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                                TECHNICAL REPORT DATA
                         /ffmr mad Imttncttont on tHt rtrtnr btfort completiiti)
       NO.
 EPA/600/2-86/072
        2.
4. TITLE AND SUBTITLE
 Critical Review of Open Source Particulate Emission
 Measurements: Field Comparison
                                   5. REPORT OATI
                                    August 1986
                                   •. PERFORMING ORGANIZATION CODE
7. AUTHORISt
Bobby £. Pyle and Joseph D. McCain
                                   I. PERFORMING ORGANIZATION REPORT NO.
                                    SoRI-EAS-85-444R
9. PERFORMINO ORGANIZATION NAME AND ADDRESS
Southern Research Institute
P. O. Box 55305
Birmingham. Alabama 35255-5305
                                   10. PROGRAM ELEMENT NO.
                                   11. CONTRACT/GRANT NOT

                                    68-02-3696. Task 2
13. SPONSORINO AGENCY NAME AND ADDRESS
 EPA, Office of Research and Development
 Air and Energy Engineering Research Laboratory
 Research Triangle Park, NC  27711
                                   1JLTVPE QJ REPORT AND PERIOD CO
                                    Task Final; 6/83 - 6785
                                                           VERED
                                   14. SPONSORINO AGENCY CODE
                                     EPA/600/13
19. SUPPLEMENTARY NOTES AEERL project officer is Robert C.  McCrillis.  Mail Drop 65.
919/54ir 2733.
16. ABSTRACT
          The report gives results of a review of sampling and analytical procedures
used by various testing firms to quantify particulate emissions from open sources;
e.g.. roads and storage piles.  Seven firms, who account for nearly 100 percent of
all open source data in the literature, described their current sampling and analyti-
cal procedures. Five of these firms then participated in a simultaneous side-by-side
field test on a simulated unpaved road at a major steel plant. Each firm independ-
ently measured the particulate emission concentrations produced by roadway traf-
fic.  These measurements produced not only the particle-size-dependence of the
emissions but also the concentrations as functions of the distance above the road sur-
face. The results for each firm were expressed as emission factors for total particu-
late and the mass fractions of the particulate with sizes <30. <15. <10. and <2.5
micrometers diameter. Based on an analysis of the results, it was found that all five
profiling systems could produce equivalent results in terms of total emissions^, This
was not the case for emissions by particle size. The only technique of those tested
that produced reliable emission factors by particle size was inertia! sizing.     ;
17.
                             KEY WORDS AND DOCUMENT ANALYSIS
                DESCRIPTORS
                       b.IDENTIFIERS/OPEN ENDED TERMS
                         C.  COSATI h Kid/Group
Pollution
Measurement
Particles
Dust
Field Tests
Sampling
Analyzing
Roads
Pollution Control
Stationary Sources
Unpaved Roads
Storage Piles
Inertia! Sizing
13B
14G

11G
14B
It. DISTRIBUTION STATEMENT
 Release to Public
                                          It. SECURITY CLASS
                                          Unclassified
                                                ii. NO. or PAGES
                                                     13A
                       M. SECURITY CLASS f7Mt*MtJ
                       Unclassified
                         22. PRICE

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                      NOTICE

This document has been reviewed in accordance with
U.S. Environmental Protection Agency policy and
approved for publication.  Mention of trade names
or commercial products does not constitute endorse-
ment or recommendation for use.
                        ii

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                                   ABSTRACT

     Current EPA emission trading  (bubble) policies  allow excessive emissions
from one source to be offset by improved  controls  on other sources within the
same industrial complex.  In implementing this  bubble policy,  many industries
have opted to reduce particulate emissions from roads,  parking lots, and
storage locations in lieu of more  stringent  controls on other  plant operations.
The predictions of these open sources emissions based upon the existing data
for measured emission factors have been found to be  subject to high
variability.  Part of this uncertainty can be attributed to the variations in
source characteristics.  However,  a  significant part of the uncertainties are
due to variations in the measuring and analytical  techniques used to assess
sources upon which the emission factor data  base was built.  In an effort to
quantify these technique dependent 'parameters,  a comparative study of the
current measuring and data reduction methods was carried out.   This study
included a simultaneous, side-by-side field  test with five independent testing
organizations sampling the dust emissions from  a simulated unpaved road at a
major steel producing facility.  Each of  the participants independently
measured the particulate emission  concentrations produced by roadway traffic.
These measurements resulted in not only particle-size dependence of the
emissions but also concentrations  as functions  of  the distance above the road
surface.  The results for each testing organization  were expressed as emission
factors for total particulate and  the mass fractions of the particulate with
sizes <30, <15, <10, and <2.5 pm diameter.   Based  on an analysis of the re-
sults, it was found that all five  profiling  systems  were capable of producing
equivalent results in terms of total emissions. This was not the case for
emissions by particle size.  The only technique among those tested that was
believed to produce reliable emission factors by particle size was the inertial
sizing method.

     This work was submitted in partial fulfillment  of EPA Contract Number
68-02-3693, work assignment 002 by Southern  Research Institute under
sponsorship of the U.S. Environmental Protection Agency.  This report covers a
period from 1 January 1984 to IS March 1985  and work was completed as of 10 May
1985.
                                      ill

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                                      CONTENTS

Section                                                                 Page
Figures	   vi

Tables.	   xi

Acknowledgment	  xn

1.  Introduction	     1

2.  Conclusions and Recommendations..	     5

3.  Fugitive Measurement Methodologies	     8

4.  Description of Test	   28

5.  Particle Size Measurements	   34

         Methods	   34
              Cyclone/lmpactors	   34
              Stacked Filters	   36
              Scanning Electron Microscopy.	   39
         Results	   41
              Stacked Filter	   43
              Scanning Electron Microscopy.	   47
              Cyclone/lmpactors	   52
         Particle Sizing Recommendation	   55

6.  Exposures and Emission Factors..	   57

         Methodologies	   57
              Sampling Xsokineticity	   57
              Exposure Integration	   58
         Field Test Results	   60
              Total Particulate Emission Factors	   60
         Exposure and Emission Recommendations	   84

7.  Modeling Fugitive Emissions	   85
         Predictive Emission Factor Equations	   85
         Modeling Recommendations	   94

References	   118

Appendix	   120

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                                    FIGURES
Number   Title                                                              Page
   1     Upwind profiling system used by EEM	10

   2     Downwind profiling system used by  BEN	11

   3     Typical sampling head used by EEM.	12

   4     Upwind profiling system used by MRI	13

   5     Downwind profiling system used by  MRI	14

   6     Typical hi-vol sampler used by MRI  (without particle sizing)	16

   7     Upwind profiling system used by PEL	17

   8     Downwind profiling system used by  PEI	18

   9     Typical stacked filter sampling head  used by PEI	..19

  10     Upwind sampling system used by TRC	20

  11     Downwind profiling system used by  TRC.	21

  12     Typical sampling head used by TRC	22

  13     Upwind sampling system used by USS	23

  14     Downwind profiling system used by  USS	24

  15     Typical sampling head used by USS	25

  16     Gary test site after covering road with dirt.  View is looking
           wes t	29

  17     Physical layout of the Gary comparative fugitive emission
           test site	30

  18     Total suspended particulate matter by test and sampling
           position as measured by standard high-volume sampler.	33

  19     MRI cyclone/cascade impactor combination	35

  20     Lundgren cascade impactor	37

  21     Collocated Lundgren cascade impactor  (left) and MRI sierra
           cyclone and impactor  (center)............	38

  22     PEI stacked  filter profiler head	40
                                      vi

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Figures (Cont.)

Number   Title                                                              Page

  23     Particle size distributions as  measured  by the various techniques..42

  24a    Plot of the ratio of PBI's TSP  concentration to hi-vol
           concentration versus  the total particulate mass collected by
           the hi-vol	46

  24b    PEI screen penetration  dependence on total mass collected by
           the profiler sampler.	«46

  25     Particle sice distribution as measured by a Lundgren cascade
           impactor and as determined by the OCSBM technique from a
           collocated profiler sample	48

  26     Total particulate emission factors by test as measured by each
           organization	64

  27     Measured total exposures  versus height for Test 1 for all
           contractors providing total particulate exposure data..	72

  28     Measured total exposures  versus height for Test 2 for all
           contractors providing total particulate exposure data	73

  29     Measured total exposures  versus height for Test 3 for all
           contractors providing total particulate exposure data	74

  30     Measured total exposures  versus height for Test 4 for all
           contractors providing total particulate exposure data	75

  31     Measured total exposures  versus height for Test 5 for all
           contractors providing total particulate exposure data	76

  32     Measured total exposures  versus height for Test 6 for all
           contractors providing total particulate exposure data	77

  33     Measured total exposures  versus height for Test 7 for all
           contractors providing total particulate exposure data	78

  34     Measured total exposures  versus height for Test 8 for all
           contractors providing total particulate exposure data.	79

  35     Measured total exposures  versus height for Test 9 for all
           contractors providing total particulate exposure data...	80

  36     Measured total exposures  versus height for Test 10 for all
           contractors providing total particulate exposure data	81

  37     Measured total exposures  versus height for Test 11 for all
           contractors providing total particulate exposure data	82
                                      vii

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Figures (Cont.)

Number   Title                                                              Page

  38     Scatter diagrams oft   the  test averaged TP emission factor
           measurements and  that predicted by EEM's equation (filled
           circles) along with  the  associated regression line (dotted
           line)} and  the values of TP emission factor both measured
           and  predicted by  EEM (open circles) along with the
           associated  regression line (broken line)	91

  39     Scatter diagrams of:   the  test averaged TP emission factor
           measurements and  that predicted by MRI's equation (filled
           circles) along with  the  associated regression line (dotted
           line); and  the values of TP emission factor both measured
           and  predicted by  MRI (open circles) along with the
           associated  regression line (broken line)	96

  40     Scatter diagrams ofi   the  test averaged TP emission factor
           measurements and  that predicted by TRC's equation (filled
           circles) along with  the  associated regression line (dotted
           line); and  the values of TP emission factor both measured
           and  predicted by  TRC (open circles) along with the
           associated  regression line (broken line)	.....97

  41     Scatter diagrams of:   the  test averaged TP emission factor
           measurements and  that predicted by USS's equation (filled
           circles) along with  the  associated regression line (dotted
           line); and  the values of TP emission factor both measured
           and  predicted by  USS (open circles) along with the
           associated  regression line (broken line)	98

  42     Scatter diagrams of:   the  test averaged TSP emission factor
           measurements and  that predicted by EEM's equation (filled circles)
           along with' the associated regression line (dotted line); and the
           values of TSP emission factor both measured and predicted by EEM
           (open circles) along with the associated regression line (broken
           line)	99

  43     Scatter diagrams of:   the  test averaged TSP emission factor
           measurements and  that predicted by MRI's equation (filled
           circles) along with  the  associated regression line (dotted
           line); and  the values of TSP emission factor both measured
           and  predicted by  MRI (open circles> along with the
           associated  regression line (broken line)	100

  44     Scatter diagrams of:   the  test averaged TSP emission factor
           measurements and  that predicted by PEI's equation (filled
           circles) along with  the  associated regression line (dotted
           line); and  the values of TSP emission factor both measured
           and  predicted by  PEI (open circles) along with the
           associated  regression line (broken line)	101
                                    viil

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Figures (Cont.)

Humber   Title                                                              Page

  45     Scatter diagrams  ofi   the  test averaged TSP emission factor
           measurements and  that predicted by TRC's equation (filled
           circles) along  with  the  associated regression line(dotted
           line)} and  the  values of TSP emission factor both measured
           and  predicted by  TRC(open circles) along with the associated
           regression  line (broken  line).............*	102

  46     Scatter diagrams  oft   the  test averaged TSP emission factor
           measurements and  that predicted by OSS's equation (filled
           circles) along  with  the  associated regression line (dotted
           line)) and  the  values of TSP omission factor both measured
           and  predicted by  USS (open circles) along with the
           associated  regression line (broken line)	103

  47     Scatter diagrams  ofi   the  test averaged PM15 emission factor
           measurements and  that predicted by EBM's equation (filled
           circles) along  with  the  associated regression line (dotted
           line); and  the  values of PM15 emission factor both measured
           and  predicted by  EEM (open circles) along with the
           associated  regression line (broken line)	104

  48     Scatter diagrams  ofs   the  test averaged PM1S emission factor
           measurements and  that predicted by MRl's equation (filled
           circles) along  with  the  associated regression line (dotted
           line); and  the  values of PH.. emission factor both measured
           and  predicted by  MRI (open circles) along with the
           associated  regression line (broken line)	105

  49     Scatter diagrams  oft   the  test averaged PH15 emission factor
           measurements and  that predicted by TRC's equation (filled
           circles) along  with  the  associated regression line (dotted
           line); and  the  values of PH., emission factor both measured
           and  predicted by  TRC (open circles) along with the
           associated  regression line (broken line)	106

  50     Scatter diagrams  oft   the  test averaged PM15 emission factor
           measurements and  that predicted by USS's equation (filled
           circles) along  with  the  associated regression line (dotted
           line); and  the  values of PMj. emission factor both measured
           and  predicted by  USS (open circles) along with the
           associated  regression line (broken line).	107

  51     Scatter diagr; 2  oft   the  test averaged PMJO emission factor
           measurements and  that predicted by EBM's equation (filled
           circles) along  with  the  associated regression line (dotted
           line); and  the  values of PM.fl emission factor both measured and
           predicted by EEM  (open circles) along with the associated
           regression  line (broken  line)	108
                                       ix

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Figures (Cont.)

Number   Title                                                              Pagt

  52     Scatter diagrams  of:   the  test averaged PH.. emission factor
           measurements  and  that predicted by MRI's equation (filled
           circles) along  with the  associated regression line (dotted
           line);  and  the  values of PMj.  emission factor both measured
           and  predicted by  MRI (open circles) along with the
           associated  regression line (broken line)	109

  53     Scatter diagrams  oft   the  test averaged PM1Q emission factor
           measurements  and  that predicted by PEI's. equation (filled
           circles) along  with the  associated regression line (dotted
           line);  and  the  values of PH..  emission factor both measured
           and  predicted by  PEX (open circles) along with the
           associated  regression line (broken line).....	110
  54     Scatter  diagrams  oft   the test averaged PM1Q emission factor
           measurements  and that predicted by TRC's equation (filled
           circles)  along  with the associated regression line (dotted
           line);  and  the  values of PH.. emission factor both measured
           and  predicted by TRC (open circles) along with the
           associated  regression line (broken line)	111

  55     Scatter  diagrams  oft   the test averaged PMJO emission factor
           measurements  and that predicted by USS's equation (filled
           circles)  along  with the associated regression line (dotted
           line);  and  the  values of PH.. emission factor both measured
           and  predicted by USS (open circles) along with the
           associated  regression line (broken line)	..112

  56     Scatter  diagrams  oft   the test averaged FP emission factor
           measurements  and that predicted by EEM's equation (filled
           circles)  along  with the associated regression line (dotted
           line);  and  the  values of FP emission factor both measured
           and  predicted by EEM (open circles) along with the
           associated  regression line (broken line)	113

  57     Scatter  diagrams  oft   the test averaged FP emission factor
           measurements  and that predicted by MRI's equation (filled
           circles)  along  with the associated regression line (dotted
           line);  and  the  values of PP emission factor both measured
           and  predicted by MRI (open circles) along with the
           associated  regression line (broken line)	114

  58     Scatter  diagrams  oft   the test averaged FP emission factor
           measurements  and that predicted by PEI's equation (filled
           circles)  along  with the associated regression line (dotted
           line);  and  the  values of FP emission factor both measured
           and  predicted by FBI (open circles) along with the
           associated  regression line (broken line)	115

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Figures (Cent.)

Number   Title                                                              Page

  59     Scatter diagrams oft  the test averaged PP emission  factor
           measurements and that predicted by TRC's equation  (filled
           circles) along with the associated regression  line (dotted
           line); and the values of FP emission factor both measured
           and predicted by TRC (open circles) along with the
           associated regression line (broken line)	116

  60     Scatter diagrams oft  the test averaged FP emission  factor
           measurements and that predicted by OSS's equation  (filled
           circles) along with the associated regression  line (dotted
           line); and the values of FP emission factor both measured
           and predicted by USS (open circles) along with the
           associated regression line (broken line)	117
                                    TABLES
  1     Profiling tyitti oharaattriitiQi««««««««t««««««««««»«««««. «...«.•. .9

  2     Average emission factors by size class* • ........................... 44

  3     Comparative  fugitive emission  test  results ......................... 61

  4     Average emission factors obtained by  each organization ............. 62

  5     Correlation  coefficients of TP, TSP,  PM1Q,  and FP emission
          factors reported by  test participants ............. ••««•• ......... 65

  6     Exposure and emission  values by test  number and organization ....... 66

  7     Size dependent  constants for the predictive emission factor ........ 87

  8     Size fractions  of particulate  as reported by MRI and
          recalculated  by Southern Research Institute ...................... 88

  9     Average emission factors as calculated  by Southern Research
          Institute* «••••*•••••««•*••••••••••••••••••••••*••'••••«»••••••• »90

  10     Correlation  and regression line coefficients for the emission
          factor comparisons t ••••*•••••••••• t • i ••••••••••»••• t •*••••••••••• 92
                                      xi

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     Several individuals and organizations contributed to  the  success  of this
study.  The efforts of those associated with the United States Steel Corporation
bear individual Mentions Victor Hordlund, Supervisor of Environmental  Engineer-
ing at the Gary Works, and his staffi William Kubiak in particular  for assisting
in selection and preparation of the test site; and T.P. Eckle  with  the USS  Tech-
nical Center who participated in the comparative test at their own  expense.
                                      xii

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                                   SECTION  1
                                 INTRODUCTION

     During the past decade, research has shown that particulate eaissions
from open sources such as roads and material storage piles contribute signifi-
cantly to ambient particulate matter concentrations in many areas*1  The cur-
rent EPA emission trading policy allows  excessive  emissions from one source to
be offset by improved control of another source within the same plant.  In
implementing this bubble policy, many steel plants have agreed to reduce fugi-
tive dust emissions in lieu of tighter controls on process emissions.2  How-
ever, the efforts of several groups to develop equipment, and methods for quan-
tifying emissions from nontraditional sources  such as roadways have resulted in
estimates of emission factors and emission  rates with substantial variability.
Whereas it is generally agreed that emission factor estimates of process emis-
sions from ducted sources are good to ±50%  of  a specified measured value, pre-
dictions of open source fugitive dust emission factors may vary from measured
values by as much as an order of magnitude. These large uncertainties are due
to both differences in the measuring techniques used and the site examined.
Even for sites with closely similar physical characteristics the measured
emissions have been found to differ by as much as  an order of magnitude.  In an
effort to resolve these differences, the U.S.   Environmental Protection Agency
contracted with Southern Research Institute (SoRI) to conduct a critical'review
of the various measurement and predictive methods  and to conduct a side-by-side
field test in which testing organisations whose methods represent the principal
techniques which have commonly been applied, would simultaneously sample the
emissions from an unpaved road*

     The first phase of this review was  the compilation of documents that
describes in detail each of the testing  methods and data reduction techniques
used in developing the existing data base.  A  list of these reports is shown in
the Appendix.  As a result of the initial phase of this study, documents were
received from the seven organizations listed belowi
     •Catizone ft Martin Associates, Inc. (CMA)
     63 McKee Street
     East Hartford, CT 06108
     (203) 269-1331

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     Energy * Environmental Management, Inc. (BEN)
     P.O.  Box 71
     Murrysville, PA 15668
     (412) 247-5124

     Energy Impact Associates (ElA)
     P.O.  Box 1893
     Pittsburgh,  PA 15230
     (412) 351-5800

     Midwest Research Institute (MRI)
     425 Volker Boulevard
     Kansas City, MO 64110
     (816) 753-7600

     PEI Associates, Inc. (PBI)
     (Formerly PEDCo Environmental, Inc.)
     11499 Chester Road
     Cincinnati,  OH 45246
     (513) 782-4700

     TRC Environmental Consultants, Inc. (TOO
     800 Connecticut Boulevard
     East Hartford, CT 06108
     (203) 289-8631

     United States Steel Corporation (OSS)
     Research Laboratory
     125 Jamison Lane
     Monroevi le, PA 15146
     (412) 372-1212

*CMA is  no longer in operation.

     Each of these current procedures documents (CPD) specifically  addressed

the following points:


     1.   A description of the testing methods and data reduction  schemes
         employed in a specific field test conducted by that organization
         for the measurement of both the total particulate  (TP) and the

         size distribution of that particulate resulting from open  source

         fugitive emissions and other ancillary measurements such as

         surface loading of silt on roadway.

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     2.   A discussion of the historical development of  the  current
         technique with particular emphasis upon any  changes  that have
         been made and the reasons for those changes.   If either the
         sampling or data analysis techniques have undergone  change, the
         respective organization described how data obtained  before the
         modifications were instituted could be correlated  with that
         obtained afterward or detail why such correlations cannot be made
         when such is the case.

     3.   One or more detailed test reports from recent  field  tests which
         utilized the sampling and data reduction techniques  described in
         (1) above.  Included in these reports were sufficient raw data to
         enable the reader to reproduce the final results quoted.

     4.   A discussion of how the testing and data reduction procedures
                                                 >-*
         described above would *e modified for use at various site
         locations and under varying site conditions.

     As a result of review of the CPD's, four organizations were selected to
participate in the simultaneous field comparison during Part  II of this study.
These organizations were selected according to the following  criteria:

     1.   Those organizations which have made a significant  contribution to
         the existing fugitive emission data base using different
         methodologies.

     2.   A representative organization for each alternative methodology
         not included in those selected by criterion  number 1.

The four organizations originally selected to participate  in  the field compari-
son were CMA, EEM, MRI, and PEL  However, before the field test could be car-
ried out CMA had to withdraw from consideration and were replaced by TRC, the
next choice in line.  Another organization, USS, participated in the field

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comparison at their own expense and  thus,  a total of five organizations were
included in the field comparison,  EEM,  MRI,  PBI,  TRC,  and USS.  The individual
field test reports from these  five organizations  are also listed in the
Appendix.

     Because much of the use of the  emissions trading policy with respect to
roadways had been in the iron  and  steel industry, the desired test site was an
unpaved road within an integrated  iron  and steel  facility.  Negotiations were
undertaken with several companies  with  regard to  possible plant access for the
tests; the United States Steel Corporation responded favorably, offering the
use of their Gary Works.  The  nature of the tests to be conducted made it ne-
cessary to use a moderately long,  straight stretch of roadway that was oriented
more or less perpendicular to  the  prevailing wind and clear of local perturbing
influences for a length of a few hundred meters.  It was also desirable that the
road have a moderately high traffic  density for emissions generation.  Unfortu-
nately, all suitable roads on  the  property of the Gary Works were either paved
or had been treated with chemical  dust  suppressant*  The most suitable road
section in terms of physical layout  and traffic density was a paved slag haul
road parallel and adjacent to  Lake Michigan.  Consequently, this road was made
to simulate an uncontrolled unpaved  road by applying a 5-10 cm thick layer of
dirt to one 300 meter section. This portion of the road was located well away
from other potentially confounding sources and wind flow obstructions.  Five
side-by-side test positions, each  approximately 15 meters wide, were then laid
out on both sides of the road  near the  center of  the simulated unpaved road
section.  A total of eleven tests  were  conducted  over a five-day period in June
1984.  The results of these tests  are the  subject of the following report.

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                                   SECTION 2
                        CONCLUSIONS AND RECOMMENDATIONS

     Each of the profiling systems used in these  tests exhibited both pros
and cons in terms of their versatility and ease of  deployment.   Consequently,
no conclusions are drawn as to the optimum mechanical design of the profiling
towers or associated hardware.  However, several  conclusions may be drawn
regarding the methods of sampling.  These conclusions and recommendations are
discussed in detail at the ends of Sections S, 6  and 7 and are  summarized in
the paragraphs below.

     The data from this test series clearly indicate that there is significant
exposure at heights up to at least the 9m level.  Consequently, the placement
of a sampler at the 9m or 10m  (preferably 10m) elevation is highly recommended.
Also, because the maximum exposure values usually occur  at a height of 1.5 to
2.0 meters, any future profiling  system should include a sampler at this level.
The "ideal" profiling system would have mass  samplers at 1.5, 2.5, 4.0, 6.0,
7.5, and 10.0 meters with concurrent particle sizing devices at 1.5, 4.5, and
7.0 meters.  This configuration would better  characterize both  the exposure and
size distribution of the particulates in the  plume. It  was also demonstrated
that sampling isokineticity can be maintained for each sampling head on the
profiler tower.  Therefore, it is recommended that  each  sampler be equipped
with a servo system and individual velocity sensors to provide  continuous
adjustment of the flow rate based on wind speed at  that  elevation.

     The five profiling systems were found to be  capable of producing equiva-
lent results in terms of total emissions.  This was not  the case for particle
size distributions and emissions by particle  size.  Long recognized problems in
reconstituting size distributions of airborne particles  from resuspensions of
collected bulk material lead to the conclusion that for  fugitive emission sam-
pling of the type undertaken here the sizing  should take place  prior to collec-
tion (or concurrent with collection as in cyclones  and impactors).  The
recommended procedure for measuring the particle  size distribution is MRl's
cyclone/impactor technique with some modifications. With regard to field

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operations, first, a further reduction  in  the  sampling flow rate from 20cfm to
IScfm would help minimize errors from particle bounce.  Alternatively, adhesive
coated substrates could be used at the  current 20cfm flow rate.   Second,
potential errors resulting from the possible transfer of material from the
outlet tube of the cyclone to the first stage  of  the impactor can be avoided by
counting only the material collected in the body  of  the cyclone  as its catch.
The outlet tube catch would then be combined with that of the first impactor
stage.  At the current 20cfm flow rate,  this would result in a cyclone D50 of
22ym being used rather than the current 14|im value.   Lastly, while particle
size was measured at the lower elevations  (1.5 and  4.5m) an additional
cyclone/impactor unit located at a height  of about 7m would provide additional
information regarding the changes in sice  distribution as a function of height
within the dust plume.

     A better data analysis technique than the current MRI procedure would be
that commonly used in reducing impactor data from industrial sources.  In the
latter, a spline fit is made to the cyclone/impactor data in the cumulative
percentage form of the distribution.  The  fit  is  made in a manner that requires
continuity in the slope of the curve and the solution is forced to be
asymptotic to 100% at a diameter equal  to  the  maximum diameter present in the
sample.  The fitted curve is then used  to  interpolate or extrapolate as needed
to obtain the mass fractions in the selected size intervals.  This technique
avoids the requirement of assuming a functional form for the distribution and
makes use of the complete data set rather  than just  two of the data points.

     With regard to the exposure integration procedure, the resultant emission
factor appears to be relatively insensitive to the technique used so long as
the exposure is adequately characterized with  regard to height.   The most
critical area is that where the peak exposures occur (usually at 1.5 to 2. 5m).
With samplers at 1.5, 2.5, and 4.0 meters  this should not be a major source of
error.  However, under greatly different site  conditions (road type, silt
content, etc) the samplers at the lower elevations may need to be positioned at
different heights.

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     The utility of an emission factor predictive  equation is that of predict
-ing the emissions from a particular  site  in  lieu  of actual measurements.  In
order that the equation be applicable over a  wide  range of site locations and
conditions, it should include as many of the  relevant parameters describing the
site as possible.  This requires that the  predictive equation be developed from
                            \
as large a data base as possible*  The equation currently described in the
AP-42 manual was developed from a  fairly broad  data base using multiple linear
regression techniques.  The data base has  some  uncertainties particularly with
regards to the particle size distributions.   These uncertainties most certainly
cast some doubt upon the accuracy  of  the values used for the particle size
multiplier, k, in this equation.   However,  without an extensive evaluation of
the existing unpaved road emissions data base,  there are no justifications for
invalidating the relation.  This equation  is  probably the most reliable
predictor of unpaved road emissions currently available.  Because of past
problems in the particle sizing techniques, the values used for the size
multiplier (k) are less reliable than the  overall  equation.  It is recommended
that these values be re-evaluated  in  the future as the data base is expanded
with more reliable particle size information.

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                                  SKTIOM  3
                      FUGITIVE MEASUREMENT MBTHOOOLOGIBS

     All five of the participating organisations  utilised variants of the
exposure profiling tower system  first developed by MHZ3  to Measure emission
rates.  However, there were potentially  significant differences in the actual
applications of the Method with  respect  to such items as the number and heights
of the profiler samplers, the filter  orientation  within  the samplers, the sam-
pling flow rates, the methods used for establishing and  maintaining isokinetic
sampling conditions, and the methods  used  to apportion the total emissions
among the various particle sise  fractions.  Fractions of interest were TSP
(assumed to be the weight fraction smaller than 30 urn),  PM10 (the weight frac-
tion contained in particles smaller than 10  urn),  and the fine particle fraction
(defined as the weight fraction  contained  in particles smaller than 2.5 urn).
All particle diameters used herein are on  an aerodynamic (density - ig/cm3)
basis unless specifically noted  otherwise*  Brief summaries of the methods used
by the participants are given in Table 1.

     The profiling methods used  by each  of the organisations were as follows:

     BEM - System composed of an upwind  and  downwind tower containing three and
five sampling heads, respectively, as shown  in Figures 1 and 2.  Bach sampling
head consisted of a hi-vol sampler motor,  a  vertically mounted filter, and an
inlet nossle as shown in Figure  3.  The  samplers  on each tower were raised and
lowered vertically by a concatenated  pulley  arrangement.  The samplers were
operated at preset fixed flow rates based  on a IS-minute average wind speed at
a height of 4 m for the period immediately preceding the test.  The vertical
velocity distribution of wind speed was  assumed to be uniform.

     MRI - System used for these tests differed somewhat from that used in the
past as indicated in Table 1.  The system  used here was  composed of a two head
upwind tower and a five head downwind tower  as shown in  Figures 4 and 5.  Bach
nonsising sampler head contained a horisontally mounted  hi-vol filter and an
                                      8

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                                         »•»»-»!§
rigor* 1.  Upwind profiling «y»t«« oMd by ON.
                    10

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- • _..


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                                                     MM-III
Figure 3.  Typical stapling  head used by RBI.
                      12

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riguc* 3.  Downwind profiling «y«tt» u«^ by mi
                       14

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inlet nozzle below the filter as seen  in Figure  6.   The sampling heads are
raised and lowered vertically by a system of  pulleys.   Periodic manual flow
adjustments were based on wind speeds  from a  logarithm wind shear curve fit to
measured wind speeds at heights of 1.5 m and  4.5 m.

     PEI - System composed of identical upwind and  downwind towers each con-
taining four sampling heads as shown in Figures  7 and  8.   Bach sampling head
consisted of a hi-vol motor and several circular, stacked filters and an inlet
nozzle as shown in Figure 9.  Sampling heads  are raised and lowered vertically
while attached to a telescoping tower. In the current tests the maximum height
of the profiler was higher than in previous tests (see Table 1).  Periodic
manual flow adjustments were based on  wind speed at a  height of 3 m with the
vertical velocity profiles adjusted for wind  shear  by  means of an assumed power
function.

     TRC - System composed of an upwind tower containing one sampler head and a
downwind tower with five sampling heads as illustrated in Figures 10 and 11,
respectively.  Each sampling head contained a hi-vol filter mounted horizontal-
ly and an air intake transformer above as shown  in  Figure 12.  The sampling
heads were gimbal mounted to the tower and maintained  their orientation as the
tower was lowered to a horizontal position.   Continuous,  servo-controlled flow
adjustments were based on wind speeds  measured by thermal anemometers located
adjacent to each sampling inlet.

     USS - System consisted of one sampling head upwind tower and a downwind
tower containing four samples as shown in Figures 13 and 14, respectively.
Each sampling head consisted of a hi-vol  filter  mounted horizontally and an
intake nozzle above as illustrated in  Figure  15. The  sampling heads were
gimbal mounted to the tower and maintained their orientation as the tower was
lowered by inclining.  Continuous, servo-controlled flow adjustments were based
on wind speeds measured by thermal anemometers  located adjacent to each
sampling inlet.
                                      15

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                                                                          MM4II
Figure 6.  Typical hi-vol sampler  used  by MRI (without particle siting).

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   •':
                                              ttl»-tli
Figure 8.   Downwind profiling system used by FBI.
                         18

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                                                           ItM-Ilt
Figure 9.  Typical stacked  filter  sampling head used by PEL
                            19

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                                               MIJ-411
Figure  10.   Upwind sailing  system used by THC.
                        20

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Figure 11.  Downwind profiling  system used by TRC.
                         21

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                                           MM-ttt
Figure 12.  Typical  sampling head used by THC.
                    22

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Figure 13.  Upwind sampling systea used by DBS.
                       23

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                                                IOtt-

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     Three different methods were  used  for  the  determination of particle size
distributions.  Both MRI and PEI used forms of  inertial sizing while the
remaining three organizations used electron microscopy of the material
collected by the profiler samplers.

     MRI used a combination of a specially  fabricated cyclone for the removal
of large particles followed by a Sierra Model 235 Hi-volume cascade impactor.1*
Two such samplers were used, located adjacent to the profiler tower, one at a
height of 1.5 m and the other at 4.5 m.   These  samplers operated at fixed flow
rates of 34 cubic meters per hour  (20 cfm)  with intake nozzles of selected
sizes such that the samples would  be obtained at near isokinetic conditions.

     PEI used the stacked filter concept developed by Cahill, et al.5  In the
PEI implementation of the concept, a stainless  steel inlet screen having a 30
urn pore size was used to provide a supposed nominal 30gm fractionation point.
The screen was followed by  two Nuclepore filters, the first of which had a pore
size (8 um) selected to provide a  2.Sum aerodynamic diameter cutoff while the
second, which had a pore size of 0.8um,  served as the final filter.

     EEM, TRC, and USS all  used computer controlled scanning electron micro-
scopy (CCSEM) for measuring particle size distributions.6  USS performed their
    analyses while Energy Technology Consultants (ETC) p«rforiMd th«
    K>th RRM AM TftC.  In this •ethod.  *«l*«e«Kt portion* of th» fU»*r«
t>«» profilers were removed, placed between  finely perforated stainless steel
pcreens, and backwashed with acetone to remove the collected particles.  The
particle in acetone suspension was then agitated, and the particles were
redeposited by vacuum filtration onto 0.2gm pore size Nuclepore filters.  A
thin coating of carbon was  evaporated onto  the redeposited specimen after
mounting on SEM sample stubs.  The SEM  was  used in conjunction with an
automated image analysis system to detect and determine the dimensions of the
projected surface of the particles.  Particle volumes were estimated by
categorizing the particle's shapes and  estimating overall dimensions based on
the measurements and assigned category.   X-ray fluorescence emissions were used
to assign a probable composition class  to each particle from which a density
                                        26

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was assigned to it.  After measuring approximately 1000 particles and assigning
estimated volumes and densities to  them, a physical size-weight distribution
curve was constructed.  Aerodynamic diameters were also estimated for each
particle based on the assigned category, the measured  dimensions, and
aerodynamic shape factors.

     In addition to the profilers and  sizing systems described above, SoRI
performed a limited number of particle size distribution measurements using
Lundgren cascade impactors.  These  samplers were  collocated with various
samplers of the other participants  at  different times  during the test program.
They can be seen hanging under the  upper MRI cyclone/impactor and above the
lower MRI cyclone/impactor in Figure 5, and below the  second lowest PEI sampler
in Figure 8.  The Lungren impactors sampled at a  fixed flow rate of 5 cubic
meters per hour (3cfm).  The cross-sectional area of the inlet was masked for
each test so that the sampling would be done at near isokinetic conditions.
These samplers provided a means of  obtaining data with an inertial
(aerodynamic) classifier collocated with each of  the other techniques.  A
description of the Lundgren cascade impactor is given  in Section 5.
                                      27

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                                  SECTION 4
                              DESCRIPTION OF TEST

     The physical layout of the simultaneous field comparison test site is
illustrated, in Figure 16.  The test  site was located along a portion of a paved
slag haul road adjacent to and approximately 50 meters due south of Lake Mich-
igan.  The road was made to simulate an unpaved,  uncontrolled, road by covering
it with a 5 to 10 cm thick layer of  fine aggregate.   The material used was a
nondescript mixture of clay, iron ore, and boiler ash (composition information
is available in TRC's Field Comparison report).  The average silt content of
the material (fraction passing through a 200 mesh screen) was approximately 10%
as measured by all five testing parties.

     The average mass concentration  (TSP) as measured throughout the testing
period by standard high-volume samplers  (hi-vols) positioned three meters from
the roadway edge was 13.3 mg/m3.  Thus,  for all intents and purposes, the test
section represented an unpaved and uncontrolled road.  In the middle of this
300 meter section of treated roadway, five testing stations were laid off as
described in Figure 17.  This configuration minimized the distance between
sampling systems while allowing sufficient space to each system.  Through the
use of identical stations on either  side of the road the upwind and downwind
locations could be swapped across the road when the wind direction reverses as
it typically does near the lake.

     In an effort to minimize the confounding  effects which might be produced
by small portable electric generators usually  used by the sampling parties, two
high capacity diesel generators were positioned on each side of the roadway and
approximately 25 meters west of the  last sampling location (No. 5 in Figure
17).  This also enabled the sampling equipment to be moved from any location to
another with a minimum amount of time and effort.

     The traffic over the test road  was a mixture of service vehicles (pickup
trucks) and dump trucks hauling solidified slag from the blast furnaces to the
                                     28

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                                                                                60SO-SIJ
?igur »  15.   ''icy
                        site ifter  covaclnq  toad  fit      .,   viaw  is  loolting  *e3t,

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  LAKE
  MICHIGAN
                  I
               GENERATOR
                                         DIRT
                                         ROAD
                                                        SAMPLING
                                                        LOCATIONS
                                                                         POWER
                                                                         PANEL
                                                                GENERATOR
                                      N
                                                                        »0lt-4ll
Figure  17.   Physical layout of  the Gary comparative  fugitive emission test
             site.
                                      30

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slag yards and returning with  loads  of  crushed slag.   Average vehicle speed  in
the test section normally ran  as high as  50  to 60 kph.  However, after covering
the test section with aggregate the  average  vehicle speed was reduced, because
of poor visibility, to approximately 40 kph.

     Exposure profiling measurements of the  test site were carried out over  the
period June 11 to June 15,  1984.   In this five day period a total of 11 data
runs were accomplished.  In terms  of downwind direction,  six tests occurred
with the wind coming out of the north  (off the lake)  and the remaining tests
with the wind out of the south.  Background  concentrations for total particu-
late (TP) varied with wind  direction.   When  the wind came from the north, off
Lake Michigan, the background  concentration  at 3 meters above the ground was
approximately 100 ug/m3.  During those  periods when the wind was from the south
the concentration was about 600 u9/"»3 •  The  difference was due mostly to par-
ticulate produced south of  the test  site  where considerable industrial
activity was concentrated.   This presented no problem for these tests because
the TP concentrations produced by  the  test road were generally several times
greater.

     The procedure used during each  of  the eleven tests was as follows:  all
parties commenced sampling  at  the  same  time,  during a break in traffic flow;
sampling continued until a  predetermined  number of vehicles had crossed the
testing section, and sampling  was  discontinued simultaneously during a break in
traffic flow.  Following each  test run, sufficient time was allowed for each
party to recycle their equipment preparatory to the next test.

     One factor of great concern during pretest planning was the possibility of
nonuniformity of particle concentrations  over the length of the road test sec-
tion.  If the particle concentrations were in fact nonuniform with respect to
concentration or size distribution,  then  comparable results could not have been
expected from the various sampling systems,  even if they were functionally
identical.  Any potential effect of  nonuniformity of conditions along the test
zone was partially obviated by rotating the  participant's locations so that
each spent one day at each  of  the  five  test positions.  The lack of a reference
                                       31

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                                 SECTIOH 5
                           PARTICLE SIZE MEASUREMENT

METHODS
     Three fundamentally different particle  sizing methods ware utilized by
the test participants.  Three of the organizations - USS,  TRC,  and BEN - used
Computer Controlled Scanning Electron Microscopy (CCSEM);  one,  MRI, used iner-
tial particle sizing devices; and one, FBI,  used a combination  Of forms of
sieving and inertial devices.  In addition,  SoRI operated  collocated inertial
sizing samplers at selected locations during some of the tests.  Unfortunately,
the lack of standard reference methods for particle size'distribution measure-
ment under circumstances like those encountered  in roadway emissions testing
makes it difficult to arrive at unequivocal  conclusions regarding the actual
distributions during these tests and in the  departures  from those distributions
in the data obtained by the participants.
Cyclone/lmpactors
     MRI used a combination of a specially fabricated cyclone for the removal
of large particles followed by a Sierra Model 235 Hi-volume cascade impactor
for size distribution measurement.  The setup is illustrated in Figure 19.  The
size distribution measurements are made separately from the exposure
measurement.  The analysis of the particulate material  collected by their
device is by gravimetric methods.  Particle  collection  in  the cyclone takes
place in two distinct zones: the body of the device, and the outlet tube.  If
the body catch is taken alone, the cyclone cut diameter is 22pm (aerodynamic
diameter); if the body and outlet tube catches are combined, the cut diameter
is reduced to 14pm.  The treatment of the cyclone data  with respect to the
handling of the catch(es) and the two possible cut diameters will be deferred
to the discussion of the test results.  With respect to the impactor portion of
the sampling system, MRI used a total of five impaction stages  (plus filter) in
the impactor producing size cuts at 0.6pm, 1.2pm, 2.0pm, 4.1pm, and 10pm.  It
should be noted, however, that in past tests only the first three of the five
                                      34

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stages were used.  The omission or inclusion of  the  Last two stages can have an
effect on the interpretation of the data as will be  discussed later.  Three
such cyclone/inpactor samplers were used, one upwind to measure both
concentration and size distribution, and two «ore downwind for sice
distribution measurement only.  The latter were  located adjacent to the
profiler tower, one at a height of 1.5m and the  other at 4.5m.  These samplers
operated at fixed flow rates of 34 cubic meters  par  hour (20cfm) with intake
nozzles of selected sizes such that the samples  would be obtained at near
isokinetic conditions.

     SoRI obtained several samples with Lundgren cascade impactors during the
tests as well.  These impactors,  illustrated in  Figure 20, are four stage (plus
filter) inertial classifiers7,8,9, providing size fractionation at diameters of
0.44 um, 1.4 um, 4.2 urn, and 14 pm as  operated in these tests.  The samples
were taken quasi-isokinetically with inlet nozzle cross-sections adjusted in
accordance with the mean wind speed at the start of  the test, but the flow rate
was held constant at about 5 cubic meters per hour (3 cfm).  Particle
collection in this impactor takes place on a moving  plastic film coated with an
adhesive.  The adhesive is used to insure retention  of the impacted particles.
The particle size distribution is measured gravimetrically.  However, by
collecting the particles on the moving film, overlapping of particles in the
collected sample is largely avoided, permitting  individual particles collected
on each stage to be easily examined by microscope.  Three of these samplers
were set up collocated at various times with samplers of EEM, MRI, and FBI as
illustrated for one case in Figure 21. Although the Lundgren impactor results
are used as a basis for some comparisons through the remaining discussions of
particle size distribution, they  should not be construed as reference
standards.
Stacked filters
     FBI used the stacked filter  concept developed by Cahill.5  In the PEI
implementation of the concept, a  stainless steel inlet screen having a 30 um
pore size is used to provide a supposed nominal  30 urn fractionation point.  The
screen is followed by two Muclepore filters, the first of which has a pore size
(8 urn) selected to provide a 2.5  pm aerodynamic  diameter cutoff while the
second, which has a pore size of  0.8 urn, serves  as the final filter.  These

                                     36

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Figure 21.  Collocated Lundgren cascade  impactor  (left)  and MRI Sierra cyclone
            and inpactor  (center).

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stacked filter units constituted  the  exposure  samplers on the identical upwind
and downwind profiler towers.  A  schematic  diagram of the sampler is shown in
Figure 22.
Scanning Electron Microscopy
     EEM, TRC, and USS all used computer  controlled scanning electron micro-
scopy (CCSEM) for measuring particle  size distributions.6  USS performed their
own analyses while Energy Technology  Consultants (ETC) performed the analyses
for both EEM and TRC.  In this method,  selected portions of the filters from
the profilers are removed, placed between finely perforated stainless steel
screens, and backwashed with acetone  (ETC)  or  backblown with compressed air
(USS) to remove the collected particles.  In ETC's procedure the acetone par-
ticle suspension is then agitated and the particles are redeposited by vacuum
filtration onto 0.2gm pore size Nuclepore filters.  USS recollects the air
suspended particles on similar Nuclepore  filters for analysis.  A thin coating
of carbon is evaporated onto the  redeposited specimen after mounting on SEM
sample stubs.

     A SEN is used in conjunction with an automated image analysis system to
detect and determine the dimensions of the  projected surface of the particles.
The same hardware and software is used by both ETC and USS for their respective
analyses.  Particle volumes are estimated by categorizing the particle shapes
and estimating overall dimensions based on  the measurements and assigned shape
category.  X-ray fluorescence emissions are used to assign a probable composi-
tion class to each particle from  which a  density is assigned to it.  After
measuring approximately 700 to 1200 particles  and assigning estimated volumes
and densities to them, a physical diameter  - weight distribution curve is con-
structed.  Aerodynamic diameters  are  also estimated for each particle based on
the assigned category, the measured dimensions, and aerodynamic shape factors.
The method by which the particles to  be measured are selected and the way in
which the decision is reached that a  sufficient number of particles have been
measured are considered proprietary information by both the USS and ETC;
therefore this information was not available for use in critiqueing the CCSEM
methodology used in this application.   Because the distributions are heavily
skewed to the small particle end  of the size spectrum in terms of number
                                       39

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                                                                          BRACKET
                                                                          TO TOWER
1.0 In.  I.D.
    INLET
   ORIFICE
                  Figure  22.  FBI  stacked  filter profiler head.
                                      40

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population, the counting statistics  for  the  large particles, which contain the
preponderance of the mass, would be  poor unless  a technique like stratified
counting were used.  A technique like  the latter may indeed have been used,
however this could not be verified.
RESULTS
     The PEI profiling system provided data  in two size fractions at each
profiler level for each test.   MRI'a system  provided data for each test in
seven size fractions at each of two  heights  for  a location adjacent to their
profiler.  The remaining three  participants  used CCSEM analysis of varying
numbers of the filters from their  profilers.   USS performed size analyses on
all of the filters from their profiler.   TRC had CCSEM analyses performed on
two or three filters from selected heights from  one test each day.  EEM had
analyses performed on complete  profiler  filter sets from two tests which were
selected as representative of typical  conditions through the week.

     The results from disparate methods  were not found to be mutually
consistent.  Comparative particle  size distribution results from Test 4 (PEI
data from Test 9) are shown in  Figure  23, in which marked differences can be
seen to exist among  the results from the various methods.  The particle size
distributions measured by a given  contractor were generally similar for all
tests.  Test to test variations for  each contractor were smaller than the
differences resulting from using different techniques.  These differences and
their probable causes will be discussed  in detail in the following paragraphs.
This test was selected for illustration  because  it is one for which inertial
sizing devices (Lundgren impactors)  were collocated with samplers for which
CCSEM size analyses were performed (EEM). The results from this test for all
participants were generally comparable to those  from the other tests for which
size data were available.  No results  are shown  for TRC because they, like EEM,
had size analyses done for only a  subset of  the  complete test series and
samples from this date were not included in  that subset.  The distributions for
all three users of CCSEM size analysis were  quite similar to that illustrated
in Figure 23 throughout the entire test  series.   The PEI data in the illus-
tration were from a different day  (Teat  9),  since complete measurements, which
                                      41

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N
55
2
99
98

95
90
iu  80
d
2
(0
(9
i
CD
*-
w
o
cc
IU
a.
70
60
BO
40
30
20

10
 6
 i    rn      r
   A 80RI)
•  O MRI
   • EEM(
   • U88  I
.  O PEOCO  TEST 9
                               I    I  I  I
                                                       I	IT
       0.4  0.60.81.0
                                 6   8  10
                                        20
40  60 80 100
     Figure 23. Particle cize distributions as measured  by
                the various techniques.
                                                          1010-411
                              42

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the effective cutoff diameter to a value  substantially smaller than 30pm in
much the same way the the SUB pores of  the Nuclepore filter produce an inertial
separation near 2.SMB.  Further, as particles  are  collected by the screen, the
openings are reduced in sice, thus making the  screen become a progressively
more efficient filter.  This filtration effect will then result in depressed
values for particle concentrations and  emission  factors for all particle sizes
that are assumed to be passed by the  screen*   It is worth noting that the
openings in the weaves of fabric filters  used  for  particulate control devices
are comparable to or larger than the  30pm openings used here.10 In Figure 24a
the PEI data obtained in this test series is used  to  illustrate that the
screens undoubtedly do become more efficient filters as a test proceeds.
   Data from other participants, which  will be discussed shortly, indicated
that the particle size distribution remained fairly constant at heights between
1.5m and 4.5m throughout the test series, leading  us to expect that the ratio
of TSP concentration to total concentration would  be constant as well.  The
particulate concentrations obtained from  the hi-vols were previously shown to
be consistent with those measured by  the  profilers at a height of two meters.
Since the profiler and the hi-vol sampling periods were identical, the hi-vol
filter weights can be used as surrogates  proportional to the missing total
weights for the PEI profiler samples  at the two  meter level, and the hi-vol
concentrations as surrogates for the  total concentrations that would have been
obtained by the profiler.  The points plotted  in Figure 24a are the ratios of
the TSP (<30um) concentrations at the two meter  height from FBI's profiler to
those of the collocated hi-vols plotted versus the corresponding hi-vol catch
weight.  As can be seen, the ratio declines as the filter weight, and hence  the
expected total catch weight of the profiler, increases.  Hashes of the sampler
screens and inlets were obtained in each  of tests  8, 9, and 10; consequently,
complete data on the system catches were  available for those sets.  The ratios
of apparent TSP to total concentrations from the lower samplers of FBI's
profiler, where the distribution might  be expected to be fairly constant, are
shown in a similar way for tests 8, 9,  and 10  in Figure 24b.  Again, the ratios
tended to decline as the catch weights  increased.   This is indicative of
decreasing screen penetration as the  profiler  samplers loaded up during a
sampling run.  This filtration effect,  together  with the misassignment of the
initial particle sice cutoff of the clean screen,  is the probable explanation
                                       45

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of why PEI's particle size distribution curve,  shown in Figure 23, fell below
those of the other participants*

     The catch weights of the PBX  samplers  were very near the detection limits
in many cases so operation with shorter sampling times in order to avoid load-
ing the screens is not feasible.   Even in  the  absence of these problems, the
PEI system can provide, at best, questionable  data with respect to PMjQ emis-
sions.  The system is purported to provide  sice distribution information at
only two particle sizes - 2.5pm and 30urn,  - both of which are relatively far
removed from 10pm.  Thus, the 10pm fraction must be estimated by means of some
assumptions regarding the shape of the distribution at each height.  Even the
most commonly used distribution form, the  log-normal approximation, cannot be
used in PEI's normal practice as the total  concentrations are not usually
determined but only the concentrations of particles nominally smaller than 30pm
and 2.5gm.
Scanning Electron Microscopy
     Turning now to the CCSEM method, Figure 25 shows a particle size distri-
bution obtained by EEM/ETC using CCSEM methodology and the distribution meas-
ured by SoRl using a collocated Lundgren cascade impactor.  Six such collocated
sampling runs were carried out and each resulted in particle size distributions
like that illustrated in Figure 25.   The points shown for the impactor results
for sizes smaller than 15 ym are from gravimetric determinations.  The results
which are shown for the impactor for sizes  larger than 15um were obtained in
two ways.  Both of these involved  microscopic  measurement of the size distribu-
tion of the material collected on  the first stage of the impactor and then
apportioning the mass collected by the stage accordingly.  In the first case
SoRl personnel performed manual counts of  random regions of the first stage
substrate of the Lundgren sample using optical microscopy.  These counts were
made in eight size classes based on Feret's diameter.  Similar measurements
were made of all of the Lundgren first stage catches with total of approximate-
ly 500 particles being measured on each.  Secondly, one half of each of the
Lundgren substrates were then sent to ETC  for  analysis of the catches by CCSEM.
Time and cost constraints led to only one  of these actually being analyzed.
                                      47

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filter.  More importantly, the probability of transfer would be low (less than
50%) for any particle larger  than 50pm  with the probability dropping to zero at
210um.  The omission of the particles in the size classes larger than 50 to 80
micrometers obviously introduces a  bias into the final reported distribution,
the severity of which depends on the relative fraction of the mass actually
contained in that fraction.   In the present instance as much as 25 to 50
percent of the total mass was probably  .contained in particles physically larger
than 50 to 80pm.  This mass would be reassigned to smaller particles in the
CCSEM results. Thus the reported OCSEM  distributions would be expected to rise
much more steeply than the true distributions in the size region above about
     Returning now to  the  results  depicted in Figure 25, we find that although
the optical and CCSEM  analyses  are not in complete agreement, both sets of
results show non-negligible  fractions of the total catch to consist of
particles larger than  50pm,  60% and 35% respectively, with 50% and 75%
respectively being larger  than  30pm.   These analyses were carried out directly
on the original specimens  with  no  particle removal and transfer from the
original substrate taking  place in either case.  (The actual results of the
CCSEM measurements of  the  substrate showed less than one percent of the mass
consisted of particles smaller  than 10pm, 22% in the 10 to 30pm range, 25% in
the 30 to 50pm range,  24%  in the 50 to 100pm range, 20% in the 100 to 200jjffl
range, and 9% in the 200 to  500pm  range.)  In contrast, only 5% of the mass on
the collocated profiler sample  was assigned to particles larger than 50pm and
only 20% was assigned  to particles larger than 30pm by the CCSEM analysis.
Even though the size range of the  particles on the substrate was limited  as
compared to that of the profiler filter, measurements of a total of about 4500
particles were needed  in order  to  obtain reasonable statistical validity  in the
data.  In contrast, only about  1000 particles were measured from the profiler
filter even though the size  range  was presumably much larger.  This raises a
question as to whether the number  of particles examined in the routine CCSEM
analyses is in fact sufficient  for obtaining reliable data.

     The lack of large particles in the CCSEM results for all of the profiler
samples may arise from three factors.  First, the analysis may not include
sufficient particles to provide valid results for the statistically rare  large

                                       50

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particles.  Second, the screens  used in the saaple transfer and preparation
procedures for the CCSBM analyses  result in a bias against the inclusion of
large particles.  And third,  the large  particles may simply be lost from the
surfaces of the filters in handling  and transport after the sampling takes
place.  Large particles are not  strongly attached to the filters and are
commonly observed to become detached from filter surfaces.  In the cases of
hi-vol filters which are folded  aid  placed in envelopes for transport, the
large particles are frequently found to migrate to the vicinity of the fold or
off the filter into the envelope while  in transit.  Thus the lack of large
particles in the CCSEM results may simply be a result of a failure in
maintaining sample integrity  and representativeness throughout delivery to the
analytical laboratory.  BTC reported that visual scans of the surfaces of the
EEM and TRC profiler filters  from  these tests revealed no particles larger than
about lOOim present on any of the  samples.  (In the case of the Lundgren
samples, the adhesive used on the  substrates insures that none are lost.)  Thus
the validity of the application  of the  CCSB1 technique to filter samples
containing the large particles encountered in roadway emissions testing is
highly questionable.

     At the other end of the  size  spectrum, it is unlikely that the techniques
used to remove the particles  from  the filters would be effective for removing
individual small particles.   Thus  the bulk of the small particles removed would
be in the form of agglomerates which would be counted as a lesser number of
larger particles.  This would have the  effect of transferring mass from the
fine particle end of the distribution to the midrange thereby depressing the
fine particle end of the distribution and again steepening the apparent distri-
bution.  Manifestation of these  potential problems can be illustrated using
data taken during these tests.   Six  Lundgren runs were made with the impactors
collocated with EEM profiler  samplers.   For these runs, the total particulate
concentrations measured by the profilers and by the impactors were within 6% of
each other on the average (range of  75% to 118%).  At the same time, however,
the average of the ratio of the  fine particle concentration as measured by
EEM/ETC to that measured by the  impactors was only 18% (range 6% to 31%).  At
10pm the average ratio of the BEN  concentrations to those from the impactors
was 72% (range of 32% to 109%).
                                       51

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     Thus aside from the difficulties  in estimating particle volumes and assig-
ning aerodynamic diameters to irregular, inhonogenous particles of the types
encountered here, there appear to be fundamental  difficulties at both the large
and small ends of the size spectrum in the  CCSEH  analyses of roadway emission
samples.  These problems render  the OCSBN methodology,  as used by the
participants of this test, unsuitable  for applications of this type.
Cyclone/lmpactors
     One of the primary advantages attributed  to  FBI's system and to the
CCSEM particles sizing methodology is  that  the methods permit the particle size
determinations to be made directly on  the profiler samples.   Thus the size
distributions can be obtained at each  height from a sample which was acquired
isokinetically.  The MRI methodology on the other hand provides data obtained
directly on an aerodynamic basis using the  well characterized and widely
accepted techniques of inertial  separation  by  cyclones and cascade impactors.
The particle size cuts span  the  range  over  which  data are needed with adequate
resolution.  However, MRI's  data are obtained  at  only two heights (1.5m and
4.5m) from samples that are  taken under only quasi-isokinetic conditions.  The
lack of true isokinetic sampling should constitute no real problem except for
tests conducted under conditions of widely  varying wind velocity.  However, it
would be desirable to have particle size data  for at least one more height, say
about 7m.

   Although MRI measures the particle  size  distribution by a means for which
the results are inherently on an aerodynamic basis, there are potential prob-
lems related to the operation of the actual hardware used.  First, particle
collection in the cyclone takes  place  in two distinct zones, the main body of
the cyclone and the outlet tuba. Particles caught in the main body are fully
contained by the body cavity and cannot be  transferred to succeeding parts of
the sampler by jostling or vibration during and after sampling.  However, a
large part of what is considered by MRI to  be  the cyclone catch in reality
collects on the wall of the  exit tube  and transform to the impactor.  There is
no way to insure that this material will remain in place during sampling or
transport and cleanup after  sampling.   The  cutoff diameter for the cyclone body
catch is about 22ym at the nominal operating flow rate while the cutoff diame-
                                            52

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ter for the combination of the body and outlet tube is about 14ym.  (These cut
diameters are based on the results of  recent recalibrations11  that were per-
formed on MRI's behalf and differ significantly from previously reported
values.12 The new calibrations would alter  the results of PM15 and PMIQ
emissions which were reported in some  of  MRI's previous work.)  If the combined
body and outlet catches are used, as is MRI's practice, the possibility exists
that some part of the catch will be dislodged and transferred from the plus 14
urn part of the size distribution defined  by the cyclone to the 10pm to I4ym
fraction collected by the first stage  of  the impactor.  Uncertainties from this
can be avoided by separate recovery of the  material from the cyclone body and
the outlet tube and treating the outlet tube catch as part of the catch of the
first impaction stage.

     A second area of potential concern in  MRI's sizing methodology is related
to their treatment of the impactor backup filter data.  Particle bounce has
long been a problem plaguing cascade impactor usage and the Sierra Model 235 is
no exception in this regard.  In developing their roadway emissions protocol,
MRI tried a number of approaches, including greases on the collection sub-
strates, the use of the inlet cyclone  to  reduce overloading and bounce problems
at the first stage, and operation at reduced flow rate - approaches which had
all proven useful in other cascade  impactor operations in the past.  Originally
the Sierra impactor was quoted by the  manufacturer as being usable at the stan-
dard hi-vol flow rate of 68 cubic meters  per hour (40 cfm); however, it soon
because apparent to MRI that particle  bounce and blowoff were very real prob-
lems under those conditions.

     At the time these problems were being  resolved the complete five-stage
impactor was being used.  Because the  principal error resulting from particle
bounce is to transfer material which should be collected by the upper stages of
the impactor to the backup filter, MRI began compensating for the effect of
bounce by using the lesser of two weights for the backup filter catch.  These
weights being either the actual filter catch or the average of the catches of
the two previous stages.  The magnitude of  the bounce errors were greatly
reduced by adding the cyclone and dropping  the sampling rate to 34 cubic meters
per hour (20 cfm).  But in spite of  the  reduction in the potential errors

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PARTICLE SIZING RECOMMENDATIONS
               *
     The recommended procedure for  meaauring the particle size distribution is
MRI'S cyclone/impactor  technique with  some modifications.  With regard to field
operations.

     With regard to field operations,  first, a further reduction in the
sampling flow rate from 20cfm to  15cfm would help minimize errors from particle
bounce.  Experience has shown that  the product of jet velocities, V, and DSO's
of impactor stages must be  limited  to  values below maximums which depend on the
type of substrate used. If the jet velocities are expressed in meters per
second and the DSO's are expressed  in  micrometers, the limits for the product
are 15pm»m/s for glass  fiber substrates and 25ym m/s if adhesive coated
substrates are used.  Operation of  the impactor at a flow rate of 20cfm results
in V«/D50 products in excess of the limit for the glass substrates which are
used.  Operation at IScfm reduces  the  products to acceptable values.
Alternatively, adhesive coated substrates could be used at the current 20cfm
flow rate.  Second, potential errors resulting from the possible transfer of
material from the outlet tube of  the cyclone to the first stage of the impactor
can be avoided by counting  only the material collected in the body of the
cyclone as its catch.   The  outlet tube catch would then be combined with that
of the first impactor stage. At  the current 20cfm flow rate, this would result
in a cyclone D50 of 22pm being used rather than the current 14pm value.
Lastly, while particle  size was measured at the lower elevations (1.5m and
4.5m) an additional cyclone/impactor unit located at a height of about 7m would
provide additional information regarding the changes in size distribution as a
function of height within the dust  plume.

     With respect to data analysis, a  better technique than the current MRI
procedure would be that commonly  used  in reducing impactor data from industrial
sources.13,11*     In the latter,  a  spline fit is made to the cyclone/impactor
data in the cumulative  percentage from of the distribution.  The fit is made in
a manner that requires  continuity in the slope of the curve and the solution is
                                      55

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forced to be asymptotic to  100% at a diameter equal to the maximum diameter
present in the sample.  The fitted curve  is  then used to interpolate or
extrapolate as needed to obtain the mass  fractions  in the selected size
intervals.  This technique  avoids the  requirement of assuming a functional form
for the distribution and makes use of  the complete  data set rather than just
'two of the data points.                                :
                                        56

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                                 SECTION  6
                        EXPOSURES AND  EMISSION  FACTORS

     Exposure ia defined as  the  total  incident  particulate mass, in the
selected size range, per unit area  in  a vertical plane parallel to the roadway.
The integral of exposure versus  height is thus  equal to the particulate emis-
sions per unit length of roadway during the  test.  The emission factor is
obtained by dividing by the  number  of  vehicles  passing the sampler during the
test.  Accurate measurement  of emission rates from the resuspension of road
dust by vehicular traffic thus hinges  on  the exposure measurements and subse-
quent integrations.
METHODOLOGIES
     All participants in the program,  both during the methods review (Phase
I) and the field test (Phase II), use  variants  of the profiling technique first
developed by MRI1.  However, there  are several  differences among the various
organizations in the detailed manner with which the method is employed.  Spe-
cific differences include the number of samplers employed, the heights at which
exposures are measured, the  approach used to obtain representative (isokinetic)
samples, the method used to  measure the background aerosol, the method used to
integrate the exposure curves to obtain emission factors,  and the method used
to partition the emissions into  the various  particle size classes of interest.
The following paragraphs discuss all of these differences except for those
related to particle size.  Discussions of particle sizing are contained in
Section 5 of this report.
Sampling Isokineticity
     All organizations involved  in  both phases  of the study attempt, to
varying extents, to perform  the  exposure  sampling in an isokinetic fashion.
USS and TRC use servo systems with  individual velocity sensors at each sampling
inlet to provide continuous  adjustment of the flow rate for each sampler.  ElA,
EEM, and PEI sample at fixed flow rates which are set based on the wind
velocity measured during a short time  period immediately prior to the start of
                                   57

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sampling. EIA and FBI do  alter  sampling flows in the event of sustained gross
changes in windspeed.  The  latter  three organizations (EIA, EEM, and PEI) use  a
measured windspeed at a single  height coupled with an assumed functional form
for wind shear to obtain  the  velocities for setting the flow rates of the
individual exposure  samplers.   Finally, MRI periodically adjusts the sampling
flows based on an assumed logarithmic vertical windspeed distribution fit to
measured speeds at two heights. Those organizations not using continuous
individual servo controls to  maintain isokinetic sampling flow rates correct
their resulting exposure  values by factors based on the mean inlet velocity for
each sampler, the mean calculated  windspeed at each sampling height, and the
particle size distribution.   Tests for which the ratio of mean sample inlet
velocity to mean windspeed  falls outside the range 0.8 to 1.3 are voided by all
participants.  The velocity ratio  approximates the limit of the ratio of true
exposure to measured exposure so the condition imposed insures that the errors
caused by deviations from isokinetic sampling will be relatively small.

     All organizations maintain the pointing angle of the sampler inlets no
greater than 30 degrees from  the mean wind direction (20 degree limits for EIA
and EEM, and a 15 degree  limit  for PEI).  No correction is made for the mean
angle of the wind with respect  to  the road by any of the organizations.  This
causes a positive bias in the results proportional to the secant of the wind
angle with respect to the road. At a 15 degree angle the error is 3 percent
and at 45 degrees it increases  to  40 percent.  All of the testing organizations
void tests in which  the mean  angle of the wind with respect to the road is
greater than 45 degrees,  so 40  percent is the greatest error which can be
introduced by ignoring the  angle factor*
Exposure Integration
     Integration of  the measured exposures for calculating emission rates are
performed using the  trapezoidal rule by BBN,  PHI,  and USS.  BIA has also used
this method in the past,  but  their Phase I current procedures documents sug-
gested that in the future they  would use a least squares fit of a half-gaussian
distribution to the  measured  exposure profile.  This procedure was proposed to
eliminate difficulties in extrapolation of exposures near the ground and above
                                        58

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FIELD TEST RESULTS

     The results obtained by the  five sampling organizations during the
five-day field comparison are summarized  in  Table 3.   As shown in this table
eleven separate tests were carried out  to characterize the emissions from the
simulated unpaved road.  Rotation of the  testing parties through the sample
locations was carried out on a daily basis as  seen in columns 2 and 3.  Data in
columns 6 through 18 were extracted from  the Field Comparison Final Reports
produced by each of the five testing companies.   As seen in these entries, some
test parameters were either not measured  or  not explicitly reported by the
various organizations.  Some of the data  variations between contractors for a
given test are explained by the fact that occasionally some of the testing
parties were late in starting and stopping their profiler systems and conse-
quently sampled over either a different number and/or type of vehicle passes.
Also there were some variations reported  in  the vehicle weight estimates, but
these differences were not significant.
               \ •
     In column 24 of Table 3, the values  of  particulate concentrations obtained
with standard high volume samplers are  tabulated.  In obtaining these data,
standard hi-vol samplers were placed at each sample location.  These samplers
were not rotated with the sampling parties and served as monitors of the
changes that took place throughout the  test  for each sampling location.
Total Particulate Emission Factors
     Of the five field test participants, four purportedly measure total
particulate emission factors while the  fifth,  PEI, normally measures only the
fraction nominally smaller than 30 ym.  The  average total emission factors for
the complete test series are summarized in Table 4.  For the four contractors
whose methods normally provide total emission  factors.  the average values were
8.34, 8.25, 8.41, and 5.73 kg/VXT.  The last value (5.73 kg/VKT) is
significantly different from the  other  three at the 90% confidence level.  TRC,
whose data produced that result,  stated in their report that their values were
generated from profiler filter catches  only  and did not include nozzle and
inlet washes.  Although the omission of the  latter material could explain the
                                        60

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                      Table  3.    COMPARATIVE  FUGITIVE  EMISSION TEST  RESULTS.
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                            TABLE 6.  (continued)
                              EXPOSURE, mg/cm2
TEST 5
ORGANIZATION TRC PEI USS MRI BEN
POSITION 12345
HEIGHT, m
10 ,0.43
9 0.34 0.42
8 0.71
7.5 1.14
7 1.02
6.5 1.09
6 0.78 1.44
5 2.56
4.5 2.08 1.21
4 2.20
3 3.92 2.15
2.5
2 3.51 3.35
1.5 0.60
1 4.49
Reported
mission
Factor,
kg/VKT 5.90 4.84 2.54 5.00
SoRI
Emission
Factor,
kg/VKT 5.65 4.56 3.73 4.40
6
EEM TRC PEI USS MRI
1 2345

0.45
-0.32 1.10
1.06
3.46
0.57
2.04
2.15 4.04
2.19
4.32 6.00
3.15
3.11 6.49

3.72 5.67
5.08
4.22
5.49 4.40 7.79 11.50
5.13 4.46 7.28 10.24
NOTEi   SoRI Emission Factor it from integration by  the  trapezoidal rule with
       linear extrapolation to eero at  the  top of the profiler and constant
       exposure from the lowest height  to the ground.
                                         68

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                            TXBLB 6.   (continued)
                              EXPOSURE, mg/cm2
TEST 7
EEM TRC FBI OSS MRI
ORGANIZATION 12 34 5
POSITION
HEIGHT, m
10 0.88
9 0.62 1.89
8 1.46
7.5 2.33
7 1.40
6.5 2.97
6 2.78 2.91
5 2.20
4.5 5.03 3.56
4 5.71
3 3.29 5.77
2.5
2 7.76 7.49
1.5 2.35
1 4.18
Reported
Emission
Factor,
kg/VKT 11.58 5.85 12.28 7.16
SoRI
Emission
Factor,
kg/VKT 10.80 5.64 11.44 7.30
8
MRI EEM TRC PEI USS
12 3 4 5


0.03
0.15 2.41 0.74
0.47
0.55
0.98
2.03
1.73 2.54
2.74 4.46
4.44 5.21
5.89
7.73 4.40
3.36
8.39 6.99
8.89
5.50 10.40


6.26 7.46 4.54 7.81 6.59


6.89 7.05 4.49 7.47 6.60
NOTEi   SoRI Emission Factor i* from  integration by the trapeeoidal rule with
       linear extrapolation to eero  at  the  top of  the profiler and constant
       exposure from the lowest height  to the  ground.
                                        69

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                               TABLE 6.   (continued)
                                 EXPOSURE, tag/cm2
TEST
           11
ORGANIZATION
POSITION
HEIGHT,m
   10
   9
   8
   7.5
   7
   6.5
   6
   5
   4.5
   4
   3
   2.5
   2
   1.5
   1
 USS   MRI   EEM    TRC   PEI
  123      45
             0.08
 0.39               0.11
             0.64
       0.74
                    0.83
 1.24
       2.40  2.06
                    1.95
 4.35  5.19
             3.69
       6.52         3.72

 7.14        5.86
       5.32
                    4.78
Reported
Emission
Factor,
kg/VKT
9.61  8.68  8.16   5.74
SoRI
Emission
Factor,
kg/VKT
8.87  8.36  7.29   5.40
   NOTEi   SoRI Emission Factor  is  from  integration by the trapezoidal rule with
           linear extrapolation  to  terp  at the  top of the profiler and constant
           exposure from the  lowest height to  the ground.
                                        71

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K>
C3

U
        10
         8
                                                         uss
                                                       0 MRI
                                                       • EEM
                                                       Q TRC
                                                       TEST1
                   1
3579
EXPOSURE  (MG/-CM2)
                                                      11     13
             Figure 27.  Measured total exposures versus height for Test 1 for all contractors
                      providing total particulate exposure data.

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   10
     8
in
                                •f uss
                                O MRI
                                0 EEM
                                Q TRC

                                TEST 2
              1
3       5      79
EXPOSURE  
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   10
     8
CP
                                + uss
                                0 MRI
                                • EEM
                                H TRC
                                TEST 3
              1
3579
EXPOSURE  
11     13
        Figure. 29-  Measured total exposures versus heiqht for Test 3 for all contractors
                 providing total particulate exposure data.

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   10
     8
£   6
u
u   4
 + uss
 0 MRI
 • EEM
 Q TRC
 TEST 4
              1
3       5      7      9
EXPOSURE  (MG/CM2)
11     13
       Figure  30. Pleasured total exposures versus heiqht for Test 4 for all contractors
                providing total particulate exposure data.

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       10
        8
09
O
                                  uss
                                O MRI
                                • EEM
                                Q TRC
                                | PEI
                                TEST 9
                e
                  1
3       5      7       9      11
EXPOSURE   
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       10
         8
CD
K>
4
                   1
                                                    uss
                                                  0 MRI
                                                  • EEM
                                                  Q TRC
                                                  TEST 11
3       5      7      9      11
EXPOSURE  (MG/CM2)
                                                         13
            Figure  37. Measured total exposures versus height for Test 11 for all contractors
                     providing total particulate exposure data.

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For some size fractions and  test numbers the differences between the two
entries are small, but for others they are quite significant.

     The SORI recalculated values of  particulate size fraction shown in Table  8
were used to define size specific average measured emission factors for each of
the 11 tests.  This was accomplished  in the following manner.  For each of  the
11 tests, the measured TP emission factor values shown in column 19 of Table 3
were averaged to obtain the  values shown in column 2 of Table 9.  The entries
in the other columns of Table  9 (TSP, PMj-r PMIQ' *"* **) were obtained by
multiplying the average TP value (column 1, Table 9) by the appropriate SoRI
size fraction entry in Table 8.   For  example, for Test Number 1, the average
emission factor for TP is, from column 19 of Table 3t  (8.56 + 9.33 + 10.24 +
7.1D/4 - 8.81 kg/VKT as shown in Table 9, column 2.  The average emission
factor for TSP is calculated using the SoRI Test Number 1 entry in Table 9,
column 4 and the average TP  abovet  (0.453) x (8.81) « 3.99 kg/VKT as shown in
Table 9, column 3.  The remaining entries in this table were calculated in  a
similar manner.  Thus, the values shown in Table 9 were used as a best estimate
against which the results of the five predictive equations were compared.

     As mentioned in Section 6,  there were differences in the reported input
values as shown in Table  3.  Some of  the data variations between contractors
for a given test are explained by the fact that occasionally some of the
testing parties were late in starting and stopping their profiler systems and
consequently sampled over either a different number and/or type of vehicle
passes.  Also there were  some  variations reported in the vehicle weight
estimates.  In an effort  to  remove the effects of these differences on the
predicted values of the emission factor/ each of the predictive equations were
evaluated using the entire set of test parameters (columns 10 and 13-18 of
Table 3) for each of the  11  tests. These predicted emission factor values  for
TP, TSP, PM1S, PMj0» and  FP  were then averaged for each test number and
equation used.  For example, the average predicted TP emission factor for Test
1 using EEM's equation was determined by using each of the five sets of
                                      83

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                                  SECTION 7
                                                          t
                          MODELING FUGITIVE EMISSIONS

     One objective of this study was to correlate the  various  predictive
equations for unpaved roads and to identify or develop,  if  feasible,  an equa-
tion or set of equations that best account for observed  differences.   As a
final step in their analysis of the field test data, each participant was to
develop a predictive equation for the test road.  The  results  of these efforts
along with an analysis of each is presented in the  following paragraphs.
PREDICTIVE EMISSION FACTOR EQUATIONS
     Three of the five participants (MRI, TRC, and  OSS)  used the existing
predictive equation described in Supplement No.  14  of  the AP-42 document.16
This equation is
                                                                          (D
where E - emission factor, kg/VKT
      k - particle size multiplier, dimensionless
      s • silt content of road surface  material, % passing a 200 mesh screen
      S - mean vehicle speed, km/hr
      W • mean vehicle weight, Mg  (metric  tons)
      w - mean number of wheels, dimensionless
      p • number of days with at least  0.2S4  mm of precipitation per year,
          dimensionless.

For the current series of tests the factor involving p was omitted.  The values
for the particle sice multiplier k as listed  in the AP-42 document are: 0.80
«30 um), 0.57 «15 ym), 0.45 «10 pa),  0.28  «5 gn), and 0.16 «2.5 u">).  No
value is listed for total particulate TO.   Each of those organisations using
Equation (1) derived different values for  the sise multiplier k.
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     The other two participants  (BEN and FBI)  developed their own predictive
equation based pn the parameters measured during  this  test series.  FBI used a
multiple linear regression analysis to develop the  predictive equation

                                 B - k(*)a(m)b                           (2)

where m - road surface moisture  content, %,  and the constants k, a, and b are
dependent upon the size fraction of the particulate being considered.  BEM also
used a multiple regression technique to develop the following predictive equa-
tion

                    B - k(.)°-139(R)-0-203(w)0-267(W)0-395               (3)

where R « ambient relative humidity, percent;  and the  other parameters are as
defined previously.    The values of the constants  in. Equations (1), (2), and
(3) for all organizations are summarized in  Table 7.  It is important to notice
that FBI's equation is applicable only for predicting  ISP, PN10, and PP emis-
sions.  Also the term containing soil moisture in Equation (2) is applicable
only for the FP fraction*

     In evaluating these predictive equations, the  question arises as to which
of the measured emission factors should be used for comparison.  In view of the
limitations of the particle  sizing  techniques  as  discussed earlier, probably
none are truly representative of the actual  road  conditions with MRI's results
being the most nearly representative.

     For physical reasons, the particle sizing techniques used by NRI have a
higher probability of correctly  describing the actual but unknown dust size
distributions.  However, because of uncertainties in MRI's data reduction proc-
ess, the "as reported" size  distributions are  somewhat questionable.  As a
result, the raw data reported by NRI  (filter weighings, cyclone washes, etc.)
were independently reduced using the cascade impactor data reduction
techniques13 described at the end of Section 5.  The results of these
recalculations are tabulated in  Table  8 along  with the values reported by NRI.
                                      86

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test parameters (columns  10 and  13-18  of Table 3)  as'inputs to Equation  (3).
The five resulting values were averaged to represent a best theoretical
approximation ta the TP emission factor for Test Number 1 using EEM's predictor
equation.  A similar process  was carried out for each predictive equation and
all size fractions.

     In order to compare  these theoretically predicted emission factors  to  the
best estimates of those measured in the field, as shown in Table 9, a
correlation/regression analysis)  was carried out.  The results of applying this
analysis to EEM's equation are summarised in Figure 38.  In this scatter
diagram the predicted values  of  TP  emission factor are plotted versus the
measured values for each  of the  11  tests.  In this figure there are shown two
sets of data.  The filled circles correspond to the paired values of the
average predicted emission factors  uoing Equation (3) and the average measured
values shown in column 2  of Table 9.  The open circles correspond to the paired
values of the predicted emission factor based on only one input data set per
test, and the values measured by that  specific organization,  in brief,  the
filled circles depict how well EEM's equation can predict emission factors
based on the average measured values for total particulate from all con-
tractors.  The open circles demonstrate the degree in which EEM's equation  can
predict the actual data measured by EEM.  For either set of points, if the
predicted and measured values of the emission factor were in a one-to-one
correspondence, the points would all lie along the solid diagonal line.  The
other lines in the figures represent the least squares linear regression lines
for the data.  The dotted line is the  regression line for the filled symbols
and the simple broken line that  for the open symbols.  The values of the least
squares correlation coefficient* (r),  and the coefficients of the regression
line in Figure 38 are shown in Table 10.

     Thus in Figure 38, EEM's emission factor predictive equation for TP is
moderately well correlated with  the average of the values measured (r •  0.68)
and also with their own measured value (r « 0.61).  Also, the slopes of  the
regression line for the averaged data  and their own data (as shown in Table 10)
are within 54% and 80%, respectively,  when compared to the one-to-one
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correspondence line.  Because  of  the  offset in the intercept values  (-3.79 and
-6.48) EEH's predictive equation  would under predict at low values of the TP
emissions and over-predict  at  higher  values.

     A ainilar analysis was applied to each of the five predictive equations
and the results shown in Table 10 and Figures 39 through 60.  By examining the
values in Table 10  it can be seen that for the case of the TP emission factors,
the errors in the slopes of the regression lines range from 54% to 318% for the
averaged data and from 80%  to  1182% for the individual data.  Thus,  even though
the correlation coefficients for  the  averaged data are very nearly the same,
the various predictive equations  will in general over-predict the measured
values by varying amounts.

     Although the data base used  for  these statistical analyses was  limited,
some general comments regarding the various predictor models can be  made.

     e MRI's equation consistently over-predicts the results measured here for
       all size fractions  considered.

     e TRC's equation predicts results similar to that of MRI as might be
       expected.  The over  prediction at TP is less .than MRI's, and  the TSP is
       greater  than MRI's  results reflecting the different  values of k used
       (see Table 7).  This is especially true for FP fraction.  Here TRC's
       equation severely  under-predicts the average measured results while
       predicting their own data quite well as seen in Figure 59.  This is due
       primarily  to the  fact that those using CCSQl techniques  simply do  not
       see  the  entire  fine particulate fraction of the dust.

     o USS's equation predicts results very much the same as TRC and is expli-
       cable for  the same reasons*

     e gat's aquation  appears  to do a better job of predicting  the average  test
       results.   This  is  primarily due to the fact that  the equation was  de-
       rived based  on the current data bam*  (11 tests).  How well  this  predic-
       tive equation can be applied to previous data has not been  determined.
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       The severe under-prediction of the FP fraction  as  seen in Figure 56 is
       again due to the inability of the CCSEM  techniques to correctly describe
       the particulate size distribution.

     o PEI's equation consistently under-predicts  the  averaged data from these
       tests while giving moderately good agreement to their own dfta.  This
       reflects the conclusions drawn earlier regarding the stacked filter
       system.

     In general the results of this analysis would suggest that either the
predictive equation of BEN or that used by MRI,  TRC, and  USS would adequately
represent the results of this test series if appropriate  values were chosen for
the constants in Table 7.  The FBI relation is  seen to be inadequate primarily
because the underlying TSP data base was systematically low.

MODELING RECOMMENDATIONS

     The utility of an emission factor predictive  equation is not necessarily
that of predicting the emissions  from a particular site in lieu of actual
measurements.   In order  that  the  equation be applicable over a wide range of
site locations  and conditions, it should include as many of the relevant
parameters describing the site as possible.  This  requires that the predictive
equation be developed from a* large a data base as possible.

     Equation (1) above  is just such a relation.  It was developed from a
fairly broad data base using multiple  linear regression techniques.  The data
base has some uncertainties particularly with  regards  to the particle size
distributions.  These uncertainties most certainly cast some doubt upon the
precision  of the values used for the particle  size multiplier, k, in Equation
(1).  However,  without an extensive evaluation  of the  existing unpaved road
emissions data  base, there are no justifications for invalidating the relation
used by MRI, TRC, and USS.
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     This predictive equation  (Equation^(2))  developed by PEI is considered
inadequate because it wa« derived ugin? an  invalid TSP data base.  Although the
relation (Equation (3)) developed by BEM did  quite well predicing the results
of this test series, the data  base  froa which it was  derived is too small to
give it much creditability for other ait«t  without extensive validation.

     In summary, the predictive emission factor equation used by MRI, TRC, and
USS and as described in the AP-42 manual^*  is probably the most reliable
predictor of unpaved road emissions currently available.  Because of past
problems in the particle sizing techniques, the values used for the size
multiplier (k) are less reliable than  the overall equation.  It is recommended
that these, values be re-evaluated in the future as the data base is expanded
with more reliable particle sice information.
                                      95

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