 475
portable instrumentation, 413,445,745,762
precipitation runoff, 111
pre-concentration, 734
propanol, 725
protocol development, 989
public health, 3
PUP (polyurethane foam), 506
PVC resin, 713
Quality Assurance, 282,373,461,545,
       796,811
                   R
radon, 77,83
RCRA compounds, directory of, 103
real-time analysis, 838
recovery, 506,532,539
refrigerants, 469
RELMAP (Regional Lagrangian Model of
   Air Pollution), 681
Remote Sensing FTIR Open Path
   Techniques, 577
removal efficiencies, 475
reproducibility, 539
residential coatings and acid deposition, 129
residential dwellings and airborne VOCs, 176
resolution and fast GC, 407
resource recovery facility (RRF), 940,989
Risk Assessment, 3,955
rocket engine tests, 244
round-robin study, 905
runoff measurements, 111, 117,123
                                        1077

-------
sample absorption spectra, 582
sample integration, 419
sampling, 31.57,176,373,481
Saudi Arabia, 3
screening, 197,663,675,700
seasonal variability, 83,306,312
selenium, 1029
semi-continuous strong aerosol acidity, 288
semivolatile compounds, 506
semivolatile hydrocarbons (C12-C18), 883
Semivolatile Organic Measurements, 615,
       905,1004,1016
SF6,669,706
showering with contaminated water, 39,669
signal processing, 647
signal-to-noise ratio, 595
simulated open burning,  1004
sink effect, 45,51
sludge, 615,1016
smoking lounge air quality, 89
solid phase extraction, 725
solvents, 895,975
sorbent-based preconcentrators, 395
sorbent tube analysis, 532
source characterization, 244
Source Monitoring, 195
source type analysis, 1029
spatial variability, 312,321
speciated hydrocarbons, 488
spectral noise, 595
SS Canister Cleaning and Techniques, 525
stability, 506,545
stack gas, 214,770
standardization of FUR open path
   techniques, 579
stationary  sources, 197,203,236,494
Stationary Source Sampling and Analysis
   Directory, 103
steel, 111, 117
 sub-slab housing construction, 83
 sulfate(s), 170,288,306,312,321,379,915
 sulfur dioxide, 3, 111, 147,153,165,312,
       333,463,475,654
 sulfuric acid, 264
 sulfide detector, 756
 Sutnma canister analysis, 532
 supercritical fluid chromatography (SFC), 433
 Superfund site, 601,700
 surface acoustic wave devices, 647
temporal variability, 321
tetrachloroethane, 975
thcrmogravimctric analysis (TGA), 864
thin film, 1035
time-course study, 981
tobacco smoke, 89,433
toluene, 182,413,445,805
total nonmethane volatile organic carbon
    emissions, 236
total strong aerosol acidity, 288
toxic air pollutants, 968
toxic chemicals and dispersion modeling, 687
toxic metals, 681,1029
traccability protocol, 463
trace elements, 915
trace metals, 827
trends in air quality, 97,811,815
TSCREEN, 700
two-chamber system, 45

                    U
urban airshed model, 271
urban ozone, 488,628
UV absorption, 214
vacuum box air sampler, 445
vacuum dust collection, 785
                                         1078

-------
 validation, 981
 vapor-phase organics, 71
 ventilation in smoking lounges, 89
 vinyl chloride, 713
 VOC emissions, 19,228,601,1016
 VOC Methods Development, 393
 VOC Monitoring Techniques, 601,607,
       641,555
 VOCs, 3,361,539,615,734,895,915,927,
       1004
 VOP (volatile organics in pesticides), 864
 VOST samples, 481

                   W
 wallboard, gypsum, 45
 water and air toxics analysis, 532
 wet deposition, 111,516
 whole air sampling, 25,607,889
 willow oak trees and isoprene emissions, 571
 wind tunnels, 687,1044
 wipe test, 791,1035

                  XYZ
 XAD-2,506
 X-Ray fluorescence (XRF), 796,1035
 yaw, 1044
 zinc, 111
Note: Italics indicates session titles and page numbers.
                  1079

-------
                                   Author Index
Adams, Andrea A., 97
Adgate, J., 791
Agarwal, P., 706
Allen, George, 288
Almasi, Elizabeth B., 734
Aneja.VineyP.,97,553
Aurian-Blajeni, B., 264

                   B
Balik, C. M., 147
Ball, Gerald, 532
Bauer, Karin M., 785
Baughman,KimW,,103
Baugues, Keith, 805,815
Bechtold, William E., 981
Benjey, William G., 1029
Berkley, Richard E., 407,413
Bernick, Mark B., 1035
Berry, J. C., 895
Berry, Peter P., 1035
Bidleman, Terry P., 911
Blaze, Stephen, 445
Boehnke, Cheryl A., 516
Booth, Gary M., 433
Bowne, Norman E., 361
Boyer, Dawn M., 796
Boyes, Brad L,, 244
Bratton, Steven A., 719
Brauer, M., 344
Breen, Joseph J., 785
Broadway, G., 401
Brook, J. R., 306
Brooks, Lance, 188,998
Brymer, David A., 25,527,889
Buckley, Timothy J., 39,981
Burns, D., 791
Burton, R. W., 264
Burton, Robert M., 962
Butler, James P., 989
Butler, William A., 615,1016
Callahan, Patrick J., 31
Campagna, Philip R., 1035
Cardelino, Carlos A., 488
Cardin, Daniel B., 419
Carr, Lewis, 641
Carter, Ray E., Jr., 601,607
Castronovo, Cynthia, 203
Chameides, William L., 488
Chang, J. C., 413
Chang, John C. S., 51
Chen, Hsiu-Wen, 989
Chiu,C.H.,713,905
Chuang, Jane C., 31,373,927
dark, Terry L., 681
Gay, Frank, 209
dement, R. E., 905
Colome, Steven D., 968
Conner, Charles P., 654
Conner, J. M., 89
Constant, Paul C, 785
Coppedge, Easter A., 463
Corcoran, Jon,  1035
Gotham, William E., 911
Coventry, Dale H., 1029
Cover, Lee W., 770
Cramer, Stephen D., 111
Crowley, C, 870

                   D
Dann,T.,905,933
Das, Mita, 553
Daughtrey, E. Hunter, Jr., 395
Davis, Claude S., 182
Davis, Dave B., 373
                                 1080

-------
 Dayton, Dave-Paul, 214
 De Brou, Gary B., 838
 DeFclice,T.P.,559
 DeMarini, David M., 998
 Dolske, Donald A., 153
 Dombro, R., 870
 Dorsey, James A., 65
 Dowdall, E., 713
 Downs, Jerry L., 244
 Draves, Jeffrey A., 214
 Drummond, John W., 750
 Eatough, Delbert J., 333,433
 Edgcxton, Eric S., 312
 Edwards, H., 870
 Edwards, Larry, 770
 Elkins, Joseph Burns, Jr., 811
 Ellenson, William, 165
 Ellestad, T. G., 282
 Evans, Gary P., 355,373,379
 Evans, Joseph D.,  481
Fang, G. C, 386
Fanner, Charles T., 419
Fellin, Philip, 176
Fillo,JohnP.,915
Fletcher, Leland, 641
Fomes, Raymond E., 129,135,141
Fortune, Christopher R., 413,454
Foster, Samuel C., H, 236
Francis, Eric S., 433
Fung, Kochy K,, 725,883,968

                   G
Gajjar, Raj, 545
Garner, J. H. B., 957
Gay, Bruce W., Jr., 571,654
Gebhart, Judith E., 506
 Gilbert, Richard D., 129,135,141
 Greenberg, Arthur, 989
 Guest, Steven A., 539
 Gulati, Amita, 706
 Gunn, Kevin N., 51
 Guo,Zhishi,45,51,71

                   H
 Halsell, Darrel, 481
 Hangal,SuniU044
 Harkov, Ronald, 915
 Harmon, Dale L,, 469
 Harper, S. L., 779
 Harrington, Dwayne, 445
 Hawkins, John, 481
 Hayden, K., 306
 Hege, R. B., 89
 Held, Joann, 989
 Hendricks, Donna M., 832
 Herget, William F., 57
 Hicks, Jeffrey B., 57
 Highsmith, V.Ross, 39,981
 Hodson, L. L., 282
 Hoffman, Alan J., 355,367
 Holsen, Thomas M., 386
 Hopke,P.K.,77
 Howard, Philip H., 565
 Hoyer, Marion, 367
 Hudson, Jody L., 601,607
 Hunt, William F., Jr., 3
 Hurley,!, 870
 Hyatt, D. Eric, 957

                  W
 Irwin, John S., 669
 Isaacs, Robert, 532
 Isil, Selma S., 516
 Jackson, Merrill D., 103,236,494
 James, Ruby H.,  103
Jayanty, R. K. M., 197,463,864
                                   1081

-------
Johnson, Larry D., 103
Johnson, R. Mark, 39
Jones, Christopher J., 25,889
Kaolin, Lawrence P., 445
Kagann, Robert R, 582,615
Karches, William E., 654
Karellas, Nicholas S., 838
Karns, Shawn A., 427
Katz, Steven, 117
Ke, Huiqiong, 407
Kebbekus, Earle R., 545
Keeler, Gerald J., 367,373,379
Kelly, Thomas J., 31,454 '
Kirshen, Norman A., 734
Knoll, Joseph E., 236
Koutrakis, Petros,  165,170,264,
    282,288,295,962
Koval, Paul, 927
Krebs, Kenneth A., 45,51,65
Kricks, Robert J., 582,595
Krivanek, Steven,  989
Kronmiller, Keith, 165
Kuhlman, Michael, 373
Kulkami, Shrikant V,, 469
Kumar, Selva, 706
Kyriakopoulos, Nicholas, 647
Lamborg, Carl, 367,379
Lands, Barry E., 527
Lane, Dennis D., 282,601,607
Lansari, Azzedine, 669
Lawrence, J. E., 295
Lee, Milton L., 433
Lec,W.J.,386
Lemieux, Paul M., 998,1004
Lentz, Catherine Dunwoody, 203
Leonelli, Joseph, 641
Levaggi, Dario A., 857
Levine, Steven P., 407
Lewis, Edwin A., 333,433
Lewis, Laura, 333
Lewis, Robert Q., 31
Lewtas, Joellen,  188
Lim, Benjamin S., 785
Lin', J. M., 386
Lin,N.-H.,559
Lindner, Gloria,  203
Lindstrom, Andrew B., 39,669,981
Linenberg, A., 762
Lioy, P., 791
Lipfert, Frederick W., 117,271,321
Little, Scott R., 1035
Liu, Lee-Jane Sally, 962
Livingston, John M., 628
Logan, Thomas J., 214,463
Loseke, W. A., 779
Lundberg, Constance K., 333
Lutes, Christopher C., 1004

                   M
McAlister, Gary D., 864
McAllister, Robert A., 821
McAndrew, James J. P., 545
McCallum, B., 77
McCauley, Carl  L., 582
Mcdenny, William A., 395
McConnell, Laura L., 911
McDonald, L. Garner, 111
McGaughey, James P., 236
McGrath, Thomas R., 844

Mackay, Gervase L, 745,750
MacPherson, Angus, 203
Manos, Charles G., Jr., 516
Marotz, Glen A., 601,607
Marple, Virgil, 188
Martin, Barry E., 312
                                    1082

-------
 Mason, Mark A., 51,65
 Mauch, Steven C., 827
 Meakin, John D., 123
 Meares, Jason, 998
 Meeks, Sarah A., 571
 Melvold, Robert W., 244
 Merrill, Raymond O., 832
 Merrill, Raymond G., Jr., 236
 Messner, Michael J., 463
 Meylan, William M., 565
 Michael, Larry C., 39
 Midgett, M. Rodney, 236,463,494
 Miller, M., 413
 Miller, W.C., 129
 Milne, Peter J., 419
 Minnich, Timothy R., 595
 Mitchner, Robert C., 756
 Mongar, Kevin, 877
 Montassier, N., 77
 Moore, Scott A., 51
 Mulik, James D., 165,962
 Murdoch, Robert W., 463

                    N
 Nagler, Lewis H., 663
 Nahas,PatA.,25,889
 Nelson, P. R., 89
 Ng, Andy C, 838
 Nielsen, Norman B., 628
 Nigam, S., 706
 Noll, Kenneth E., 386

                   O
 O'Hara, Phyllis L,, 821
 Ogle, Larry D., 25,527,870,889
Oldakcr, G. B., ffl, 89
Oliver, Karen D., 395,413
Olsakovsky, Adrianne C, 915
Otson, Rein, 176,182
Oyung, Walter, 857
 Pahl.DaleA.,259,355
 Pankas, Steven M., 506
 Panwar, T. S., 706
 Parmar, Sucha S., 228
 Parrish, Todd D., 433
 Pate, Brace A., 197
 Pate, William J., 39
 Patterson, Ronald K., 520
 Perdue, Larry, 488
 Pescatore, Douglas E,, 582,595
 Petersen, Ronald L., 687
 Peterson, Max R., 197,864
 Pierett, Stephen L., 244
 Piispanen, William, 927
 Pilkington, Matthew B. G., 694
 Piorek, Stanislaw, 1035
 Pleil, Joachim D., 19,31
 Powers, William, 228
 Prangcr, L. J., 779
 Pritchett, Thomas H., 532,595
 Pueyo, Maria, 445
 Purdue, Larry J., 259
Raizenne, M., 306
Randtke, S. J., 282
Rehme.K.A.,779
Reiss, Nathan M., 989
Riggle, Bruce, 730
Riggs, Karen, 927
Rivers, Joan C., 19
Roache, Nancy, 65
Robbins, John E., 821
Robinson, David S,, 762
Rosecrance, Ann, 499
Rungsimuntakul, Naraporn, 135
Russwurm, George M., 579
Ryan, J., 401
Ryan, Jeffrey V., 427,1004
                                   1083

-------
 Sager, T. W., 821
 Salman, D. I., 895
 Santanam, Suresh, 832
 Saxena, V. K., 559
 Schiff, Harold L, 745,750
 Schreiber, Judith S., 975
 Schwemberger, John, 785
 Scotto,  Robert L., 595
 Seeley,I.,401
 Serageldin, M. A., 895
 Serne, James C, 940
 Shaulis, Carl L., 527
 Shea, Tracey D., 864
 Sheldon, Linda S., 981
 Shepson, Paul B., 750
 Sherwood, Susan L, 123
 Shi, Y., 77
 Shores, Richard C, 463
 Short, Michael, 228
 Silverman, Randy H., 333
 Simendinger, W, H,, 147
 Simpson, E., 870
 Singh, M. P., 706
 Singhvi, Rajeshmal, 532
 Small, James R., 615
 Solecki, Michael, 445
 Soroka, Joseph M., 532
 Spafford, Ralph B., 103
 Speer, J. Alexander, 129,141
 Spence, JohnW., 117,129,135,141
 Spengler, John D., 170,306
 Steer, P., 905
 Stefanski, Leonard A., 475
 Stevens, Robert K., 188,654
 Straley,  Yvonne H., 864
Straub, Harold E., 89
Streicher, John, 675
Stroupe, Keven T., 700
Suggs, J. C., 779
 Suh, Helen H., 170,962
 Sullivan, Ralph J., 506
 Tardif, M., 713
 Tashiro, C., 905
 Templeman, Brian D., 669,675
 Thomas, Mark J., 601,607
 Thurston, G. D., 282
 Tian,Yi,968
 Tichenor, Bruce A., 71
 Tilton, Beverly E., 571
 Topham, Lesli A., 745
 Touma, Jawad S., 700
 Tyson, James L., 83

                  U-V
 Uthe, Edward E., 628
 ul Haq, Tanvir, 647
 Vallero, Daniel A., 957
 Yarns, Jerry L., 165
 Vincent, Harold A., 796

                   W
 Wainman, T., 791
 Waldman,J.M.,282
 Ward, Gerald F., 454
 Wasiolek.P.,77
 Wasson, Shirley J., 469
 Watts, Randall R., 998
 Weis, Peddrick, 989
 Weisel,C.,791
 Wellhausen, Nancy A., 244
 Whitaker, Craig O., 469
White, Douglas, 135,141
Whitmore, Roy, 176
Wiener, Russell W., 19
Willeke, Klaus, 1044
Williams, Anne Sensel, 539
Williams, Dennis, 165
                                   1084

-------
Williams, Nathan, 333
Williams, Ron, 188,998
Wilson, A. L., 968
Wilson, Nancy K., 373
Wilson, William E., 259,264
Winegar.EricD.,57,770
Wisner, Chester E., 687
Withers, Charles R., 83
Wojtenko, Izabela, 989
Wolfson, M. J., 165,264
Woolfenden, E., 401
Wynnyk, Renata, 445
Wyzga, Ronald E., 321

                  Y-Z
Yang, P., 791
Zapkin, Michael A., 832
Zemba, Stephen G., 694
Zerrudo, Rodolfo V., 857
Zhang, Chunshan, 135
Zielinska, Barbara, 883
Zika.RodO.,419
Zimmerman, Michael, 506
           1085

-------