United States                    EPA-600 /7-84~077
               Environmental Protection
               Agency                       July 1984
<>EPA        Research and
               Development
               PAVED ROAD

               PARTICULATE EMISSIONS

               Source Category Report
               Prepared for
               Office of Air Quality Planning and Standards
               Prepared by

               Industrial Environmental Research
               Laboratory
               Research Triangle Park NC 27711

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                 RESEARCH REPORTING SERIES


Research reports of the Office of Research and Development, U.S. Environmental
Protection Agency, have been grouped into nine series. These nine broad cate-
gories were established to facilitate further development and application of en-
vironmental technology. Elimination  of  traditional  grouping was consciously
planned to foster technology transfer and a maximum interface in related fields.
The nine series are:

    1. Environmental Health Effects Research

    2. Environmental Protection Technology

    3. Ecological Research

    4. Environmental Monitoring

    5. Socioeconomic Environmental Studies

    6. Scientific and Technical Assessment Reports  (STAR)

    7. Interagency Energy-Environment Research and Development

    8. "Special" Reports

    9. Miscellaneous Reports

This report has been assigned to the INTERAGENCY ENERGY-ENVIRONMENT
RESEARCH AND  DEVELOPMENT series. Reports in this series result from the
effort funded  under the 17-agency Federal Energy/Environment Research and
Development Program. These studies relate to EPA's mission to protect the public
health and welfare from adverse effects of pollutants associated with energy sys-
tems. The goal of the Program is to assure the rapid development of domestic
energy supplies in an environmentally-compatible manner by providing the nec-
essary environmental data and control technology. Investigations include analy-
ses of the transport  of energy-related pollutants and their health and ecological
effects;  assessments of, and development of, control technologies for energy
systems; and integrated assessments of a wide range of energy-related environ-
mental issues.
                        EPA REVIEW NOTICE
This report has been reviewed by the participating Federal Agencies, and approved
for  publication. Approval does not signify that the contents necessarily reflect
the views and policies of the Government, nor does mention of trade names or
commercial products constitute endorsement or recommendation for use.

This document is available to the public through the National Technical Informa-
tion Service, Springfield, Virginia 22161.

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                                     EPA-600/7-84-077
                                     July 1984
   PAVED ROAD PARTICULATE EMISSIONS

            Source Category Report
                      by
 Chatten Cowherd, Jr. and Phillip J. Englehart
           Midwest Research Institute
             425 Volker Boulevard
          Kansas City, Missouri 64110

       EPA Contract 68-02-3158, Task 19

     EPA Project Officer:  Dale L. Harmon
 Industrial Environmental Research Laboratory
 Research Triangle Park, North Carolina 27711
                 Prepared for:


U.S. ENVIRONMENTAL PROTECTION AGENCY
      Office of Research and Development
            Washington, DC 20460

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                                   PREFACE
     This report was prepared for the Environmental Protection Agency's In-
dustrial Environmental Research Laboratory under EPA Contract No. 68-02-3158,
Technical Directive No.  19.       Dale L.  Harmon was the project officer and
William    B. Kuykendal was  the  task manager for the preparation of this
report.      Dennis C. Drehmel and     William B.  Kuykendal served as tech-
nical project officers for the field testing portion of the study.
                                    i1

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                                 CONTENTS

Preface	   ii
Figures	   jv
Tables 	    v

     1.0  Introduction 	    1
     2.0  Background Information 	    3
               2.1  Street dust composition	    3
               2.2  Street dust loadings	    4
               2.3  Deposition and removal processes 	    4
               2.4  Traffic-generated emissions	    7
     3.0  Sampling Site Selection	    9
               3.1  Site presurveys	    9
               3.2  Site selection	   12
     4.0  Sampling Equipment 	   19
               4.1  Air sampling equipment	   19
               4.2  Roadway dust sampling equipment	   26
               4.3  Vehicle characterization equipment 	   26
     5.0  Sampling and Analysis Procedures 	   29
               5.1  Preparation of sample collection media 	   29
               5.2  Pre-test procedures/evaluation of sampling
                      conditions	   33
               5.3  Air sampling	   34
               5.4  Sample handling and analysis 	   34
               5.5  Emission factor calculation	   36
     6.0  Test Results	   37
               6.1  Test site conditions	   37
               6.2  Street surface particulate loadings	   41
               6.3  Airborne particulate concentrations	   41
               6.4  Emission factors 	   45
     7.0  Multiple Regression Analysis 	   51
               7.1  Introduction	   51
               7.2  Analysis and results	   53
               7.3  Comparative evaluation 	   58
               7.4  Extension of the predictive equation to
                      different particulate size fractions 	   61
               7.5  Emissions inventory applications 	   62
     8.0  Summary and Conclusions	   67
     9.0  References	   69

Appendices

    A.   Emission Factor Calculation Procedure	A-l
    B.   Correction Parameter Calculation Procedures	B-l
    C.   Proposed AP-42 Section 	  C-l
                                    111

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                                  FIGURES


Number

  1  Empirical relationship between sampler catch and traffic
       volumes 	

  2  Parameters for calculations of angle of unobstructed wind
       flow	   16

  3  MRI exposure profiler 	   21

  4  Sampling equipment deployment for winter testing in Greater
       Kansas City Area	   23

  5  Sampling equipment deployment "A" for spring testing in
       Greater St. Louis Area	   24

  6  Sampling equipment deployment "B" for spring testing in
       Greater St. Louis Area	   25

  7  Predicted versus observed IP emission factors by land use
       category	   57

  8  Comparison of emission factor models	   60

A-l  Downwind particle size distribution measured at a height of
       1 m for Run M-3	A-5

A-2  Downwind particle size distribution measured at a height of
       3 m for Run M-3	A-6

A-3  Exposure profile for Run M-3	'	A-9
                                     IV

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                                     TABLES


Number

  1  Contaminant Loadings on Urban Street Surfaces 	    5
  2  Estimated Deposition and Removal Rates	    6
  3  General Sampling Areas Designated by EPA	   10
  4  Field Data Requirements for Each Sampling Site Presurvey. ...   11
  5  Application of Selection Criteria to Candidate Sampling Sites  .   18
  6  Field Measurements	   20
  7  Quality Control Procedures for Sampling Flow Rates..	   30
  8  Quality Control Procedures for Sampling Media 	   31
  9  Quality Control Procedures for Sampling Equipment 	   32
 10  Quality Control Procedures for Data Processing and
       Calculations	   33
 11  Criteria for Suspending or Terminating an Exposure Profiling
       Test	   35
 12  Winter Test Site Conditions	   38
 13  Spring Test Site Conditions	   39
 14  Acceptable Tests for MLR	   40
 15  Paved Road Surface Dust Loadings	   42
 16  Particulate Concentrations and Plume Height 	   43
 17  Summary of Particulate Size Ratios	   44
 18  Paved Road Emission Factors 	   46
 19  Source Characterization Parameters	   47
 20  Summary of Paved Road Emission Factors	   48
 21  Summary of Source Characterization Parameters 	   49
 22  Correlation Matrix for Entire Data Set	   54
 23  Correlation Matrix for "MRL" Data Set	   54
 24  Predicted Versus Observed IP Emission Factors 	   56
 25  Paved Road Emission Factor Equation Parameters	   62
 26  Paved Roadway Classification	   63
 27  Summary of Silt Loadings (g/m2) for Urban Paved Roadways by
       City	'	   64
 28  Recommended Emission Factors for Specific Roadway Categories
       and Particle Size Fractions	   65
A-l  Inhalable Concentrations and Exposures	A-3
B-l  Silt Analysis Procedures	B-2

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                             1.0  INTRODUCTION
     Traffic-entrained participate from paved roads has been identified as
a major cause of nonattainment of air quality standards for total  suspended
particulates (TSP)  in urban areas.1  Therefore, the quantification of this
source is necessary to the development of effective strategies for the at-
tainment and maintenance  of  the TSP standards,  as well as the anticipated
standard for inhalable particulate.

     Based on previous limited field testing of this source,2 suspended par-
ticulate emissions  have been  found to vary  in direct proportion to traffic
volume and  surface  loading of fines  on the  traveled portion  of the street.
Measured emission factors for street particulate reentrainment added to ve-
hicle exhaust  have  been  found to be an order of magnitude larger than the
factors for vehicle exhaust alone.3

     This document  presents the  results of  an expanded measurement program
to develop particulate emission factors for paved roads.   The emission sam-
pling procedure used in this  program provided emission factors for the fol-
lowing particle size ranges:

     IP = Inhalable particulate  matter consisting of particles equal  to or
            smaller than 15 urn in aerodynamic diameter

     PM-10 = Particulate matter consisting of particles equal to or smaller
               than 10 urn in  aerodynamic diameter

     FP =  Fine particulate matter  consisting of particles  equal  to or
            smaller than 2.5  urn in aerodynamic diameter

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Results are  presented  for winter  testing  in  the  Kansas  City,  Missouri  area
and spring testing in areas of St. Louis,  Missouri and Granite City, Illinois
These results are used as a basis for the  derivation of a matrix of emission
factors for specific road categories and particle size ranges.

     The presentation of this report is organized in the following sequence:

          Section 2  -  Background Information
          Section 3  -  Sampling Site Selection
          Section 4  -  Sampling Equipment
          Section 5  -  Sampling and  Analysis  Procedures
          Section 6  -  Test  Results
          Section 7  -  Test  Data  Reduction  and  Analysis
          Section 8  -  Conclusions and  Recommendations
          Appendix A  -  Emission Factor  Calculation  Procedure
          Appendix B  -  Correction  Parameters  Calculation  Procedures
          Appendix C  -  Proposed AP-42 Section

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                        2.0  BACKGROUND INFORMATION
     This section  reviews  published  background  information  on  the  dynamics
of the paved roadway dust emissions problem.

2.1  STREET DUST COMPOSITION

     In a comprehensive study of runoff from street surfaces as a source of
water pollution,4 81 samples were taken from streets in 12 cities by vacuum
sweeping and/or  flushing.   The  samples were dry sieved  and  chemically  ana-
lyzed to determine composition.   The major  constituent  of  street  surface
contaminants was  consistently  found  to be  mineral-like  matter similar to
common sand  and  silt.   Typically,  78% of  the material  was  located within
6 in. from  the curb  and 88% within 12  in.  from  the  curb.  The  silt content
of the material  (particles smaller than 75  micrometers  (urn)  in diameter)
fell in  the  5  to 15% range  reported  elsewhere5 7  for surface  dust from
paved streets and parking  lots  and from  gravel  roads  and parking lots.   In
addition, it was  found  that 5.9% of the  material  was less than 43 urn  in
size.  The  silt  size fraction,  which  is  readily suspendable  in the atmo-
sphere, was  found to contain more than  proportional  amounts  of the total
heavy metals and pesticides.

     In a study  which  entailed a comprehensive  review on the  topic of  re-
entrained dust from paved streets,8 129 samples  of street surface materials
were taken  in Kansas City  and Cincinnati  by means  of broom sweeping  and
subsequent vacuuming.  The  samples were  weighed and analyzed  by microscopy
to determine the  particle  size distribution.   The  results  of the  sample
analyses showed  that approximately 9.5%  of the  paved  road surface  material
was less than 44 urn  in size.

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2.2  STREET DUST LOADINGS

     Table 1 summarizes  the results of field measurements  of  surface load-
ings at sites in 12 cities.4  In addition to land use characteristics, dust
loadings were found to depend  on:

          Time elapsed since  the  last cleaning by mechanical  means  or by
          substantial rainfall (exceeding 0.5 in.  accumulation).

          Street  surface  characteristics:   asphalt  streets had loadings
          that were  80%  higher  than concrete-surfaced streets;  and  streets
          in  fair-to-poor  condition  had  loadings  about  twice  as high as
          streets in good-to-excellent condition.

          Public works practices:   average loadings were reduced by  regular
          street  cleaning  (as  reflected  by  lower values  for  commercial
          areas),  and  loadings  were increased during winter in  areas where
          sand and salt were applied.

Although  traffic  speed and density were  believed to be important factors,
effects  of  these  parameters could  not be  separated from  more  dominant fac-
tors  such as land use.

2.3   DEPOSITION AND  REMOVAL PROCESSES

      On  the  average,  vehicular  carry-out  from unpaved areas (unpaved roads
and  parking  lots,  construction  sites, demolition  sites)  may be  the  largest
source  of  dust  on  paved  streets.8  Maximum carry-out occurs in  wet weather
when  dust  emissions  from open sources are at a minimum.   In  a  study con-
ducted  in  the Seattle  area,7'9  a car  driven at 10 miles/hr on  a wet  gravel
road  collected approximately 80 Ib of mud on tires and underbody, and  carry-
out on  tires from  a  wet  unpaved parking lot averaged about 3/4  Ib/vehicle.

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          TABLE 1.   CONTAMINANT LOADINGS ON URBAN STREET SURFACES4
     Land use
  Mean initial
accumulation rate
  (Ib/mile/day)
  Loading intensity (Ib/curb mile)
                  Numerical   Weighted
Minimum  Maximum    mean       mean
Residential 373
Low/old/single
Low/old/multi
Med/new/s ingle
Med/old/single
Med/old/multi
Industrial 447
Light
Medi urn
Heavy
Commercial 226
Central business
district
Shopping center
Overall 348

120
31
180
260
140

260
280
240

60

63


1,900
1,300
1,200
1,900
6,900

12,000
1,300
12,000

1,200

640


850
890
430
-
1,400

2,600
890
3,500

290

290

1,200





2,800



290



1,500
   There are 2 curb miles per street mile.

     An American  Public  Works Association study10 found  that  10.2 Ib  of
dust under  1/8  in.  in  size comes onto each 100 ft of curb!ess paved road
in Chicago  each  day;  this amount is cut by a factor of four if curbs are
added.
     As evidence  of  the  importance of the carry-out  process,  a positive
correlation has been observed between TSP concentration  and the occurrence
of precipitation  several days before sampling,  i.e.,  after sufficient  time
for the carry-out residue to dry out.11

     In addition  to  vehicular  carry-out,  other potentially  significant
sources of street dust are:

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         Water and wind erosion from adjacent  exposed  areas  (sparsely vege-

         tated land, unpaved parking lots,  etc.).


         Motor vehicle  exhaust,  lubricant leaks, and tire and brake wear.


         Truck spills.


         Street repair.


         Winter sanding and  salting.


         Atmospheric  dustfall.


         Vegetation  and  litter.


     Table  2 presents typical annualized  deposition  and removal  rates for

street surface material estimated  by one  study.8  The  values were derived

by applying assumptions  to data  found in other  literature sources.   One as-
sumption was that  the typical  street has four lanes,  is 50 ft wide, and has

an average  daily traffic volume  of 10,000  vehicles.


             TABLE 2.   ESTIMATED  DEPOSITION AND REMOVAL RATES
     Deposition          Typical  rate        Removal         Typical rate
      process         (Ib/curb-miles/day)    process     (Ib/curb-miles/day)


Mud and dirt                  100         Reentrainment         100
  carry-out                       .        Displacement           40
Litter                         40         Wind erosion           20
Biological debris              20         Rainfall               50
Ice control compounds          20           runoff
Dustfall                       10         Sweeping               35
Pavement wear and              10
  decomposition
Vehicle-related                17
  (including tire
  wear)
Spills                        < 2
Erosion from adjacent          20
  areas

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     In  a recent  field study  of  street  surface  contaminants in  the
Washinton, D.C. area,12 roadway deposition of traffic-related materials was
found to be directly proportional to the traffic volume, at a rate of about
10 3 Ib/vehide-mile.  The  rate appeared to be independent of the loading
already present.

     However,  the  accumulation  of  materials on the roadway has been found
to  level  off  within a period of 3 to 10 days after a rain storm or street
cleaning.4'12  This leveling off occurs when traffic-related removal rates,
which increase with loading intensity,  balance traffic-related deposition
rates.  The equilibrium is established more rapidly with increasing traffic
speed.

2.4  TRAFFIC-GENERATED EMISSIONS

     Few  data  on  directly measured dust emissions  from paved  streets are
available  in  the  literature.   An isolated study of dust emissions  from a
paved road in  the Seattle area yielded  an emission factor of  0.83  Ib/ve-
hicle-mile at  20  mph.7'9   The test road was  noticeably  dusty  and had no
curbs or  street cleaning  program;  it was  located adjacent to gravel roads
and  unpaved  parking lots  from which dirt was  tracked.  Dust  emissions gen-
erated by  vehicular traffic with average  daily traffic exceeding 200 ve-
hicles was estimated to equal the amount removed by sweeping every 2 weeks.9

     A single-valued emission factor of 3.7 g/vehicle-kilometer for dust en-
trainment  from paved  roads  was  developed from another  field  study.8   Emis-
sion measurements  were  obtained using the upwind-downwind technique  with
four high-volume samplers,, one  located 10 m upwind, with the remaining three
located at 10, 20, and 30 m  downwind.   Thirty-five successful  tests  were
completed.  It was determined through microscopy that 78% (by weight) of the
emissions  consisted  of  particulate less than 30 urn in size.   Also through
optical  microscopy it  was found that 59%  of the particulate collected was
mineral  matter while  40%  consisted of combustion  products.   It was also
concluded  in this  study that particulate emissions  from a street are propor-
tional to  traffic volume  but independent  of  street surface  dust  loading.

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     In a third field study quantitative emission factors for dust entrain-
ment from paved urban roads were developed using exposure profiling.2  Field
testing was conducted at three representative sites in the Kansas City area.
At one location, controlled amounts of pulverized top soil and gravel fines
were applied to the road surface.   Eight tests were performed at the artifi-
cially loaded  site,  and five  tests were made  at  a different  site  under  ac-
tual traffic conditions.   Emissions were found to vary directly with traffic
volume and  surface  loading of silt (fines).   The dust emission factor for
normally  loaded urban streets ranged  from 1 to 15 g/vehicle-kilometer,  de-
pending on  land use.   Approximately  90% of the emissions (by weight) were
found  to  be less  than 30 urn  in Stokes diameter  and 50%  less  than  5  urn  in
Stokes diameter, based on a particle density of 2.5 g/cm3.

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                       3.0  SAMPLING SITE SELECTION
     Eight  candidate  sampling areas in Kansas. Missouri and Illinois were
designated  by  the Environmental  Protection Agency (EPA) as representative
sites  for  the  field study.   As  indicated  in  Table  3,  these  areas  represent
a  range  of typical  road, traffic,  geographical, and  environmental  condi-
tions  within  residential,  commercial,  and industrial  land uses.   Each  sam-
pling  area  contained a TSP monitoring site providing historical air quality
data.  In  1975,  ambient  TSP  concentrations  in  the  candidate sampling areas
ranged from annual  geometric means  of  52  ug/m3  at  Brauer School,  Wyandotte
County,  Kansas,  to 157  ug/m3at  2001 East 20th, Granite City,  Illinois.

3.1  SITE  PRESURVEYS

     Before going to the field,  liaison was established with the  appropriate
state  and  local environmental and transportation authorities.  Support data
were compiled  for each proposed  sampling  area to aid in careful site selec-
tion.  This information  included local street maps, topographic maps, street
maintenance and  traffic  data, and  1976 microinventories supplied by EPA.
Based  on this  research,  previous Midwest  Research Institute (MRI) road dust
sampling experience,  and EPA recommendations,  presurvey data requirements
were developed.   Table 4 identifies specific field  data that were obtained
during the presurveys for use in final sampling site selection.

     It was decided to  presurvey two or  three  sites  within each  sampling
area to  provide  roadway  orientations suitable  for  sampling under various
wind direction ranges.   Similarly,  street segments were surveyed  where mini-
mum obstruction to wind  flow  existed to provide a wide  spread of  wind fetch
corresponding  to acceptable  sampling conditions.

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                                           TABLE  3.   GENERAL SAMPLING AREAS  DESIGNATED  BY  EPA
o
Sampling area
Preaurvey
Identification Name
I 321 Delaware

2 Brauer School

3 Baltimore and Miami

4 Slireve and 1-70

5 River dea Peres
Address of associated Ill-Vol
321 Delaware, Tonganoxle,
Kanaaa
K-7 and Leavenuortll Roadv
Wyandotte County, Kansas
Baltimore and Miami, Kansas
City, Kanaaa
Slireve and 1-70, St. Lou la,
Missouri
E. of Sulnlier, between
SAROAD
Identification
17-2000-001-F01

17-3840-008-1101

17-1800-002-1101

26-4280-061

26-4280-062
Ill-Vol
currently
operat iona I
No

No

No

Yes

Yea
Annual geometric
TSP concentrations
1974
82

45

107

111

-
1975
90

52

110

105

90
mean
.ilJB/JiLl
1976
107

-

-

96

-
                                                        Manchester and  1-44,
                                                        St.  louls, Missouri
                                  (15th and Madison     15cli and Madison, Granite City,   14-2960-10
                                                        III*	j _
                                  2001 f.  20th
  Illinois

2001 E. 20tli. Granite City,       14-2960-09
  Illinois
                                  23rd and Madlaon     23rd and MaJlson, Granite City,   14-2960-07
                                                        Illinois
                                                                                                        Yea
                                                                                                        Yea
                                                                                                        Yes
                                                                                                                 158
                                                                                                                  93
                                                                                                                           137
                                                                                                                           157
                                                                                                                           105
                                                                                                                                     154
                                                                                                                                     205
                                                                                                                                     122

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    TABLE 4.   FIELD DATA REQUIREMENTS FOR EACH SAMPLING SITE PRESURVEY



 1.   Accurate location of each presurvey site on street and topographic map

 2.   Location of site with respect to reference Hi-Vol monitor.

 3.   Primary land use in the surrounding area.

 4.   Street information including:

          Direction of travel
          Number of travel and parking lanes
          Presence of curbs and sidewalks
          Street surface composition
          Street surface roughness {qualitative - smooth, medium, rough)

 5.   Road maintenance information including:

          Cleaning activities and frequency
          Winter snow mitigation procedures

 6.   Street surface particulate loading in curb area, parking lanes, and
       travel lanes (qualitative - light, medium, heavy)

 7.   Detailed sketch of the road dimensions.

 8.   Detailed sketch of surrounding area including:

          Topography
          Buildings (type, dimensions, address)
          Open areas (use, dimensions)
          Street names and locations
          Fences, trees, billboards, and other miscellaneous information

 9.   A 15 to 30 min traffic count by vehicle- type.

10.   A photographic survey including views of:

          The sampling street (both directions)
          The sampling set-up area
          The fetch area
          The road surface (travel lane and curb area)
                                    11

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     Seven sites in Areas 1, 2, and 3 (identified in Table 1) were surveyed
on August 2 and 3, 1979.  An additional  11 sites  were  surveyed  in Areas 4,
5, 6, and 7  on August 7 and 8, 1979.  The 2001 East 20th location and  the
15th and Madison  location in Granite  City,  Illinois were combined into one
sampling area (Area 6) because of their proximity.

     A wide  variety  of road and traffic characteristics were found  in  the
areas presurveyed.  Equivalent hourly traffic volume ranged  from  36  vehicles
at  Site  2A  to 2,944 vehicles at Site 5A.  Road width  varied from 22 ft at
Site  1C  to  216 ft at  Site  28.  Both asphalt and  concrete street  surfaces,
curbed and uncurbed, were included.  Qualitative  evaluation  of  street surface
conditions indicated that the surfaces ranged from  smooth to rough,  and that
surface  particulate  loadings  varied from light  to heavy in  comparison with
typically observed loadings.

3.2  SITE SELECTION

      Three  major criteria were used  to  determine the  suitability of each
 candidate  site for sampling of road dust emissions  by  the exposure profiling
 technique.6

      1.   Adequate space  for sampling  equipment,

      2.   Sufficient  traffic and/or surface  dust  loading so that adequate
 mass would  be captured during  a reasonable  sampling time period,  and

      3.   A wide range  of acceptable wind directions.

 3.2.1  Adequate Space

      Adequate space  for equipment deployment and easy accessibility  to  the
 area is  required for  road dust sampling.   All of  the 18 candidate paved road
 sites were  chosen so  as  to  provide  necessary space, as well  as  accessibility
 for the  setup of all  sampling  equipment  and  to  ensure  the  safety of  the sam-
 pling crew.
                                      12

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3.2.2  Adequate Mass Catch

     To provide  for  accurate  determination of the dust emission rate from
exposure profiling data, at least 5 mg of sample should be collected by each
profiling head.  Particulate concentration and sampling time must be suffi-
cient to provide the 5 mg weight gain under isokinetic sampling conditions.
This requirement  is  the  most  difficult  to  achieve  for  the  highest sampling
head (located  at 4 m above ground) because of the significant decrease in
particulate concentration with height.

     An empirical relationship between sampler catch and traffic volume ob-
tained  in  MRI's  previous testing of  traffic  entrained dust emissions  is
illustrated in Figure 1.  Assuming a  typical silt loading (excluding curbs)
of 5 kg/km, approximately 3,600 vehicle passes are required to collect 5 mg
of sample  (above background)  on the  top  sampler;  for  roads with heavier
loadings, fewer passes are required.

     Roads with  light traffic are excluded from consideration because (a)  it
is not  possible  to collect sufficient sample mass within an acceptable sam-
pling period (4  to 6 hrs), and (b) such roads probably do not contribute sub-
stantially to  total  emissions of traffic entrained dust in  urban areas.  In
any case, the  emission factor equations developed in this study are expressed
in terms  of  emissions  per unit  of  traffic volume  (Kg/VKT);  therefore these
equations should be  applicable regardless  of traffic density.

3.2.3   Adequate  Traffic  Volume

     During the  presurvey of  each candidate testing site, traffic was counted
visually during  a 15 to  40 min period.  These traffic  counts were then con-
verted  to an average hourly count  (AHT) by simple  linear extrapolation in  time

     In order  to evaluate each site with  respect to the requirement of 3,600
vehicle passes in a 4-hr test period,  it  was necessary to  convert  the ob-
served  AHT into an  equivalent 4-hr count.  This was accomplished by using
reported data  on the diurnal  variation  of  hourly traffic  in Detroit, Chicago,

                                      13

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  100,000
 3
 o
•«*•
 c
 «   10,000
 l>»     *
 o
a.
ju
 u
     1,000
                                                           O Data Point from
                                                             Reference 2
                                             10.0
                          Mass (mg) Collected by  Top  Sampler  (h = 4m. )
100.0
             Figure 1.  Empirical relationship  between sampler catch and
                          traffic volume.
                                           14

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Pittsburgh, and Toronto.13  In order to maximize the projected vehicle count,
it was  assumed  that  testing would  be conducted  between  3:30  PM and  7:30  PM
which encompasses the evening traffic peak.  After analysis of the collected
data, eleven of the eighteen site candidates met the traffic requirement and
were eligible for selection.

3.2.4  Acceptable Wind Directions

     Wind directions that would successfully transport the traffic entrained
dust from  paved streets to the exposure  profiler  depend  on  the  following
factors:

        Street Orientation - the mean (15-min average) direction of the wind
        must lie within 45 degrees of the perpendicular to the road.

     •  Wind Fetch - the wind flowing toward the test roadway should not be
        blocked by obstacles on the upwind side.

     In order to evaluate the candidate sites for the wind fetch requirement,
the  arc of wind direction for  which  the wind would flow freely between the
two  nearest upwind obstacles (houses,   buildings, or trees) was  calculated
as follows:

                              6 =  arctan  ^7

where 9 represents the half  angle  of the  arc,   b  is  half the distance be-
tween  the   two  blocking  obstacles  (fetch), and  a  is  the perpendicular
distance from  the  line joining the  rear  corners of the  obstacles  to  the
proposed location  of the profiler  (5 m from the downwind edge of the road-
way.)   Figure 2 illustrates these  parameters.

3.2.5   Summary  of  Selection Criteri?

     Selection  criteria  for sampling sites  included,  in descending  order of
importance:

                                     15

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                      Wind
                   b/2
       Obstacle
       to  Flow
b/2
       Obstacle
       to  Flow
                                        Test  Roadway
                       v
                       o
                               'Exposure Profiler
Figure 2.  Parameters for calculations of angle
             of unobstructed wind  flow.
                     16

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        Adequate space - for operation of equipment and for safety of crew.

        Adequate mass - as determined by number of vehicle passes in a 4-hr
        test period.

     •   Wind direction - range of unobstructed wind directions.

A summary  of  the selection criteria as  applied  to  each  site,  is  shown  in
Table 5.   It  should be noted that accessibility was determined during the
presurveys, and all candidates were assured of this.

     Suitability was determined by an examination of all criteria, and rat-
ings were  assigned as  follows:   (A = primary  choice,  B =  alternate choice,
C =  emergency  choice,  R = rejected).  Those  sites  designated  A or B were
selected to be considered for source testing.   It should be noted that sam-
pling sites 1A and 1C were considered primary because it was desirable to
sample  at  rural  locations.   These  sites  were  easily accessible to the  sam-
pling crew so that  a longer sampling period was possible.
                                      17

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      TABLE  5.   APPLICATION  OF  SELECTION CRITERIA TO CANDIDATE
                  SAMPLING SITES
Site
1-A
1-B
1-C
2-A
2-B
3-A
3-B
4- A
4-B
5-A
5-B
5-C
6-A
6-B
6-C
7-A
7-B
7-C
Traffic
count
(peak
4 hr)a
Low
Low
Low
Low
High
High
Low
Medi urn
Low
High
Medium
High
Medi urn
Medium
Medi urn
Low
Medium
Low
Curbed
Yes
Yes
No
No
No
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
One side
One side
Street
parti culats
loading
Moderate
Moderate
Moderate
Moderate
Light
Light
Moderate
Moderate
Moderate
Light
Moderate
Light
Moderate
Moderate
Heavy
Moderate
Moderate
Heavy
Adequate Wind Suitability
sample direction, for
mass versatility testing
No
No
No
No
Yes
Yes
No
Yes
No
Yes
Yes
Yes
Yes
Yes
Yes
No
Yes
No
N/2Q°
E/40°
W/90°
N/90°, 5/90°
W/90°, E/90°
W/70°, E/50°
N/40°, S/20°
W/5Q°, E/70°
WNW/900
N/90°, S/90°
N/90°
ESE/200
NE/400
SE/200
ESE/400
SE/400
NNW/400, SE/900
ENE/700
Pd
Rd
Pa
R
P
P
R
P
R
P
S
E
P
E
P
R
P
S

Four-hour traffic count:   low = 1,000 to 4,000;  medium = 4,000 to
8,000; high = > 8,000.

Centerline directions and ranges of unobstructed wind flow.

P = prime site; S = alternate site; E = emergency site; R = rejected
site.

Sampling will be attempted for periods longer than 4 hr (see text).
                                 18

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                         4.0  SAMPLING EQUIPMENT
     A variety  of  sampling  equipment was  utilized  in  this  study  to  measure
particulate emissions,  roadway  surface particulate loadings, and traffic
characteristics.

          Table 6  specifies the kinds  and frequencies of field measurements
that were  conducted during each run.  "Composite" samples denote a set of
single samples  taken from several  locations  in  the area; "integrated"  sam-
ples are those taken at one location  for the duration of the run.

4.1  AIR SAMPLING  EQUIPMENT

     The primary tool  for quantification  of  emissions was  the MRI exposure
profiler, which was developed under  EPA Contract No.  68-02-0619.6  The pro-
filer  (Figure  3) consists of  a  portable tower  (4 to 6 m  height)  supporting
an array of four sampling heads.  Each sampling head is operated as an isoki-
netic  total particulate matter  exposure sampler directing  passage  of  the
flow stream through a settling chamber (trapping particles larger than about
50 urn  in diameter)  and then upward through a standard 8 in. by 10 in. glass
fiber  filter positioned horizontally.  Sampling intakes are pointed into the
wind,  and  sampling velocity of each  intake is adjusted to match the local
mean wind  speed,  as determined prior  to each test.  Throughout each test,
wind speed  is  monitored by recording  anemometers  at  two heights, and  the
vertical wind profile of wind speed  is determined  by assuming a logarithmic
distribution.   Normally,  the  exposure profiler  is  positioned  at  a distance
of 5 m from the downwind edge of the  road.
                                     19

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                                                 TABLE  6.   FIELD  MEASUREMENTS
ro
CD

1.

2.

3.

4.

lest Parameter
Meteorology
a. Wind speed
b. Wind direction
c. Cloud Cover
d. Temperature
e. Relative humidity
lload Surface
a. Pavement type
b. Surface condition
c. Particulate loading
d. Particulate texture
Vehicular Traffic
a. Mix
b. Count
Atmospheric Particulate
a. Total participate
b. Total suspended
participate
c. Inhalable particulate
d. Inhalable particulate
Units

m/s
deg
%
"C
%

q/m2
% silt

-

mass cone. (|ig/m3)
mass cone. (|ig/m3)
mass cone. (|ig/m3)
mass size dist. (ug)
Samp I i no Mode

continuous
continuous
s i ng 1 e
single
single

compos i te
composite
multiple
multiple

multiple
cumulative

integrated
integrated
integrated
integrated
Measurement/ Instrument
method

warm wire anemometer
wind vane
visual observation
sling psychrometer
sling psychrometer

observation
observation
dry vacuuming
dry sieving

observation
pneumatic tube axle
counters

Iso-kinetic prof i ler
Hi-Volume sampler
size selective inlet
slotted high-volume
Manufacturer/Model

Kurz Model 410
Wong Eco-System 111
Taylor cat. no. 146-761
Taylor cat. no. 146-761

Hoover, Model S2015 Quick Broom
Forney, Inc. , IA-410 Sieve Shaker

Streeter Amet, J R traf f {counter.
Model No. 160

MRI developed under EPA Contract
No. 68-02-0619
Sierra Instruments, Inc., Model 305
Andersen Samplers, Inc., Model 7001
Sierra Instruments, Inc., Model 23(
                                                                            cascade impactor

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                                      Flow Control Circuit Box
                     Warm-Wire
                     Anemometer
                       Electronic Readout/Control Unit
Figure 3.  i'1RI  exposure profiler.
               21

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     The recently developed EPA  version of the size selective inlet (SSI)
for the high volume  air sampler was used to determine the IP concentrations.
To obtain the particle size distribution of IP, a high-volume parallel-slot
cascade impactor (CI)  with  greased substrates was  positioned  beneath  the
SSI.  This  five  stage  cascade  impactor  has, at a  flow  rate  of  40  SCFM,  50%
efficiency  cutpoints  at 7.2, 3.0,  1.5,  0.95,  and  0.49  urn  aerodynamic  diam-
eter.

     The cascade impactors were  used  in conjunction with  the SSI's  for  two
reasons.  First, the  15 urn cutpoint for inhalable particulate  (IP)  was  not
well established as a standard at  the time  of this  study.   With  the use of
the  cascade impactor  data, alternate  cutpoints for  IP  could be determined.
The  second  reason for  using the cascade impactors was to obtain a fine  par-
ticle  (FP)  cutpoint of 2.5 urn.

     Other  air  sampling  instrumentation used  included  standard high-volume
air  samplers to measure total  suspended particulate matter  (TSP) consisting
of  particles smaller  than about 30 urn in aerodynamic diameter.

     Three  variations of air  sampling  equipment  deployment were used  in
this study.   The deployment used  in the winter testing (Kansas City area)
is  shown  in Figure  4.  The two  deployments of sampling  equipment for the
spring  testing  (St.  Louis/Granite  City  areas) are shown in  Figures  5 and  6.

     The  basic  downwind  equipment included an exposure profiling sampling
system with four sampling heads  positioned at I-  to 4-m  heights.   In addi-
tion,  size  selective  inlets  fitted with high-volume cascade impactors were
placed at 1- and 3-m  heights  to  determine the respective  IP  and FP mass
fractions  of the total particulate emissions.  A standard  high-volume  air
sampler was also operated at a height of 2 m.

     Optional  equipment  operated downwind  in  the  winter  testing included a
1-m high  size-selective  inlet, fitted with  a  cascade impactor  with  ungreased
substrates.   No optional  equipment was operated  downwind in the  St.  Loui.s
testing.
                                      22

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                                     2m  A
                                                                             3m
IV)
U)

                   -#gg#£ Roadway

          4m
                  2m
^L.A
                                        mm
r4m

 3m

 2m



U0m
LEGEND:
 A Standard Hi Vol
 D Profiler Head
 Q Hi Vol with SSI
 Q Hi Vol with SSI/lmpactor
 O Hi Vol with Cyclone/lmpactor
 G Greased Filters
        Figure 4.  Sampling equipment deployment for winter testing in Greater Kansas City Area.

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                                  3m
4m  f"

3m  -
                                                    2m
                                                     1m
              A  2m
                                                v
                                               ^:^:::^:^::: Roadway

                                                          ~4m

                                                          -3m  LEGEND:
                                                                 A Standard Hi Vol
                                                          h2m   D Profiler Head
                                                                 ^Hi Vol with SSI
                                                          -1m   ^ Hi Vol with SSI/Impactor
                                                                 O Hi Vol with Cyclone/Impactor
                                                          L0m   G Greased  Filters
Figure 5.  Sampling equipment deployment "A" for spring testing in Greater St. Louis Area.

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                                                    3m
                                                                                         A   2m
ro
en
                                                                           Roadway ;::::::::::::>::^:o:::::::::::::::::::::::::::::::::::::::::^:::::::::::::::::::::::::::::::::::

                                                                              4m

                                                                              3m

                                                                              2m

                                                                              1m

                                                                              Om
LEGEND:
 A Standard Hi Vol
 D Profiler Head
    Hi Vol with  SSI
    Hi Vol with  SSI/lmpactor
    Hi Vol with  Cyclone/lmpactor
  G Greased  Filters
           Figure  6.   Sampling equipment  deployment "B"  for spring testing in Greater St.  Louis  Area.

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     The basic upwind  equipment  included SSIs and  a  standard high-volume
air sampler.  In the Kansas City testing, two  SSIs  at heights of 2 and 4 m
were used to obtain the IP concentration of  upwind  particulate matter.   In
the St. Louis testing, the primary upwind equipment included a high-volume
air sampler and  an  SSI/CI  with greased substrates.    For the  secondary  de-
ployment array,  two SSIs were used to obtain the vertical distribution  of
IP.

4.2  ROADWAY DUST SAMPLING  EQUIPMENT

     Samples of the dust found on the roadway surface were collected during
the source  tests.   In  order to collect this  surface dust,  it was necessary
to close each traffic  lane  for a period of approximately'15 min.   Normally,
an area  that  was 3 m  by the  width of a  lane was  sampled.   For each test,
collection  of material from  all  travel  lanes and curb areas  (extending  to
about  25-30 cm  from the curbing)  was attempted.   A  hand held  portable
vacuum  cleaner was  used  to collect the  roadway  dust.  The attached brush
on the  collection  inlet  was   used to  abrade  surface compacted dust and to
remove  dust from the crevices of the  road surface.  Vacuuming was preceded
by broom sweeping if large aggregate was present.

4.3  VEHICLE CHARACTERIZATION EQUIPMENT

     The characteristics of the vehicular traffic during the  source testing,
were determined  by  both  automatic  and manual means.   The vehicular charac-
teristics  included:   (a)  total  traffic count, (b)  mean  traffic  speed,  and
(c) vehicle mix.

     Total  vehicle  count was  determined by  using pneumatic-tube counters.
In order to convert the axle  counts to total vehicles, visual  1-min vehicle
mix summaries were  tabulated  every 15 min during the source  testing.   The
vehicle  mix summaries  recorded vehicle type,  number  of  vehicle axles and
number  of  vehicle  wheels.   From this information,  the total  axle counts
were corrected to the  total number of vehicles by type.
                                     26

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     The speed of the traveling vehicles was determined by noting the posted
speed limits of the roadway test section.  As a check against this determin-
ation method, speeds of the vehicles were determined through the occasional
use of a hand-held radar gun.

     The weights of the vehicle types were estimated by consulting (a) auto-
mobile  literature  concerning  curb  weights of vehicles and  (b) distributors
of medium  duty and  semi-trailer type trucks as  to  their  curb  weights.
                                     27

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(This page intentionally blank)
                  28

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                  5.0  SAMPLING AND ANALYSIS PROCEDURES
     The sampling  and  analysis  procedures  employed  in  this  study were  sub-
ject to the Quality Control guidelines summarized in Tables 7 to 10.  These
procedures met or exceeded the requirements specified by EPA.14'15

     As part  of  the QC program for this study, routine audits of sampling
and analysis  procedures  were performed.   The purpose of the audits was to
demonstrate that  measurements  were made within acceptable  control  condi-
tions for particulate source sampling and to assess the source testing data
for precision  and accuracy.   Examples  of  items  audited  include  gravimetric
analysis, flowrate  calibration,  data processing,  and emission factor cal-
culation.  The mandatory use of specially designed reporting forms for sam-
pling and analysis  data  obtained  in the field and laboratory aided in the
auditing procedure.  Further detail  on  specific sampling and  analysis  pro-
cedures are provided in the following sections.

5.1  PREPARATION OF SAMPLE COLLECTION MEDIA

     Particulate  samples were  collected on type A slotted glass fiber im-
pactor  substrates  and  on Type AE  (8 x  10 in.) glass fiber filters.   To
minimize the  problem of  particle  bounce, the glass fiber cascade impactor
substrates were  greased.   The grease solution was  prepared by  dissolving
140 g of stopcock grease in  one  liter  of  reagent  grade  toluene.  No grease
was applied to the borders and backs  of  the substrates.   The substrates
were handled,  transported  and stored in  specially  designed frames which
protected the  greased surfaces.
                                     29

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        TABLE 7.   QUALITY CONTROL PROCEDURES FOR SAMPLING FLOW RATES
Activity
        QC check/requirement
Calibration
     Profilers, hi-vols,  and
       impactors
Single-point checks

     Profilers, hi-vols,  and
       impactors
  •  Alternative
Orifice calibration
Calibrate flows in operating ranges
using calibration orifice every two
weeks at each regional site prior
to testing.
Check 25% of units with rotameter
calibration orifice or electronic
calibrator once at each site prior
to testing (different units each
time).  If any flows deviate by
more than 7%, check all other units
of same type and recalibrate non-
complying units.   (See alternative
below.)

If flows cannot be checked at test
site, check all units every two
weeks and recalibrate units which
deviate by more than 7%.

Calibrate against displaced volume
test meter annually.
                                     30

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          TABLE 8.  QUALITY CONTROL PROCEDURES FOR SAMPLING MEDIA
Activity
         QC check/requirement
Preparation


Conditioning
Weighing
Auditing of weights
  (Tare and Final)
Correction for handling
  effects
Calibration of balance
Inspect and imprint glass fiber
media with ID numbers.

Equilibrate media for 24 hr in
clean controlled room with relative
humidity of less than 50% (vari-
ation of less than ± 5%) and with
temperature between 20° ± and 25°C
(variation of less than ± 3%).

Weigh hi-vol  filters and impactor
substrates to nearest 0.1 mg.

Independently verify weights of 10%
of filters and substrates (at least
4 from each batch).   Reweigh batch
if weights of any hi-vol filters
(8 x 10 in.)  or substrates deviate
by more than  ±1.0 and ± 0.5 mg
respectively.

Weigh and handle at least one blank
for each 1 to 10 filters or sub-
strates of each type for each test.

Balance to be calibrated once per
year by certified manufacturer's
representative check prior to each
use with laboratory Class S weights.
                                     31

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        TABLE 9.   QUALITY CONTROL PROCEDURES FOR SAMPLING EQUIPMENT
Activity
         QC check/requirements
Maintenance

  •  All samplers



Equipment siting


Operation

   •  Timing
     Isokinetic sampling
       (profilers only)
     Prevention of static
       mode deposition
Check motors, gaskets, timers, and
flow measuring devices at each re-
gional site prior to testing.

Separate colocated samplers by 3 to
10 equipment widths.
Start and stop all samplers during
time spans not exceeding 1 min.

Adjust all sampling intake orienta-
tations whenever mean (15 min. average)
wind direction changes by more than
30 degrees.

Adjust all sampling rates whenever mean
(15 min average) wind speed approach-
ing samplers changes by more than 20%.

Cap sampler inlets prior to and im-
mediately after sampling.
                                     32

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 TABLE 10.  QUALITY CONTROL PROCEDURES FOR DATA PROCESSING AND CALCULATIONS

Activity                                          QA check/requirements

Data recording                          Use specially designed data forms to
                                        assure all necessary data are re-
                                        corded.  All data sheets must be
                                        initialed and dated.
Calculations                            Independently verify 10% of calcu-
                                        lations of each type.  Recheck all
                                        calculations if any value audited
                                        deviates by more than ± 3%.
     Prior to the initial weighing, the greased substrates and filters were
equilibrated  for  24 hr at constant temperature  and  humidity  in  a  special
weighing room.  During weighing, the balance was checked at frequent inter-
vals with  standard  weights  to assure  accuracy.   The  substrates and filters
remained in  the  same controlled environment for  another  24  hr, after which
a second analyst  reweighed them as a precision check.  Substrates or filters
that could  not  pass audit limits were discarded.  Ten percent of the sub-
strates and  filters taken to the field were used as blanks.   Paper bags
for  the  vacuum  cleaner were  conditioned  and tared in a  similar manner.

5.2  PRE-TEST PROCEDURES/EVALUATION OF SAMPLING CONDITIONS

     Prior  to equipment deployment,  a number of decisions were  made as to
the  potential for acceptable source testing  conditions.  These  decisions
were based on forecast  information obtained  fom the  local U.S. Weather Ser-
vice office.   A  specific sampling  location was  identified based  on  the
prognosticated wind direction.  Sampling would ensue only if the wind speed
forecast was between 4  and 20 mph.  Sampling was not planned  if  there was a
high probability  of measurable precipitation (normally  >  20%)   or  if the
road surface was  damp.
                                      33

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     If conditions were  considered  acceptable,  the sampling equipment was
transported to the site, and deployment was initiated.  This procedure nor-
mally took 1  to  2 hr to complete.   During this period, the samples of the
road surface  particulate were  collected at a location within 100 m of the
air sampling  site.   For a  4-lane roadway, the collection  of road  surface
particulate samples required approximately 1 hr to complete.

5.3  AIR SAMPLING

     Once the source testing equipment was set up and filters put in place,
air  sampling  commenced.  Information  recorded for  each  test included:   (a)
exposure profiler  -  start/stop  times, wind speed profiles  and  sampler  flow
rates (determined every 15 min) and wind direction (relative to roadway per-
pendicular);  SSI/CIs,  Hi-Vols   - start/stop times, and  sampler flow  rates,
(c)  vehicle  traffic  -  total count,  vehicle mix count,  and speed;  and  (d)
general meteorology  -  wind speed and direction,  temperature, relative hu-
midity and solar radiation.

     Sampling usually  lasted 4  to 6 hr.  Occasionally,  sampling was  inter-
rupted due to occurrence of unacceptable meteorological conditions and then
restarted when suitable conditions returned.   Table 11 presents the criteria
used for suspending or terminating a source test.

     The upwind-background  samplers were  normally  operated concurrent  with
the downwind  samplers.   Care was taken to position the upwind samplers away
from any influencing particulate emission source.

5.4  SAMPLE HANDLING AND ANALYSIS

     To prevent particulate losses,  the exposed media were  carefully trans-
ferred at the end of each run to protective containers within the MRI  instru-
ment van.   Exposed filters and  substrates were placed in individual glassine
envelopes and numbered file folders and then returned to the MRI laboratory.
Particulate that  collected on  the interior surfaces  of  each exposure probe
was rinsed with distilled water into separate glass jars.

                                     34

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TABLE 11.  CRITERIA FOR SUSPENDING OR TERMINATING AN EXPOSURE PROFILING TEST


A test will be suspended or terminated  if:a

1.  Rainfall ensues during equipment setup or when sampling is in progress.

2.  Mean  wind  speed during sampling moves outside the 4 to 20 mph accept-
      able range for more than 20% of the sampling time.

3.  The angle between mean wind direction and the perpendicular to the path
      of  the moving point source during sampling exceeds 45 degrees for more
      than 20% of the sampling time.

4.  Mean  wind direction during sampling shifts by more than 30 degrees from
      profiler intake direction.

5.  Mean  wind speed approaching profiler sampling intake is less than 80% or
      greater than 120% of intake speed.

6.  Daylight is  insufficient  for safe equipment operation.

7.  Source condition deviates from predetermined criteria  (e.g., occurrence
      of  truck spill).
a  "Mean"  denotes  a  15-min  average.
                                      35

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     When exposed substrates  and  filters  (and the associated blanks) were
returned from the field,  they were equilibrated under the same conditions
as the  initial weighing.  After reweighing, 10% were  audited to check  pre-
cision.

     The vacuum bags were weighed to determine total net mass collected.
Then the dust was removed from the bags  and  was  dry sieved.   The screen
sizes used for the dry  sieving process were the following:   3/8 in., 4, 10,
20, 40,  100, 140, and 200 mesh.  The material passing a 200 mesh  screen  is
referred to as silt  content.

5.5  EMISSION FACTOR CALCULATION

     The primary quantities  used in obtaining emission factors  in this study
were the concentrations measured  by the size selective inlet/cascade  im-
pactor sampler combinations.   This combination not only  provides  a reliable
cut point for 15 urn  but also  permits the determination of concentrations in
other particle size ranges.   The MRI exposure profiler collects total  par-
ti cul ate matter and  enables  one to determine the plume height.   A knowledge
of the  vertical distributions  of  plume concentration is necessary  in  the
numerical integration required to  calculate emission factors.   The emission
factor calculation procedure  is presented in Appendix A.
                                     36

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                             6.0  TEST RESULTS
6.1  TEST SITE CONDITIONS

     As indicated  in Table  12,  the winter  testing was conducted during the
months of  February and March 1980 at three sites in the Kansas City area:
7th Street in Kansas City, Kansas; Volker Boulevard/Rockhill Road in Kansas
City, Missouri,  and  4th Street in Tonganoxie, Kansas.   The spring testing
(Table 13) was  conducted during the month  of  May  1980, at two sites in
St. Louis  (1-44  and Kingshighway) and  at  three  closely spaced sites in
Granite City, Illinois.

     The sites where  source testing occurred can be classified into four
land use categories, based  upon source  parameters such  as  road type, vehi-
cle mix, and vehicle speed.  The categories  are:   commercial/industrial;
commercial/residential;  expressway,  and rural  town.  Much  of the  data pre-
sented in  the following sections  is  broken  out according to these categor-
ies.

     Table 14 presents an evaluation of the source tests according to estab-
lished QA criteria.  Seven of the nine  Kansas City tests (Runs M-l,  -2,  -3,
-6, -7, -8, and -9) met all  of the. QA criteria, while only three of the ten
tests conducted  in the St.  Louis, Granite  City  area (Runs  M-ll,  -12, and
-15)  met the QA  criteria.   The  spring testing, in particular, was hampered
by unseasonably  light  wind  conditions  as wind speed for  four of the ten
tests did not meet the minimum wind speed criterion of 4 mph.

     The results of  the ten runs which met the  QA criteria were used as
input to Multiple  Linear Regression (MLR) analysis  (see Section 7.0).  These
runs  are subsequently referred to as the "MLR" data set.

                                     37

-------
                          TABLE 12.  WINTER TEST SITE CONDITIONS  (Kansas City Area Paved Roads)
Profiler Operation

Run
M-l
M-2
M-3
M-4
M-5
M-6
H-7
M-8
M-9

Site
7 Lh Street
7th Street
7th Street
Volker Boulevard
Volker Boulevard
Roc kill 11 Road
Volker Boulevard
Tonganoxie - 4th St.
7th Street

Date
2/7/80
2/11/80
2/12/BO
2/26/80
2/27/80
2/28/80
3/5/80
3/6/80
3/10/80
Start
Time
13:08
14:21
10:54
11:22
10:35
10:19
11:30
11:17
10:30
Stop
Time
15:08
15:47
12:54
15:22
14:21
15:00
15:41
17:02
12:51
Sampling
Duration
120
86
120
240
226
281
251
345
136
Ambient
Temperature
°C
-2.0
-2.8
-2.5
3.5
11.5
1.8
-5.0
10.0
10.0
"F
28
27
28
38
53
35
23
50
50
Wind Speed
m/sec
3.3
2.9
3.5
3.5
1.0
2.5
2.4
2.1
3.3
mph
7.4
6.5
7.8
7.8
2.2
5.6
5.4
4.7
7.4
Number of
Vehicle Passes
Cars/
Vans
1,932
1.952
1,848
2,732
2,419
3,672
3,017
1.936
2.705
Light
Trucks
359
107
120
31
54
32
57
39
270
Heavy
Trucks
336
107
176
0
0
0
17
0
273
Mean Vehicle
Speed
mph
30
30
30
35
35
30
35
20
30
kph
48
48
48
56
56
48
56
32
48
OJ
oo

-------
                            TABLE 13.  SPRING TEST SITE CONDITIONS  (St.  Louis Area  Paved  Roads)
Profiler Operation

Run
M-10
M-ll
M-12
M-13
M-14
M-15
M-16
M-17
M-18
M-19

M-20


Site
1-44, Hampton by Sublette
1-44, Hampton by Sublette
1-44, Hampton by Sublette
Kingshighway and Penrose Park
Kingshighway and Penrose Park
Kingshighway and Penrose Park
1-44, Hampton by Sublette
24th and Madison, Granite City
24th and Madison, Granite City
Benton Road and Oregon,
Granite City
Ben ton Road and Hameok,
Granite City

Date
5/7/00
5/8/80
5/B/BO
5/9/00
5/11/80
5/13/80
5/14/80
5/15/80
5/15/80

5/19/80

5/21/80
Start
Time
11:30
9:42
15:27
11:16
9:20
13:46
10:18
12:23
16:19

9:45

10:00
Stop
Time
14:32
12:43
17:57
14:30
12:18
16:01
14:32
14:53
19:11

17:53

10:20
Sampling
Duration
182
181
150
194
178
135
254
150
172

488

Ambient
Temperature
~V
15.5
13.3
18.3
15.5
12.7
24.9
21.1
23.8
23.8

21.1

Test Aborted -
"F
60
56
65
60
55
77
70
75
75

70

light
Wind Speed
in/sec mph
1.3 2.9
3.9 8.7
2.1 4.7
1.2 2.7
4.1 9.2
5.1 11.4
1.8 4.0
1.8 4.0
2.3 5.1

1.2 2.7

and variable
Number of
Vehicle Passes
Cars/
Vans
9.595
9.563
7.751
5,000
3,800
3,900
13.200
3.390
3,670

5,500

winds
Light
Trucks
450
520
850
40
30
30
1.010
-
-

300


Heavy
Trucks
1.095
1.016
1.211
150
110
110
1,220
-
-

-


Mean Vehicle
Speed
mph
55
55
55
35
35
35
55
30
30

30


kph
89
89
89
56
56
56
89
48
48

48


Sampling
Equipment
Config-
uration
A
A
B
A
A
B
A
A
A

A


CO

-------
                                                         TABLE  14.   ACCEPTABLE  TESTS  FOR MLR

                                                                 "'"'Sim Runibor
           Criteria              12345670     9    10    11    12    13     14    15    16    17    18    19
        .   Mean angle of        Yes  Yes  Yes    No    No   Yes  Yes  Yes  Yes    No   Yes   Yes    No    Yes   Yes    No   Yes   Yes   Yes
             wind direction
             and profiler
             orientation
             less llian 20°.

        .   Mean angle of        Yes  Yes  Yes    No    No   Yes  Yes  Yes  Yes    Yes  Yes   Yes    Yes   Yes   Yes    Yes  Yes   Yes   Yes
             profiler orien-
             tation and road-
             way less tlian 45°.

        .   Adequate sam-        Yes  Yes  Yes    Yes   Yes  Yes  Yes  Yes  Yes    No   Yes   Yes    No    Yes   Yes    No   Yes   Yes   No
             pi ing wind
             speed conditions,
             greater than 4 inpli.

        .   Acceptable back-     Yes  Yes  Yes    No    Yes  Yes  Yes  Yes  Yes    Yes  Yes   Yes    Yes   Yes   Yes    Yes  Yes   No    Yes
             ground particle
             concentration re-
             lative to downwind
             samplers
-£;
0         Results are not      Yes  Yes  Yes    Yes   Yes  Yes  Yes  Yes  Yes    Yes  Yes   Yes    Yes   No    Yes    Yes  No    Yes   Yes
             based on average
             emissions data of
             other test runs.

        Acceptable test for     Yes  Yes  Yes    No    No   Yes  Yes  Yes  Yes    No   Yes   Yes    No    No    Yes    No   No    No    No
          MLR

-------
6.2  STREET SURFACE PARTICIPATE LOADINGS

     During each  emissions  sampling run and at other times when emissions
sampling  was  not being conducted,  samples  of  street surface particulate
were collected to determine total particulate loadings and silt percentages.
The  silt  percentage corresponds  to  that  fraction of the surface  sample
< 75 urn in  equivalent  physical  diameter.  As shown  in Table  15,  silt  load-
ings on active travel  lanes ranged from about 0.022 g/m2 on a freeway (1-44)
to more than  2.5 g/m2  on a lightly traveled rural road in Tonganoxie.  As
expected,  loadings  in  curb  areas  substantially  exceeded  loadings  in travel
lanes.  The range of day-to-day variations  in  loadings at a  given  site was
generally within  a factor of 2.  Higher  loadings tended to  occur  after a
precipitation event.

6.3  AIRBORNE PARTICULATE CONCENTRATIONS

     Table 16 lists the upwind  and downwind particulate mass concentrations
for  the various  particle  size  fractions measured  during  the  field  program.
These concentration data were collected under a broad range of environmental
conditions, some  of which did  not  meet the QA  criteria  established for a
valid profiling test (see page  40).   The latter data are included  in Table 16
because they  reflect  the  air quality impact of the roadway under meteoro-
logical conditions  which  occur a significant portion of  the time.  Also
shown in this table is the effective plume  height found by extrapolating the
upper net  (i.e.,  due to the source) TP concentrations to a value  of zero.

     Table 17 provides a summary  of the mass fraction ratios.  As  indicated,
the  IP concentration measured downwind of the test road segment was found to
decrease with  height.   The  mean  ratio of downwind IP to TSP concentration
(2 m) was 0.45 (a = 0.14), and  the corresponding  mean upwind ratio was 0.54
(a = 0.18).   This indicates  that background TSP,  although  lower  in concen-
tration ,  contains a higher percentage of IP.   Similar differences are also
evident in  the mean upwind  versus downwind  < 10  urn  to TSP  ratios  and  FP to
TSP  ratios.
                                     41

-------
                                       TABLE  15.   PAVED ROAD SURFACE DUST LOADINGS
1X3


Test site by land use category
COMMERCIAL/INDUSTRIAL
7th Street
7th Street
7th Street
7th Street
7th Street
7th Street
COMMERCIAL/RESIDENTIAL
Volker Boulevard
Volker Boulevard
Volker Boulevard
Volker Boulevard
Volker Boulevard
Volker Blvd. (2 blks. E of prev. site)
Rockhill Road
Kingshighway and Penrose Park
Kingshighway and Penrose Park
Kingshighway and Penrose Park
24th and Madison, Granite City
24th and Madison, Granite City
Uenton Road and Oregon
20th Street (E. of Steel Plant)
EXPRESSWAY
1-44, Hampton by Sublette
1-44, Hampton by Sublette
1-44, Hampton by Sublette
1-44, Hampton by Sublette
1-44, Hampton by Sublette
RURAL 10WN
Tonganoxie - 4th St. (W of Church St.)
Tonganoxie - 4th St. (W of Church St.)
Tonganoxie - 4th St. (3 blocks W of
previous site)
Tonganoxie - 4th St. (3 blocks W of
previous site)
Tonganoxie - Main Street
Tonganoxie - Main Street


Date

2/11/80
2/12/80
2/12/80
2/22/80
3/03/80
3/10/80

2/13/80
2/26/80
2/27/80
3/03/80
3/05/80
3/05/80
2/28/80
5/09/80
5/11/00
5/13/80
5/15/80
5/15/80
5/19/80
5/21/80

5/07/80
5/08/80
5/08/80
5/14/80
5/21/80

3/16/80
3/17/80
3/06/80

3/17/80

3/06/80
3/17/80


Run

M-l
M-2
M-3
-
-
M-9

_
M-4
M-5
-
-
-
M-6
M-13
M-14
M-15
M-17
M-18
M-19
-

M-10
M-ll
M-12
M-16
-

-
-
M-8

-

-

No. of
traffic
lanes

4
4
4
4
4
4








2
2
2
4
4
2
4

8
8
8
8
B

2
2
2

2

2
2
Average
width
(m)

3.4
3.4
3.4
3.4
3.4
3.4

2.7
2.7
2.7
2.7
2.7
2.7
2.7
3.4
3.4
3.4
3.0
3.0
3.0
2.7

3.6
3.6
3.6
3.6
3.6

3.0
3.0
3.0

3.0

3.0
3.0
lane

(ft)

11
11
11
11
11
11

9
9
9
9
9
9
9
11
11
11
10
10
10
9

12
12
12
12
12

10
10
10

10

10
10
Total
Curb
(gr/ftz) (g/mz)

203 142
a a
a a
5,670 3,160
-
-

a h
2.590 I.BIO"
3,640 2,540°
-
h
1,330 929"
910 635°
41.3 28.
-
— -
~K
560 391,
168 117D
245 171

-
-
-
-
-

-
-
-

-

-

loading
Travel
(gr/ftzi

6.2
6.1
6.0
7.7
4.5
3.4

3.1
3.3
6.7
3.2
3.8
9.8
4.7
8 1.12
-
0.81
20.3
14.8
15.4
20.3

-
-
-
-
0.07

322.0
238.0
24.5

35.7

13.3
14.7

lanes
(9/B)Z)

4.3
4.2
4.2
5.4
3.1
2.4

2.2
2.3
4.7
2.2
2.6
6.8
3.3
0.8
-
0.6
14.2
10.3
10.8
14.2

-
-
-
-
0.05

224.8
166.2
17.1

24.9

9.3
10.3
Silt Content
{%)
Curb Travel lanes

15.7 10.7
a 6.2
a 3.5
8.7 11.9
5.5
12.2

a 5.9
12.3 18.8
13.7 21.4
20.2
22.7
11.3° 20.7
21.2 21.7
8.2 13.7
-
2.6 8.1
5.7
12.5° 7.1
15.5° 8.6
13.2 6.7

-
-
-
-
46.0

9.6
6.9
14.5

7.4

11.0
41.1
          Curb area wet.
          Average of two samples.

-------
                                      TABLE  16.   PARTICIPATE  CONCENTRATIONS AND PLUME HEIGHT
        Run number
Upwind concentration (|iq/m*)
IP
(2 m)
£10 |im
(2 in)
FP
(2 m)
TSP
(2 m)
IP
(1 m/3 m)
Downwind concentration dig/in*}
£10 pin
(1 m/3 m)
FP
(1 m/3 m)
TSP
(2 m)
IP
(2 m)
Downwind
plume height
(m) '
       COMMfRClAt/INDUSTRIAL

                        M-l
                        M-2
                        M-3
                        M-9

       COMMERCIAL/RESIDENTIAL
to
        EXPRESSWAY
        RURAL TOWN

                        M-fl

          No daTa collected

        a
19
12
35
65
M-4
M-5
M-6
M-7
M-13
M-14
M-15
M-17
M-18
M-19
M-10
M-ll
M-12
M-16
37
83
57
31
60
37
59a
65
75
47a
83
71
65a
42
62
                                          54
                                          31

                                          60
                                          60
                                          70
                                          63

                                          38
                    33
                    16

                    39
                    47
                    34
                    40

                    24
120
 46
 77
128
 65
 99
 78
 42
 79
 80
161
 98
113
 72
131
154
198
 67
                              100
146/100
 35/33
 93/62
207/106
 37/32
110/95
 69/71
154/70
 00/71
 34/38
100/13
 64/61
 92/85
 57/50
           171/125
124/94
 33/31
 79/60
169/06
 31/27
 90/85
 63/63
130/61
 70/63
 20/34
 09/10
 56/53
 82/74
 51/42
             140/109
68/60
28/23
44/40
77/31
17/11
55/46
41/38
57/26
42/39
15/22
56/6
39/35
51/48
33/31
121/110
99/03
96/79
71/63
104/100
86/75
84/70
65/56
53/50
51/46
55/45
44/37
275
233
228
128
323
322
161
191
             59/49
l)
TSP
(2 m)
490
68
BO
400
76
190
127
190
164
116
200
160
187
109
275
233
226
128

IP
(2 m)
368
124
183
437
85
248
138
210
199
184
242
228
230
112
323
322
161
191
Downwind
plume height
(m) '
8K5
106
0.1
0.5
4.6
6.1
7.2
V
I0b
7.1
6.0
6.5
M
10"
4.0
4.5
4.8
5.8
            348
                                                                                       307
0.5
          Represents the average  of 1 and 3 meter measurements.
          Assumed value.

-------
TABLE 17.  SUMMARY OF PARTICULATE SIZE RATIOS
Statistical
parameter
X
o
RSI)
t)

JP/TSP
0.54
O.lb
0.2fl
19

<.10 pm/TSP
0.54
0.11
0.20
7
Upwind
FP/1SP
0.33
0.090
0.27
7

<10 ,.n,/IP
0.88
0.034
0.039
7

FP/TP
0.53
0.08'j
0.16
7

IP/TSP
0.45
0.14
0.3J
19

<10 iMU/TSP
0.40
0.13
0.32
19
Downwind
FP/TSP
0.24
0. 092
0.38
19

<10 pin/IP
0.87
0.028
0.032
19

FP/IP
0.52
0.098
0.19
19

-------
     The FP  to  IP mean ratio measured downwind was 0.52 (cr = 0.098) while
the mean upwind  ratio was 0.53  (a  = 0.085).   This finding  implies  that
there is no  significant enrichment of fine  particles  attributable to  the
paved road source.

6.4  EMISSION FACTORS

     Tables 18 and 19 present for each test the calculated emission factors
(IP, < 10  |jm, and FP) and corresponding  source  characterization  parameters
which are  thought to affect the  intensity  of emissions  from paved roads.
Appendix A describes  the  procedures used to  calculate  the  emission factors
from field testing data.

     Tables 20 and 21 summarize, by  land  use  category  and test series qual-
ity, the emission factor and associated  parameter  data.   As  can be  seen,
the smallest  emission factors  were measured  in the freeway category which
also had the lowest surface silt  loadings.  The highest emission  factor was
measured in  the  rural town category which  showed a correspondingly high
surface silt loading.

     Intercomparison  of emission  factors by land-use category  indicates
that relative to the mean expressway  IP emissions:   (a) mean commercial/
residential IP emissions were approximately 10 times larger;  (b)  commercial/
industrial emissions  were approximately  20  times  larger; and (c) the  rural
town roadway produced IP emissions  that  were  roughly 60 times larger.  Rela-
tive to mean  expressway silt  loading:  (a) the silt loading for  commercial/
residential roadways was approximately 25 times higher; (b) the  silt loading
for commercial/industrial roadways  was roughly 15 times higher;  and (c)  silt
loading on the   rural  town roadway  was  approximately  115  times  higher.
                                     45

-------
                                             TABLE  18.   PAVED  ROAD EMISSION FACTORS9
cn
Inhalable particulate < 10 pin particulate Fine particulate
emission factor , emission factor , emission factor ,
Run No.

Site
(g/VKT)
(Ib/VMT x 101)" (g/VKT)
(Ib/VMT x 10T (g/VKT)
(Ib/VMf x 10')
COMMERCIAL/INDUSTRIAL




M-l
M-2
M-3
M-9
7th Street
7th Street
7th Street
7th Street
3.52
1.01
2.39
2.80
125.0
35.7
84.8
99.3
3.10
0.96
2.20
2.01
110.0
34.0
78.1
71.2
1.78
0.86
1.54
1.14
63.2
30.4
52.0
40.5
COMMERCIAL/RESIDENTIAL
















EXPRESSWAY








RURAL TOWN

M-4
M-5
M-6
M-7
M-13

M-14

M-15

M-17

M-18

M-19


M-10

M-ll

M-12

M-16


M-8
Volker Boulevard
Volker Boulevard
Rockhill Road
Volker Boulevard
Kingshighway and
Penrose Park
Kingshighway and
Penrose Park
Kingshighway and
Penrose Park
Granite City. 24th
and Madison
Granite City. 24th
and Madison
Granite City, Benton
Road and Oregon

1-44, Hampton .by
Sublette
1-44, Hampton by
Sublette
1-44, Hampton by
Sublette
1-44, Hampton by
Sublette

longanoxie, 4th Street
0.19
0.47
0.93
3.30
0.22

0.93

1.01

1.92

0.32

0.16


0.12

0.22

0.059

0.16


8.77
6.7
16.8
32.9
117.0
7.8

33.0

35.8

68.0

11.4

5.8


4.1

7.8

2.1

5.8


311.0
0.11
0.43
0.86
2.62
0.19

0.85

0.91

1.64

0.23

0.11


0.11

0.20

0.052

0.15


6.96
4.0
15.3
30.4
92.8
6.8

30.1

32.3

58.2

8.0

3.9


3.9

7.0

1.9

5.3


247.0
c
0.16
0.59
1.04
0.11

0.62

0.62

c

0.052

d


0.063

0.097

0.039

d


1.42
c
5.6
20.9
36.8
4.0

22.0

22.0

c

1.9

d


2.3

3.4

1.4

d


50.4

              Emission  factors for <  10 and FP require use of interpolated concentrations.



              To convert these factors to Ib/VMT multiply by 10 4.



              Downwind  and upwind concentrations were equal.
              Data
                        preclude the
                                          ination of  an emission factor.

-------
                                   TABLE 19.   SOURCE CHARACTERIZATION PARAMETERS
Sill loading
Hun number
COMMERCIAL/INIHISIKIAL
M-l
M-2
M-3
M-9
COMMERCIAL/RESIDENTIAL
M-4
M-5
M-6
M-7
M-13

M-14

M-15

M-17

M-18

M-19

EXPRESSWAY
M-10

M-ll

M-12

M-16

Site

7th Street
7th Street
7th Street
7lh Street

Volker Boulevard
Volker Boulevard
Rockhill Road
Volker Boulevard
Kingshighway and
Penrose Park
Kingshighway and
Penrose Park
Kingshighway and
Penrose Park
Granite City. 24th
and Madison
Granite City. 24lh
and Madison
Granite City, Benton
Road and Oregon

1-44, Hampton by
Sublette
1-44, Hampton by
Sublette
1-44, Hampton by
Sublette
1-44, Hampton by
Sublelte
fiTi T

0.46
0.26
0.15
0.29

0.43
1.00
0.68
0.59
0.11

0.079

0.047

0.83

0.73

0.93


0.022

0.022

0.022

0.022

(gr/ft*)

0.66
0.37
0.21
1.41

0.61
1.43
0.97
0.84
0.16

0.11

0.067

1.19

1.04

1.33


0.03]

0.031

0.031

0.031

Moan vehicle speed
(W)

48
40
48
48

56
56
48
56
56

56

56

48

48

48


89

89

89

89

(mph)

30
30
30
30

35
35
30
35
35

35

35

30

30

30


55

55

55

55

Mean vehicle weight
(Mg)

5.1
3.4
4.1
3.7

1.9
2.0
1.9
2.1
2.4

2.4

2.4

1.8

1.8

2.2


4.1

4.4

3.4

3.9

(tons)

5.6
3.8
4.5
4.1

2.1
2.2
2.1
2.3
2.7

2.7

2.7

2.0

2.0

2.4


4.5

4.8

3.8

4.3

RURAL TOWN
               M-0
Tonganoxie, 4th St.
                                           2.50
3.58
32
20
                                                                                           2.0
2.2

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                                 TABLE  20.   SUMMARY OF PAVED ROAD EMISSION FACTORS
Land use
category
Commercial/
Industrial
Commercial/
Residential
Lxpresswoy
Rural Town
Test
series
quality
All tests
MLR tests
All tests
MLR tests
All tests
MIR tests
All tests
MLR tests
Test numbers
M-l, 2. 3, 9
M-l, 2, 3, 9
M-4, 5, 6. 7, 13, 14,
15, 17. 18, 19
M-6, 7. 15
M-10. 11, 12, 16
M-ll, 12
M-8
M-8
IP
x
(fl/VKl)
2.43
2.43
0.94
1 75
0.14
0.14
8.77
8.77
emission factor
(9/VKT)
1.06
1.06
0.99
1.35
0.069
0.12
-
RSI)/ROa
0.44
0.44
1.05
0.77
0.50
1.16
-
SJO |iin emission factor
x
(gMi)
2.07
2.07
0.80
1.46
0.13
0.12
6.96
6.96
i)
(g/VKI)
0.88
0.99
0.80
1.00
0.062
0.10
-
RSO/RO3
0.42
0.42
1.01
0.68
0.48
1.16
-
f-P emission factor
x
(g/VKl)
1.31
1.31
0.46
0.75
0.66
0.068
1.42
1.42
a
(g/VKf)
0.40
0.40
0.36
0.25
0.029
0.041
-
HSI)/KI)a
0.30
0.30
0.79
0.34
0.44
0.85
-
USD (relative standard deviation) calculated when more than  two data  points are present.



                        Ix - xj
RO
deviation) =
-*- calculated when two data points  are present.

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                                TABLE  21.   SUMMARY  OF SOURCE  CHARACTERIZATION  PARAMETERS
,„.., Silt loading
Land use
category
Commercial/
Industrial
Commercial/
Residential
Expressway
Rura 1 Town
series
qual ily
All runs
MLR runs
Al 1 runs
MLR runs
All runs
MLR runs
A 1 1 runs
MLR runs
Test numbers
M-l. 2, 3, 9
M-l. 2. 3. 9
M-4. 5. 6. 7. 13.
15. 17. 18. 19
M-6. 7, 15
M-10. 11, 12, 16
M-ll, 12
M'8
M-8
x o
(a/w2) (9/m2)
0.29 0.13
0.29 0.13
14. 0.51 0.36
0.14 0.34
0.022
0.022
2.5
2.5
x
RSD/RO3 (kph)
0.45 48
0.45 48
0.67 53
0.77 53
89
89
32
32
Vehicle speed Vehicle weight
0 a x
(kph) RSD/KIT (Mfl)
4.1
4.1
4.2 0.079 2.1
4.6 0.087 2.1
4.0
3.9
2.0
2.0
u
(Mfl)
0.75
0.75
0.25
0.25
0.42
0.71
-
RSI)/RDa
-
0.12
0. 12
0.26
:
KSD (relative standard deviation) calculated when more than two data points are present.

                        £Jx - x I
            leviation) =  -'	A
RO (relative deviation)
calculated when two data points are present.

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               50

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                    7.0  MULTIPLE REGRESSION ANALYSIS
7.1  INTRODUCTION

     Stepwise Multiple Linear Regression (MLR) was the method used to evalu-
ate independent  variables  for possible  use  as  correction  factors  in  a pre-
dictive emission factor equation.  It is available as a computer program in
the Statistical  Package  for  the  Social  Sciences  (SPSS).17  The MLR program
outputs of  interest  in evaluating the data sets for the paved road source
tests are the multiple regression coefficient, significance of the variable,
and reduction in relative standard deviation due to each variable.  Further
information on MLR can be found elsewhere.16 18

     It is desirable to have correction factors in the emission factor equa-
tions multiplicative rather than additive; consequently all independent and
dependent variable data  are  transformed to  natural  logarithms before being
entered in the MLR program.

     The stepwise regression program:  (a) selects the potential  correction
factor that  is  the  best predictor of IP emission factors; (b) changes the
dependent variable values  to reflect the impact of this independent vari-
able; and, (c) repeats this process with remaining potential  correction fac-
tors until  all  have  been used in the MLR equation or until no improvement
in the predictive equation is obtained by adding another variable.  Not all
variables included in  the  MLR equation  are  necessarily  selected  as correc-
tion factors.
                                     51

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 The steps followed in developing correction  factors  are  listed below:

 1.    Create a data array  of all monitored independent variables with
      corresponding emissions measurements.

 2.    Input these  data into  the MLR program using a COMPUTE statement
      to transform both  independent and dependent variables  to their
      natural  logarithms.

 3.    From the summary statistics,  find variables that  have  a  signifi-
      cance less  than 0.05.   These are definite  correction factors.

 4.    Next, evaluate  those  variables  with a  significance  of 0.05 to
      0.20.  If any of these variables are judged to be pertinent in-
      dependent variables  they  may also  be  included  as  correction
      factors.

 5.    Determine the form of  the  emission  factor equation,  exclusive  of
      the coefficient  (base emission factor).

 6.    Assume typical  values for the  correction parameters.

 7.    Calculate adjusted  emission factors  at the average conditions for
      all the correction  parameters, using the relationships established
      in the emission  factor equation.

 8.    Determine the geometric mean for the adjusted data set.  This mean
      is the base emission factor or coefficient in the emission factor
      equation.

 9.    Finalize  the emission factor equation as the base emission factor
      times each  correction parameter normalized to average conditions.

10.    Determine the precision factor for  the  emission factor  equation.
                                 52

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7.2  ANALYSIS AND RESULTS

     The independent  variables  evaluated initially as possible correction
factors were  silt loading (g/m2), total  loading  (g/m2),  average vehicle
speed,  (Kph),  and average vehicle weight (Mg).  The rationale for includ-
ing measures  of  roadway  particulate loading  stems  from  findings  of an
earlier MRI program3  which indicated that the  magnitude  of  roadway  emis-
sions was  directly  related to variations in  surface  loadings.   The  vehi-
cle parameters—mean  weight  and  speed—were  included  largely by  analogy  to
MRI's unpaved  road equation,19 although  it was recognized that the dust gen-
eration mechanism for paved roads may differ from that for  unpaved roads.
The moisture  content  of the  road surface particulate  was  not included  as  a
correction parameter  because of  the  difficulty of collecting a sample with-
out altering  its  moisture  content.

     The correlation  matrix  associated with a preliminary MLR analysis of
the entire  data set  is shown in  Table  22.   Examination  of the  matrix indi-
cated that  all the  independent  variables except vehicle weight were  highly
intercorrelated.   Although the  stepwise algorithm  would  include vehicle
speed first  in a predictive equation, silt  loading and total  loading show
essentially the same  correlation with IP emissions  (r  =  0.60).   In  other
words,  the  variables  represent  a common  set  of source  conditions—either
low vehicle  speed, high  surface loadings and emissions  or  high  vehicle
speed,  low loadings and emissions.

     The decision was  made to use silt loading  rather than total loading or
vehicle speed  in  the development of the  emission factor  equation from the
"MLR" data  set.  This decision  was  based on the  perception  that (a) silt
loading is  the most physically  plausible indicator of  the magnitude of  IP
emissions, and (b)  it will yield more reproducible results  in independent
applications  than total  loading, a  parameter  which  can be  biased by the
presence of macro size particles (i.e.,  gravel).
                                      53

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             TABLE 22.   CORRELATION MATRIX FOR ENTIRE DATA SET
                          (n = 19)
eIP
IP Emission factor 1.0
C.IP)
Silt loading
Total loading
Vehicle speed
Vehicle weight
Silt
loading
0.56

1.0



Total
loading
0.63

0.94
1.0


Vehicle
speed
-0.74

-0.86
-0.94
1.0

Vehicle
weight
0.02

-0.62
-0.56
0.48
1.0
     The correlation matrix associated with the "MLR" data set is presented
in Table 23.   Including  silt  loading as the primary predictor effectively
precludes total loading or vehicle speed from entering the equation.  This
follows from the high intercorrelations (multicollinearity) mentioned above.
Examination of the regression  statistics indicated that inclusion of vehicle
weight as a second correction  parameter could not be justified.
             TABLE 23.   CORRELATION MATRIX FOR "MLR" DATA SET
                          (n = 10)
SIP
IP Emission factor
(elp) 1.0
Silt loading
Total loading
Vehicle speed
Vehicle weight
Silt
loading
0.85
1.0
Total
loading
0.91
0.92
1.0
Vehicle
speed
-0.89
-0.89
-0.97
1.0
Vehicle
weight
-0.08
-0.46
-0.31
0.37
1.0
                                     54

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     The raw  MLR  equation  for  the  "MLR"  data  set  ,  as  output from the  SPSS
package is as follows:
                              elp = 4.37 (sL)°-8                      (1)
where:

               6jp =  IP emission  factor  expressed in grams per  vehicle
                       kilometer traveled (g/VKT)

               sL =   Silt  loading of road surface  part icu late matter ex-
                       pressed in grams per square meter (g/m2).

This  equation  explains  73% of the variation  in  the emission factors.  As
noted earlier, the  "MLR"  data set does contain data from all  the land use
categories sampled during the field program.

      Equation 2 presents the comparable predictive IP emission factor equa
tion  normalized to a typical value for silt loading:

                                             0
The normalization  procedure  consists of steps 6 through 10 as outlined in
Section 7.1 (p. 52).

     Table 24  presents  the  predicted versus measured IP emission factors,
and provides  a comparative  statistic—the ratio of  predicted  to  measured
emission factors  for  each test.   The same  information  is  presented  graphi-
cally by land  use category in Figure 7.  As can be seen, there is consider-
able variation between predicted and measured emission factors, both overall
and within individual  categories.  The only discernible, predictive bias ap-
pears in the  commercial/industrial  subset  where  the  tendency  appears  to  be
for the emission factor equation to  underpredict observed emissions.
                                     55

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TABLE 24.   PREDICTED VERSUS OBSERVED IP EMISSION FACTORS
  Land use
  category
  IP Emission factor
        (g/VKT)
Observed
Predicted
Ratio'
Commercial/
  industrial
Commercial/
  residential
Expressway
Rural town
               M-l
               M-2
               M-3
               M-9
               M-6
               M-7
               M-15
               M-ll
               M-12
               M-8
  3.52
  1.01
  2.39
  2.80
  0.928
  3.30
  1.01
  0.222
  0.0589
  8.77
  2.37
  1.51
  0.970
  1.64
  3.25
  2.90
  0.384
  0.209
  0.209
  9.20
 0.67
 1.50
 0.41
 0.58
 3.50
 0.88
 0.38
 0.94
 3.55
 1.05
   Predicted divided by observed.
                            56

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     10
 u
 a
E
UJ
a.
•o
4)
.3
o
    0.1
   0.01
                         1  1 1 1 1       1    1   1  1  1 1  1 1 1       1    1  1   1 1  1 1
                    /
                 .
               /
                            /
              1    1   1  1  1  1 1 1 1
                                                                       /:
                                                         °   /
                                                /
                                                      /
                                                   /  o
                                                 Land Use Category
                                                  O Commercial/Industrial
                                                  C3 Commercial/Residential
                                                  A Expressway
                                                  • Rural  town
     0.01
                             0.1                      1
                         Predicted IP Emission Factor (g/VKT)
10
Figure 7.   Predicted versus observed IP emission factors by  land  use  category.
                                   57

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This tendency may be the result of a combination of the  high percentage  of
heavy-duty vehicles (~  20%)  coupled  with vehicle  idle,  acceleration,  and
deceleration typically  associated with  proximity to traffic lights.   The
latter condition normally  produces a significant  increase  in the  exhaust
emissions component, which would  not be incorporated  in the silt  loading
model.

7.3  COMPARATIVE EVALUATION

     The emission factor equation predicts the "MLR" series test data  with
a precision factor of 2.0.   The precision factor (f) for an emission factor
is  defined  such that the 68% confidence  interval for a predicted value (P)
extends from P/f to Pf.   The precision  factor is determined by exponentiat-
ing  the  standard deviation of  the differences (standard  error of the esti-
mate) between the natural  logarithms  of the predicted and observed emission
factors.

     The precision factor may be interpreted as  a measure of "average"  error
in  predicting IP emissions from the regression equation.   Assuming that the
actual IP emission factors are log normally distributed about the regression
line, it can be stated that approximately 68% of the predictions are within
a factor of 2.   The effective outer bounds of predictability are determined
by  exponentiating twice the standard error of the  estimate.  The resultant
estimate of predictive accuracy, in this case 4.0,  then encompasses approxi-
mately 95% of the predictions.

     To put the precision factor of the IP predictive emission factor  equa-
tion emission  factor into  perspective,  two comparisons were undertaken
utilizing the single-value emission  factor  found in the  current AP-42  man-
ual.3  However,  before valid comparisons could be made, it was necessary  to
convert the AP-42 single value factor which represents TSP emissions,  to  an
approximate IP emission factor.
                                     58

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This was  accomplished by multiplying the AP-42  value  by  0.4 which  is  the
mean ratio  of  net IP (downwind minus upwind) to net TSP concentrations as
determined  from  the  data collected in this  study.   This  ratio  may  be  ex-
pressed as  follows:
                            " IPUp)
Because this  ratio  reflects  net emissions,  that  is,  the  emissions  directly
attributable  to  the source,  it is  preferable  to  one  based  on  sizing  infor-
mation given  in AP-42 which describes emissions due to both source and back-
ground.  As  noted  in AP-42,  the latter  information  will be biased toward
small particle sizes.

     The first comparison involved the calculation of a precision  factor for
the AP-42 data set.  The resulting value of 2.1 is a measure of the ability
of the  single-value factor  to  represent the  40  pieces of  data which were
averaged originally to produce  the AP-42 factor.   The second comparison in-
volved the  calculation  of a precision factor using the single value AP-42
factor to  represent the "MLR"  data set, as collected in this study.   This
comparison yielded  a precision  factor of 4.4.

     The precision  factors and the range of the  data values  (emission  fac-
tors)  upon  which they are based,  are  presented  graphically in Figure 8.
The ideal model has a precision  factor of 1.0, implying that each  predicted
value  is  identical  to the corresponding observed  valuer over an  infinite
range of emission factors.  The  most important conclusion  that can be drawn
from Figure  8 is that the emission factor  equation,  though far from  ideal,
does predict  IP emissions more  accurately over a much greater range of val-
ues than  does the AP-42 single-value  factor  over  a considerably  smaller
range of data values corresponding to the AP-42 data  set.  Furthermore,  ap-
plication  of  the single-value AP-42 factor to represent the wide  range  of
IP emissions  from paved roads  as  measured  during  this program, yields  a
                                     59

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  5p-
u
o
                            AP-42 Applied to Present Data
c
o

                         Present Regression Equation

                                                 r	 AP-42 Emission Factor
                                      Ideal Model
           I    I   I  I  I II I I       I    I   I  I  I  I I I
   0.01                   0.1                      1                       10

                            Emission Factor ~(g/VKT)



            Figure 8.   Comparison of emission factor  models.
                                     60

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precision factor which is more than double (4.4 versus 2.0) that associated
with the  predictive  equation.   This ability of the predictive equation to
more accurately  represent variations  in  IP  emissions  is  directly  attribut-
able to  the relatively strong relationship  between  roadway surface silt
loading and IP emissions.

7.4  EXTENSION OF THE PREDICTIVE EQUATION TO DIFFERENT PARTICLE SIZE
       FRACTIONS

     The particle sizing  data obtained from the SSI/CI combinations was also
used to develop emission  factors and predictive emission factor equations for
the ^ 10 urn and FP particle size fractions.  These analyses used the same pro-
cedure as that applied in developing the equation for IP (see Section 7.1).
Derivation of TSP emission factors for use in developing a predictive equation
required different initial calculations, since only two TSP samplers (one up-
wind, one downwind) were  operated during the measurement phase of the program.
In essence, the initial calculation involved multiplication of the IP emission
factor for each run in the "MLR" series data set by the corresponding net ratio
of TSP to IP concentration as measured by appropriate samplers (see Figures 4
to 6).   This procedure assumes that the TSP/IP ratio is constant over the ver-
tical extent of the plume.

     The  general  form of the emission factor  equation  applicable to all
particle size fractions,  is as follows:

                      p
          e = k (^)              (metric)                           (3)
                      p
          e = K (f)              (English)                          (4)
The  base  emission factor coefficients  (k,  K) ,  exponent  (P),  and  precision
factor for each size  fraction are  listed  in Table  25.  For  the  metric  equa
tion,  silt  loading is expressed as  grams per square meter;  silt loading
for  the English equation  is  expressed  as  grains  per  square  foot.
                                      61

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         TABLE 25.   PAVED ROAD EMISSION FACTOR EQUATION PARAMETERS
                      (by particle size fraction)
Particle size fraction
TSP
IP
^ 10 |jm
FP
k (g/VKT)
5.87
2.54
2.28
1.02
K (Ib/VMT)
0.0208
0.0090
0.0081
0.0036
P
0.9
0.8
0.8
0.6
Precision factor3
2.4
2.0
2.2
2.2
a  Represents the interval  encompassing 68% of the predicted values.

     It should be noted that the tendency for the power term in the equation
to increase with larger particle size fraction is generally consistent with
MRI's previous paved road  equation  in which silt loading to the 1.0 power
was employed to account for variations in TSP emissions.

7.5  EMISSIONS INVENTORY APPLICATIONS

     For the majority  of emissions  inventory applications involving urban
paved roads, actual  measurements of silt loading will  probably not be made.
Therefore,  in order to  facilitate the use of the previously described equa-
tions,  it  is necessary to characterize silt  loadings according  to  a param-
eter(s) more readily available to persons developing emissions inventories.
After examination and  analysis  of silt loading and traffic data collected
during  relevant  MRI  sampling programs, as  well  as surface loading data
gathered in connection with  an  extensive study  of  urban water  pollution,
the decision  was  made  to characterize variations  in  silt loading based
upon a roadway classification  system.   The roadway classification system
developed by MRI for this purpose is presented in Table 26.
                                     62

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                  TABLE 26.   PAVED ROADWAY CLASSIFICATION
                                Average daily traffic
          Roadway type                  (ADT)             No.  of lanes
Freeway/expressway
Major street/highway
Collector street
Local street
> 50,000
> 10,000
500-10,000
< 500
> 4
> 4
2a
2b
     a  Total roadway width g 32 ft.
        Total roadway width < 32 ft.

This system  generally corresponds to the  functional classification systems
employed by  transportation  agency  personnel;  and thus the data necessary
for emissions inventory—number of road miles per road category and traffic
counts—should be  easily estimated.  It  should be  noted that  in some situa-
tions it may be  necessary  to combine this  silt loading  information with
sound engineering judgment in order to approximate the loadings for roadway
types not specifically included in Table 26.

     It should be  recalled  from Section 2.0 that  traffic volume is not the
only factor affecting roadway silt loadings.  For all  roadways that provide
access to  immediately adjacent areas, land  use, particularly as it relates
to the potential for mud and dirt  "tracking," is  important.   Silt  loadings
may also be  affected by  street surface  type and condition, the presence  or
absence of curb, as well as  public works  practices  and season of the  year.
However,  given the  present  data base,  it  is  not  possible to incorporate
relationships between these  factors and silt loadings in a manner applicable
to the majority of emissions  inventories.

     The data  base  made  up  of 44 samples collected and analyzed according
to the procedures outlined in Sections 4.2  and  5.4 may be used to character-
ize the  silt loadings  for each roadway category.  These samples, obtained
                                     63

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during MRI field sampling programs over the past 3 years, represent a broad
range of  urban  land  use and roadway conditions.  Geometric means for this
data set are broken out by sampling location (i.e., city) and roadway cate-
gory in Table 27

    TABLE 27.  SUMMARY OF TYPICAL SILT LOADINGS (g/m2) FOR URBAN PAVED
                 ROADWAYS3 BY CITY
Roadway
Local Collector
City Xgb
Baltimore1" 1.42
Buffalod 1.41
Granite City (111.)8
Kansas City6
St. Louis6
n Xg
2 0.72
5 0.29
.
2.11
- -
n
4
2
-
4
-
category
Major
Xg
0.39
0.24
0.82
0.41
0.16
n
3
4
3
13
3
Overal 1
xg
0.68
0.56
0.82
0.60
0.16
n
9
11
3
17
3
  a  Freeway/expressway loading measurement (0.022 g/m2) from Table 19 not
     included.
     Xg's are geometric means based on the corresponding n sample size.
  c  Reference 20.
     Reference 21.
  6  From this report.

     The sampling  locations  can be considered  representative  of  most  large
urban areas  in  the United States with the possible exception of those lo-
cated in the Southwest.  Except for the collector roadway category, the over-
all mean silt  loadings do not vary greatly from  city  to  city, though the
St. Louis mean for major roads is somewhat lower than the other  four  cities.
The substantial variation within the collector roadway category  is probably
attributable to the deposition effects of land use associated with the spe-
cific sampling  locations.   It should  also be noted that an examination of
data collected at three cites in Montana during early spring, indicates that
winter road  sanding may produce loadings  five  to  six times  higher  than the
means of the loadings given in Table 27 for the respective road  categories.22

                                     64

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     Typical silt loadings by roadway category (from Table 27) are as follows:
          Local streets                 1.41 g/m2
          Collector streets             0.92 g/m2
          Major streets and highways    0.36 g/m2
          Expressways/freeways          0.022 g/m2
It should be noted that regression analysis indicates a significant (a = 0.01)
relationship between silt loading and traffic volume of the following form.
                          sL = 21.3 (ADT)
                                         -0.41
This equation explains 35% of the sample variation.

     Table 28 presents  the emission  factors  broken out  by  roadway category
and particle size.  These were obtained by inserting the typical silt loadings
of each roadway category into the emission factor equations found in Section
7.4, Table 25.   These emission factors can be utilized directly for emission
inventory purposes.  It is important to note that the current AP-42 paved road
emission factors3 for TSP agree quite well with those developed in this study.
For example, those cited in connection with MRI's previous testing2 were con-
ducted at two roadway sites in the major street and highway category.  Those
tests yielded a  mean TSP emission factor of 4.3 g/VKT versus 4.4 g/VKT as
determined from the data presented here.
   TABLE 28.   RECOMMENDED EMISSION FACTORS FOR SPECIFIC ROADWAY CATEGORIES
                AND PARTICLE SIZE FRACTIONS
Emission factor by parti cl
Roadway
category
Local
Collector
Major street

g/VKT
15
10
4.4
TSP
Ib/VMT
0.053
0.035
0.016
^ 15
g/VKT
5.8
4.1
2.0
urn
1 b/VMT
0.021
0.015
0.0071
^
g/VKT
5.2
3.7
1.8
e size fraction
10 urn
1 b/VMT
0.018
0.013
0.0064
^ 2.
g/VKT
1.9
1.5
0.84
5 |jm
1 b/VMT
0.0067
0.0053
0.0030
  and highway
Freeway/       0.35
  Expressway
0.0012  0.21   0.00074  0.19   0.00067  0.16   O.OOOS7
                                     65

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                    66

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                       8.0  SUMMARY AND CONCLUSIONS
     The purpose of this  study was  to  quantify  inhalable  particulate  emis-
sions generated by  traffic entrainment of paved  road  surface  particulate
matter.   Paved road  source testing was performed  at sites  representative
of significant  emission sources within a  broad range  of urban  land-use
categories.

     The measured inhalable  particulate  emission factors ranged from 0.06
to 8.77 g/VKT.   Lowest mean emissions were  measured for  the "Expressway"
use category; highest mean emissions were measured for the "Rural Town1' use
category.   Approximately  90% of the IP emissions  consisted of particles
smaller than 10 urn in aerodynamic diameter, and approximately 50% of the IP
emission consisted of particles smaller than 2.5 |jm in aerodynamic diameter

     Correlation analysis  of IP  emissions  with parameters  characterizing
the source conditions  showed the  existence of a relatively  strong positive
relationship between  intensity of  emissions  and roadway  surface  silt  load-
ing.   This confirms the findings  of earlier  testing..2  Based on  regression
analysis of a subset of acceptable  ("MLR") test runs, the following predic-
tive IP emission factor equation was developed:

                                                o- s
                              elp=2.54  (gtj)                       (5)

     where     e,p = Inhalable particulate emission factor  (g/VKT).
               sL  = Road  surface silt loading  (g/m2).
                                     67

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     This predictive equation has an associated precision factor of  2.0  in
relation to the  "MLR"  data set.   By way of comparison, the AP-42  single-
value factor (corrected  to  represent  IP emissions) has a precision factor
of 2.1  for  its  data set and a precision factor of 4.4 for the "MLR"  data
set,  which  spans  a  much larger range of values  than the AP-42 data set.
Therefore the predictive equation,  though  far from  ideal, does represent
IP emissions more accurately  over a much larger range of values  than does
the AP-42 single-value  factor.   This  fact  is  directly attributable to the
relationship of IP emissions to silt loading.

     Extension of the regression  analysis to include emission factor  equa-
tions for other  particle size  fractions—FP,  < 10 urn, and TSP—yielded  a
set of  equations  in which  the power term for silt loading increased with
larger  particle  size fraction.   This  result is generally consistent with
MRI's previous paved road  equation  in  which silt loading to  the  1.0 power
was employed to account for variations  in TSP  emissions.

     To facilitate the  use of these particle size specific equations in the
development of  emission inventories,  a classification system of  mean or
typical silt loadings as a function of  roadway category was  derived.   These
mean silt loadings  were then  inserted  into  the respective emission factor
equations.   The  resultant  emission  factors  for specific  roadway category
and particle size fractions  can  be utilized directly for emissions inven-
tory purposes.   By  accounting  for variations  in silt loading,  these emis-
sion factors are  significantly more reliable than an overall average  emis-
sion factor in developing  components  of an  urban paved road emission
inventory.
                                     68

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                            9.0  REFERENCES
1.   Lynn, D.  L. ,  G.  Deane, R. Galkiewicz,  R.  M.  Bradway,  and  F.  Record.
    National Assessment  of Urban  Particulate  Problem.   Volume  I  -  Summary
    of National Assessment.   U.S.  Environmental  Protection Agency,  Publi-
    cation No. EPA 450/3-76-024, July 1976.

2.   Cowherd, C. ,  Jr.,  C.  M. Maxwell,  and  D. W.  Nelson.   Quantification  of
    Oust Entrainment  From Paved Roadways.  U.S. Environmental Protection
    Agency, Publication No. EPA-450/3-77-027, July 1977.

3.   Compilation of  Air Pollutant  Emission  Factors,  Third Edition, U.S.
    Environmental  Protection  Agency,  Publication No. AP-42, August 1977.

4.   Sartor, J. D., and G.  B. Boyd.  Water Pollution Aspects of Street Sur-
    face Contaminants.   U.S.  Environmental  Protection Agency,  Publication
    No.  EPA-R2-72-081, November 1972.

5.   Abel, M.  P.   The  Impact of Refloatation on Chicago's  Total Suspended
    Particulate Levels.   Master's  Thesis,  Purdue University,  August 1974.

6.   Cowherd,  C.,  Jr., K.  Axetell, Jr., C. M.  Guenther, and G.  Jutze.
    Development of  Emission  Factors  for Fugitive Dust  Sources.   Final
    Report, Midwest Research  Institute for U.S. Environmental Protection
    Agency,  Publication   No.  EPA-450/3-74-037,  NTIS No.  PB 238262/AS,
    June 1974.
                                    69

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 7-   Roberts, J.  W.,  A.  T.  Rossano, P.  T.  Bosserman, G. C. Hofer, and H. A.
     Watters.  The Measurement, Cost and Control of Traffic Dust and Gravel
     Roads in Seattle's  Duwamish  Valley.   Paper No. AP-72-5, Presented  at
     the Annual Meeting  of  the Pacific Northwest International Section  of
     the Air Pollution Control Association, Eugene, Oregon,  November  1972.

 8.   Axetell, K.,  and J. Zell.   Control  of  Reentrained Dust from  Paved
     Streets.  EPA Publication No. EPA-907/9-77-007, August 1977.

 9.   Roberts, J.  W.,  H.  A.  Watters, C.  A.  Margold, and A.  T.  Rossano.   Cost
     and Benefits  of Road Dust Control  in  Seattle's Industrial Valley.
     Paper No.  74-83, Presented at the 67th Annual  Meeting of the Air Pol-
     lution  Control  Association,  Denver, Colorado, June  9  to 13,  1974.

10.   American Public Works Association.   Water Pollution Aspects of Urban
     Runoff,  APWA, Chicago,  1969.   pp.  171-175.

11.   Hanna, T.  R., and T. M.  Gilmore.   Applicability of the  Mass Concentra-
     tion Standards for Particulate Matter in Alaskan Areas.   Alaska Depart-
     ment of Environmental  Conservation,  Juneau, Alaska, 1973.

12.   Shaheen, D.  G.   Contribution  of Urban Roadway Usage to  Water Pollution.
     U.S. Environmental  Protection Agency, Publication No. EPA-600/2-75-004,
     March 1975.

13.   Transportation and Traffic Engineering Handbook.   Institute of Traffic
     Engineers.   Prentice-Hall, Inc.,  London,  1976.   pp. 162-163.

14.   Quality Assurance  Handbook  for Air  Pollution Measurement  Systems.
     Volume II - Ambient Air Specific Methods.  U.S. Environmental  Protec-
     tion Agency,  Publication No.  EPA 600/4-77-027a, May 1977.

15.   Ambient Monitoring  Guidelines  for  Prevention of Significant Deteri-
     oration.  U.S.   Environmental  Protection  Agency,  Publication No. EPA
     450/2-78-019, May 1978.
                                     70

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16.   Draper, N.  R.  and  H.  Smith.   Applied Regression Analysis.   John Wiley
     and Sones, New York, 1965.

17.   Nie, N. H.,  et al.   Statistical  Package for the Social  Sciences,  Sec-
     ond Edition.  McGraw-Hill, Inc., New York,  1975.

18.   Snedecor,  G. W.  Statistical  Methods.   Fourth  Edition.  The  Iowa  State
     College Press, Ames, Iowa, 1946.

19.   Cowherd, C. ,  Jr.,  R.  Bohn, and T. Cuscino, Jr.   Iron and Steel Plant
     Open  Source Fugitive  Emission Evaluation.   Final  Report,   Midwest
     Research  Institute for U.S.  Environmental  Protection Agency, Publica-
     tion No. EPA-600/2-79-103, May 1979.

20.   Cuscino,  T. , Jr.   Total  Suspended  Particulate  Matter Analysis  in
     Baltimore,  Maryland.   State of Maryland, Baltimore, Maryland,  October
     1981.

21.   Bohn,  R.   Evaluation of Open Dust Sources  in the Vicinity of Buffalo,
     New  York.   EPA Contract  No.  68-02-2545, Assignment 1,  Environmental
     Protection Agency,  New  York,  New York,  March  1979.

22.   Bohn,  R.   Update and Improvement  of the Emission Inventory for MAPS
     Study  Areas.   State of  Montana,  Helena,  Montana,  August 1979.
                                      71

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              APPENDIX A






EMISSION FACTOR CALCULATION PROCEDURES
                  A-l

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INTRODUCTION

     This appendix describes  the  calculation of participate emission fac-
tors from exposure profiling  data.  The example calculation presented here
is based on actual  data obtained from an exposure profiling test (M-3) per-
formed at the 7th Street site in Kansas City, Kansas on February 12, 1980.

     The following definitions  for particulate matter will be  used  in this
appendix:

     TP   Total  airborne particulate matter.

     IP   Inhalable particulate matter consisting of particles smaller than
          15 urn in aerodynamic diameter.

PARTICULATE CONCENTRATION

     The concentration  of  airborne  particulate  matter measured by  an air
sampler  is given by

                              C = 103 _|

Where     C = particulate concentration (ug/m3)
          m = particulate sample weight (mg)
          Q = sampler flow rate (m3/hr)
          t = duration of sampling (hr)
     The specific particulate matter  concentrations from the various par-
ticulate catches are as follows:

          Size range                    Particulate catches
             TP                     Profiler filter and intake catches
             IP                     Size Selective Inlet (SSI) filter and
                                     impactor substrate catches
                                    A-2

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     The measured IP concentrations for the sample test are found in Table A-l.
       TABLE A-l.   INHALABLE PARTICULATE CONCENTRATIONS FOR RUN M-3

Height
(m)
1.0
2.0
3.0
4.0
Location
Qownwi nd
Upwind
Downwi nd
Upwi nd
Total
sample mass
(nig)
12.75
5.25
8.45
4.45
Sample
flow rate
(nrVhr)
68.0
68.0
68.0
68.0
Sampling
duration
(min)
120
130
120
130
Measured IP
concentration
(ug/m3)
93.8
35.6
62.1
30.2





To be consistent  with  the National Ambient Air Quality Standard for TSP,
all concentrations  are  adjusted  to standard conditions (25°C and 760 mm of
Hg).
ISOKINETIC FLOW RATIO

     The isokinetic flow ratio (IFR) is defined only for a directional sam
pler.  It is the ratio of intake air speed to the mean wind speed approach
ing the sampler.  It is given by
                                                                      (2)
where     Q = sampler flow rate (m3/hr)
          a = intake area of sampler (m2)
          U = mean wind speed at height of sampler (m/hr)
This  ratio  is  of interest  in  the  sampling of TP,  since isokinetic sampling
assures that particles of all sizes are sampled without bias.   For  Run M-3,
the profiler IFRs at 1.0, 2.0, 3.0, and 4.0  m  heights  were  0.98,  0.96, 0.96,
                                    A-3

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and 0.96, respectively.   The profiler was the only directional sampler used
in this study.

PARTICLE SIZE DISTRIBUTIONS

     The particle size  distribution  at a given height is determined using
concentration measurements from the profiler head (or Hi-Vol for upwind dis-
tributions) and the SSI/cascade impactor at the same height and at the same
distance from the source.  The determination of concentrations corresponding
to particulate  fractions  <  10  urn and <  2.5  urn  requires an  interpolation  of
the particle size-mass  distribution.   In this study, a  spline  fit  of  the
natural  logarithms  of  the SSI/cascade  impactor data was used to determine
these  concentrations.   The downwind particle  size  data  for Run M-3 are
plotted  on log-probability paper in Figures A-l and A-2.

NET IP EXPOSURES

     The upwind  IP  concentrations  from  Table A-l  are  averaged to  produce  a
representative  upwind  (uniform)  concentration.   This value is  subtracted
from the downwind concentrations at each height to obtain net IP concentra-
tions  (i.e., due to vehicular traffic on the road).   The net concentrations
are used to produce net exposure values at each downwind sampling height  by
the expression.

                              E = 10~7C U t                            (3)
where     E = net IP exposure (mg/cm2)
          C = net IP concentration, (ug/m3)
          U = mean wind speed (m/s)
          t = duration of sampling (s)

Exposure represents the net mass flux of airborne particulate matter at the
downwind sampling point,  integrated  over the time of sampling, or equiva-
lently,  the  total  net  particulate mass passing through  a unit area normal
to the mean  wind direction  during  the  test.  Net  IP  concentrations  and ex-
posures  for  the  sample  test are presented  in  Table  A-2.   The  sample  test
lasted 120 min.
                                    A-4

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                           WEIGHT % GREATER THAN STATED SIZE
        993 99J   99 98  98  90   80  70 60 30 40 30 20    10  3    2   I  0.5  0.2 O.I
       100 r	
       so
       20
        IO
     o
     I  s
     IT
     LJ
       O.S
       0.2
       OJ
100
                                                                            30
                                                                            20
                                                                            10
                                                                            0.3
                                                                            0.2
                                                                            0,
         ai 0.2  0.3  I  2    5   10   20  30 4O  50 60 TO 80   90  93   98 99   994 99.9
                            WEIGHT % LESS THAN STATED SIZE

Figure A-l.   Downwind  particle size distribution  measured at  a height of
                  1  m for Run  M-3.
                                       A-5

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      100
       90
                          WEIGHT % GREATER THAN STATED SIZE

        993 99.8  99 98   99  90   80 70 60 50 4O 30 20    10  8    2     OS  02 01
       20
       10
    to

    I
    o
    I  9
    j5
    LU
    UJ
    IT
    2
      0.9
      0.2
       OJ
                                                                           100
                                                                           so
                                                                           10
                                                                           09
        0.1 02  0.3  I  2    S    10   20  30 40 50 60 70  80   90   99   9« 99    994 9*9
                           WEIGHT % LESS THAN STATED SIZE
                                                                           0.2
                                                                           0.1
Figure A-2.   Downwind particle  size  distribution measured  at a  height  of
                 3 m  for  Run M-3.
                                      A-6

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           TABLE A-2.   NET INHALABLE CONCENTRATIONS AND EXPOSURES

Height Concentration (|jq/m3) Wind speed
Cm; Downwind Upwind Net (m/s)
1.0 93.8 32.9 60.9 2.78
3.0 62.1 32.9 29.2 3.48
Net IP
exposure
(mg/cm2)
0.122
0.0732

EXPOSURE PROFILE

     Typically the (net) exposure values decrease with increasing height in
the plume.   If  exposure  is mathematically  integrated  over  the vertical  ex-
tent of the  plume, then  the  quantity  obtained  represents the total passage
of airborne  particulate  matter  due  to the  source, per unit length of  road-
way.   This quantity  is  called the  integrated  exposure A and is  found by:
                                      TH
                                A =   /    E  dh                       (4)
                                    QJ
where:    A = integrated IP exposure  (m-mg/cm2)
          E = net IP exposure (mg/cm2)
          h = height (m)
          H = vertical extent of plume above ground (m)

     The exposure must  equal  zero  at  the  vertical  extremes  of the  profile,
i.e., at the ground where the wind velocity equals zero and at the vertical
extent of  the  plume where the net concentration equals zero.  Because ex-
posure increases  sharply  over the first  few  centimeters  of plume  height,
the  value  of exposure at the ground  level  is  set  equal  to  the value at  a
height of  1  m.
                                    A-7

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     The vertical extent  of  the plume is found by linear extrapolation of
the uppermost net TP concentrations to a value of zero.   Net  TP  concentra-
tions are found  by subtracting  the upwind TSP concentration from the  down-
wind profiler concentration.  In the case of Run M-3, Table 16 of the text
shows that a  plume  height value of 8.1 m was found by extrapolation.   For
cases in which  extrapolation  was  not possible,  a plume height of 10 m was
used.

     Linear interpolation  is  used to generate the  intermediate  exposure
values (at 1  m  intervals)  needed  for the Simpson's  rule integration of A.
Because Simpson's Rule  requires an odd number of equally spaced points,
additional  points are added  (if needed)  by setting  exposures of heights
greater than  H  equal  to zero.   From the data presented in Table  A-2,  the
exposure profile of Figure A-3 is  thus obtained.

     Application of Simpson's rule  to  perform the integration in  Eq.  (4)
for Run M-3 yields:

A = § (E0 * 4EX  + 2E2  +  4E3 + 2E4  + 4ES + 2E6 + 4E7  + 2E8  + 4E9 + E10)  (5)

where:    A  = Integrated IP exposure (m-mg/cm2)
          E.  = Net IP  exposure at  i m above ground (mg/cm2)
          h  = Distance  between  exposure  values (i.e., 1 m)
          EQ = Net IP  exposure at  ground  level  = Ex

When the values  from  Figure  A-3 are substituted into Eq.  (5), it is found
that the integrated exposure for Run M-3  equals 0.512 m-mg/cm2).
                                    A-8

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   10.
              • Vertical Extent of Plume
               Determined by Extrapolation
               of Net TP Concentration Profile
O)

1
    0
                    0.05            0.10
                                        f\
                 Net .IP Exposure ( mg/cm )
0.15
     Figure  A-3.   Exposure  profile for Run M-3.
                          A-9

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INHALABLE PARTICIPATE EMISSION FACTORS

     The emission factor for IP generated by vehicular traffic  on  the  paved
road is given by

                              e = 104 j}                                  (6)

where     e = IP emission factor (g/VKT)
          A = integrated IP exposure (m-mg/cm2)
          N = number of vehicle passes

Note that the leading term of Eq.  (-6) is a conversion factor.   The  IP  emis-
sion factor  for  Run  M-3  is 2.39 g/VKT based on  2,144  veh.icle passes during
the  120  min sampling  period.   To convert g/VKT  to  Ib/VMT,  multiply  by
0.00355.

OTHER EMISSION FACTORS

     Particulate emission factors for other size ranges are  found  in a man-
ner  analogous to  that  described above for IP.   The concentrations  for the
other  size  ranges  are  determined using  the  sizing information presented
earlier.   Once the net concentrations are obtained, the exposure values and
emission factors are found in the same manner as those for IP.
                                    A-10

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                APPENDIX B





CORRECTION PARAMETER CALCULATION PROCEDURES
                    B-l

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     Silt loading  is  calculated  as the product of total loading and  frac-
tional silt content.   The  total  loading is simply the mass of street sur-
face particulate sample  divided  by the surface area from which the sample
was obtained.   The  tare  weights  of sample containers  are  subtracted  from
the total  weights  to  obtain  the  sample weights.   Table B-l gives the
procedure for determination of silt content.

     Mean vehicle  weight is  the  arithmatic average  of the weights  of
vehicles passing  over the  test  road segment during  the emissions sam-
pling period.   Vehicle weights  are  assigned to  vehicle types as  des-
cribed in the body of this report.
                   TABLE B-l.   SILT ANALYSIS PROCEDURES
1.   Select the appropriate  8-in  diameter,  2-in deep sieve sizes.  Recom-
     mended U.S.  Standard Series sizes are:   3/8 in., No.  4, No.  20, No. 40,
     No. 100, No.  140,  No.  200, and a pan.   Comparable Tyler Series sizes
     can also be utilized.   The No. 20 and the No. 200 are  mandatory.   The
     others can be varied if the recommended sieves are not available or if
     buildup on one particular sieve during sieving indicates that an inter-
     mediate sieve should be inserted.

2.   Obtain a mechanical  sieving  device  such as a vibratory shaker or a
     Roto-Tap (without the tapping function).

3.   Clean the sieves with dry compressed air and/or a soft brush.  Material
     lodged in the  sieve  openings or adhering to  the  sides of the sieve
     should be removed  (if  possible)  without handling the  screen roughly.

4.   Obtain a scale (capacity of at least 1,600 g (3.5 lb)) and record  ;nake,
     capacity, smallest division,  date  of last calibration, and accuracy.
                                    B-2

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                           TABLE B-l (concluded)
5.    Tare sieves  and  pan.   Check the  zero  before  every  weighing.   Record
     weights.

6.    After nesting  the  sieves in order  from  the  largest to the smallest
     openings with pan at the bottom,  dump dried laboratory sample (immedi-
     ately after  drying)  into the top sieve.  The sample should weigh be-
     tween 800 and 1,600 g (1.8 and 3.5  lb).a  Brush fine material adhering
     to the  sides of  the container  into the  top  sieve and cover the top
     sieve with a special lid normally purchased with the pan.

7.    Place nested sieves  into the mechanical device and sieve for 10 min.
     Remove  pan  containing  minus 200  mesh and weigh.  Replace pan beneath
     the sieves  and sieve for another 10 min.   Remove  pan  and  weigh.  When
     the difference between  two  successive pan sample weighings  spaced
     10 min  apart (where the tare of  the pan has been subtracted) is less
     than 3.0%,  the sieving  is  complete.  Do  not  sieve longer  than 40 min.

8.    Weigh each  sieve and its contents  and  record the weight.   Check the
     zero before  every weighing.

9.    Calculate the percent of mass passing the 200 mesh screen (75 urn phys-
     ical diameter).  This is the silt content.
a  This amount will vary for the finer textured materials; 100 to  300  g may
   be  sufficient  when  90 percent of  the  sample passes a No. 8  (2.36  mm)
   sieve.
                                     B-3

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                                APPENDIX C


                          PROPOSED AP-42 SECTION
          The reader is cautioned that this proposed AP-42 section is subject
to probable change resulting from internal EPA reviews before it is published
in AP-42.
                                   C-l

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11.2.5  PAVED URBAN ROADS

General -  Various  field  studies  have indicated that dust emissions from
paved streets are a major component of the material collected by high vol-
ume samplers.1  Reentrained traffic dust  has  been found to consist primarily
of mineral matter similar to common sand  and  soil,  mostly tracked or depos-
ited onto the roadway by vehicle traffic itself.  Other particulate matter
is emitted directly by the vehicles from,  for example,  engine exhaust,  wear
of bearings  and brake linings, and abrasion of tires against the road sur-
face.  Some of these direct emissions  may settle to the street surface,  sub-
sequently to be reentrained.  Appreciable emissions from paved streets are
added by  wind erosion  when the wind velocity exceeds  a threshold value  of
about 20 km/hr (13 mi/hr).2  Figure 11.2.5-1  illustrates particulate trans-
fer processes occurring on urban streets.

Emission Factors and Correction Parameters - Dust  emission rates may vary
according to a  number  of factors.  " The most  important  are  thought to be
traffic volume and the quantity and particle  size of loose surface material
on the  street.  As  shown in Figure 11.2.5-1,  various activities add or re-
move street  surface material.  On a normal paved street, an equilibrium is
reached whereby the accumulated street deposits are maintained at a rela-
tively  constant level.   On  average, vehicular carryout from unpaved areas
may be  the  largest  single source  of street  deposit.   Accidental spills,
street cleaning and rainfall are activities that disrupt the street loading
equilibrium, usually for a relatively  short duration.

     The lead content of fuels also becomes a part  of reentrained dust  from
vehicle traffic.  Studies have found that,  for the  1975-76 sampling period,
the  lead  emission  factor for this source was approximately 0.03 gram per
vehicle mile.   With the  reduction of lead in gasoline and the use of cata-
lyst equipped vehicles,  the  lead  factor  for  reentrained dust was expected
to drop below 0.01 grams per mile  by 1980.3

     The  quantity of  dust emissions  of vehicle traffic on a paved roadway
per vehicle kilometer of travel may be estimated using the following empir-
ical expression4:


                            ••*(&  "

          where:  e = particulate  emission factor (g/VKT)
                  L = total road surface  dust loading (g/m2)
                  s = surface silt content,  fraction of particles
                        < 75 |Jm diameter  (American Association of
                        State Highway  Officials)
                  k = base emission factor (g/VKT)
                  p = exponent (dimensionless)

The total loading  (excluding  litter) is measured by sweeping and vacuuming
lateral strips  of known  area  from  each active travel lane.  The  silt frac-
tion is determined  by measuring the proportion  of  loose  dry road dust that
passes a 200 mesh screen, using the ASTM-C-136 method.   Silt loading is the
product of total loading and silt content.
                           Miscellaneous Sources                 n 25-1
                                   02

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Cn
 I
t-l
co
t-3
o
50
               	DEPOSITION
               PAVEMENT WEAR AND DECOMPOSITION
               VEHICLE RELATED DEPOSITION
               OUSTFALL
               LITTER
               MUD AND OIRT CARRYOUT
               EROSION FROM ADJACENT AREAS
               SPILLS
            8)  BIOLOGICAL DEBRIS
            ?)  ICE CONTROL COMPOUNDS
               REMOVAL
             REENTRAINMENT
             WIND EROSION
             DISPLACEMENT
             RAINFALL RUNOFF TO CATCH BASIN
             STREET SWEEPING
                                    >-~^ s*-*-
3*W8ft».ftfe^
                                         11.2.5-1, Deposition and removal processes.

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     The base emission  factor  coefficients  (k) and exponents  (p)  in the
equation for each  size  fraction are listed in Table 11.2.5-1.   Total sus-
pended particulate  (TSP)  denotes  that particle size fraction of airborne
particulate matter  that would  be  collected by  a  standard high volume
sampler.


   TABLE 11.2.5-1.   Paved Urban Road Emission Factor Equation Parameters3
     Particle Size Fraction             k (g/VKT)
TSP
< 15 |jm
£ 10 Mm
< 2.5 Mm
5.87
2.54
2.28
1.02
0.9
0.8
0.8
0.6
,  Reference 4.  See p. 11.2.5-1 for equation.
  Aerodynamic diameter.  TSP is total suspended particulate.


     Microscopic analysis indicates the origin of material collected on high
volume filters to be about 40 weight percent combustion products and 59 per-
cent mineral  matter,  with traces of biological matter and rubber tire par-
ticles.  The small particulate is mainly combustion products,  while most of
the large material is of mineral origin.3

Emissions Inventory Applications4  -  For most emissions inventory applica-
tions involving urban paved roads,  actual measurements of silt loading will
probably not  be  made.   Therefore,  to facilitate the use of the previously
described equation, it is necessary to characterize silt loadings according
to parameters  readily available  to persons  developing the inventories.   It
is convenient  to  characterize variations in silt  loading with a roadway
classification system,  and  this  is. presented in Table 11.2.5-2.  This  sys-
tem generally corresponds to the classification systems used by transporta-
tion agencies, and  thus the data necessary for  an emissions  inventory -
number of road miles  per road category  and  traffic  counts - should  be  easy
to obtain.   In  some situations it may  be necessary to combine this silt
loading information with sound engineering judgment in order to approximate
the loadings for roadway types not specifically included in Table 11.2.5-2.

     A data  base  of 44 samples analyzed according  to  consistent procedures
may be used  to characterize the silt loadings for each roadway category.4
These samples, obtained during recent  field sampling  programs,  represent a
broad range  of urban  land use and  roadway conditions.   Geometric means  for
this data set are  given by  sampling  location and  roadway  category  in Table
11.2.5-3.
                           Miscellaneous Sources                 11.2.5-3
                                  C-4

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            TABLE 11.2.5-2.   Paved Urban Roadway Classification"
Roadway
Category
Freeways / exp r es sways
Major streets /highways
Collector streets
Local streets
Average Daily Traffic
(ADT)
> 50,000
> 10,000
500 - 10,000
< 500
Lanes
> 4
> 4
2b
2C
  Reference 4.
  Road width £ 32 ft.
  Road width < 32 ft.
           TABLE 11.2.5-3.   Summary of Silt Loadings  (sL)  for Paved
                              Urban Roadways
Roadway
Local
Streets

X (g/m2) n
g
Baltimore 1.42 2
Buffalo 1.41 5
Granite City (IL)
Kansas City
St. Louis
All 1.41 7
Collector
Streets

X (g/m2)
g
0.72
0.29
-
2,11
-
0.92

n

4
2
-
4
-
10
Category

Major Streets/
Highways

X (g/m2)
g
0.39
0.24
0.82
0.41
0.16
0.36

n

3
4
3
13
3
26

Freeways/
Expressways
X (g/m2) n
g
-
-
-
-
0.022 1
0.022 1
  Reference 4.  X   = geometric mean based on corresponding n sample size.
11.2.5-4
EMISSION FACTORS
     05

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     These sampling locations can be considered representative of most large
urban areas in  the  United  States, with the possible exception of those in
the Southwest.  Except  for  the  collector roadway category, the mean  silt
loadings do not vary  greatly from city to city,  though the St. Louis mean
for major roads is somewhat lower than those of the  other four cities.  The
substantial variation within the collector roadway category is probably at-
tributable to the effects of land use around the  specific sampling locations.
It should also be noted that an examination of data  collected at three cities
in Montana during early spring indicates that winter road sanding may produce
loadings five to  six  times  higher than the means of the loadings given in
Table 11.2.5-3 for the respective road categories.5

     Table  11.2.5-4  presents the  emission  factors  by  roadway category
and particle  size.  These  were  obtained by inserting the above mean  silt
loadings into the equation on page 11.2.5-1.  These  emission factors can be
used directly for many emission inventory purposes.   It is important to note
that the paved  road  emission factors for TSP agree quite well with those
developed from previous testing of roadway sites  in  the major street and high-
way category, yielding mean TSP emission factors  of  4.3 g/VKT (Reference 6)
and 2.6 g/VKT (Reference 7).
  TABLE 11.2.5-4.
Recommended Particulate Emission Factors for Specific
  Roadway Categories and Particle Size Fractions
Emission Factor (by oarticle
Roadway
Category
Local streets
Collector streets
Major streets/
highways
Freeways/
expressways
TSP <
g/VKT (Ib/VHT) g/VKT
15
(0.053)
10
(0.035)
4.4
(0.016)
0.35
(0.0012)
15 Mm <
Ub/VMT) g/VKT
5-3
(0.021)
4.1
(0.015)
2.0
(0.0071)
0.21
(0.00074)
size fraction)
10 Mm
Ub/VMT)
5.2
(0.018)
3.7
(0.013)
1.8
(0.0064)
0.19
(0.00067)
< 2.5 Mm
g/VKT (lb/VMT)
1.9
(0.0067)
1.5
(0.0053)
0.34
(0.0030)
0. 16
(0.00057)
References for Section 11.2.5

1.   D. R. Dunbar, Resuspension of Particulate Matter, U. S. Environmental
     Protection Agency, Research Triangle Park, NC, March 1976.

2.   M. P. Abel,  "The Impact of Refloatation on Chicago's Total Suspended
     Particulate  Levels",  Purdue University,  Purdue,  IN,  August 1974.
                           Miscellaneous Sources
                                   C-6
                                              11.2.5-5

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2.   M. P- Abel,  "The  Impact of Refloatation on Chicago's Total Suspended
     Participate  Levels",  Purdue University,  Purdue,  IN, August  1974.

3.   C. M. Maxwell and D. W. Nelson, A Lead Emission Factor for Reentrained
     Dust from a Paved Roadway,  EPA-450/3-78-021,   U.  S.  Environmental
     Protection Agency, Research Triangle Park, NC, April 1978.

4.   C. Cowherd, Jr., et al., Paved Road Particulate Emissions, EPA Contract
     No. 68-02-3158, Midwest Research Institute, Kansas City,  MO, April 1982.

5.   R. Bonn, Update and Improvement of the Emission Inventory for MAPS Study
     Areas. State of Montana, Helena, MT, August 1979.

6.   C. Cowherd,  Jr. et  al.,  Quantification  of  Dust Entrainment  from Paved
     Roadways,  EPA  450/3-77-027, U.  S.  Environmental  Protection Agency,
     Research Triangle Park, NC, July 1977.

7.   K. Axetell, and J. Zell, Control of Reentrained Dust from Paved Streets,
     EPA Contract No. 68-02-1375, PEDCo Environmental,  Inc. Cincinnati, OH,
     July 1977.
11.2.5-6                     EMISSION FACTORS
                                   07

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                                TECHNICAL REPORT DATA     .
                          (Please read Instructions on the reverse before completing)
1 . REPORT NO.
EPA-600/7-84-077
4. TITLE AND SUBTITLE
Paved Road Particulate Emissions—Source Category
 Report
              6. PERFORMING ORGANIZATION CODE
                                                       3. RECIPIENT'S ACCESSION-NO.
              5 REPORT DATE
              July 1984
7. AUTHORIS)

Chatten Cowherd,  Jr.  and Phillip J.  Englehart
             8. PERFORMING ORGANIZATION REPORT NO,

              4892-L
9. PERFORMING ORGANIZATION NAME AND ADDRESS
Midwest Research Institute
425 Volker Boulevard
Kansas City, Missouri  64110
                                                       10. PROGRAM ELEMENT NO.
              11. CONTRACT/GRANT NO.
              68-02-3158, Task 19
 12. SPONSORING AGENCY NAME AND ADDRESS
 EPA, Office of Research and Development
 Industrial Environmental Research Laboratory
 Research Triangle Park, NC  27711
              13 TYPE OF REPORT AND PERIOD COVERED
              Final; 1/80-4/84
              14. SPONSORING AGENCY CODE
               EPA/600/13
 is. SUPPLEMENTARY NOTESlERL-RTP project officer W.B. Kuykendal is no longer with the
 Laboratory; for report details,  contact Dale L. Harmon,  Mail Drop 61, 919/541-2429.
 is. ABSTRACT The report gives results of extensive field tests to develop emission fac-
 tors for particulate emissions generated by traffic entrainment of paved road surface
 particulate matter. Emission factors were developed for the following particle size
 ranges: < or = 30, 15, 10, and 2. 5 micrometer aerodynamic diameter.  Sites tested
 represented commercial/industrial,  commercial/residential,  expressway,  and
 rural town land-use categories. The measured inhalable particulate (IP--< or = 15
 micrometer aerodynamic diameter) emission factors ranged from 0.06 to 8.8 g/VKT
 (vehicle km traveled). Lowest emissions were measured for the expressway cate-
 gory; highest emissions were measured for the rural town category.  About 90% of the
 IP emissions consisted of particles < or = 10 micrometers in aerodynamic diameter,
 and about 50% of the IP emissions consisted of particles < or = 2. 5 micrometers in
 aerodynamic diameter. Using roadway surface silt loading as the basis, predictive
 emission factor equations for each particle size range were derived.  To facilitate
 the use of these particle-size-specific equations in developing emission inventories,
 a classification system was derived of mean or typical silt loadings as a function of
 roadway category.  These mean silt loadings were then inserted into the respective
 emission factor equations for specific, roadway categories and particle size fractions.
17.
                             KEY WORDS AND DOCUMENT ANALYSIS
                 DESCRIPTORS
                                           b.IDENTIFIERS/OPEN ENDED TERMS
                                                                   c.  COSATI Field/Group
 Pollution
 Pavements
 Roads
 Particles
 Dust
 Silts
  Pollution Control
  Stationary Sources
  Particulate
  Emission Factors
  Silt Loading
13 B
14G
11G
 3. DISTRIBUTION STATEMEN1
 Release to Public
                                           19. SECURITY CLASS (This Report)
                                           Unclassified
                           21. NO. OF PAGES
                                  97
 20. SECURITY CLASS (This page)
  Unclassified
                                                                    22. PRICE
EPA Form 2220-1 (9-73)
C-8

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