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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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Q.
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0 60
Q.
ra
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0s-
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BOS
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;TON
i i
• i
•
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/
/
/
/
/
•T-
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s / ~
V . / -
T "
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V 72
V / ~
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Summer
Fall
Win
Spr
rn FIT i
ter
ing
fl '
HOU
STON
•
•
/
/
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/
/
/ -
jl
\ / -
s / ;
v / -
ii
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1 /
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\ /
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r ^
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-
IT ^
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u
-
L
-
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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-------
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
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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
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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
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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
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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
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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
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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
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- 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
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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
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Session 4
Chemometrics and Data Analysis
Donald R. Scott, Chairman
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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
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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
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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
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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).
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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
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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.
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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
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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).
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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.
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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.
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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.
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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.
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Session 5
Effects of Pollution on Materials
John Spence, Chairman
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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
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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*-
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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
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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
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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
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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
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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.
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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
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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
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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
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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
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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
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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
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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
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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.
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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
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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
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Films Exposed to UV and Pollutant-Viewed on and Dew for 94 Days. Areal EDS Scan.
Side Opposite of Exposure. Areal EDS Scan.
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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
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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
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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
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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
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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
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Horizontal Distance (Jim)
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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.
.
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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,
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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
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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
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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
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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
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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
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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
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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
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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.
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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
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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
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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.
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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
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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
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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
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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
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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.
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(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
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^ 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).
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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
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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
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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
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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
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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
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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
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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.
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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
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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
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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.
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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
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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
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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
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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
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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
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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
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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
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INLET IMPACTOR
ANNULAR DENUDER
ll I \ \ \l
FILTER PACK
RESIN CHAMBER HOSE BARB
Figure 1. Simplified schematic of EPAs1 minipersonal sampler.
193
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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
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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.
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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
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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
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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
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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
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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
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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.
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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
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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.
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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
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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
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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
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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
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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
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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
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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
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• 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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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'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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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.
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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
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00
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111
S 1.5 -\
cc
UJ
O
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UJ
00
_l
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O
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+
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
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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
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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
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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
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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
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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
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•
*;
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
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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
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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
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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
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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
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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
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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
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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.
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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
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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
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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
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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
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-
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
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!-
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
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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
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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
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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
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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
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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
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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
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.
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
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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
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ACKNOWLEDGMENTS
This research was supported by the Electric Power Research Institute, under RP
3253; however, the opinions expressed are those of the authors alone.
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28. J. Schwartz et al., "Acute effects of acid aerosols on respiratory symptom reporting in
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patterns in summertime sulfate aerosol acidity and neutralization within a metropolitan
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39. G.D. Thurston, J. Gorczynski, P. Jaques, J. Currie, and Deke He, "Daily acid aerosol
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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
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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,
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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LAKE MICHIGAN OZONE STUDY
LAKE MICHIGAN OZONE STUDY
-------
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-------
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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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.
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441
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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).
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_
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
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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
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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.
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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.
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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
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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
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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
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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.
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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.
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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
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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
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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
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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
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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.
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504
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SAMPLE DATA REVIEW CHECKLIST
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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
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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
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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
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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
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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
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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
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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
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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.
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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
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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
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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.
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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.
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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
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^ 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
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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
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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
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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
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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
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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
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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
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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).
-------
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im p.«. LSI.
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.
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M C d dry maaa) ' b '.
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Oregon .'iwrtm fmnymnm l^i-ugl i
Ltv* oik (CWmu nrjfiiuiWKi Mi// )
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Cowl live .«k (ffwrrw agnf,,l,a Ntr)
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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
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Session 14
Remote Sensing FTIR Open Path Techniques
Thomas Pritchett and William Vaughan, Chairmen
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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
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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
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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
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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
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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
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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
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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.
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
-------
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voter b^lroo»-a
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Living roam-i
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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
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-oca
131
,
g t9-»
J
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-------
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I
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___ !968
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•
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,
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-
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. JiTiOfiS
•
Figure 5
Table 1. Model Input
Table 2, Stability Catagories
680
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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
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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
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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
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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
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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
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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
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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
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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
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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
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Solvent Extraction
10 20 30 40 50 60 70
Solvent Extraction
o
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a
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0.8-
0.7-
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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
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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
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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
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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
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698
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636
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25:88
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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*
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i
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i
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(
tl
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T
T
I
•?•
I
1
•
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T
1
«•
T
*
Hguml. Swiping dartbudom far rantodmonlorino date from Beaumont. TX;
Ata8to48-24SOOOe.
Ftaum2.
nyui
aa -
400 -
IK -
MO -
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T
m
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m -
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r ~
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IW -
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-*-
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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ii I r
11 iPel
11 (Nil
12 1 Cu|
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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
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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-
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2 IAsl-69.71
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2 |Pb|-65,2|
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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
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I I ,.,!,. 1
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Figure 2. Overall sampling efficiency for several yaw angles.
1048
-------
G
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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
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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
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(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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
-------
|