Emission Factor Documentation for AP-42,
Section 13.2.1
Paved Roads
For Emission Factors and Inventory Group
Office of Air Quality Planning and Standards
U.S. Environmental Protection Agency
EPA Contract No. 68-D0-0123
Work Assignment No. 44
MRI Project No. 9712-44
March 8, 1993
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Emission Factor Documentation for AP-42,
Section 13.2.1
Paved Roads
For Emission Factors and Inventory Group
Office of Air Quality Planning and Standards
U.S. Environmental Protection Agency
Research Triangle Park, NC 27711
Attn: Dennis Shipman
EPA Contract No. 68-D0-0123
Work Assignment No. 44
MRI Project No. 9712-44
March 8, 1993
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NOTICE
This document is a final product. However, it should not be
construed to represent Agency policy. It is has been circulated
for comments on its technical merit.
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PREFACE
This report was prepared for Mr. Dennis Shipman of the Emission Inventory
Branch, Technical Support Division, Office of Air Quality Planning and Standards, U.S.
Environmental Protection Agency, Research Triangle Park, North Carolina, under EPA
Contract No. 68-DO-0123, Work Assignment No. I-44. This report describes the
development of a new AP-42 section to replace sections 11.2.5, "Urban Paved Roads,"
and 11.2.6, "Industrial Paved Roads" which werer in the fourth Edition of AP-42.
Midwest Research Institute's Project Leader for the assignment is Dr. Gregory E.
Muleski. Dr. Muleski and Dr. Chatten Cowherd prepared this report.
Approved for:
MIDWEST RESEARCH INSTITUTE
Richard V. Crume
Program Manager
Environmental Engineering Department
Charles F. Holt, Ph.D., Director
Engineering and Environmental
Technology Department
March 8, 1993
iii
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iv
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CONTENTS
Preface iii
List of Figures vii
List of Tables vii
1. Introduction 1-1
2. Source Description 2-1
2.1 Public and industrial roads 2-1
2.2 Review of current paved road emission factors 2-2
3. General Data Review and Analysis 3-1
3.1 Literature search and screening 3-1
3.2 Emission data quality rating system 3-2
3.3 Emission factor quality rating system 3-4
3.4 Methods of emission factor determination 3-5
3.5 Emission factor quality rating scheme used in
this study 3-8
4. AP-42 Section Development 4-1
4.1 Revisions to section narrative 4-1
4.2 Pollutant emission factor development 4-2
4.3 Development of other material in AP-42 section 4-23
5. Draft AP-42 Section 5-1
6. References 6-1
v
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vi
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LIST OF FIGURES
Number Page
4-1 Final data set 4-17
4-2 Validation data from Test Report I 4-19
4-3 Correlation and regression results for the data set 4-21
4-4 Cumulative freguency distribution obtained during
cross-validation study 4-24
LIST OF TABLES
Number Page
3-1 Quality rating scheme for single-valued emission factors 3-12
3-2 Quality rating scheme for emission factors eguations 3-13
4-1 Applicable test reports 4-3
4-2 Summary information for Test Report I 4-5
4-3 Summary information for Test Report II 4-8
4-4 Summary information for Test Report III 4-11
4-5 Recommended emission factor models 4-22
4-6 Results of cross-validation study 4-23
4-7 Results from independent application of the PM-10 model 4-25
4-8 Decision rule for paved road emission estimates 4-25
4-9 Ratio of predicted to measured PM-10 emission factors 4-27
vii
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SECTION 1
INTRODUCTION
The document "Compilation of Air Pollutant Emissions Factors" (AP-42) has
been published by the U.S. Environmental Protection Agency (EPA) since 1972.
Supplements to AP-42 have been routinely published to add new emission source
categories and to update existing emission factors. AP-42 is periodically updated by
EPA to respond to new emission factor needs of EPA, State, and local air pollution
control programs and industry.
An emission factor relates the quantity (weight) of pollutants emitted to a unit of
activity of the source. The uses for the emission factors reported in AP-42 include:
1. Estimates of area-wide emissions.
2. Estimates of emissions for a specific facility.
3. Evaluation of emissions relative to ambient air quality.
The purpose of this report is to provide background information from test reports
and other information to support preparation of a consolidated AP-42 section to replace
existing Sections 11.2.5, "Urban Paved Roads," and 11.2.6, "Industrial Paved Roads."
The principal pollutant of interest in this report is "particulate matter" (PM), with
special emphasis placed on "PM-10"—particulate matter no greater than 10 |jmA
(microns in aerodynamic diameter). PM-10 forms the basis for the current National
Ambient Air Quality Standards (NAAQSs) for particulate matter.
PM-10 thus represents the size range of particulate matter that is of the greatest
regulatory interest. Nevertheless, formal establishment of PM-10 as the standard basis
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is relatively recent, and many emission tests have referenced other particle size
ranges. Other size ranges employed in this report are:
TSP Total Suspended Particulate, as measured by the standard high-volume
(hi-vol) air sampler. TSP was the basis for the previous NAAQSs for
particulate matter. TSP consists of a relatively coarse particle size
fraction. While the particle capture characteristics of the hi-vol sampler
are dependent upon approach wind velocity, the effective D50 (i.e., 50%
of the particles are captured and 50% are not) varies roughly from 25 to
50 |jmA.
SP Suspended Particulate, which is used as a surrogate for TSP. Defined as
PM no greater than 30 |jmA. SP also may be denoted as "PM-30."
IP Inhalable Particulate, defined as PM no greater than 15 |jmA. Throughout
the late 1970s and the early 1980s, it was clear that EPA intended to
revise the NAAQSs to reflect a particle size range finer than TSP. What
was not clear was the size fraction that would be eventually used, with
values between 7 and 15 |jmA frequently mentioned. Thus, many field
studies were conducted using IP emission measurements because it was
believed that IP would be the basis for the new NAAQS. IP may also be
represented by "PM-15."
FP Fine Particulate, defined as PM no greater than 2.5 |jmA. FP also may be
denoted as "PM-2.5."
This background report consists of five sections. Section 1 provides an
introduction to the report. Section 2 presents descriptions of the paved road source
types and emissions from those sources as well as a brief history of the current AP-42
emission factors. Section 3 is a review of emissions data collection and analysis
procedures; it describes the literature search, the screening of emission test reports,
and the quality rating system for both emission data and emission factors. Section 4
details the development of paved road emission factors for the draft AP-42 section; it
includes the review of specific data sets and the results of data analysis. Section 5
presents the AP-42 section for paved roads.
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SECTION 2
SOURCE DESCRIPTION
Particulate emissions occur whenever vehicles travel over a paved surface, such
as public and industrial roads and parking lots. These emissions may originate from
material previously deposited on the travel surface, or resuspension of material from
tires and undercarriages. In general, emissions arise primarily from the surface
material loading (measured as mass of material per unit area). Surface loading is in
turn replenished by other sources (e.g., pavement wear, deposition of material from
vehicles, deposition from other nearby sources, carryout from surrounding unpaved
areas, and litter). Because of the importance of the surface loading, available control
techniques either attempt to prevent material from being deposited on the surface or to
remove (from the travel lanes) any material that has been deposited.
2.1 PUBLIC AND INDUSTRIAL ROADS
While the mechanisms of particle deposition and resuspension are largely the
same for public and industrial roads, there can be major differences in surface loading
characteristics, emission levels, traffic characteristics, and viable control options. For
the purpose of estimating particulate emissions and determining control programs, the
distinction between public and industrial roads is not a question of ownership but rather
a question of surface loading and traffic characteristics.
Although public roads generally tend to have lower surface loadings than
industrial roads, the fact that these roads have far greater traffic volumes may result in
a substantial contribution to the measured air quality in certain areas. In addition,
public roads in industrial areas can be often heavily loaded and traveled by heavy
vehicles. In that instance, better emission estimates might be obtained by treating
these roads as industrial roads. In an extreme case, an industrial road or parking lot
may have such a high surface loading that the paved surface is essentially covered and
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is easily mistaken for an unpaved surface. In that event, use of a paved road emission
factor may actually result in a higher estimate than that obtained from the unpaved road
emission factor, and the road is better characterized as unpaved in nature rather than
paved.
2.2 REVIEW OF CURRENT PAVED ROAD EMISSION FACTORS
AP-42 currently contains two sections concerning paved road fugitive emissions.
The first, Section 11.2.5, is entitled "Urban Paved Roads" and was first drafted in 1984
using test results from public paved roads.2 Emission factors are given in the form of
the following equation:
E = k (sl_/0.5)p (2-1)
where: E = particulate emission factor (g/VKT)
s = surface material content silt, defined as particles < 75 |jm in
diameter (%)
L = surface material loading, defined as mass of particles per
unit area of the travel surface (g/m2)
k = base emission factor (g/VKT)
p = exponent (dimensionless)
The factors k and p are given by
Particle
size fraction
k (aA/KTI
a
TSP
5.87
0.9
PM-15
2.54
0.8
PM-10
2.28
0.8
PM-2.5
1.02
0.6
The form of the emission factor model is reasonably consistent throughout all particle
size fractions of interest.
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The urban paved road emission factors represented by Equation 2-1 have not
changed since their inclusion in the 4th Edition (September 1985). It should be noted
that these emission factors have not been quality rated "A" through "E." (See Section 3
for an overview of the AP-42 quality rating scheme.)
Section 11.2.6, "Industrial Paved Roads," was first published in 19833 and was
slightly modified in Supplement B (1988) to the 4th Edition. Section 11.2.6 contains
three distinct sets of emission factor models as described below.
ForTSP, the following equation is recommended:
E = 0.022 I (-) (—) (—) (—)07 (2-2)
n 10 280 2.7 K '
where: E = emission factor (kg/VKT)
I = industrial augmentation factor (dimensionless)
n = number of traffic lanes (dimensionless)
s = surface material silt content (%)
L = surface material loading across all traffic lanes (kg/km)
W = average vehicle weight (Mg)
The basic form of Equation 2-2 dates from a 1979 report4 and was originally
included in Supplement 14 to AP-42 (May 1983). The version currently in AP-42 was
slightly revised in that the leading term (i.e., 0.022 in Eq. [2-2]) was reduced by 14%.
The industrial road augmentation factor (I) was included to take into account for higher
emissions from industrial roads than from urban roads; it varies from 1 to 7. The
emission factor equation is rated "B" for cases with I = 1 and "D" otherwise.
For smaller particle size ranges, models somewhat similar to those in Eq. (2-1)
are recommended:
E = k (sL/12)0-3 (2-3)
where: E = emission factor (kg/VKT)
k = base emission factor (kg/VKT), see below
sL = road surface silt loading (g/m2)
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The base emission factor (k) above varies with aerodynamic size range as follows:
Particle
size fraction k (a/VKT)
PM-15 0.28
PM-10 0.22
PM-2.5 0.081
These models represented by Equation 2-3 were first developed in 19843 from
15 emission tests of uncontrolled paved roads and they are rated "A."
During the development of Eq. (2-3), tests of light-duty traffic on heavily loaded
road surfaces were identified as a separate subset, for which separate single-valued
emission factors were developed. Section 11.2.6 recommends the following for
light-duty (less than 4 tons) vehicles traveling over dry, heavily loaded (silt loading
greater than 15 g/m2):
E = k (2-4)
where: E = emission factor (kg/VKT)
k = single-valued factor depending on particle size range of
interest (see below)
Particle
size fraction k (a/VKT)
PM-15 0.12
PM-10 0.093
The single-valued emission factors are quality rated "C."
Since the time that the current models first appeared in Sections 11.2.5 and
11.2.6, several users of AP-42 have noted difficulty selecting the appropriate emission
factor model to use in their applications.5'6'7 For example, inventories of industrial
facilities (particularly of iron and steel plants) conducted throughout the 1980s have
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yielded measured silt loading values substantially lower than those in the
Section 11.2.6 data base. In extreme cases when the models were used with silt
loading values outside the range for which they were developed, estimated PM-10
emission factors were larger than the corresponding TSP emission factors.
Furthermore, the distinction between "urban" and "industrial" paved roads has
become blurred. For the purpose of estimating emissions, it was gradually realized that
source emission levels are not a question of ownership but rather a question of surface
loading and traffic characteristics. Confirmatory evidence was obtained in a 1989 field
program5 which found that paved roads at an iron and steel facility far more closely
resembled "urban" roads rather than "industrial" roads in terms of emission
characteristics.
Finally, it is unknown how well current emission factors perform for cases of
increased surface loading on public roads, such as after application of antiskid
materials or within areas of trackout from unpaved areas.6 These situations are of
considerable interest to several state and local regulatory agencies, most notably in the
western United States.
The current update attempts to correct as many of those shortcomings as
possible. To that end, the update employs an approach slightly different than that used
in the past. In addition to reviewing test data obtained since the previous update,8
previous test data were also included for reexamination in the final data set. In
assembling the data base, no distinction was made between public and industrial roads
or between controlled and uncontrolled tests, with the anticipation that the reformulated
emission factor will be applicable over a far greater range of source conditions.
Inclusion of controlled tests represents a break with EPA guidelines for
preparing AP-42 sections.9 Those guidelines present a clear preference that only
uncontrolled tests be used to develop an emission factor. However, the principal
control measures for paved roads seek to reduce the value of an independent variable
in the emission factor equation, i.e., the silt loading.
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SECTION 3
GENERAL DATA REVIEW AND ANALYSIS
To reduce the amount of literature collected to a final group of references from
which emission factors could be developed, the following general criteria were used:
1. Emissions data must be from a primary reference:
a. Source testing must be from a referenced study that does not
reiterate information from previous studies.
b. The document must constitute the original source of test data. For
example, a technical paper was not included if the original study
was contained in the previous document. If the exact source of the
data could not be determined, the document was eliminated.
2. The referenced study must contain test results based on more than one
test run.
3. The report must contain sufficient data to evaluate the testing procedures
and source operating conditions.
A final set of reference materials was compiled after a thorough review of the
pertinent reports, documents, and information according to these criteria.
3.1 LITERATURE SEARCH AND SCREENING
Review of available literature identified three paved road testing programs
(presented later as Table 4-1) since the time of the last Section 11.2 update.8 The
individual programs are discussed in detail in the next section. In addition, as
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discussed at the end of Section 2, earlier controlled industrial road test data were
reexamined. The previous update8 noted that Eq. (2-4) yielded quite good estimates
for emissions from vacuum swept and water flushed roads. Furthermore, it became
apparent that previous distinctions between "industrial" and "urban" roads had become
blurred as interest focused on heavily loaded urban roads (e.g., after snow/ice controls)
and on cleaner industrial roads (as the result of plant-wide control programs).
3.2 EMISSION DATA QUALITY RATING SYSTEM
As part of the analysis of the emission data, the quantity and quality of the
information contained in the final set of reference documents were evaluated. The
following data are to be excluded from consideration:
1. Test series averages reported in units cannot be converted to the
selected reporting units.
2. Test series representing incompatible test methods (i.e., comparison of
EPA Method 5 front-half with EPA Method 5 front- and back-half).
3. Test series of controlled emissions for which the control device is not
specified.
4. Test series in which the source process is not clearly identified and
described.
5. Test series in which it is not clear whether the emissions were measured
before or after the control device.
Test data sets that were not excluded were assigned a quality rating. The rating
system used was that specified by EIB for preparing AP-42 sections.9 The data were
rated as follows:
A Multiple tests that were performed on the same source using sound
methodology and reported in enough detail for adequate validation.
These tests do not necessarily conform to the methodology specified in
3-2
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EPA reference test methods, although these methods were used as a
guide for the methodology actually used.
B Tests that were performed by a generally sound methodology, but lack
enough detail for adequate validation.
C Tests that were based on an untested or new methodology or that lacked
a significant amount of background data.
D Tests that were based on a generally unacceptable method but may
provide an order-of-magnitude value for the source.
The following criteria were used to evaluate source test reports for sound
methodology and adequate detail:
1. Source operation. The manner in which the source was operated is well
documented in the report. The source was operating within typical
parameters during the test.
2. Sampling procedures. The sampling procedures conformed to a
generally acceptable methodology. If actual procedures deviated from
accepted methods, the deviations are well documented. When this
occurred, an evaluation was made of the extent such alternative
procedures could influence the test results.
3. Sampling and process data. Adequate sampling and process data are
documented in the report, and any variations in the sampling and process
operation are noted. If a large spread between test results cannot be
explained by information contained in the test report, the data are suspect
and were given a lower rating.
4. Analysis and calculations. The test reports contain original raw data
sheets. The nomenclature and equations used were compared to those
(if any) specified by EPA to establish equivalency. The depth of review of
the calculations was dictated by the reviewer's confidence in the ability
and conscientiousness of the tester, which in turn was based on factors
3-3
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such as consistency of results and completeness of other areas of the test
report.
3.3 EMISSION FACTOR QUALITY RATING SYSTEM
The quality of the emission factors developed from analysis of the test data was
rated utilizing the following general criteria:
A—Excellent: Developed only from A-rated test data taken from many randomly
chosen facilities in the industry population. The source category is specific
enough so that variability within the source category population may be
minimized.
B—Above average: Developed only from A-rated test data from a reasonable
number of facilities. Although no specific bias is evident, it is not clear if the
facilities tested represent a random sample of the industries. The source
category is specific enough so that variability within the source category
population may be minimized.
C—Average: Developed only from A- and B-rated test data from a reasonable
number of facilities. Although no specific bias is evident, it is not clear if the
facilities tested represent a random sample of the industry. In addition, the
source category is specific enough so that variability within the source category
population may be minimized.
D—Below average: The emission factor was developed only from A- and
B-rated test data from a small number of facilities, and there is reason to suspect
that these facilities do not represent a random sample of the industry. There
also may be evidence of variability within the source category population.
Limitations on the use of the emission factor are noted in the emission factor
table.
E—Poor: The emission factor was developed from C- and D-rated test data, and
there is reason to suspect that the facilities tested do not represent a random
sample of the industry. There also may be evidence of variability within the
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source category population. Limitations on the use of these factors are always
noted.
The use of these criteria is somewhat subjective and depends to an extent on
the individual reviewer.
3.4 METHODS OF EMISSION FACTOR DETERMINATION
Fugitive dust emission rates and particle size distributions are difficult to quantify
because of the diffuse and variable nature of such sources and the wide range of
particle size involved including particles which deposit immediately adjacent to the
source. Standard source testing methods, which are designed for application to
confined flows under steady state, forced-flow conditions, are not suitable for
measurement of fugitive emissions unless the plume can be draw into a forced-flow
system. The following presents a brief overview of applicable measurement
techniques. More detail can be found in earlier AP-42 updates.8'10
3.4.1 Mass Emission Measurements
Because it is usually impractical to enclose open dust sources or to capture the
entire emissions plume, only the upwind-downwind and exposure profiling methods are
suitable for measurement of particulate emissions from most open dust sources.10
These two methods are discussed separately below.
The basic procedure of the upwind-downwind method involves the measurement
of particulate concentrations both upwind and downwind of the pollutant source. The
number of upwind sampling instruments depends on the degree of isolation of the
source operation of concern (i.e., the absence of interference from other sources
upwind). Increasing the number of downwind instruments improves the reliability in
determining the emission rate by providing better plume definition. In order to
reasonably define the plume emanating from a point source, instruments need to be
located at two downwind distances and three crosswind distances, at a minimum. The
same sampling requirements pertain to line sources except that measurement need not
be made at multiple crosswind distances.
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Net downwind (i.e., downwind minus upwind) concentrations are used as input to
dispersion equations (normally of the Gaussian type) to backcalculate the particulate
emission rate (i.e., source strength) required to generate the pollutant concentration
measured. Emission factors are obtained by dividing the calculated emission rate by a
source activity rate (e.g., number of vehicles, or weight of material transferred per unit
time). A number of meteorological parameters must be concurrently recorded for input
to this dispersion equation. At a minimum the wind direction and speed must be
recorded on-site.
While the upwind-downwind method is applicable to virtually all types of
sources, it has significant limitations with regard to development of source-specific
emission factors. The major limitations are as follows:
1. In attempting to quantify a large area source, overlapping of plumes from
upwind (background) sources may preclude the determination of the
specific contribution of the area source.
2. Because of the impracticality of adjusting the locations of the sampling
array for shifts in wind direction during sampling, it cannot be assumed
that plume position is fixed in the application of the dispersion model.
3. The usual assumption that an area source is uniformly emitting does not
allow for realistic representation of spatial variation in source activity.
4. The typical use of uncalibrated atmospheric dispersion models introduces
the possibility of substantial error (a factor of three according to
Reference 11) in the calculated emission rate, even if the stringent
requirement of unobstructed dispersion from a simplified (e.g., constant
emission rate from a single point) source configuration is met.
The other measurement technique, exposure profiling, offers distinct advantages
for source-specific quantification of fugitive emissions from open dust sources. The
method uses the isokinetic profiling concept that is the basis for conventional (ducted)
source testing. The passage of airborne pollutant immediately downwind of the source
is measured directly by means of simultaneous multipoint sampling over the effective
cross section of the fugitive emissions plume. This technique uses a mass-balance
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calculation scheme similar to EPA Method 5 stack testing rather than requiring indirect
calculation through the application of a generalized atmospheric dispersion model.
For measurement of nonbuoyant fugitive emissions, profiling sampling heads are
distributed over a vertical network positioned just downwind (usually about 5 m) from
the source. If total particulate emissions are to be measured, sampling intakes are
pointed into the wind and sampling velocity is adjusted to match the local mean wind
speed, as monitored by anemometers distributed over height above ground level.
The size of the sampling grid needed for exposure profiling of a particular source
may be estimated by observation of the visible size of the plume or by calculation of
plume dispersion. Grid size adjustments may be required based on the results of
preliminary testing. Particulate sampling heads should be symmetrically distributed
over the concentrated portion of the plume containing about 90% of the total mass flux
(exposure). For example, assuming that the exposure from a point source is normally
distributed, the exposure values measured by the samplers at the edge of the grid
should be about 25% of the centerline exposure.
To calculate emission rates using the exposure profiling technique, a
conservation of mass approach is used. The passage of airborne particulate (i.e., the
quantity of emissions per unit of source activity) is obtained by spatial integration of
distributed measurements of exposure (mass/area) over the effective cross section of
the plume. The exposure is the point value of the flux (mass/area/time) of airborne
particulate integrated over the time of measurement.
3.4.2 Emission Factor Derivation
Usually the final emission factor for a given source operation, as presented in a
test report, is derived simply as the arithmetic average of the individual emission
factors calculated from each test of that source. Frequently the range of individual
emission factor values is also presented.
As an alternative to the presentation of a final emission factor as a single-valued
arithmetic mean, an emission factor may be presented in the form of a predictive
equation derived by regression analysis of test data. Such an equation mathematically
3-7
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relates emissions to parameters when characterize source conditions. These
parameters may be grouped into three categories:
1. Measures of source activity or energy expended (e.g., the speed and
weight of a vehicle traveling on an unpaved road).
2. Properties of the material being disturbed (e.g., the content of
suspendable fines in the surface material on an unpaved road).
3. Climatic parameters (e.g., number of precipitation-free days per year on
which emissions tend to be at a maximum).
An emission factor equation is useful if it is successful in "explaining" much of the
observed variance in emission factor values on the basis of corresponding variance sin
specific source parameters. This enables more reliable estimates of source emissions
on a site-specific basis.
A generic emission factor equation is one that is developed for a source
operation defined on the basis of a single dust generation mechanism which crosses
industry lines. An example would be vehicular traffic on unpaved roads. To establish
its applicability, a generic equation should be developed from test data obtained in
different industries.
3.5 EMISSION FACTOR QUALITY RATING SCHEME USED IN THIS STUDY
The uncontrolled emission factor quality rating scheme used in this study is
identical to that used in two earlier updates8'11 and represents a refinement of the
rating system developed by EPA for AP-42 emission factors, as described in
Section 3.3. The scheme entails the rating of test data quality followed by the rating of
the emission factor(s) developed from the test data.
Test data that were developed from well documented, sound methodologies
were assigned an A rating. Data generated by a methodology that was generally
sound but either did not meet a minimum test system requirements or lacked enough
detail for adequate validation received a B rating.
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In evaluating whether an upwind-downwind sampling strategy qualified as a
sound methodology, the following minimum test system requirements were used. At
least five particulate measuring devices must be operated during a test, with one
device located upwind and the other located at two downwind and three crosswind
distances. The requirement of measurements at crosswind distances is waived for the
case of line sources. Also wind direction and speed must be monitored concurrently
on-site.
The minimum requirements for a sound exposure profiling program were the
following. A one-dimensional, vertical grid of at least three samplers is sufficient for
measurement of emissions from line or moving point sources while a two-dimensional
array of at least five samplers is required for quantification of fixed virtual point source
missions. At least one upwind sampler must be operated to measure background
concentration, and wind speed must be measured on-site.
Neither the upwind-downwind nor the exposure profiling method can be
expected to produce A-rated emissions data when applied to large, poorly defined area
sources, or under very light and variable wind flow conditions. In these situations, data
ratings based on degree of compliance with minimum test system requirements were
reduced one letter.
After the test data supporting a particular single-valued emission factor were
evaluated, the criteria presented in Table 3-1 were used to assign a quality rating to the
resulting emission factor. These criteria were developed to provide objective definition
for: (a) industry representativeness; and (b) levels of variability within the data set for
the source category. The rating system obviously does not include estimates of
statistical confidence, nor does it reflect the expected accuracy of fugitive dust
emission factors relative to conventional stack emission factors. It does, however,
serve as useful tool for evaluation of the quality of a given set of emission factors
relative to the entire available fugitive dust emission factor data base.
Minimum industry representativeness is defined in terms of number of test sites
and number of tests per site. These criteria were derived from two principles:
1. Traditionally, three tests of a source represent the minimum requirement
for reliable quantification.
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TABLE 3-1. QUALITY RATING SCHEME FOR SINGLE-VALUED
EMISSION FACTORS
No. of
No. of
Total
Test
Adjustment
test
tests
No. of
data
forEF
Code
sites
per site
tests
variability3
rating13
1
> 3
> 3
-
< F2
0
2
> 3
> 3
-
> F2
-1
3
2
> 2
> 5
< F2
-1
4
2
> 2
> 5
> F2
-2
5
-
-
> 3
< F2
-2
6
-
-
> 3
> F2
-3
7
1
2
2
> F2
-3
8
1
2
2
> F2
-4
9
1
1
1
-
-4
a Data spread in relation to central value. F2 denotes factor of two
b Difference between emission factor rating and test data rating.
2. More than two plant sites are needed to provide minimum industry
representativeness.
The level of variability within an emission factor data set was defined in terms of
the spread of the original emission factor data values about the mean or median
single-valued factor for the source category. The fairly rigorous criterion that all data
points must lie within a factor of two of the central value was adopted. It is recognized
that this criterion is not insensitive to sample size in that for a sufficiently large test
series, at least one value may be expected to fall outside the factor-of-two limits.
However, this is not considered to be a problem because most of the current
single-valued factors for fugitive dust sources are based on relatively small sample
sizes.
Development of quality ratings for emission factor equations also required
consideration of data representativeness and variability, as in the case of single-valued
3-10
-------
emission factors. However, the criteria used to assign ratings (Table 3-2) were
different, reflecting the more sophisticated model being used to represent the test data.
As a general principle, the quality rating for a given equation should lie between the
test data rating and the rating that would assigned to a single-valued factor based on
the test data. The following criteria were established for an emission factor equation to
have the same rating as the supporting test data:
1. At least three test sites and three tests per site, plus an additional three
tests for each independent parameter in the equation.
2. Quantitative indication that a significant portion of the emission factor
variation is attributable to the independent parameter(s) in the equation.
Loss of quality rating in the translation of these data to an emission factor
equation occurs when these criteria are not met. In practice, the first criterion was far
more influential than the second in rating an emission factor equation, because
development of an equation implies that a substantial portion of the emission factor
variation is attributable to the independent parameter(s). As indicated in Table 3-2, the
rating was reduced by one level below the test data rating if the number of tests did not
meet the first criterion, but was at least three times greater than the number of
independent parameters in the equation. The rating was reduced two levels if this
supplementary criterion was not met.
The rationale for the supplementary criterion follows from the fact that the
likelihood of including "spurious" relationships between the dependent variable
(emissions) and the independent parameters in the equation increases as the ratio of
number of independent parameters to sample size increases. For example, a four
parameter equation based on five tests would exhibit perfect explanation (R2 = 1.0) of
the emission factor data, but the relationships expressed by such an equation cannot
be expected to hold true in independent applications.
3-11
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TABLE 3-2. QUALITY RATING SCHEME FOR EMISSION
FACTORS EQUATIONS
No. of
No. of
Total
Adjustment
test
tests
No. of
forEF
Code
sites
per site
tests3
rating13
1
> 3
> 3
> (9 + 3P)
0
2
> 2
> 3
> 3P
-1
3
> 1
-
< 3P
-1
a P denotes number of correction parameters in emission factor
equation.
b Difference between emission factor rating and test data rating.
3-12
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SECTION 4
AP-42 SECTION DEVELOPMENT
4.1 REVISIONS TO SECTION NARRATIVE
The draft AP-42 presented later in this background document is intended to
replace the current versions of both Section 11.2.5 "Urban Paved Roads" and Section
11.2.6 "Industrial Paved Roads" in AP-42. Both sections date from the mid-1980s and
only slight revisions have been made over the past 8 years.
As discussed earlier in this report, some AP-42 users have noted difficulty in
selecting the appropriate emission factor model to use in particular applications. For
example, field-measurement-based inventories have demonstrated that silt loading has
tended to decrease at industrial facilities throughout the 1980s, so that, at present, silt
loadings found on industrial roads often can be substantially lower than those in the
underlying data base. In extreme cases of silt loading outside the range supporting the
models, resulting PM10 factors may be greater than corresponding TSP factors. Due to
the trend of lower silt loadings, the distinction made between "urban" and "industrial"
paved roads in AP-42 has not been found as clear-cut in real-world situations.
Several investigators have also commented that the current emission factors for
public paved roads may not be applicable when the equilibrium between deposition and
removal processes is upset. This situation can occur for various reasons, including (a)
application of snow and ice controls, (b) trackout from construction activities in the
area, and (c) wind and/or water erosion from surrounding unstabilized areas.
4-1
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4.2 POLLUTANT EMISSION FACTOR DEVELOPMENT
This update to Sections 11.2.5 and 11.2.6 was planned to address the
shortcomings described above. In order to achieve this goal, the following general
approach was taken
1. Assemble the available test data for paved roads in a single data base,
making no distinction between public and industrial roads or between
controlled and uncontrolled roads.
2. Conduct a series of stepwise linear regression analyses of the revised
data base to develop an emission factor model with:
silt loading,
mean vehicle weight,
mean number of wheels, and,
mean travel speeds
as potential correction parameters.
3. Conduct an appropriate validation study of the reformulated model.
4.2.1 Review of Specific Data Sets
Table 4-1 presents the specific test reports reviewed in this update. As can be
seen, test reports reviewed in the 1987 update were again reviewed to determine if
controlled emissions data should be included in the final data set. Test reports I, II,
and III are new since the 1987 update. Test reports 1, 5, and 8 are those from the
1987 update that were re-reviewed.
Test Report I. This test program was undertaken to characterize PM-10
emissions from six streets that were periodically sanded for anti-skid control within the
Denver area. The primary objective was given as development of a predictive
algorithm for clean and sanded streets, with a secondary objective stated as defining
the effectiveness of control measures. Summary information is given in Table 4-2.
4-2
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TABLE 4-1. APPLICABLE TEST REPORTS
New reports since 1987 update:
I. PEI Associates 1989. "Street Sanding Emissions and Control Study," EPA
Contract No. 68-02-4394, Work Assignment No. 27, prepared for U.S.
Environmental Protection Agency, Region 8. October 1989.
II. Midwest Research Institute 1990. "Roadway Emission Field Tests at U.S.
Steel's Fairless Works." USX Purchase Order No. 146-0001191-0068,
prepared for United States Steel Corporation. May 1990.
III. RTP Environmental Associates 1990. "Street Sanding Emissions and Control
Study," prepared for the Colorado Department of Health. July 1990.
Reports3 considered during 1987 update:
1. T. Cuscino, Jr., et al., Iron and Steel Plant Open Source Fugitive Emission
Control Evaluation, EPA-600/2-83-110, U.S. Environmental Protection Agency,
Research Triangle Park, North Carolina, October 1983.
5. G. E. Muleski, Measurement of Fugitive Dust Emissions from Prilled Sulfur
Handling, Final Report, MRI Project No. 7995-L, Prepared for Gardinier, Inc.,
June 1984.
8. T. F. Eckle and D. L. Trozzo, "Verification of the Efficiency of a Road-Dust
Emission-Reduction Program by Exposure Profile Measurement," Presented
at EPA/AISI Symposium on Iron and Steel Pollution Abatement, Cleveland,
Ohio, October 1984.
a Same numbers as in 1987 update.8
Sampling employed six to eight 8 PM-10 samplers equipped with volumetric flow
control. Samplers were arranged in two upwind/downwind configurations. The "basic"
configuration consisted of six samplers arranged in identical patterns upwind and
downwind of the test road, with one sampler and one pair of samplers at nominal
distances of 20 and 5 m, respectively, from the road.
The second configuration was used for tests of control measure effectiveness.
The road segment was divided into two halves, corresponding to the treated and
experimental control (untreated) portions. Identical sampling arrays were again used
4-3
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TABLE 4-2. SUMMARY INFORMATION FOR TEST REPORT I
PM-m emission factor (g/VKT)
Operation
Location
State
Test dates
No. of tests
Geom. mean
Range
Vehicle traffic
Colfax
Colorado
3-4/89
17
1.33
0.53-9.01
Vehicle traffic
York St.
Colorado
4/89
1
1.07
1.07
Vehicle traffic
Belleview
Colorado
4/89
4
1.62
1.10-4.77
Vehicle traffic
1-225
Colorado
4/89
9
0.31
0.17-0.51
Vehicle traffic
Evans
Colorado
5-6/89
29
1.06
0.21-7.83
Vehicle traffic
Louisiana
Colorado
6/89
7
0.96
0.42-1.73
-------
upwind and downwind on both halves, at nominal distances of 20 and 5 m. Because
this array employed all eight samplers available, no collocation was possible for the
second configuration.
In addition to the PM-10 concentration measurements, several other types of
samples were collected:
• Wind speed/direction and incoming solar radiation were collected on-site,
and the results were combined to estimate atmospheric stability class
needed to calculate emission factors.
• Colorado Air Pollution Control Division (APCD) representatives collected
traffic data, including traffic counts, travel speeds, and percentage of
heavy-duty vehicles.
• Vacuums with disposable paper bags were used to collect the loose
material from the road surface. In addition to samples taken from the
travel lanes, the field crew took daily samples of material adjacent to
curbs and periodic duplicate samples.
The study collected PM-10 concentration data on 24 different days and
calculated a total of 69 different emission rates for baseline, sanded and controlled
paved road surfaces. Emission factors were obtained by back-calculation from the
CALINE3 dispersion model12 together with a series of assumptions involving mixing
widths and heights and an effective release height. Although data collected at the 20 m
distance were used to evaluate results, the test report did not describe any sensitivity
analysis to determine how dependent the emission rates were on the underlying
assumptions.
The testing program found difficulty in defining "upwind" concentrations for
several of the runs, including cases with wind reversals or winds nearly parallel to the
roadway orientation. A total of eight of the 69 tests required that either an average
concentration from other test days or a downwind concentration be used to define
"upwind" conditions. In addition, the test report described another seven runs as
invalid for reasons such as wet road surfaces, nearby dust sources or concentrations
increasing with downwind distance.
4-5
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A series of stepwise regression analyses were conducted, with different
predictive equations presented for (a) baseline conditions, (b) sanded roads, and
(c) roads swept to remove the sand applied, and (d) all conditions combined. In each
case, only one independent variable was included in the predictive equation: silt
loading, for cases (a) and (d); and time since treatment, for (b) and (c).
In general, Test Report I is reasonably well documented in terms of describing
test conditions, sampling methodology, data reduction and analysis. A chief limitation
lies in the fact that neither sampling configuration fully met minimum requirements for
the upwind-downwind method presented in Section 3.4. Specifically, only two or three
samplers were used downwind rather than the minimum of four.
Furthermore, a later report6 drawing upon the results from Test Reports I and III
effectively eliminated 24% of the combined baseline tests because of wind directions.
In addition, the later report6 noted that the baseline data should be considered as
"conservatively high" because roughly 70% of the data were calculated assuming the
most unstable atmospheric class (which results in the highest backcalculated emission
factor). Because of these limitations, the emission data have been given an overall
rating of between "B" and "C."
Test Report II. This 1989 field program used exposure profiling to characterize
emissions from paved roads at an integrated iron and steel plant. In many respects,
this program arose because of uncertainties with paved road emission factor models
used outside their range of applicability. During the preparation of an alternative
emission reduction ("bubble") plan for the plant, questions arose about the use of
AP-42 equations and other EPA guidance13 in estimating roadway emissions involved
in the emissions trade. This program provided site-specific data to support the bubble
plan. This testing program also represents the first exposure profiling data to
supplement the AP-42 paved road data base since 1984. Table 4-3 provides summary
information.
The program involved two paved road test sites. The first (site "C") was along
the four-lane main access route to the plant. Average daily traffic (ADT) had been
estimated as more than 4,000 vehicle passes per day, with most vehicles representa-
tive of "foreign" equipment (i.e., cars, pickups, and semi-trailers rather than plant haul
4-6
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TABLE 4-3. SUMMARY INFORMATION FOR TEST REPORT II
Emission factor Emission factors
(g/VKT) TSP (g/VKT) PMin
Test No. of Geom. Geom.
Operation Location State dates test mean Range mean Range
Vehicle traffic Unpaved road Pennsylvania 11/89 2 172 110-270 45.1 40-51
Vehicle traffic Site C Pennsylvania 11/89 6 9.19 3.4-34 2.69 0.25-10
Vehicle traffic Site E Pennsylvania 11/89 4 21.9 9.3-84 6.21 2-10
-------
trucks and other equipment). Site "E," on the other hand, was located near the iron-
and steel-making facilities and had both lower ADT and heavier vehicles than site "C."
The plant regularly vacuum swept paved roads, and two cleaning frequencies (two
times and five times per week) were considered during the test program.
Depending on traffic characteristics of the road being tested, a 6 to 7.5 m high
profiling array was used to measure downwind mass flux. This array consisted of four
or five total particulate sampling heads spaced at 1.5 m heights and was positioned at
a nominal 5 m distance downwind from the road. Additional concentration and particle
size measurements were obtained from standard high volume ("hi-vol") sampler and
cyclone/cascade impactor combination operated downwind as well as a standard hi-
vol/impactor combination operated upwind. The height for downwind sizing devices
(2.2 m) was selected after review of prior test results. It approximated the height in a
roadway dust plume at which half the mass emissions pass above and half below.
Additional samples included:
• Average wind speeds at two heights and wind direction at one height
were recorded during testing to maintain isokinetic sampling.
• Traffic data, including traffic counts, travel speeds, and vehicle class were
recorded manually.
• Vacuums with disposable paper bags were used to collect the loose
material from the road surface.
The sampling equipment met the requirements of a sound exposure profiling
methodology specified in Section 3.4 so that the emission test data are rated "A." The
test report presents emission factors for total particulate (TP), total suspended
particulate (TSP) and PM-10, for the ten paved road emission tests conducted.
Test Report II found that the emission factors and silt loadings more closely
resembled those in the "urban" rather than the "industrial" data base. That is to say,
emissions agreed more closely with factors estimated by the methods of AP-42 Section
11.2.5 than by methods in Section 11.2.6. Given the traffic rate of 4000 vehicles per
day at Site "C," this finding was not terribly surprising. What was far more surprising
4-8
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was that emissions at Site "E" were also more "urban" than "industrial." Although the
TSP and PM-10 models in Section 11.2.5 showed a slight tendency to underpredict, the
Section 11.2.6 PM-10 model overestimated measured emissions by at least an order of
magnitude. The performance of the industrial TSP model, on the other hand, was only
slightly poorer than that for the urban TSP model.
Test Report III. This test program was quite similar to that described in Test
Report I and used an essentially identical methodology. In fact, the two test reports are
very similar in outline, and many passages in the two reports are identical. The primary
objective was given as expanding the data base in Test Report I to further develop
predictive algorithms for clean and sanded streets. Summary information is given in
Table 4-4.
The test program employed the same two basic PM-10 sampling arrays as did
Test Report I. A third configuration was used for "profile" tests, in which additional
samplers were placed at 10 and 20 ft heights. (Analysis of results from elevated
samplers is not presented in Test Report III.)
As was the case in Test Report I, additional samples were collected including:
• Wind speed/direction were collected on-site, and the results used in
estimating atmospheric stability class needed to calculate emission
factors. (Unlike Test Report I, solar radiation measurements were not
collected.)
• Traffic data, including traffic counts, travel speeds, and percentage of
heavy-duty vehicles were collected.
• Vacuums with disposable paper bags were used to collect the loose
material from the road surface. The program developed an extensive set
of collocated samples of material along the edges of the roadway.
The study collected PM-10 concentration data on 33 days and calculated a total
of 131 different emission rates for baseline, sanded and controlled paved road
surfaces. Emission factors were obtained by back-calculation from the CALINE3
dispersion model12 together with essentially the same assumptions as those in Test
4-9
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TABLE 4-4. SUMMARY INFORMATION FOR TEST REPORT III
PM-10 emission factor (g/VKT)
Operation
Location
State
Test dates
No. of test
Geom. mean
Range
Vehicle traffic
Mexico
Colorado
2/90
3
2.75
1.08-6.45
Vehicle traffic
State Hwy 36
Colorado
1-3/90
13
1.31
0.14-4.18
Vehicle traffic
Colfax
Colorado
2-4/90
41
1.32
0.27-5.04
Vehicle traffic
Park Rd.
Colorado
4/90
11
1.26
0.69-3.33
Vehicle traffic
Evans
Colorado
2-3/90
11
2.10
0.87-7.27
Vehicle traffic
Louisiana
Colorado
1,3/90
9
3.24
1.40-5.66
Vehicle traffic
Jewell
Colorado
1/90
1
6.36
6.36
Vehicle traffic
Bryon
Colorado
4/90
3
8.38
5.53-14.72
-------
Report I. This report also noted the same difficulty as Test Report I in defining
"upwind" concentrations in cases with wind reversals or winds nearly parallel to the
roadway orientation. Unlike Test Report I, however, this report does not provide readily
available information on how many tests used either an average concentration from
other test days or a downwind concentration to define "upwind" conditions. Test Report
III does, however, describe seven tests as invalid because of filter problems or because
upwind concentrations were higher than downwind values.
As with the Test Report I program, a series of stepwise regression analyses
were conducted. This test program combined data from Test Reports I and III and
considered predictive equations for (a) baseline conditions, (b) sanded roads, and
(c) roads swept to remove the sand applied, and (d) all conditions combined.
Unlike Test Report I, however, Test Report III appears to present silt loading
values that are based on wet sieving (see page 8 of the test report) rather than the dry
sieving technique (as described in Appendix E to AP-42) routinely used in fugitive dust
tests. (MRI could not obtain any clarifying information during telephone calls to the
testing organization and the laboratory that analyzed the samples.) Wet sieving
disaggregates composite particles and results from the two types of sieving are not
comparable.
There is additional confusion over the silt loading values given in Test Report III
for cleaning tests. Specifically, the same silt loading value is associated with both the
treatment and the experimental control. This point could not be clarified during
telephone conversation with the testing organization. Attempts to clarify using test
report appendices were unsuccessful. Two appendices appear to interchange silt
loading with silt percentage. More importantly, it could not be determined whether the
surface sample results reported in Appendix D to Test Report III pertain to treated or
the experimental control segment, and with which emission rate a silt loading should be
associated.
Test Report III contains substantial amounts of information, but is not particularly
well documented in terms of describing test conditions, sampling methodology, data
4-11
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reduction and analysis. In addition, the same limitations mentioned in connection with
Test Report I are equally applicable to Test Report III, as follows:
• not meeting the minimum number of samplers.
• numerous tests conducted under variable wind conditions.
• frequent use (70% to 80% of the tests) of the most unstable atmospheric
stability class in the CALINE 3 model which will result in the highest
calculated emission rate.
Because of these limitations, emission rate data have been given an overall rating of
"C." Furthermore, the silt loading data in this report are considered suspect for reasons
noted above.
Reexamination of Earlier Data Sets. As remarked earlier, it was decided to
assemble paved road test data distinguishing neither between public and industrial
roads nor between controlled and uncontrolled tests. In addition to simply combining
the data bases supporting Sections 11.2.5 and 11.2.6, this involved reexamining earlier
reports for controlled test results. Specifically, the paved road Test Reports 1, 5, and 8
identified in the 1987 update (see Table 4-1) were reexamined.
Test Report 1 in 1987 update: This study evaluated paved road control
techniques at two different iron and steel plants. (See Tables 9 and 10 in
Reference 8.) Data were quality rated as "A," and uncontrolled test results were
incorporated into the data base for Section 11.2.6. The only use of the controlled test
results, however, has been the following addition to Section 11.2.6.4 in 1988:
"Although there are relatively few quantitative data on emissions from
controlled paved roads, those that are available indicate that adequate
estimates generally may be obtained by substituting controlled loading
values into .. [Equations (2-2) and (2-3)].... The major exception to this is
water flushing combined with broom sweeping. In that case, the
equations tend to overestimate emissions substantially (by an average
factor of 4 or more)."
4-12
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In the current update, the controlled emission factors have been used as part of
the overall data base to develop predictive models. Although PM-10 emission data are
not specifically presented in the report, appropriate values were previously developed
by log-normal interpolation of the PM-15 and PM-2.5 factors.8
Test Report 5 in 1987 update: This was first report identified to suggest that
heavily loaded paved roads may be better considered as unpaved in terms of emission
estimates. The program produced three tests of emissions from end-loader travel over
paved surfaces. Two of the three tests were conducted on very heavily loaded surface,
while the third was on a cleaned paved surface. (See Tables 20 and 21 of the 1987
update.)8
No PM-10 emission factors were reported; results were presented for total
particulate (TP) and suspended particulate (SP, or PM-30). Data were quality rated "A"
in the 1987 report.
Because no PM-10 data were given, Test Report 5 data were most directly
useful as independent data against which the TSP emission factor model (Eq. (2-2))
could be assessed. This comparison showed generally good agreement between
predicted and observed with agreement becoming better as source conditions
approached those in the underlying data base.
The 1987 update8 developed PM-10 emission factors based on information
contained in the test report. When compared to the single valued factors
(Equation [2-4]), agreement for the first two tests was within a factor of approximately
two. The third test—that of the cleaned surface—could not be used to assess the
performance of either Eq. (2-1) or Eq. (2-3) because the surface loading value could
not be converted to the necessary units with information presented in the report.
Test Report 8 in 1987 update: This paper discussed the development of an
exposure profiling system as well as an evaluation of the effectiveness of a paved road
vacuum sweeping program. Because no reference is made to an earlier test report,
this paper is considered to be the original source of the test data. Although ten
uncontrolled and five controlled tests are mentioned, test data are reported only in
terms of averages. (See Tables 24 and 25 in Reference 8.) Only TSP emission factors
4-13
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are presented. Although data were obtained using a sound methodology, data were
rated "B" because of inadequate detail in the paper.
Averaged data from Test Report 8 were used in an independent assessment of
Eq. (2-2). Although only average emission levels could be compared, the data
suggested that TSP emissions could be estimated within very acceptable limits.
4.2.2 Compilation of Final Data Base
In keeping with the results from the data set review, a final data base was
compiled by combining the following sets:
1. Data base supporting Section 11.2.5
2. Data base supporting Section 11.2.6
3. The controlled tests of Test Report 1 in the 1987 update
4. All data contained in Test Report II
The final PM-10 data base is shown in Figure 4-1, with the origin of each of the 64 data
points indicated by a key letter:
I - Data point used to develop the predictive equations in Section 11.2.6.
i - Data point used in developing the single-valued factors in Section 11.2.6.
U - Data point used to develop the predictive equation in Section 11.2.5.
u - Data point excluded during development of the urban paved road
equation (Section 11.2.5).
V,W,F - Controlled industrial test in Test Report 1 corresponding to vacuum
swept, water flushed or flushed/broom swept.
N - Data from Test Report II
4-14
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10,000 --
Predictive emission factor equation
in Section 11.2.6 (Equation 2-3)
1,000 --
100 --
10 --
1 --
0.1 --
0.01 --
Single-valued emission factor
in Section 11.2.6 (Equation 2-4)
Predictive emission
factor equation from
Section 11.2.5
(Equation 2-1)
Q Industrial road tests conducted
in 1989 ("AU" test series)
Controlled industrial paved road
tests not included in previous
Section 11.2.6 data base
°*01 0,1 1 "J 100 1,000 10|000
Silt Loading, sL (g/m2)
Figure 4-1. Final data set. See text for key letters.
4-15
-------
The "new" data, namely those in data sets (3) and (4), are shown in diamonds or circles
in the figure. Note that the new data sets function somewhat like "glue" in combining
the old industrial and urban data sets in the sense that the new data effectively bridge
the two older data sets.
Test data from Test Reports I and III were excluded from the final data base for
the following reasons:
a. Only PM-10 emission factors were available, rather than a group of
particle size ranges.
b. Unresolved questions about the silt loading values in Test Report III
remain.
Note, however, that Test Report I data provide very useful information about the
accuracy of the revised emission factor model. Figure 4-2 presents the 43 data points
from Test Report I used in the validation study.
4.2.3 Emission Factor Development
Stepwise multiple linear regression14 was used to develop a predictive model
with the final data set. The potential correction factors included:
- silt loading, sL
- mean vehicle weight, W
- mean vehicle speed, S
- mean number of wheels, w
All variables were log-transformed in order to obtain a multiplicative model as in the
past. Figure 4-3 presents the correlation matrix of the log-transformed independent
and dependent variables, as well as the multiple regression results. The most notable
features of the correlation matrix are the high degree of interdependence between silt
4-16
-------
10,000 -
1,000 --
100 --
5
ra
S
S S
S
s
s s ss
ss s
S "SS
s
0.1 --
0.01 --
0.01 o.i 1 10 100 1,000 ioJooo
Silt Loading, sL (g/m2)
Figure 4-2. Validation data from Test Report I. "B" represents a
baseline while "S" indicates a sand road test.
4-17
10 --
1 --
B
"B
B
8"
S
B
-------
loading, emission factors, and speed; and the low degree of interdependence between
silt loading and weight. This suggests that silt loading and weight may be effectively
used to derive an emission factor model.
Several points should be noted about the regression results. First, the
expression for PM-10 was always considered first so that a series of models
comparable over several size ranges would result. As Figure 4-3 shows, the models
for PM-30 and PM-15 are quite similar to that for PM-10; the expression for PM-2.5, on
the other hand, has substantially lower exponents for both sL and W.
Second, during an initial exploratory phase, it was found that models with
essentially equivalent accuracy could be developed using only the independent
variables of weight W and speed S. Nevertheless, those two variables cannot be
expected to vary substantially during the year. In other words, a model based on W
and S could not be expected to predict higher emission levels known to occur after
road sanding, etc. Models incorporating surface loading values as an independent
variable were pursued because surface loading represents a reasonable means of
introducing seasonal variability.
The following equation presents the final recommended emission factor models.
e = k(sL)0 65 (W)1-5
where e is emission factor in g/vehicle-mile traveled (gA/MT), sL is silt loading in g/m2,
W is mean vehicle weight in tons, and k is constant given in Table 4-5.
TABLE 4-5. RECOMMENDED EMISSION FACTOR MODELS
Size range
Sample size
k
Multiple R2
PM-2.5
52
0.41
NA
PM-10
64
0.90
0.761
PM-15
65
1.1
0.765
PM-30
18
4.7
0.752
4-18
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PEARSON CORRELATION MATRIX FOR PM-2.5
Multiple Linear Regression for PM-10
LGVMT
LSL
LTONS LMPH LWHEELS
DEP VAR:
LGVMT N:
64
MULTIPLE R: 0.873
SQUARED MULTIPLE R:
LGVMT
1.000
ADJUSTED SQUARED MULTIPLE R:
0.754
STANDARD ERROR OF ESTIMATE:
LSL
0.697
1.000
LTONS
0.646
0.282
1.000
VARIABLE
COEFFICIENT
STDERROR
STD COEF TOLERANCE T
LMPH
-0.812
-0.809
-0.208 1.000
LWHEELS
-0.006
-0.596
0.885 0.513 1.000
CONSTANT
-0.099
0.424
0.000
-0.232
LSL
0.648
0.074
0.586
0.880 8.790
FREQUENCY TABLE
LTONS
1.487
0.209
0.474
0.880 7.117
LGVMT
LSL
LTONS LMPH LWHEELS
ANALYSIS OF VARIANCE
LGVMT
52
LSL
52
52
SOURCE
SUM-OF-SQUARES
DF
MEAN-SQUARE
F-RATIO P
LTONS
52
52
52
LMPH
30
30
30 30
REGRESSION
377.698
2
188.849
97.371 0.000
LWHEELS
13
13
13 13 13
RESIDUAL
118.309
61
1.939
PEARSON CORRELATION MATRIX FOR PM-10
Multiple Linear Regression for PM-2.5
LGVMTLSL LTONS LMPH LWHEELS
DEP VAR:
LGVMT N:
52
MULTIPLE R: 0.839
SQUARED MULTIPLE R:
LGVMT
1.000
ADJUSTED SQUARED MULTIPLE R:
0.693
STANDARD ERROR OF ESTIMATE:
LSL
0.751
1.000
LTONS
0.676
0.347
1.000
VARIABLE
COEFFICIENT
STD ERROR
STD COEF TOLERANCE T
LMPH
-0.768
-0.837
-0.202 1.000
LWHEELS
0.141
-0.596
0.885 0.513 1.000
CONSTANT
0.007
0.457
0.000
0.015
LSL
0.487
0.070
0.559
0.920 6.912
FREQUENCY TABLE
LTONS
1.258
0.209
0.488
0.920 6.030
LGVMTLSL LTONS LMPH LWHEELS
ANALYSIS OF VARIANCE
LGVMT
65
LSL
64
64
SOURCE
SUM-OF-SQUARES
DF
MEAN-SQUARE
F-RATIO P
LTONS
65
64
65
LMPH
42
42
42 42
REGRESSION
186.960
2
93.480
58.472 0.000
LWHEELS
13
13
13 13 13
RESIDUAL
78.337
49
1.599
PEARSON CORRELATION MATRIX FOR PM-15
Multiple Linear Regression for PM-15
LGVMTLSL LTONS LMPH LWHEELS
DEP VAR:
LGVMT N:
64
MULTIPLE R: 0.879
SQUARED MULTIPLE R:
LGVMT
1.000
ADJUSTED SQUARED MULTIPLE R:
0.765
STANDARD ERROR OF ESTIMATE:
LSL
0.765
1.000
LTONS
0.672
0.348
1.000
VARIABLE
COEFFICIENT
STD ERROR
STD COEF TOLERANCE T
LMPH
-0.775
-0.837
-0.202 1.000
LWHEELS
0.159
-0.596
0.885 0.513 1.000
CONSTANT
0.182
0.422
0.000
0.432
LSL
0.678
0.073
0.604
0.879 9.264
FREQUENCY TABLE
LTONS
1.470
0.208
0.462
0.879 7.081
LGVMTLSL LTONS LMPH LWHEELS
ANALYSIS OF VARIANCE
LGVMT
64
LSL
64
64
SOURCE
SUM-OF-SQUARES
DF
MEAN-SQUARE
F-RATIO P
LTONS
64
64
64
LMPH
42
42
42 42
REGRESSION
395.337
2
197.669
103.275 0.000
LWHEELS
13
13
13 13 13
RESIDUAL
116.754
61
1.914
PEARSON CORRELATION MATRIX FOR PM-30
Multiple Linear Regression for PM-30
LGVMT
LSL LTONS LMPH LWHEELS
DEP VAR:
LGVMT N:
18
MULTIPLE R: 0.868
SQUARED MULTIPLE R:
LGVMT
1.000
ADJUSTED SQUARED MULTIPLE R:
0.72
STANDARD ERROR OF ESTIMATE:
LSL
0.748
1.000
LTONS
0.787
0.568
1.000
VARIABLE
COEFFICIENT
STD ERROR
STD COEF TOLERANCE T
LMPH
-0.737
-0.875
-0.338 1.000
LWHEELS
CONSTANT
1.342
0.815
0.000
1.648
LSL
0.596
0.210
0.443
0.677 2.843
FREQUENCY TABLE
LTONS
1.638
0.477
0.535
0.677 3.434
LGVMT
LSL LTONS LMPH LWHEELS
ANALYSIS OF VARIANCE
LGVMT
18
LSL
18
18
SOURCE
SUM-OF-SQUARES
DF
MEAN-SQUARE
F-RATIO P
LTONS
18
18
18
LMPH
12
12
12 12
REGRESSION
35.115
2
17.557
22.883 0.000
LWHEELS
0
0
0 0 0
RESIDUAL
11.509
15
0.767
0.761
1.393
P(2 TAIL)
0.817
0.000
0.000
0.705
1.264
P(2 TAIL)
0.988
0.000
0.000
0.772
1.383
P(2 TAIL)
0.667
0.000
0.000
0.753
0.876
P(2 TAIL)
0.120
0.012
0.004
Figure 4-3. Correlation and regression results for the data set.
-------
All models, except that for PM-2.5, are quality rated "A." The expression for PM-
2.5 was based on a mean ratio of PM-2.5 to PM-10 because of slightly different powers
on the sL and W terms; the PM-2.5 factor is rated "B." The high R2 values for the other
size ranges indicate that approximately 75% of variability in emission factors are
"explained" by the predictive equation.
4.2.4 Validation Studies
Two sets of validation studies were undertaken to assess the predictive
capability of the revised paved road emission model for PM-10. The first employed a
standard cross-validation (CV) technique.15 Using this technique, each point in the
underlying data base is excluded one at a time, and the equation generated from the
reduced data base is used to estimate the missing value. The second evaluation
applied the new PM-10 expression to the independent data of Test Report I.
By using a CV technique, "n" quasi-independent estimates are obtained from a
data base of "n" tests, and the overall validity of using stepwise regression to obtain a
model of the form
e = k (sL)a (W)b
is evaluated. Summary information is shown in Table 4-6.
TABLE 4-6. RESULTS OF CROSS-VALIDATION STUDY
Variable
Minimum
Maximum
Mean
Std. deviation
a
Exponent of sL
0.63
0.67
0.649
0.009
b
Exponent of W
1.42
1.57
1.49
0.027
k
Leading term
0.79
1.07
0.90a
1.058a
Ratio of quasi-
independent estimate
to measured emission
factor
0.050
30
1.004a
4.23a
a Geometric mean/standard deviation.
4-20
-------
Figure 4-4 presents the cumulative frequency distribution of the ratio of the
quasi-independent estimate to the measured emission factor. A little over half of the
estimates are within a factor of 3 and approximately 70% are within a factor of 5. The
90% confidence interval corresponds to a factor of approximately 8.
The second validation study applied the recommended PM-10 emission factor
model to the data of Test Report I (see Figure 4-2). This represents an independent
application of the equation in that none of the Test Report I data were used to develop
the equation. Summary information is given in Table 4-7:
TABLE 4-7. RESULTS FROM INDEPENDENT APPLICATION OF THE PM-10 MODEL
Ratio of predicted to observed PM-10 emission factor
Sample
size
Minimum
Maximum
Geo. mean
Geo. std.
deviation
Baseline roads
23
0.23
1.59
0.528
1.69
Sanded roads
20
0.35
2.51
1.03
1.69
Overall
43
0.23
2.51
0.724
1.86
As can be seen, agreement is generally quite good, especially for sanded roads.
For baseline (unsanded) roads, the new PM-10 emission factor model tends to
underpredict emissions. Recall that a later report6 making use of Test Reports I and III
stated that the combined baseline data "should be considered to be conservatively
high." If that is true, then the tendency of the new model to underpredict could be
expected.
4-21
-------
0.05 0.1 0.2 0.5 1 2 5 10 20
Ratio of predicted to measured PM-10 emission factors
Figure 4-4. Cumulative frequency distribution obtained during cross-
validation study.
4-22
-------
One final examination compared performance of the new PM-10 versus the
current AP-42 factors and EPA guidance.13 The document "Control of Open Fugitive
Dust Sources" (EPA-450/3-88-008) presented the following decision rule for paved
road emission estimates (Table 4-8).
TABLE 4-8. DECISION RULE FOR PAVED ROAD EMISSION ESTIMATES
Silt loading (sL)
(g/m2)
Average vehicle weight (W)
(tons)
Use model given by
sL < 2
W> 4
Equation (2-3)
sL < 2
W< 4
Equation (2-1)
sL > 2a
W> 6
Equation (2-3)
2 < sL < 15
W< 6
Equation (2-3)
sL > 15a
W< 6
Equation (2-4)
a For heavily loaded surfaces (i.e., sL < ~ 300 to 400 g/m2) it is recommended that
the resulting estimate be compared to that from the unpaved road models.
Table 4-9 presents the results from this comparison. As can be seen, in almost
every data set comparison, results using the new model are comparable, if not better,
than those using the three different equations currently contained in AP-42, together
with the selection method of Table 4-8.
4.3 DEVELOPMENT OF OTHER MATERIAL IN AP-42 SECTION
Concurrent with the development of the revised AP-42 section for paved roads,
a separate effort was conducted to assemble a silt loading data base for nonindustrial
roads. Over the past 10 years, numerous organizations have collected silt loading
samples from public paved roads. Unfortunately, uniformity—in sampling and analysis
methodology as well as roadway classification schemes—has been sorely lacking in
these studies.
Silt loading data were compiled in the following manner. Persons
knowledgeable about PM-10 at each EPA regional office were asked to identify sL data
for public roads. In many instances, the EPA representatives identified state/local air
regulatory personnel who were then asked to supply the data. Given that the relative
importance of PM-10 emissions from public sources is greater in the western United
States, it is not surprising that most of the data are from that area of the country. What
4-23
-------
TABLE 4-9. RATIO OF PREDICTED TO MEASURED PM-10 EMISSION FACTORS
Data set code3
Sample size
Minimum13
Maximum13
Geo. meanb
Std. geo.
deviation13
I
19
0.086 / 0.056
2.9/12
0.80/0.70
2.3/4.5
i
5
0.24/0.39
4.1 / 5.5
0.96/1.0
2.8/2.8
U
10
0.39/0.38
170/6.6
8.8/1.2
6.8/2.4
u
9
0.61 / 0.56
300 /18
14/3.4
7.7/2.9
V, F, W
11
0.52/0.14
8.6/3.7
1.7/0.54
2.4/2.9
N
10
0.13/0.094
79/28
5.8/1.1
10/5.5
Overall
64
0.086 / 0.056
300 / 28
2.7/1.0
6.4/3.9
a Same data subset code as for Figure 4-1.
b First entry represents value using current AP-42 factors and decision rule in Table 4-8. Second entry represents
value using new PM-10 equation.
-------
is surprising, perhaps, is that Montana has collected roughly two-thirds of all data.
Furthermore, only Montana had data collected from the same road over extended
periods of time, thus permitting examination of temporal variation.
The assembled data set did not yield any readily identifiable, coherent
relationship between silt loading and road class, average daily traffic (ADT), etc. Much
of the difficulty is probably due to the fact that not all variables were reported by each
organization. Further complicating the analysis is the fact that, in many parts of the
country, paved road silt loading varies greatly over the course of the year. Recall that
repeated sampling at Montana municipalities indicated a very noticeable annual cycle.
Nevertheless, it is questionable whether the seasonal variation noted in the Montana
data base could successfully predict variations for many other sites. While one could
possibly expect similar variations for, say, Idaho or Wyoming roads, there is far less
reason to suspect a similar cycle in, say, Maine or Michigan, in the absence of
additional information.
Because no meaningful relationship could be established between sL and an
independent variable, the decision was made to directly employ the nonindustrial data
base in the AP-42 section. The draft AP-42 section presents the cumulative frequency
distribution for the sL data base, with subdivisions into (a) low-ADT (< 5000
vehicles/day) and high-ADT roads and (b) first and second halves of the year.
Suggested default values are based on the 50th and 90th percentile values.
The second use of the assembled data set recognizes that the end users of AP-
42 are the most capable in identifying which roads in the data base are similar to roads
of interest to them. The draft AP-42 section presents the paved road surface loading
values together with the city, state, road name, collection date (samples collected from
the same road during the same month are averaged), road ADT if reported, classi-
fication of the roadway, etc. Readers of AP-42 are invited to review the data base and
to select values that they deem appropriate for the roads and seasons of interest.
4-25
-------
4-26
-------
Date:
September 30, 1997
Subject: Review and Update of AP-42 Sections in Chapters 11, 12, and 13 Covering Mineral Products
Industries, Metallurgical Industries and Miscellaneous Sources
EPA Contract 68-D2-0159, Work Assignment 4-02
MRI Project 4604-02
From: Greg Muleski
To: Ron Myers
EPA/EFIG/EMAD (MD-14)
U. S. Environmental Protection Agency
Research Triangle Park, N.C. 27711
Attached is an addendum to the report entitled "Emission Factor Documentation for AP-42, Sections
11.2.5 and 11.2.6" (dated March 8, 1993). That report consolidated sections 11.2.5 (Urban Paved Roads)
and 11.2.6 (Industrial Paved Roads)into a single paved road section (now numbered 13.2.1). Because it
relied on "old" data supporting sections 11.2.5 and 11.2.6, the March 8, 1993 only discussed the additional
test data reviewed in the process of updating the paved road emission factor equation. In other words, the
1993 report did not describe the older paved road test data, which had been discussed in previous AP-42
updates.
However, since the time that the March 8, 1993 became available, users of the TTN 2000 have
inquired about the test data not described in the report. Presentation of that data is a key feature of the
addendum attached to this memo. The addendum also updates the public paved road silt loading data base as
well as AP-42 Section 13.2.1 itself.
Also attached is a copy of the comment/response log prepared for the March 8, 1993 report.
Comments were provided by:
1. William Barnard of E. H. Pechan;
2. Gary Neuroth of the Arizona DEQ; and
3. Doug Cole of Idaho DEQ.
Copies of their letters are attached as well. Attachment 1 presents the verbatim comments of the reviewers as
well as MRI's responses to the comments. Attachment 2 contains the public road silt loading ("sL") data
sets. The data set presented in the March 1993 background document consists of approximately 400 values
collected between April 1978 and June 1992. As the addendum describes, there were reasons to suspect
(even at the time that the "old" data set was assembled) that the sL values presented were biased high relative
to normal or typical conditions. However, independent data were not available to confirm those suspicions.
Since the time that the background document was assembled, however, several newer field sampling
programs were undertaken. Some of these programs had the goal of defining the annual sL cycle. The "new"
data set, which consists of 169 sL values, clearly shows that the old data set is biased high relative to normal
-------
2
conditions. The new data set, which is contained in Attachment 3, is used in the Addendum to develop
revised default sL values. However, the emphasis on developing site-specific inputs to the predictive
emission factor is still emphasized in the AP-42 section.
This memo, the addendum and the attachments are also being submitted in electronic form, so that
those materials can be posted on EPA's BBS.
-------
Addendum to Emission Factor Documentation for AP-42
Section 11.2.5 and 11.2.6 (Now 13.2.1)
Paved Roads
Final Report
For U. S. Environmental Protection Agency
Office of Air Quality Planning and Standards
Emission Factor and Inventory Group
EPA Contract 68-D2-0159
Work Assignment No. 4-02
MRI Project No. 4604-02
September 1997
-------
Addendum to Emission Factor Documentation for AP-42
Section 11.2.5 and 11.2.6 (Now 13.2.1)
Paved Roads
Final Report
For U. S. Environmental Protection Agency
Office of Air Quality Planning and Standards
Emission Factor and Inventory Group
Research Triangle Park, NC 27711
Attn: Mr. Ron Myers (MD-14)
EPA Contract 68-D2-0159
Work Assignment No. 4-02
MRI Project No. 4604-02
September 1997
-------
NOTICE
The information in this document has been funded wholly or in part by the United States
Environmental Protection Agency under Contract No. 68-D2-0159 to Midwest Research Institute. It has
been reviewed by the Office of Air Quality Planning and Standards, U. S. Environmental Protection Agency,
and has been approved for publication. Mention of trade names or commercial products does not constitute
endorsement or recommendation for use.
11
-------
PREFACE
This report was prepared by Midwest Research Institute (MRI) for the Office of Air Quality
Planning and Standards (OAQPS), U. S. Environmental Protection Agency (EPA), under Contract
No. 68-D2-0159, Work Assignment No. 4-02. Mr. Ron Myers was the requester of the work.
Approved for:
MIDWEST RESEARCH INSTITUTE
Roy Neulicht
Program Manager
Environmental Engineering Department
Jeff Shular
Director, Environmental Engineering
Department
September, 1997
in
-------
iv
-------
TABLE OF CONTENTS
Page
1.0 BACKGROUND DOCUMENTATION-PAVED ROADS SECTION 13 1-1
1.1 Section l~Test Report Descriptions 1-1
1.1.1 Reference 1 - Midwest Research Institute, Roadway Emissions Field Tests at
US Steel's Fairless Works, for U.S. Steel Corporation, May 1990 1-2
1.1.2 Reference 2 - Midwest Research Institute, Paved Road Particulate Emissions -
Source Category Report, for U.S. EPA, July 1984 1-2
1.1.3 Reference 3 - Midwest Research Institute, Size Specific Particulate Emission
Factors for Uncontrolled Industrial 1-6
1.1.4 Reference 4 - Midwest Research Institute, Iron and Steel Plant Open Source
Fugitive Emission Control Evaluation, for U. S. EPA, August 1983 1-6
1.2 Revision of the Public Paved Road Silt Loading Default Values 1-13
1.3 Summary of Changes to AP-42 Section 13.2.1 1-17
2.0 PROPOSED AP-42 SECTION 13.2.1 2-1
Attachment 1. Comment/Response Log for March 8, 1993, Paved Road Background Document
Attachment 2. Public Paved Road Surface Loading Presented as Appendix X in March 8, 1993
Paved Road Background Document
Attachment 3 New Silt Loading Data Set Used to Develop Revised Default Silt Loading Values
v
-------
LIST OF TABLES
Table Page
A 1-1. SUMMARY INFORMATION FOR REFERENCE 1 1-3
Al-2. DETAILED INFORMATION FROM PAVED ROAD TESTS FOR REFERENCE 1 . . . 1-3
A1-3. SUMMARY INFORMATION FOR REFERENCE 2 1-4
Al-4. DETAILED INFORMATION FOR PAVED ROAD TESTS FOR REFERENCE 2 1-5
Al-5. SUMMARY OF PAVED ROAD EMISSION FACTORS FOR REFERENCE 3 1-7
Al-6. DETAILED INFORMATION FOR PAVED ROAD TESTS FOR REFERENCE 3 1-8
Al-7. SUMMARY OF PAVED ROAD EMISSION FACTORS FROM REFERENCE 4 1-10
Al-8. DETAILED INFORMATION FOR PAVED ROAD TESTS FROM REFERENCE 4 ... 1-11
Al-9. PAVED ROAD SILT LOADING STUDIES SINCE THE 1993 BACKGROUND
REPORT 1-14
Al-10. SUMMARY STATISTICS FOR RECENT PAVED ROAD SILT LOADING
STUDIES 1-14
vi
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1.0 BACKGROUND DOCUMENTATION-PAVED ROADS SECTION 13.2.1
This document is an addendum to Emission Factor Documentation for AP-42, Sections 11.2.5 and
11.2.6, Paved Roads, EPA Contract No. 68-D0-0123, Assignment 44, dated March 8, 1993 and prepared for
the Office of Air Quality Planning and Standards, U. S. Environmental Protection Agency (EPA). Since the
preparation of the 1993 document, the Fifth edition of AP-42 incorporated Sections 11.2.5, Paved Urban
Roads, and 11.2.6, Industrial Paved Roads, into Section 13.2.1, Paved Roads. An update to AP-42 Section
13.2.1 is warranted to address the U. S. EPA's recent focus on particulate matter (PM) emissions less than
2.5 am in aerodynamic diameter (PM-2.5) and to permit the reexamination of test information on public road
surface silt loadings.
Information in this Addendum includes descriptions of the test reports used to develop the current
emission factor equation in AP-42, Section 13.2.1; a narrative of the reexamination of the road surface silt
loading data base; and a summary of changes included in the AP-42 Paved Road Section including the new
emission factor equation multiplier for PM-2.5. The format for this Addendum is as follows: (a) Section 1.1
- Test Report Descriptions, (b) Section 1.2 - Revision of the Public Paved Road Silt Loading Default Values,
(c) Section 1.3 - Summary of Changes to AP-42 Section 13.2.1, (d) Section 2 - a copy of the revised AP-42
Section 13.2.1, (e) Attachment 1 - Comments/Response Logs for external review comments on the March 8,
1993 Paved Road Background Document, (f) Attachment 2 - Public Paved Road Surface Loading AP-42
data base from March 8, 1993, and (g) Attachment 3 - New Silt Loading Data Set..
1.1 Section 1-Test Report Descriptions
Test reports containing data used to develop the paved road emission factor equation in the March 8,
1993, Paved Road Background Document, are discussed in the following subsections. Summary emission
data and detailed test data from each of the four test reports are provided along with a brief description of
each test site and test methodology.
Profiling methodologies are used for these test reports and include the following test parameters:
(a) downwind test equipment should be located approximately 5 meters from the source, (b) background
equipment should be located approximately 15 meters upwind of the source, (c) and no disturbances should
exist immediately upwind or downwind of the testing location. For wind conditions to remain acceptable
during an exposure profiling test, 5- to 10-minute averages of speed and direction are examined. If the mean
wind direction moves out of an arc within 45 degrees of the line perpendicular to the road centerline for two
consecutive averaging periods, testing is suspended. Similarly, if the mean wind speed falls outside the
acceptable range (typically 4 to 20 mph) for two consecutive periods, testing is suspended. While sampling is
suspended, mean wind speed and direction are still monitored. To restart a test, analogous criteria are used.
That is to say, if the mean wind direction lies within 45 degree of the perpendicular for two consecutive
averaging periods, testing can be reinitiated. Likewise, if the average wind speed falls in the acceptable range
for two consecutive periods, sampling may resume.
When following standard testing methodologies some vehicle heights may exceed the height of the
sampling equipment; however, the fact that the emissions originate at the road curve and the emission plume
can be characterized as decreasing with height indicates the total plume can be estimated. Vehicle heights are
not generally reported in the source test reports. Analyses for silt content of the road surface follow
methodologies described in Appendix C. 1 and Appendix C.2 of AP-42. Moisture content was reported for
several of these paved road studies. Variations from the generally accepted test methodology stated above or
any other nontraditional methodology are discussed within the individual test report reviews. Test reports
1-1
-------
were not down graded on their qualities ratings due to unreported data if it was not significant to the paved
road emission factor equation development.
1.1.1 Reference 1 - Midwest Research Institute. Roadway Emissions Field Tests at IJS Steel's Fairless
Works, for U.S. Steel Corporation. Mav 1990.
This testing program focused on paved and unpaved road PM emissions at an integrated iron and
steel plant near Philadelphia, Pennsylvania, in November 1989. Exposure profiling was used to characterize
emissions from two paved roads. Site C-l was located along the main access route and had a mix of light-
and medium-duty vehicles. Site E-2 was located near the southwest corner of the plant and the traffic
consisted mostly of plant equipment.
Tests were conducted using a profiling array, with four sampling heights from 1.5 m to 6.0 m, for
measuring the downwind mass flux of airborne PM. A high-volume sampler with a parallel-slot cascade
impactor and a cyclone preseparator (cutpoint of 15 |imA) was employed to measure the downwind particle
size distribution, and a standard high-volume sampler was utilized to determine the downwind mass fraction
of total suspended particulate matter (TSP). The upwind (background) particle size distribution was
determined with a high-volume cyclone/ impactor combination. Warm wire anemometers at two heights
measured wind speed.
Eight tests were conducted at Site C-1 and four tests were conducted at Site E-2. The paved road
test sites were considered uncontrolled. The road width, moisture content, and mean number of wheels were
not reported. The test data are assigned an A rating. Table Al-1 presents summary information and Table
Al-2 presents detailed test information. Warm wire anemometers at two heights measured wind speed.
1.1.2 Reference 2 - Midwest Research Institute. Paved Road Particulate Emissions - Source Category
Report, for U.S. EPA. July 1984
This document reports the results of testing of paved roads conducted in 1980 at sites in Kansas
City, MO, St. Louis, MO, Tonganoxie, KS, and Granite City, IL. Paved road test sites included
commercial/industrial roads, commercial/residential roads, expressways, and a street in a rural town. The
expanded measurement program reported in this document was used to develop emission factors for paved
roads and focused on the following particle sizes: PM-15 (inhalable particulate matter [IP]), PM-10, and
PM-2.5.
Total airborne PM emissions were characterized using an exposure profiler containing four sampling
heads. High-volume samplers with size selective inlets (SSI) having a cutpoint of 15 |imA were used to
characterize upwind and downwind PM-15 concentrations. A high-volume sampler with a SSI and a cascade
impactor was also located downwind to characterize particle size distribution within the PM-15 component.
Upwind and downwind standard high-volume samplers measured TSP concentrations. Warm wire
anemometers at two heights measured wind speed.
A total of 19 paved road emission tests were conducted in four cities. These included four tests of
commercial/industrial paved roads, ten tests of commercial/residential paved roads, four expressway tests,
and one test of a street in a rural town. Additionally, as part of this study, 81 dust samples were collected in
12 cities. The mean number of vehicle wheels was not reported. The test data are assigned an A rating.
Table A1-3 presents summary test data and Table A1-4 presents detailed test information.
1-2
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TABLE A1-1. SUMMARY
NFORMATION FOR REFERENCE 1
Test
dates
No. of
tests
TSP emission factor. lb/VMT
PM-10 emission factor. lb/VMT
Operation
Location
State
Geom. mean
Range
Geom. mean
Range
Vehicle traffic
AU-X (Unpaved
road)
PA
11/89
2
0.61
0.39-0.96
0.16
0.14-0.18
Vehicle traffic
Paved road
PA
11/89
6
0.033
0.012-0.12
0.0095
0.0009-0.036
Vehicle traffic
Paved road
PA
11/89
4
0.078
0.033-0.30
0.022
0.0071-0.036
1 lb/VMT = 281.9 g/VKT.
TABLE A1-2. DETAILED INFORMATION FROM PAY
Test runs
PM-10
emission
factor, lb/VMT
Duration,
min
Meterorology
Vehicle characteristics
Silt
loading,
g/m2
Silt, %
Temperature,
°F
Mean wind
speed,
mph
No. of
vehicle
passes
Mean
vehicle
weight,
ton
Mean
vehicle
speeda
AU-C-3
0.00497
103
50
12
836
5.5
(27)
0.42
10
AU-C-4
0.0355
147
63
11
1057
6.0
25
0.52
12
AU-C-5
0.0337
120
62
14
963
3.9
29
0.23
9.7
AU-C-6
0.00816c
187
39
14
685
6.2
(27)
0.23
8.6
AU-C-7
0.000887
96
42
12
703
3.0
(27)
0.26
7.7
AU-C-8
0.0174
218
40
15
779
2.0
(27)
0.15
9.9
AU-E-1
0.00709
154
43
12
210
12
15
4.0
17
AU-E-2
0.0234
89
44
13
373
5.1
16
4.0
17
AU-E-3
0.0355
118
41
9.3
330
2.6
(15)
2.2
18
AU-E-4
0.0199
130
41
9.3
364
2.6
(15)
1.3
15
;d road tests for reference i
aValue in parentheses is the average speed measured for test road during the field exercise.
bTest conducted on a paved road surface vacuum-swept five times per week.
cMean TSP/TP or PM10/TP ratio applied.
1 lb/VMT = 281.9 g/VKT.
-------
TABLE Al-3. SUMMARY INFORMA'
Operation
State
Test
dates
No. of
tests
PM-15 emission factor, lb/VMT
PM-10 emission factor, lb/VMT
PM-2.5 emission factor, lb/VMT
Geom. mean
Range
Geom. mean
Range
Geom. mean
Range
Commercial/
Industrial
MO
2/80
4
0.0078
0.0036-0.013
0.0068
0.0034-0.011
0.0045
0.0030 - 0.0063
Commercial/
Residential
MO, IL
2/80
10
0.0021
0.0006-0.012
0.0017
0.0004 - 0.0093
0.0011
0.0002 - 0.0037
Expressway
MO
5/80
4
0.0004
0.0002 - 0.0008
0.0004
0.0002 - 0.0007
0.0002
0.0001 - 0.0003
Rural Town
KS
3/80
1
0.031
0.031
0.025
0.025
0.005
0.005
ION FOR REFERENCE 2
1 lb/VMT = 281.9 g/VKT.
-------
"ABLE Al-^
k DETAILED INFORIV
1ATION FOR PAVED ROAD TESTS FOR REFERENCE 2
Category
Run test
No.
PM-10
emission
factor,
lb/VMT
Duration,
min.
Temp., °F
Mean
wind
speed,
mph
Road
width,
ft
No. of
vehicle
passes
Mean
vehicle
speed,
mph
Mean
vehicle
weight,
tons
Silt
loading,
g/m2
Silt (%)
Commercial/Industrial
M-l
0.0110
120
28
7.4
44
2,627
30
5.6
0.46
10.7
Commercial/Industrial
M-2
0.00340
86
27
6.5
44
2,166
30
3.8
0.26
6.2
Commercial/Industrial
M-3
0.00781
120
28
7.8
44
2,144
30
4.5
0.15
3.5
Commercial/Industrial
M-9
0.00712
136
50
7.4
44
3,248
30
4.1
0.29
12.2
Commercial/Residential
M-4
0.000400
240
38
7.8
36
2,763
35
2.1
0.43
18.8
Commercial/Residential
M-5
0.00153
226
53
2.2
36
2,473
35
2.2
1.00
21.4
Commercial/Residential
M-6
0.00304
281
35
5.6
36
3,204
30
2.1
0.68
21.7
Commercial/Residential
M-l 3
0.00680
194
60
2.7
22
5,190
35
2.7
0.11
13.7
Commercial/Residential
M-l 4
0.00301
178
55
9.2
22
3,940
35
2.7
0.079
-
Commercial/Residential
M-l 5
0.00323
135
77
11.4
22
4,040
35
2.7
0.047
8.1
Commercial/Residential
M-l 7
0.00582
150
75
4.0
40
3,390
30
2.0
0.83
5.7
Commercial/Residential
M-l 8
0.000800
172
75
5.1
40
3,670
30
2.0
0.73
7.1
Commercial/Residential
M-l 9
0.000390
488
70
2.7
20
5,800
30
2.4
0.93
8.6
Expressway
M-10
0.000390
182
60
2.9
96
11,148
55
4.5
0.022
-
Expressway
M-l 1
0.000700
181
56
8.7
96
11,099
55
4.8
0.022
-
Expressway
M-l 2
0.000190
150
65
4.7
96
9,812
55
3.8
0.022
-
Expressway
M-l 6
0.000530
254
70
4.0
96
15,430
55
4.3
0.022
-
Rural Town
M-8
0.0247
345
50
4.7
30
1,975
20
2.2
2.50
14.5
1 lb/VMT = 281.9 g/VKT.
1 g/m2 = 1.434 gr/ft2
-------
1.1.3 Reference 3 - Midwest Research Institute. Size Specific Particulate Emission Factors for
Uncontrolled Industrial and Rural Roads, for IJ. S. EPA. January 1983
This document reports the results of testing conducted in 1981 and 1982 at industrial unpaved and
paved roads and at rural unpaved roads. Unpaved industrial roads were tested at a sand and gravel
processing facility in Kansas, a copper smelting facility in Arizona, and both a concrete batch and asphalt
batch plant in Missouri. The study was conducted to increase the existing data base for size-specific PM
emissions. The following particle sizes were of specific interest for the study: PM-15, PM-10, and PM-2.5.
Exposure profiling was utilized to characterize total PM emissions. Five sampling heads, located at
heights of up to 5 m, were deployed on the profiler. A standard high-volume sampler and a high-volume
sampler with an SSI (cutpoint of 15 |imA) were also deployed downwind. In addition, two high-volume
cyclone/impactors were operated to measure particle size distribution. A standard high-volume sampler, a
high-volume sampler with an SSI, and a high-volume cyclone/impactor were utilized to characterize the
upwind TSP and PM-15 concentrations and the particle size distribution within the PM-15 fraction. Wind
speed was monitored with warm wire anemometers.
A total of 18 paved road tests and 21 unpaved road tests are completed. The test data are assigned
an A rating. Industrial paved road tests were conducted as follows: three unpaved road tests at the sand and
gravel processing plant, three paved road tests at the copper smelting plant, four paved road tests at the
asphalt batch facility, and three paved road tests at the concrete batch facility. The industrial road tests were
considered uncontrolled and were conducted with heavy duty vehicles at the sand and gravel processing plant
and with medium duty vehicles at the asphalt batch, concrete batch, and copper smelting plants. Table Al-5
presents summary test data and Table A1-6 presents detailed test information.
1.1.4 Reference 4 - Midwest Research Institute. Iron and Steel Plant Open Source Fugitive Emission
Control Evaluation, for IJ. S. EPA. August 1983
This test report centered on the measurement of the effectiveness of different control techniques for
PM emissions from fugitive dust sources in the iron and steel industry. The test program was performed at
two integrated iron and steel plants, one located in Houston, Texas, and the other in Middletown, Ohio.
Control techniques to reduce emissions from paved roads, unpaved roads, and coal storage piles were
evaluated. For paved roads, control techniques included vacuum sweeping, water flushing, and flushing with
broom sweeping. Particle emission sizes of interest in this study were total PM, PM-15, and PM-2.5.
The exposure profiling method was used to measure paved road particulate emissions at the Iron and
Steel plants. For this study, a profiler with four or five sampling heads located at heights of 1 to 5 m was
deployed. Two high-volume cascade impactors with cyclone preseparators (cutpoint of 15 |imA). one at 1 m
and the other at 3 m, measured the downwind particle size distribution. A standard high-volume sampler and
an additional high-volume sampler fitted with a SSI (cutpoint of 15 pmA) were located downwind at a height
2 m. One standard high-volume sampler and two high-volume samplers with SSIs were located upwind for
measurement of background concentrations of TSP and PM-15.
Twenty-three paved road tests of controlled and uncontrolled emissions were performed. These
included 11 uncontrolled tests, 4 vacuum sweeping tests, 4 water flushing tests, and 4 flushing and broom
sweeping tests. For paved roads, this test report does not present vehicle speeds, mean number of wheels, or
moisture contents. Because vehicle speeds and moisture content do not figure into the emission
1-6
-------
TABLE A
-5. SUMMARY OF PAVED ROAD EMISSION FACTORS FOR REFERENCE 3
Industrial category
Type
TP, lb/VMT
PM-15, lb/VMT
PM-10, lb/VMT
PM-2.5, lb/VMT
Geo. mean
Range
Geo. mean
Range
Geo. mean
Range
Geo.
mean
Range
Asphalt Batching
Medium duty
1.83
0.750-3.65
0.437
0.124-0.741
0.295
0.0801-0.441
0.130
0.0427-0.214
Concrete Batching
Medium duty
4.74
2.25-7.23
1.66
0.976-2.34
1.17
0.699-1.63
0.381
0.200-0.562
Copper Smelting
Medium duty
11.2
7.07-15.7
4.01
2.02-5.56
2.78
1.35-3.86
0.607
0.260-0.846
Sand and Gravel
Processing
Medium Duty
5.50
4.35-6.64
1.02
0.783-1.26
0.633
0.513-0.753
0.203
0.194-0.211
1 lb/VMT = 281.9 g/VKT.
-------
TABLE A1-6. DETAILED INFORMATION FOR PAVED ROAD TESTS FOR REFEREN
Run
No.
Industrial category
Traffic
PM-10
emission
factor,
lb/VMT
Duration,
min.
Mean
wind
speed,
mph
Road
width,
ft
No. of
vehicle
passes
Vehicle characteristics
Moisture
content, %
Silt
loading,
g/m2
Silt, %
Mean
vehicle
weight,
tons
No. of
wheels
Mean
vehicle
speed,
mph
Y-l
Asphalt Batching
Medium
Duty
0.257
274
5.37
13.8
47
3.6
6
10
0.22
91
2.6
Y-2
Asphalt Batching
Medium
Duty
0.401
344
4.70
14.1
76
3.7
7
10
0.51
76
2.7
Y-3
Asphalt Batching
Medium
Duty
0.0801
95
6.04
14.1
100
3.8
6.5
10
0.32
193
4.6
Y-4
Asphalt Batching
Medium
Duty
0.441
102
5.59
14.1
150
3.7
6
10
0.32
193
4.6
Z-l
Concrete Batching
Medium
Duty
0.699
170
6.71
24.3
149
8.0
10
10
a
11.3
6.0
Z-2
Concrete Batching
Medium
Duty
1.63
143
9.84
24.9
161
8.0
10
15
a
12.4
5.2
Z-3
Concrete Batching
Medium
Duty
4.01
109
9.62
24.9
62
8.0
10
15
a
12.4
5.2
AC-4
Copper Smelting
Medium
Duty
3.86
38
8.72
34.8
45
5.7
7.4
10
0.43
287
19.8
AC-5
Copper Smelting
Medium
Duty
3.13
36
9.62
34.8
36
7.0
6.2
15
0.43
188
15.4
AC-6
Copper Smelting
Medium
Duty
1.35
33
4.92
34.8
42
3.1
4.2
20
0.53
400
21.7
AD-1
Sand and Gravel
Heavy Duty
3.27
110
7.61
12.1
11
42
11
23
a
94.8
6.4
AD-2
Sand and Gravel
Heavy Duty
0.753
69
5.15
12.1
16
39
17
23
a
63.6
7.9
AD-3
Sand and Gravel
Heavy Duty
0.513
76
3.13
12.1
20
40
15
23
a
52.6
7.0
CE 3
1 lb/VMT = 281.9 g/VKT.
1 g/m2 = 1.434 gr/ft2
a Not measured.
-------
equation, the test data are assigned an A rating. Table Al-7 presents summary test data and Table Al-8
presents detailed test information. The PM-10 emission factors presented in Table Al-8 were calculated
from the PM-15 and PM-2.5 data using logarithmic interpolation.
After vacuum sweeping, emissions were reduced slightly more than 50 percent for two test runs and
less than 16 percent for two test runs. Water flushing applied at 0.48 gal/yd2 achieved emission reductions
ranging from 30 percent to 70 percent. Flushing at 0.48 gal/yd2 combined with broom sweeping resulted in
emission reductions ranging from 35 percent to 90 percent.
1-9
-------
TABLE A1-7. SUMMARY OF PAVED
ROAD EMISSION FACTORS FROM REFERENC1
34
Control
method
Location
State
Test date
No. of
tests
TP, lb/VMT
PM-15, lb/VMT
PM-2.5, lb/VMT
Geo mean
Range
Geo mean
Range
Geo mean
Range
None
a,d,f,j
OH
7/80,
10/80, &
11/80
7
1.22
0.29-5.50
0.38
0.13-2.14
0.10
0.04-0.52
Vacuum
Sweeping
A
OH
10/80 &
11/80
4
0.87
0.53-1.46
0.45
0.27-0.87
0.14
0.08-0.26
Water
Flushing
D,L
TX
6/81
4
1.43
1.30-1.74
0.47
0.32-0.65
0.08
0.08-0.09
Flushing &
Broom
Sweep
K,L,M
TX
6/81
4
0.96
0.54-2.03
0.20
0.10-0.49
0.07
0.04-0.13
None
L,M
TX
6/81
4
3.12
0.83-5.46
0.92
0.31-1.83
0.26
0.06-0.62
1 lb/VMT = 281.9 g/VKT.
-------
TABLE A1-8. DETAILED INFORMATION FOR PAVED ROAD TESTS FROM REFERENCE 4
Site
Test
Run No.
Control
method
PM-10
emission
factor, lb/VMT
Duration,
min.
Temp., °F
Mean wind
speed, mph
No. of
vehicle
passes
Mean
vehicle
weight, tons
Silt loading,
g/m2
Silt, %
A
F-34
None
0.536
62
90
4.2
79
28
2.79
16
A
F-35
None
0.849
127
90
7.5
130
25
2.03
10.4
A
F-36
VS
0.147
335
50
5.9
263
8.3
0.202
18.3
A
F-37
VS
0.209
241
50
4.8
199
17
0.043
26.4
A
F-38
VS
0.430
127
50
4.5
141
18
0.217
27.9
A
F-39
VS
0.686
215
50
6.4
190
18
0.441
19.6
D
F-61
None
1.35
108
40
11.0
93
40
17.9
21.0
D
F-62
None
0.929
77
45
12.1
94
36
14.4
20.3
D
F-74
WF
1.32
205
50
9.0
67
29
5.59
9.45
F
F-27
None
0.357
91
100
9.5
158
14
17.7
35.7
F
F-45
None
0.608
135
50
4.0
172
16
5.11
28.4
J
F-32
none
0.144
259
90
5.8
301
14
0.117
13.4
K
B-52
FBS
0.0946
60
90
2.9
119
12
7.19
34.3
L
B-50
FBS
0.230
104
90
5.6
123
9.4
13.6
28.2
L
B-51
FBS
0.435
93
90
4.2
127
11
13.6
28.2
L
B-54
WF
0.268
101
90
5.4
118
10
3.77
22.6
L
B-55
WF
0.575
82
90
8.5
98
11
6.29
19.6
L
B-56
WF
0.398
61
90
6.3
118
9.2
2.40
11.2
L
B-58
None
1.08
96
90
6.7
67
18
10.4
17.9
M
B-53
FBS
0.161
81
90
5.3
72
20
-
9.94
M
B-57
0.554
None
101
90
3.6
68
12
2.32
6.45
M
B-59
0.993
None
114
90
6.1
67
11
2.06
14.0
M
B-60
1.18
None
112
90
5.0
50
12
3.19
13.5
aAverage of 2+ values
bSample used for more than 1 run.
CPM-10 emission factors were calculated from the PM-15 and PM-2.5 data using logarithmic interpolation.
VS = Vacuum sweeping; WF = Water flushing; FBS = Water flushing and broom sweeping; 1 lb/VMT = 281.9 g/VKT; 1 g/3i= 1.434 gr/ft2
-------
References for Section 1
1. Roadway Emissions Field Tests at U.S. Steel s Fairless Works, U.S. Steel Corporation, Fairless
Hills, PA, USX Purchase Order No. 146-0001191-0068, May 1990.
2. Paved Road Particulate Emissions Source Category Report, U. S. Environmental Protection
Agency, Research Triangle Park, NC, EPA Contract No. 68-02-3158, Assignment 19, July 1984.
3. Size Specific Particulate Emission Factors for Uncontrolled Industrial and Rural Roads, U.S.
Environmental Protection Agency, Research Triangle Park, NC, EPA Contract No. 68-02-3158,
Assignment 12, January 1983.
4. Iron and Steel Plant Open Source Fugitive Emission Control Evaluation, U.S. Environmental
Protection Agency, Research Triangle Park, NC, EPA Contract No. 68-02-3177, Assignment 4,
August 1983.
5. Emission Factor Documentation for AP-42, Sections 11.2.5 and 11.2.6 Paved Roads, EPA
Contract No. 68-D0-0123, Midwest Research Institute, Kansas City, MO, March 1993.
1-12
-------
1.2 Revision of the Public Paved Road Silt Loading Default Values
During the preparation of the March 8, 1993 Paved Road Background Document1, the available
public road silt loading ("sL") values from test reports dated 1992 and earlier were assembled into a data
base. Appendices C. 1 and C.2 to AP-42 describe the sampling and analysis procedures, respectively, used to
determine sL values. This "old" data set was originally presented as Appendix X in the March 8, 1993
background report. Subsequently, EPA requested that the sL data set be moved into the AP-42 Section. In
response, MRI prepared the current Table 13.2.1-2. (An electronic version of the old sL data set has been
supplied with this addendum.)
Although hundreds of public paved road sL measurements had been collected from 1980 until 1992
2"10, the paved road sL data base was limited in its usefulness for various reasons:
1. Almost two-thirds of the available data had been collected in one state (Montana).
2. Only Montana had collected extensive data that addressed temporal variation of sL. While this
provided very useful information on the annual cycle of silt loadings, the data were not generally transferable
to most regions in the United States.
3. There had been no uniformity in either the sampling/analysis methods used to generate sL values
or in schemes used to report roadway classifications. Similarly, the different sampling programs do not all
report the necessary information to develop a coherent data set. For example, the following items are not
always reported: whether the road is curbed; the posted speed limit; if surrounding land use would lead to
trackout from unpaved shoulders or parking lots; or, if anti-skid materials were recently applied. These
unknowns result from the lack of uniform reporting.
4. Examination of the data base did not reveal any meaningful relationship between silt loading and
other variables (such as average daily traffic [ADT], road class, etc.). For example, a significant negative
correlation was found between sL and ADT for roads with ADTs of 5,000 or more. However, on further
investigation of that road class, it was found that there was a significant positive and a significant negative
correlation over the first and second halves, respectively, of the calendar year.
5. There were strong reasons to suspect that the assembled data base was skewed towards high
values:
-- The majority of measurements were collected during the first calendar half (which was found to
have substantially higher values than the second half).
-- There was anecdotal information that at least some of the sampling programs focused on
suspected trouble spots that were heavily loaded (such as after snow/ice storms, near
construction sites, etc.).
Note that the assembled data base was composed of "point values" of silt loading. Here the term
"point value" is used to denote samples collected at a specific point along a roadway and at a single point in
time. In this sense, the term is contrasted with "composite" samples, for which increments from different
roadways and/or from different times are aggregated in a single vacuum bag. The resulting composite sample
thus represents a spatially or temporally averaged value of silt loading. At the time the data base was
assembled, two sets of spatial averages were available -one set covering the South Coast Air Quality
Management District (REF 11) and another from three study areas in Oregon (REF 12). Because of their
1-13
-------
composite nature, these measurements were not included in the data base assembled for the 1993 background
document.
Although there were strong reasons to suspect that the assembled data base was biased towards high
values, independent data were not available to confirm the suspicions. Since the time that the background
document was prepared, a number of field sampling programs have been undertaken; the references that
document these programs are shown in Table A1-9.
TABLE Al-9. PAVED ROAD SILT LOADING
STUDIES SINCE THE 1993 BACKGROUND REPORT
Reference
Study description
13
A characterization of control measures to reduce mud/dirt carryout onto paved roads from
a construction site in Kansas City
14
Collection of late winter/early spring silt loadings in the Pocatello, Idaho area,
emphasizing post-storm conditions
15
A yearlong study to define temporal variations of silt loading on roads in the Reno,
Nevada area.
16
Collection of sets of spatially averaged silt loadings in four study areas of the desert
southwest: South Coast, Coachella Valley, Las Vegas, Bakersfield
17
An ongoing study to track silt loading trends over a yearlong period in the Pocatello, Idaho
area
Note that the first two studies in Table Al-9 were directed to higher values of sL due to their focus
on mud/dirt carryout and post-winter storm conditions. As such, results from these two studies were
excluded from further consideration in revising the public road silt loading values. Data from the second
Pocatello study (Reference 17) were not available at the time of this addendum.
Results from References 15 and 16, together with results from the composite samples in References
11 and 12 and the silt loading values from the recent PM-2.5/PM-10 study18 for baseline road surface
conditions (i.e., not immediately after road sanding), formed the basis for revising the default values for
public paved road silt loading. An electronic version of the new sL data set has been supplied with this
addendum. Table A1-10 presents summary statistics for the new data set.
TABLE A1-10. SUMMARY STATISTICS FOR RECENT PAVED ROAD SILT
LOADING STUDIES
Data set
Sample size
Silt loading, g/m2
Range
Geo. mean
Geo. std. dev.
Median
90th
percentile
High ADTa
50
0.01 - 1.02
0.093
3.13
0.086
0.38
Low ADT
103
0.054-6.82
0.41
2.64
0.39
1.52
Overall
169b
0.01-6.82
0.26
3.34
0.27
1.05
aIn this context, high ADT refers to roadways with at least 5,000 vehicles per day.
bThe overall data set includes 16 spatially average samples that included increments from both high and
low ADT roads.
1-14
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When the results in Table A1-10 are compared to those presented in Table 13.2.1-2 of AP-42, it
becomes immediately apparent that the current default guidance in Section 13.2 leads to overly conservative
values for silt loading. Values in the newer data set are roughly 5 times lower than those in the data set
compiled for the 1993 background document. Consequently, it is recommended that AP-42 Table 13.2.1-2
be modified to include the (rounded) median values from Table A2-2 for "normal" conditions. However, the
newer data set also indicates that substantially higher or lower than "normal" silt loadings may occur on
public paved roads. As a result, it is further recommended that the modified AP-42 table present the former
median values for the January-to-June period as suitable for use when estimates of elevated silt loading (e.g.,
after snow/ice controls or near trackout areas) are desired.
Additional revisions are recommended for default values for limited access roads. Reference 18
presents the results from not only baseline sampling, but also samples collected immediately after sanding an
interstate highway in Denver:
Baseline: 0.0127 g/m2
After sanding: 0.184 g/m2
After averaging the baseline with the older data for limited access roads, the recommended default
for limited access roads under "normal" conditions is 0.015 g/m2- Furthermore, the section text has been
revised to suggest a default value of 0.2 g/m2 for short periods of time following the application of snow/ice
controls (antiskid abrasives) to limited access roads.
References for Section 1.2
1. Emission Factor Documentation For AP-42, Sections 11.2.5 and 11.2.6 Paved Roads, EPA Contract
No. 68-D0-0123, Midwest Research Institute, Kansas City, MO, March 1993.
2. Cowherd, Jr., and P. J. Englehart, Paved Road Particulate Emissions, EPA-600/7-84-077, U. S.
Environmental Protection Agency, Cincinnati, OH, July 1984.
3. Montana Street Sampling Data, Montana Department Of Health And Environmental Sciences, Helena,
MT, July 1992.
4. Street Sanding Emissions And Control Study, PEI Associates, Inc., Cincinnati, OH, October 1989.
5. Evaluation OfPM-10 Emission Factors For Paved Streets, Harding Lawson Associates, Denver, CO,
October 1991.
6. Street Sanding Emissions And Control Study, RTP Environmental Associates, Inc., Denver, CO,
July 1990.
7. Post-storm Measurement Results Salt Lake County Road Dust Silt Loading Winter 1991/92
Measurement Program, Aerovironment, Inc., Monrovia, CA, June 1992.
8. Written communication from Harold Glasser, Department of Health, Clark County (NV).
9. PM-10 Emissions Inventory Data For The Maricopa And Pima Planning Areas, EPA Contract No. 68-
02-3888, Engineering-Science, Pasadena, CA, January 1987.
1-15
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10. Characterization OfPM-10 Emissions From Antiskid Materials Applied To Ice- And Snow-covered
Roadways, EPA Contract No. 68-D0-0137, Midwest Research Institute, Kansas City, MO, October
1992.
11. Open Fugitive DustPMlO Control Strategies Study, South Coast Air Quality Management District
Contract No. 90059, Midwest Research Institute, Kansas City, MO, July 1990.
12. Oregon Fugitive Dust Emission Inventory, EPA Contract No. 68-D0-0123, Work Assignment No. 24,
Midwest Research Institute, Kansas City, MO, January 1992.
13. Characterization of Mud/Dirt Carryout onto Paved Roads from Construction and Demolition
Activities, EPA Contract No. 68-D2-0159, Work Assignment No. 1-04, Midwest Research Institute,
Kansas City, MO, December, 1995.
14. Letter Report to Doug Cole, Idaho Operations Office, EPA Region 10, dated April 30, 1993, EPA
Contract 68-D0-0123, Work Assignment 11-76.
15. Personal communication with Andy Goodrich of Washoe County Department of Health, Reno, NV.
16. Improvement of Specific Emission Factors (BACM Project No. I), South Coast Air Quality
Management District Contract No. 95040, Midwest Research Institute, Kansas City, MO, March 1996.
17. Personal communication with J. Light, c/o Bannock Planning Organization, Pocatello, ID.
18. Fugitive Particulate Matter Emissions, EPA Contract No. 68-D2-0159, Work Assignment No. 4-06,
Midwest Research Institute, Kansas City, MO, April 1997.
1-16
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1.3 Summary of Changes to AP-42 Section 13.2.1
Although the equation for particulate emissions from paved roads remains unchanged, the PM-2.5
multiplier has been updated based on findings in Reference 22. The PM-2.5 multiplier update is reflected in
the list of particle size multipliers for the paved road equation. Also, the default silt loading (sL) values for
public paved roads have been updated. Table 13.2.1-2 has been revised along with associated text to reflect
this new analysis. The silt loading data base, formerly presented as Table 13.2.1-3, will only be available as
an electronic file. (The new sL data set is also available as an electronic file.)
Section 13.2.1 follows with text removed from the old AP-42 version striked out and new text in
bold. Although not shown here, no changes were made to Figure 13.2.1-1, and Figures 13.2.1-2 through
13.2.1-7 (showing the silt loading frequency distribution) have been removed from the AP-42 section.
13.2.1 Paved Roads
13.2.1.1 General
Particulate emissions occur whenever vehicles travel over a paved surface, such as a road or parking
lot. Particulate emissions from paved roads are due to direct exhaust from vehicles and resuspension
of loose material on the road surface. In general terms, the resuspended particulate emissions from paved
roads originate from the loose material present on the surface. In turn, that surface loading, as it is moved or
removed, is continuously replenished by other sources. At industrial sites, surface loading is replenished by
spillage of material and trackout from unpaved roads and staging areas. Figure 13.2.1-1 illustrates several
transfer processes occurring on public streets.
Various field studies have found that public streets and highways, as well as roadways at industrial
facilities, can be major sources of the atmospheric particulate matter within an area.1-9 Of particular interest
in many parts of the United States are the increased levels of emissions from public paved roads when the
equilibrium between deposition and removal processes is upset. This situation can occur for various reasons,
including application of snow and ice controls, carryout from construction activities in the area, and wind
and/or water erosion from surrounding unstabilized areas. In the absence of continuous addition of fresh
material (through localized trackout or application of antiskid material), paved road surface loading
should reach equilibrium values in which the amount of material resuspended matches the amount
replenished. The equilibrium sL value depends upon numerous factors. It is believed that the most
important factors are: mean speed of vehicles traveling the road; the average daily traffic (ADT); the
number of lanes and ADT per lane; the fraction of heavy vehicles (buses and trucks); and the
presence/absence of curbs, storm sewers and parking lanes.
13.2.1.2 Emissions And Correction Parameters
Dust emissions from paved roads have been found to vary with what is termed the "silt loading"
present on the road surface as well as the average weight of vehicles traveling the road. The term silt loading
(sL) refers to the mass of silt-size material (equal to or less than 75 micrometers [pm] in physical diameter)
per unit area of the travel surface.4"5 The total road surface dust loading is that of loose material that can be
collected by broom sweeping and vacuuming of the traveled portion of the paved road. The silt fraction is
determined by measuring the proportion of the loose dry surface dust that passes through a 200-mesh screen,
using the ASTM-C-136 method. Silt loading is the product of the silt fraction and the total loading, and is
abbreviated "sL". Additional details on the sampling and analysis of such material are provided in AP-42
Appendices C. 1 and C.2.
1-17
-------
The surface sL provides a reasonable means of characterizing seasonal variability in a paved road
emission inventory.9 In many areas of the country, road surface loadings are heaviest during the late winter
and early spring months when the residual loading from snow/ice controls is greatest. As noted earlier, once
replenishment of fresh material is eliminated, the road surface loading can be expected to reach an
equilibrium value, which is substantially lower than the late winter/early spring value.
13.2.1.3 Predictive Emission Factor Equations10
The quantity of dust emissions from vehicle traffic on a paved road may be estimated using the
following empirical expression:
E=k (sL/2)0-65 (W/3 )1-5 (1)
where:
E = particulate emission factor (having units matching the units of k)
k = base emission factor for particle size range and units of interest (see below)
sL = road surface silt loading (grams per square meter) (g/m2)
W = average weight (tons) of the vehicles traveling the road
It is important to note that Equation 1 calls for the average weight of all vehicles traveling the road.
For example, if 99 percent of traffic on the road are 2 Mg cars/trucks while the remaining 1 percent consists
of 20 Mg trucks, then the mean weight "W" is 2.2 Mg. More specifically, Equation 1 is not intended to be
used to calculate a separate emission factor for each vehicle weight class. Instead, only one emission factor
should be calculated to represent the "fleet" average weight of all vehicles traveling the road.
The particle size multiplier (k) above varies with aerodynamic size range as follows: shown in
Table 13.2.1-1. To determine particulate emissions for a specific particle size range, use the appropriate
value of k shown in Table 13.2.1-1..
The above equation is based on a regression analysis of numerous emission tests, including 65 tests
for PM-10.10 Sources tested include public paved roads, as well as controlled and uncontrolled industrial
paved roads. No tests of "stop-and-go" traffic were available for inclusion in the data base. The equations
retain the quality rating of A (B for PM-2.5), if applied within the range of source conditions that were tested
in developing the equation as follows:
Silt loading: 0.02 - 400 g/m2
0.03 - 570 grains/square foot (ft2)
Mean vehicle weight: 1.8-38 megagrams (Mg)
2.0 - 42 tons
Mean vehicle speed: 16-88 kilometers per hour (kph)
10 - 55 miles per hour (mph)
To retain the quality rating for the emission factor equation when it is applied to a specific paved
road, it is necessary that reliable correction parameter values for the specific road in question be determined.
With the exception of limited access roadways, which are difficult to sample, the collection and use of
site-specific sL data for public paved road emission inventories are strongly recommended. The field
and laboratory procedures for determining surface material silt content and surface dust loading are
summarized in Appendices C. 1 and C.2. In the event that site-specific values
1-18
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Table 13.2.1-1. PARTICLE SIZE MULTIPLIERS FOR PAVED ROAD EQUATION
Size rangea
Multiplier kb
g/VKT
g/VMT
lb/VMT
PM-2.5C
0.0073
1.1
1.8
0.0040
PM-10
4.6
7.3
0.016
PM-15
5.5
9.0
0.020
PM-SO^
24
38
0.082
a Refers to airborne particulate matter (PM-x) with an aerodynamic diameter equal to or less than
x micrometers.
b Units shown are grams per vehicle kilometer traveled (g/VKT), grams per vehicle mile traveled
(g/VMT), and pounds per vehicle mile traveled (lb/VMT). The muliplier k includes unit conversions
to produce emission factors in the units shown for the indicated size range from the mixed units
required in Equation 1.
c Ratio of PM-2.5 to PM-10 taken from Reference 22.
c d PM-30 is sometimes termed "suspendable particulate" (SP) and is often used as a surrogate for TSP.
cannot be obtained, an appropriate value for an industrial road may be selected from the mean values given in
Table 13.2.1-2, but the quality rating of the equation should be reduced by 1 level.
With the exception of limited access roadways, which are difficult to sample, the collection and use
of site-specific sL data fr public paved road emission inventories are strongly recommended. Although
hundreds of public paved road sL measurements have been made since 1980,"'14-21 uniformity has been
lacking in sampling equipment and analysis techniques, in roadway classification schemes, and in the types of
data reported.^ The assembled data set (described below) does not yield any readily identifiable, coherent
relationship between sL and road class, average daily traffic (ADT), etc., even though an inverse relationship
between sL and ADT had been found for a subclass of curbed paved roads in urban areas* The absence of
such a relationship in the composite data set is believed to be due to the blending of data (industrial and
nonindustrial. uncontrolled, and controlled, and so on). Further complicating any analysis is the fact that, in
many parts of the country, paved road sL varies greatly over the course of the year, probably because of
cyclic variations in mud/dirt carryout and in use of anti-skid materials. For example, repeated sampling of the
same roads over a period of 3 calendar years at 4 Montana municipalities indicated a noticeable annual cycle.
In those areas, silt loading declines during the first 2 calendar quarters and increases during the fourth
quarter.
Figure 13.2.1-2 and Figure 13.2.1-3 present the cumulative frequency distribution for the public
paved road sL data base assembled during the preparation of this AP-42 section.^ The data base includes
samples taken from roads that were treated with sand and other snow/ice controls. Roadways are grouped
into high- and low-ADT sets, with 5000 vehicles per day being the approximate cutpoint. Figure 13.2.1-2
and Figure 13.2.1-3, respectively, present the cumulative frequency distributions for high- and low-ADT
roads.
In the absence of site-specific sL data to serve as input to a public paved road inventory,
conservatively high emission estimates can be obtained by using the following values taken from the figures.
1-19
-------
For annual conditions, the median sL values of 0.4 g/m? can be used for high-ADT roads (excluding limited
access roads that arc discussed below) and 2.5 g/m? for low-ADT roads. Worst-case loadings can be
estimated for high-ADT (excluding limited access roads) and low-ADT roads, respectively, with the 90th
percentile values of 7 and 25 give?. Figure 13.2.1-4, Figure 13.2.1-5, Figure 13.2.1-G, and Figure 13.2.1-7
present similar cumulative frequency distribution information for high- and low-ADT roads, except that the
sets were divided based on whether the sample was collected during the first or second half of the year.
Information on the 50th and 90th percentile values is summarized in Table 13.2.1-2.
Table 13.2.1-2 (Metric Units). PERCENTILES FOR NONINDUSTRIAL SILT LOADING (g/m8) DATA
BASE
Averaging Period
Annual
January-June
July-December
High-APT Roads
SO1
A
rȣWL_
y UUl
€h4
±4
%
Low-ADT Roads
fAi 1-
j Ulll
rirwL.
y Ulll
%
25
5
During the preparation of the background document (Reference 10), public road silt loading
values from 1992 and earlier were assembled into a data base. This data base is available as
. Although hundreds of public paved road sL measurements had been collected, there
was no uniformity in sampling equipment and analysis techniques, in roadway classification schemes,
and in the types of data reported. Not surprisingly, the data set did not yield a coherent relationship
between sL and road class, average daily traffic (ADT), etc., even though an inverse relationship
between sL and ADT has been found for a subclass of curbed paved roads in urban areas. Further
complicating the analysis is the fact that, in many parts of the country, paved road sL varies greatly
over the course of the year, probably because of cyclic variations in mud/dirt carryout and in use of
anti-skid materials. Although there were strong reasons to suspect that the assembled data base was
skewed towards high values, independent data were not available to confirm the suspicions.
Since the time that the background document was prepared, new field sampling programs
have shown that the assembled sL data set is biased high for normal situations. Just as
importantly, however, the newer programs confirm that substantially higher than normal silt
loadings can occur on public paved roads. As a result, two sets of default values are provided in
Table 13.2.1-2, one for normal conditions and another for worst-case conditions (such as after
winter storm seasons or in areas with substantial mud/dirt trackout). The newer sL data base is
available as .
The range of sL values in the data base for normal conditions is 0.01 to 1.0 for high-ADT roads and
0.054 to 6.8 for low-ADT roads. Consequently the use of a default value from Table 13.2.1-2 should be
expected to yield only an order-of-magnitude estimate of the emission factor. Public paved road silt loadings
are dependent upon: traffic characteristics (speed, ADT, and fraction of heavy vehicles); road characteristics
(curbs, number of lanes, parking lanes); local land use (agriculture, new residential construction) and
regional/seasonal factors (snow/ice controls, wind blown dust). As a result, the collection and use of site-
specific silt loading data is highly recommended.
1-20
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Table 13.2.1-2 (Metric Units). RECOMMENDED DEFAULT SILT LOADING (g/m2) VALUES
FOR PUBLIC PAVED ROADSa
High ADT roadsb
Low ADT roads
Normal conditions
0.1
0.4
Worst-case conditions0
0.5
3
a Excluding limited access roads. See discussion in text. 1 g/m2 is equal to
1.43 grains/ft2
b High ADT refers to roads with at least 5,000 vehicles per day.
c For conditions such as post-winter-storm or areas with substantial
mud/dirt carryout.
In the event that sL values are taken from any of the cumulative frequency distribution figures, the
quality ratings for the emission estimates should be downgraded 2 levels.
In the event that default sL values are used the quality ratings for the equation should be
downgraded 2 levels.
As an alternative method of selecting sL values in the absence of site-specific data, users can review
the public (I. e., nonindustrial) paved road sL data base presented in Table 13.2.1-3 and can select values that
are appropriate for the roads and seasons of interest. Table 13.2.1-3 presents paved road surface loading
values together with the city, state, road name, collection date (samples collected from the same road during
the same month are averaged), road ADT if reported, classification of the roadway, etc. Recommendation of
this approach recognizes that end users of AP-42 are capable of identifying roads in the data base that are
similar to roads in the area being inventoried. In the event that sL values are developed in this way, and that
the selection process is fully described, then the quality ratings for the emission estimates should be
downgraded only 1 level.
Limited access roadways pose severe logistical difficulties in terms of surface sampling, and few sL
data are available for such roads. Nevertheless, the available data do not suggest great variation in sL for
limited access roadways from 1 part of the country to another. For annual conditions, a default value of 0^2-
0.015 g/m2 is recommended for limited access roadways.9'22 Even fewer of the available data correspond to
worst-case situations, and elevated loadings are observed to be quickly depleted because of high ADT rates.
A default value of 0?+ 0.2 g/m2 is recommended for short periods of time following application of snow/ice
controls to limited access roads.22
13.2.1.4 Controls6,22 23
Because of the importance of the surface loading, control techniques for paved roads attempt either
to prevent material from being deposited onto the surface (preventive controls) or to remove from the travel
lanes any material that has been deposited (mitigative controls). Regulations requiring the covering of loads
in trucks, or the paving of access areas to unpaved lots or construction sites, are preventive measures.
Examples of mitigative controls include vacuum sweeping, water flushing, and broom sweeping and flushing.
It is particularly important to note that street sweeping of gutters and curb areas may actually increase the silt
loading on the traveled portion of the road. Redistribution of loose material onto the travel lanes will
actually produce a short-term increase in the emissions.
1-21
-------
In general, preventive controls are usually more cost effective than mitigative controls. The cost-
effectiveness of mitigative controls falls off dramatically as the size of an area to be treated increases. The
cost-effectiveness of mitigative measures is also unfavorable if only a short period of time is required for the
road to return to equilibrium silt loading condition. That is to say, the number and length of public roads
within most areas of interest preclude any widespread and routine use of mitigative controls. On the other
hand, because of the more limited scope of roads at an industrial site, mitigative measures may be used quite
successfully (especially in situations where truck spillage occurs). Note, however, that public agencies could
make effective use of mitigative controls to remove sand/salt from roads after the winter ends.
Because available controls will affect the sL, controlled emission factors may be obtained by
substituting controlled silt loading values into the equation. (Emission factors from controlled industrial
roads were used in the development of the equation.) The collection of surface loading samples from treated,
as well as baseline (untreated), roads provides a means to track effectiveness of the controls over time.
References For Section 13.2.1
1. D. R. Dunbar, Resuspension Of Particulate Matter, EPA-450/2-76-031, U. S. Environmental
Protection Agency, Research Triangle Park, NC, March 1976.
2. R. Bohn, et al., Fugitive Emissions From Integrated Iron And Steel Plants, EPA-600/2-78-050, U. S.
Environmental Protection Agency, Cincinnati, OH, March 1978.
3. C. Cowherd, Jr., et al.,Iron And Steel Plant Open Dust Source Fugitive Emission Evaluation,
EPA-600/2-79-103, U. S. Environmental Protection Agency, Cincinnati, OH, May 1979.
4. 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.
5. Size Specific Particulate Emission Factors For Uncontrolled Industrial And Rural Roads, EPA
Contract No. 68-02-3158, Midwest Research Institute, Kansas City, MO, September 1983.
6. T. Cuscino, Jr., et al., Iron And Steel Plant Open Source Fugitive Emission Control Evaluation,
EPA-600/2-83-110, U. S. Environmental Protection Agency, Cincinnati, OH, October 1983.
7. J. P. Reider, Size-specific Particulate Emission Factors For Uncontrolled Industrial And Rural
Roads, EPA Contract 68-02-3158, Midwest Research Institute, Kansas City, MO, September 1983.
8. C. Cowherd, Jr., and P. J. Englehart, Paved Road Particulate Emissions, EPA-600/7-84-077, U. S.
Environmental Protection Agency, Cincinnati, OH, July 1984.
9. C. Cowherd, Jr., and P. J. Englehart, Size Specific Particulate Emission Factors For Industrial And
Rural Roads, EPA-600/7-85-038, U. S. Environmental Protection Agency, Cincinnati, OH, September
1985.
10. Emission Factor Documentation For AP-42, Sections 11.2.5 and 11.2.6 Paved Roads, EPA
Contract No. 68-D0-0123, Midwest Research Institute, Kansas City, MO, March 1993.
11. Evaluation Of Open Dust Sources In The Vicinity Of Buffalo, New York, EPA Contract
No. 68-02-2545, Midwest Research Institute, Kansas City, MO, March 1979.
1-22
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12. PM-10 Emission Inventory Of Landfills In The Lake Calumet Area, EPA Contract No. 68-02-3891,
Midwest Research Institute, Kansas City, MO, September 1987.
13. Chicago Area Particulate Matter Emission Inventory Sampling And Analysis, Contract
No. 68-02-4395, Midwest Research Institute, Kansas City, MO, May 1988.
14. Montana Street Sampling Data, Montana Department Of Health And Environmental Sciences,
Helena, MT, July 1992.
15. Street Sanding Emissions And Control Study, PEI Associates, Inc., Cincinnati, OH, October 1989.
16. Evaluation Of PM-10 Emission Factors For Paved Streets, Harding Lawson Associates, Denver, CO,
October 1991.
17. Street Sanding Emissions And Control Study, RTP Environmental Associates, Inc., Denver, CO, July
1990.
18. Post-storm Measurement Results Salt Lake County Road Dust Silt Loading Winter 1991/92
Measurement Program, Aerovironment, Inc., Monrovia, CA, June 1992.
19. Written communication from Harold Glasser, Department of Health, Clark County (NV).
20. PM-10 Emissions Inventory Data For The Maricopa And Pima Planning Areas, EPA Contract No.
68-02-3888, Engineering-Science, Pasadena, CA, January 1987.
21. Characterization OfPM-10 Emissions From Antiskid Materials Applied To Ice- And Snow-covered
Roadways, EPA Contract No. 68-D0-0137, Midwest Research Institute, Kansas City, MO, October
1992.
22. Fugitive Particulate Matter Emissions, EPA Contract No. 68-D2-0159, Work Assignment No. 4-06,
Midwest Research Institute, Kansas City, MO, April 1997.
23. C. Cowherd, Jr., et al., Control Of Open Fugitive Dust Sources, EPA-450/3-88-008,
U. S. Environmental Protection Agency, Research Triangle Park, NC, September 1988.
24. Written communication from G. Muleski, Midwest Research Institute, Kansas City, MO, to R. Myers,
U. S. Environmental Protection Agency, Research Triangle Park, NC, September 30, 1997.
1-23
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2.0 PROPOSED AP-42 SECTION 13.2.1
The proposed AP-42 Section for paved roads is presented on the following pages as it would appear in
the document.
2-1
-------
13.2.1 Paved Roads
13.2.1.1 General
Particulate emissions occur whenever vehicles travel over a paved surface, such as a road or parking
lot. Particulate emissions from paved roads are due to direct exhaust from vehicles and resuspension of loose
material on the road surface. In general terms, particulate emissions from paved roads originate from the
loose material present on the surface. In turn, that surface loading, as it is moved or removed, is continuously
replenished by other sources. At industrial sites, surface loading is replenished by spillage of material and
trackout from unpaved roads and staging areas. Figure 13.2.1-1 illustrates several transfer processes
occurring on public streets.
Various field studies have found that public streets and highways, as well as roadways at industrial
facilities, can be major sources of the atmospheric particulate matter within an area.1-9 Of particular interest
in many parts of the United States are the increased levels of emissions from public paved roads when the
equilibrium between deposition and removal processes is upset. This situation can occur for various reasons,
including application of snow and ice controls, carryout from construction activities in the area, and wind
and/or water erosion from surrounding unstabilized areas. In the absence of continuous addition of fresh
material (through localized trackout or application of antiskid material), paved road surface loading should
reach equilibrium values in which the amount of material resuspended matches the amount replenished. The
equilibrium sL value depends upon numerous factors. It is believed that the most important factors are:
mean speed of vehicles traveling the road; the average daily traffic (ADT); the number of lanes and ADT per
lane; the fraction of heavy vehicles (buses and trucks); and the presence/absence of curbs, storm sewers and
parking lanes.
13.2.1.2 Emissions And Correction Parameters
Dust emissions from paved roads have been found to vary with what is termed the "silt loading"
present on the road surface as well as the average weight of vehicles traveling the road. The term silt loading
(sL) refers to the mass of silt-size material (equal to or less than 75 micrometers [pm] in physical diameter)
per unit area of the travel surface.4"5 The total road surface dust loading is that of loose material that can be
collected by broom sweeping and vacuuming of the traveled portion of the paved road. The silt fraction is
determined by measuring the proportion of the loose dry surface dust that passes through a 200-mesh screen,
using the ASTM-C-136 method. Silt loading is the product of the silt fraction and the total loading, and is
abbreviated "sL". Additional details on the sampling and analysis of such material are provided in AP-42
Appendices C. 1 and C.2.
The surface sL provides a reasonable means of characterizing seasonal variability in a paved road
emission inventory.9 In many areas of the country, road surface loadings are heaviest during the late winter
and early spring months when the residual loading from snow/ice controls is greatest. As noted earlier, once
replenishment of fresh material is eliminated, the road surface loading can be expected to reach an
equilibrium value, which is substantially lower than the late winter/early spring value.
Miscellaneous Sources
13.2.1-1
-------
13.2.1.3 Predictive Emission Factor Equations10
The quantity of dust emissions from vehicle traffic on a paved road may be estimated using the
following empirical expression:
E=k (sL/2)0-65 (W/3 )1-5 (1)
where:
E = particulate emission factor (having units matching the units of k)
k = base emission factor for particle size range and units of interest (see below)
sL = road surface silt loading (grams per square meter) (g/m2)
W = average weight (tons) of the vehicles traveling the road
It is important to note that Equation 1 calls for the average weight of all vehicles traveling the road.
For example, if 99 percent of traffic on the road are 2 Mg cars/trucks while the remaining 1 percent consists
of 20 Mg trucks, then the mean weight "W" is 2.2 Mg. More specifically, Equation 1 is not intended to be
used to calculate a separate emission factor for each vehicle weight class. Instead, only one emission factor
should be calculated to represent the "fleet" average weight of all vehicles traveling the road.
The particle size multiplier (k) above varies with aerodynamic size range as shown in Table 13.2.1-1.
To determine particulate emissions for a specific particle size range, use the appropriate value of k shown in
Table 13.2.1-1.
Table 13.2-1.1. PARTICLE SIZE MULTIPLIERS FOR PAVED ROAD EQUATION
Size rangea
Multiplier kb
g/VKT
g/VMT
lb/VMT
PM-2.5C
1.1
1.8
0.0040
PM-10
4.6
7.3
0.016
PM-15
5.5
9.0
0.020
PM-30d
24
38
0.082
a Refers to airborne particulate matter (PM-x) with an aerodynamic diameter equal to or less than
x micrometers.
b Units shown are grams per vehicle kilometer traveled (g/VKT), grams per vehicle mile traveled (g/VMT),
and pounds per vehicle mile traveled (lb/VMT). The muliplier k includes unit conversions to produce
emission factors in the units shown for the indicated size range from the mixed units required in Equation
1.
c Ratio of PM-2.5 to PM-10 taken from Reference 22.
d PM-30 is sometimes termed "suspendable particulate" (SP) and is often used as a surrogate for TSP.
The above equation is based on a regression analysis of numerous emission tests, including 65 tests for
PM-10.10 Sources tested include public paved roads, as well as controlled and uncontrolled industrial paved
roads. No tests of "stop-and-go" traffic were available for inclusion in the data base. The equations retain
the quality rating of A (B for PM-2.5), if applied within the range of source conditions that were tested in
developing the equation as follows:
13.2.1-2
EMISSION FACTORS
-------
Silt loading: 0.02 - 400 g/m2
0.03 - 570 grains/square foot (ft2)
Mean vehicle weight: 1.8-38 megagrams (Mg)
2.0 - 42 tons
Mean vehicle speed: 16-88 kilometers per hour (kph)
10 - 55 miles per hour (mph)
To retain the quality rating for the emission factor equation when it is applied to a specific paved
road, it is necessary that reliable correction parameter values for the specific road in question be determined.
With the exception of limited access roadways, which are difficult to sample, the collection and use of site-
specific sL data for public paved road emission inventories are strongly recommended. The field and
laboratory procedures for determining surface material silt content and surface dust loading are summarized
in Appendices C. 1 and C.2. In the event that site-specific values cannot be obtained, an appropriate value for
an industrial road may be selected from the mean values given in Table 13.2.1-2, but the quality rating of the
equation should be reduced by 1 level. Also, recall that Equation 1 refers to emissions due to freely flowing
(not stop-and-go) traffic.
During the preparation of the background document (Reference 10), public road silt loading values
from 1992 and earlier were assembled into a data base. This data base is available as .
Although hundreds of public paved road sL measurements had been collected, there was no uniformity in
sampling equipment and analysis techniques, in roadway classification schemes, and in the types of data
reported. Not surprisingly, the data set did not yield a coherent relationship between sL and road class,
average daily traffic (ADT), etc., even though an inverse relationship between sL and ADT has been found
for a subclass of curbed paved roads in urban areas. Further complicating the analysis is the fact that, in
many parts of the country, paved road sL varies greatly over the course of the year, probably because of
cyclic variations in mud/dirt carryout and in use of anti-skid materials. Although there were strong reasons to
suspect that the assembled data base was skewed towards high values, independent data were not available to
confirm the suspicions.
Since the time that the background document was prepared, new field sampling programs have
shown that the assembled sL data set is biased high for "normal" situations. Just as importantly, however,
the newer programs confirm that substantially higher than "normal" silt loadings can occur on public paved
roads. As a result, two sets of default values are provided in Table 13.2.1-2, one for "normal" conditions and
another for worst-case conditions (such as after winter storm seasons or in areas with substantial mud/dirt
trackout). The newer sL data base is available as .
Table 13.2.1-2 (Metric Units). RECOMMENDED DEFAULT SILT LOADING (g/m2)
VALUES FOR PUBLIC PAVED ROADSa
High ADT roadsb
Low ADT roads
Normal conditions
Worst-case conditions0
0.1
0.5
0.4
3
a Excluding limited access roads. See discussion in text. 1 g/m2 is equal to 1.43
grains/ft2
b High ADT refers to roads with at least 5,000 vehicles per day.
c For conditions such as post-winter-storm or areas with substantial mud/dirt
carryout.
Miscellaneous Sources
13.2.1-3
-------
The range of sL values in the data base for normal conditions is 0.01 to 1.0 for high-ADT roads and
0.054 to 6.8 for low-ADT roads. Consequently the use of a default value from Table 13.2.1-2 should be
expected to yield only an order-of-magnitude estimate of the emission factor. Public paved road silt loadings
are dependent upon: traffic characteristics (speed, ADT, and fraction of heavy vehicles); road characteristics
(curbs, number of lanes, parking lanes); local land use (agriculture, new residential construction) and
regional/seasonal factors (snow/ice controls, wind blown dust). As a result, the collection and use of site-
specific silt loading data is highly recommended. In the event that default sL values are used, the quality
ratings for the equation should be downgraded 2 levels.
Limited access roadways pose severe logistical difficulties in terms of surface sampling, and few sL
data are available for such roads. Nevertheless, the available data do not suggest great variation in sL for
limited access roadways from 1 part of the country to another. For annual conditions, a default value of
0.015.g/m2 is recommended for limited access roadways.9'22 Even fewer of the available data correspond to
worst-case situations, and elevated loadings are observed to be quickly depleted because of high ADT rates.
A default value of 0.2 g/m2 is recommended for short periods of time following application of snow/ice
controls to limited access roads 22
13.2.1.4 Controls6'23
Because of the importance of the surface loading, control techniques for paved roads attempt either
to prevent material from being deposited onto the surface (preventive controls) or to remove from the travel
lanes any material that has been deposited (mitigative controls). Regulations requiring the covering of loads
in trucks, or the paving of access areas to unpaved lots or construction sites, are preventive measures.
Examples of mitigative controls include vacuum sweeping, water flushing, and broom sweeping and flushing.
It is particularly important to note that street sweeping of gutters and curb areas may actually increase the silt
loading on the traveled portion of the road. Redistribution of loose material onto the travel lanes will
actually produce a short-term increase in the emissions.
In general, preventive controls are usually more cost effective than mitigative controls. The cost-
effectiveness of mitigative controls falls off dramatically as the size of an area to be treated increases. The
cost-effectiveness of mitigative measures is also unfavorable if only a short period of time is required for the
road to return to equilibrium silt loading condition. That is to say, the number and length of public roads
within most areas of interest preclude any widespread and routine use of mitigative controls. On the other
hand, because of the more limited scope of roads at an industrial site, mitigative measures may be used quite
successfully (especially in situations where truck spillage occurs). Note, however, that public agencies could
make effective use of mitigative controls to remove sand/salt from roads after the winter ends.
Because available controls will affect the sL, controlled emission factors may be obtained by
substituting controlled silt loading values into the equation. (Emission factors from controlled industrial
roads were used in the development of the equation.) The collection of surface loading samples from treated,
as well as baseline (untreated), roads provides a means to track effectiveness of the controls over time.
References For Section 13.2.1
1. D. R. Dunbar, Resuspension Of Particulate Matter, EPA-450/2-76-031, U. S. Environmental
Protection Agency, Research Triangle Park, NC, March 1976.
2. R. Bohn, et al., Fugitive Emissions From Integrated Iron And Steel Plants, EPA-600/2-78-050, U. S.
Environmental Protection Agency, Cincinnati, OH, March 1978.
13.2.1-4
EMISSION FACTORS
-------
3. C. Cowherd, Jr., et al.,Iron And Steel Plant Open Dust Source Fugitive Emission Evaluation,
EPA-600/2-79-103, U. S. Environmental Protection Agency, Cincinnati, OH, May 1979.
4. 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.
5. Size Specific Particulate Emission Factors For Uncontrolled Industrial And Rural Roads, EPA
Contract No. 68-02-3158, Midwest Research Institute, Kansas City, MO, September 1983.
6. T. Cuscino, Jr., et al., Iron And Steel Plant Open Source Fugitive Emission Control Evaluation,
EPA-600/2-83-110, U. S. Environmental Protection Agency, Cincinnati, OH, October 1983.
7. J. P. Reider, Size-specific Particulate Emission Factors For Uncontrolled Industrial And Rural
Roads, EPA Contract 68-02-3158, Midwest Research Institute, Kansas City, MO, September 1983.
8. C. Cowherd, Jr., and P. J. Englehart, Paved Road Particulate Emissions, EPA-600/7-84-077, U. S.
Environmental Protection Agency, Cincinnati, OH, July 1984.
9. C. Cowherd, Jr., and P. J. Englehart, Size Specific Particulate Emission Factors For Industrial And
Rural Roads, EPA-600/7-85-038, U. S. Environmental Protection Agency, Cincinnati, OH, September
1985.
10. Emission Factor Documentation For AP-42, Sections 11.2.5 and 11.2.6 Paved Roads, EPA
Contract No. 68-D0-0123, Midwest Research Institute, Kansas City, MO, March 1993.
11. Evaluation Of Open Dust Sources In The Vicinity Of Buffalo, New York, EPA Contract
No. 68-02-2545, Midwest Research Institute, Kansas City, MO, March 1979.
12. PM-10 Emission Inventory Of Landfills In The Lake Calumet Area, EPA Contract No. 68-02-3891,
Midwest Research Institute, Kansas City, MO, September 1987.
13. Chicago Area Particulate Matter Emission Inventory Sampling And Analysis, Contract
No. 68-02-4395, Midwest Research Institute, Kansas City, MO, May 1988.
14. Montana Street Sampling Data, Montana Department Of Health And Environmental Sciences, Helena,
MT, July 1992.
15. Street Sanding Emissions And Control Study, PEI Associates, Inc., Cincinnati, OH, October 1989.
16. Evaluation Of PM-10 Emission Factors For Paved Streets, Harding Lawson Associates, Denver, CO,
October 1991.
17. Street Sanding Emissions And Control Study, RTP Environmental Associates, Inc., Denver, CO, July
1990.
18. Post-storm Measurement Results Salt Lake County Road Dust Silt Loading Winter 1991/92
Measurement Program, Aerovironment, Inc., Monrovia, CA, June 1992.
19. Written communication from Harold Glasser, Department of Health, Clark County (NV).
Miscellaneous Sources
13.2.1-5
-------
20. PM-10 Emissions Inventory Data For The Maricopa And Pima Planning Areas, EPA Contract No.
68-02-3888, Engineering-Science, Pasadena, CA, January 1987.
21. Characterization OfPM-10 Emissions From Antiskid Materials Applied To Ice- And Snow-Covered
Roadways, EPA Contract No. 68-D0-0137, Midwest Research Institute, Kansas City, MO, October
1992.
22. Fugitive Particulate Matter Emissions, EPA Contract No. 68-D2-0159, Work Assignment No. 4-06,
Midwest Research Institute, Kansas City, MO, April 1997.
23. C. Cowherd, Jr., et al., Control Of Open Fugitive Dust Sources, EPA-450/3-88-008,
U. S. Environmental Protection Agency, Research Triangle Park, NC, September 1988.
24. Written communication from G. Muleski, Midwest Research Institute, Kansas City, MO, to R. Myers,
U. S. Environmental Protection Agency, Research Triangle Park, NC, September 30, 1997.
13.2.1-6
EMISSION FACTORS
-------
Attachment 1
Comment/Response Log for March 8,1993,
Paved Road Background Document
-------
RESPONSE TO COMMENTS MADE IN ATTACHMENTS TO WILLIAM R. BARNARD LETTER OF MAY 12, 1993
PAVED ROADS
COMMENT
RESPONSE
1. Page 2-2, 1st paragraph, sentence that starts "In addition..." change from
"can be often heavily loaded" to "can often be..."
Page 2-2, In definitions of equation 2-1, change "s=surface material content
silt" to read "surface material silt content"
Page 2-4, 1st paragraph at the top, sentence that begins "The industrial road
augmentation factor..." change "was included to take into account for..." to
"was included to account for..."
1 These all address typographical errors or recommended wording changes to the background
document. Changes will be made in any revision to the background document.
2. Although I know that you are simply "quoting" AP-42, it is very
confusing to the reader that in equation 2-1, s = surface material silt
content and L = surface material loading, but in equation 2-3, sL = road
surface silt loading and has the same units as L alone in equation 2-1.
2. MRI agrees that the use of "sL" and the combination of "s" and "L" can prove confusing.
Because the revised AP-42 section will replace all three paved road equations currently
contained in Sections 11.2.5 and 11.2.6, "sL" will be used in only one sense thus eliminating any
confusion.
3. I would suggest moving most of section 3 forward (to become section 2)
and would place section 2 as the new section 3. It would seem more
logical to have a general description of the ratings system prior to
summarizing the existing information, including the current ratings for
current AP-42 emission factors. I also think that sections 3.0 and 3.1
would be better "tagged" onto the end of section 2 and the remaining
current section 3 moved to section 2 as indicated above.
3. MRI will consider the merit of reorganizing the background document prior to any revision to
the report.
4. In the discussion on page 2-6, the indication is that the reformulated
emission factor will include data using controls. Although a rationale is
given for this, I strongly question the wisdom of this approach. If
controlled and uncontrolled information is used to generate the emission
factor, then it becomes extremely difficult to perform any control strategy
analyses for SIP purposes using an emission factor that may already
incorporate some level of control. There is virtually no data on how
much the various control options for paved roads reduce silt content
(which is the information needed with the new approach), while there is
limited data on overall control efficiency. Although I know that most of
the control approaches are aimed at reducing the silt loading, what
happens if you are wrong and the silt loading is not really the controlling
factor for paved road emissions?
4. MRI firmly believes that the approach employed in the background document is "best" in the
sense that the approach
• addresses confusion that may result from having two or more different paved road models might
be used to estimate emissions in various size ranges from roads at a single facility, municipality,
etc.
• recognizes the very dynamic nature of silt loading in that emissions are reduced substantially
(i.e., "controlled") through rainfall. To a very real extent, a truly "uncontrolled" paved road
would have to be completely sheltered from the direct rain and water runoff.
• provides the regulatory and regulated communities a cost-effective means (through relatively
inexpensive surface sampling) to evaluate seasonal variations in emissions and the efficiency of
control programs
• recognizes that there is a far larger data base in which efficiency is tied to reduction in silt loading
rather than reduction in the emission factor
With reference to the potential for mistaking the importance of silt loading, please see discussion on
page 4-20. As stated there, the most notable features about the correlation matrix are the high degree
of interdependence between (i) emisison factor; (ii) speed: and (iii) silt loading; and, the low degree of
interdependence between (a) silt loading and weight and (b) weight and speed. The selection of
combination (a) over combination (b) is explained at the bottom of page 4-20.
-------
RESPONSE TO COMMENTS MADE IN ATTACHMENTS TO WILLIAM R. BARNARD LETTER OF MAY 12, 1993
PAVED ROADS (continued)
>
i
to
COMMENT
RESPONSE
5. I think another criteria should be added to all reviews and AP-42 chapter
development efforts. All primary source reports should contain sufficient
information and data so that all data reduction procedures and/or
calculations can be verified. Frequently, even when information has been
given in fugitive emission factor development reports, the data cannot be
used to give reproducible results using the data reduction/calculation
methods presented.
Section 2, page 2-6 next to last paragraph indicates that previous test data were
included in the reexamination and that no distinction was made between public
and industrial roads or controlled/uncontrolled tests. However, on page 3-2,
the top paragraph indicates that "earlier controlled industrial road test data were
reexamined in addition to new data." Which is it? In section 4, it looks like all
data were reviewed. Be consistent.
5. Please see the discussion in response 6 regarding independent calculation of exposure profiling
test results.
MRI does not see the two statements as contradictory; however, there may be some confusion about
the meaning of terms such as "reexamined" or "reviewed". The background document does not make
any hard and fast distinctions between terms such as "considered," "(re)examined," or "reviewed."
Simply put, data are first examined — or equivalently, "reviewed" or "considered" — to decide from
which data emission factors will be developed. New data (from test reports I, II and III) were
examined. In addition, MRI reconsidered field test results that had been available during the earlier
updates of this section (in 1983 and, to a lesser extent, 1987) but not used (because of the "controlled"
nature of the surface) to develop an emission factor. The reasons for including the controlled tests in
the current update are described in the background document and in the previous response.
6. Page 3-2, item #2 in the section 3-2 list. What do EPA method 5 front-
half and back-half have to do with fugitives? A better example of
incompatible methods should be found.
A great deal of the discussion on upwind-downwind tends to deal with
drawbacks to using this method. However, it can be utilized with standardized,
wind tunnel certified sampling devices and really requires little more
meteorological data than exposure profiling (wind speed and direction vs. wind
speed). Equal time should be devoted towards drawbacks/uncertainties
associated with exposure profiling.
For instance, the samplers used for exposure profiling have never been wind
tunnel certified for size cutpoints to the best of my knowledge (i.e., never
published). Also, I have never been able to successfully duplicate the "spatial
integration of measurements" even when data and example calculations have
been provided.
In the case of PM-10, how can you truly estimate the visual extent of the
plume to insure that at least 90% is captured? I believe that visually estimating
the extent of 10 micron particles (mainly invisible) would be extremely
difficult.
Finally, the discussion of exposure profiling should discuss the relative error (as
was done for upwind-downwind).
The overall tone of the discussion tends to sound "heavy-handed" and biased
towards the method that MRI developed rather than an objective presentation
of the two methodologies which is what an objective review should do.
6. This text is drawn verbatim from the EPA guideline document for development of AP-42
sections. MRI will revise this passage to better reflect the particulars involved with paved road
testing procedures in any new version of the background document.
It is iniDortant to recall that exoosure orofilins reoresents a samolins aooroach rather than anv soecific
type of sampler. In other words, "standardized, wind tunnel certified samplers" can (and have been)
used in exposure profiling programs. The reviewer is quite right in stating that upwind/downwind
(UW/DW) approach requires little more meteorlolgical data than exposure profiling. As a matter of
fact, MRI requires that wind direction be monitored throughout any exposure profiling test.
The important distinction to be drawn between the UW/DW and the exposure profiling methods
involves how data are used to characterize the source. The background document discusses basic
limitations of using uncalibrated dispersion models to estimate emission strength. Beyond the
relatively simple discussion presented in the background document, UW/DW suffers other
fundamental limitations. For example, traffic on many roads is too low to pose a steady, uniformly
emitting line source as required in dispersion models. A better representation would view the source
as a series of discrete moving point source.
Even assuming the source is reasonably steady in nature, the modeled line source/wind geometry does
not necessarily properly account for dispersion from the moving point sources. As the plume is
released, dispersion occurs in all three cartestian coordinate directions. Only dispersion in the
direction parallel to the plume centerline would be negligible. Depending on the direction a vehicle is
traveling, an oblique wind would appear to "dilute" or "concentrate" the plume as seen by the
UW/DW samplers. Correction for each plume depends upon the magnitude and direction of the wind
relative to vehicle velocity vector. In other words, if two vehicles passed in opposite directions at the
same time, one plume would be concentrated and the other diluted.
Because the exposure profiling approach focuses on the mass flux through a plane, concentration/
dilution issues are not a concern. As noted earlier, standardized samplers can be and have been readily
used in the exposure profiling arrays. Because of the interest in total particulate and size-specific
factors, MRI has traditionally used directional samplers operated isokinetically, together with
aerodynamic particle sizing instruments. (In addition to manufacturer tests for the cascade impactors,
the cyclone preseparator has been wind tunnel tested. Results are reported in Baxter et al 1986.)
The Southern Research Institute (SoRI) collaborative study (Pyle and McClain 1986) examined many
issues associated with exposure profiling. The authors duplicated MRI's and four other organization's
calculations from 11 test runs on a "simulated" unpaved road. In addition, SoRI investigated potential
errors associated with isokinetic tracking, different particle sizing approaches, maximum sampling
height, spatial integration schemes, etc.
-------
RESPONSE TO COMMENTS MADE IN ATTACHMENTS TO WILLIAM R. BARNARD LETTER OF MAY 12, 1993
PAVED ROADS (continued)
COMMENT
RESPONSE
7. Page 3-9, next to last sentence says, "sin specific source parameters"
should say "in specific source parameters"
Page 3-11, top of page "virtual point source missions" should be "virtual point
source emissions"
7. These changes will be made to any subsequent version of the background document.
8. On page 3-11, one of the criteria used for evaluating emission factor data
is "industry representativeness." Why are we concerned about industry
representativeness as a criteria in developing a new emission factor when
the new emission factor is to be reflective of emissions from any paved
road, regardless of whether industrial or public?
8. As stated above, this text is drawn verbatim from the EPA guideline document. The passage will
be revised in any subsequent version of the background document.
9. Page 4-7, 1st full paragraph indicates that the Test Report I does not fully
meet the minimum requirements for upwind-downwind sampling (i.e., a
minimum of 4 samplers).
The description of the sampling set-up says that even when 6 samplers were
used they were set up identically with one at 20 m and a pair at 5 m on each
side of the road. This means 3 samplers on upwind side at 2 distances and 3
on downwind at 2 distances. On page 3-10, next to last paragraph, the
minimum test requirements for upwind-downwind are stated as 1 device
upwind (satisfied here by 3 at 2 distances) and the others at 2 downwind
(satisfied here by the 5 m and 20 m distances) and 3 crosswind. The
requirement for crosswind distances is waived for line sources. A paved road
is a line source, thus this report does meet the minimum requirements for
sampling and should be included in the analysis.
9. MRI mistakenly stated in the background document that "neither" sampling configuration met
minimum reauirements. Onlv the second confieuration (described on oase 4-4) failed to meet
minimum requirements because the sources tested were not truly line sources. Instead, the
halves of each road segment were considered separately. Test Report I did not explain how far
samplers were separated from the end of segments nor did it describe any attempt to prevent
tracking of material from one segment to another. (See, for example, Figure 2-3 of Test Report
I.) Thirty-two of the 69 emission tests used the second configuration.
10 In the discussion of Test Report II, the text indicates that only 1 particle
size device is used to determine a PM-10 emission factor. Are the
investigators really sure that there is no variability in the distribution of
the PM-10 concentration (flux) with height? Unpaved road studies
performed as part of NAPAP indicate otherwise.
10. Test Report II's use of single height for particle sizing measurements resulted from the limited
number of devices available. MRI has found in numerous past studies and one would certainly
expect the PM-10 fraction to increase with height in the plume. To at least partially account for
this, the single height was selected to approximate the height in a dust plum at which half the
mass emissions pass above and half below.
11. Figure 4-3 is really a table.
11. MRI called this a "figure" because it is a photocopy of two different outputs from a computer
program. No change is planned.
12. Table 4-5, the multiple R2 for PM-15 = .765, but "Figure" 4-3 indicates it
should be .772.
12. To ensure that the different size fractions had functional forms similar to that for PM-10, all final
models were "forced" to have the same exponents for silt loading and weight. Thus, the to-
transformed emission factors were regressed against the term
0.65 to sL + 1.5 to W
with the line-of-fit forced to pass through the origin to determine the final form. The lower R2 results
from the fact that the final factor is not "best" in an independent least-squares sense.
-------
RESPONSE TO COMMENTS MADE IN ATTACHMENTS TO WILLIAM R. BARNARD LETTER OF MAY 12, 1993
PAVED ROADS (continued)
COMMENT
RESPONSE
13. Based upon the discussion above concerning inclusion of Test Report I
and due to the fact that it was considered good enough for validation,
what would the emission factor equation look like if that data was
included?
13. Inclusion of the Test Report I data could be expected to lower the exponent for "sL" for the PM-
10 equation from 0.65 to approximately 0.5. At a summer 1992 meeting with the commentor,
Chuck Masser, Tom Pace, and Robin Dunkins, we discussed how, the discussion in Zimmer
1991 notwithstanding, Test Report I emission rates exhibited a strong dependence on silt
loading. (Figure 4-2 of the background document clearly shows this.) It is also important to
recall that primary reason for not including Test Report I data was that only PM-10 factors were
available.
14. On page 4-23, the validation results indicate that at least 50% of the data
are outside the factor of 3 range. Does this mean that the factor of 2 used
for rating (see Table 3-1) is unrealistic for rating emission factors and that
a more appropriate lower end would be 3 rather than 2?
14. Page 4-23 states that "a little over half' of the quasi-independent values are within a factor of 3.
This certainly does not indicate that "at least 50% ... are outside" that range. A rough scaling of
Figure 4-4 on page suggests that approximately 57% ~ 60% are within a factor of 3.
Table 3-1 pertains to single-valued emission factors. The quality ratings for predictive equations are
assigned following the scheme presented in Table 3-2.
15. Why is the equation on the first page of the proposed new section 11,2.x
different from the new one derived in the report (equation on page 4-22).
Specifically, why is sL divided by 2 and W by 3? Why doesn't the
equation on page 4-22 have an equation number as earlier equations did?
15. The backsround document discusses a "workine" form for the model. Bv that is meant all
emission factors are measured in g/VMT, all silt loadings are in g/m , and so on. For example,
in order to be exactly precise, one must either
• consider silt loading and weight "nondimensionalized" by implicit division by 1 g/m2 and 1 ton
respectively
or
g • m13 _ g035 • m13
g065 • tons15 • veh-mile tons15 • veh-mile
The working versions of models are used to establish properties of candidate emission factors. On the
other hand, once a factor has been selected, the AP-42 section must present a final product. In the
AP-42, sections, nondimensionalization occurs through the explicit division by the "default" values of
2 g/m and 3 tons. Furthermore, k is expressed in a variety of compatible units.
One can readily verify that all working and final expressions result in the same emission factor for the
same input values.
An equation number will be added on page 4-22 in any subsequent version of the background
document.
References
Baxter, T. E. et al. 1986. "Calibration of Cyclone for Monitoring Inhalable Particles," Journal of Environmental Engineering. 112, 3, pp. 468-478.
Pyle, B. E. and J. D. McCain 1986. Critical Review of Open Source Particulate Emission Measurements ~ Part II: Field Comparison. Work
Assignment 002, EPA Contract 68-02-3936. February 1986.
Zimmer, R. A. 1991."Evaluation of PM10 Emission Factors for Paved Streets." Harding Lawson and Associates report for the Regional Air
Quality Council (Denver). October 1991.
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RESPONSE TO COMMENTS MADE IN ATTACHMENTS TO WILLIAM R. BARNARD LETTER OF MAY 12, 1993
CONSTRUCTION ACTIVITIES
COMMENT
RESPONSE
Specific comments
1. On page v, there is a superscript 8 in the Section 3.3
line of the Table of Contents.
On page vi, there is a superscript in #2-3 line of Tables list
1. These all address typographical errors or recommended wording changes to the background document. These
changes will be made in any subsequent version of the background document.
2. As with the Paved Roads document, I'd probably flip-
flop Sections 2 and 3, although the reason for switching
them is less compelling in this document, since there
are few if any references to the previous AP-42
emission factor quality rating.
2. MRI will consider the merit of reorganizing the background document prior to any revision to the report.
Comments on Section 2
3. Page 2-1 In the discussion of the number of
construction industries, you list 2.0 million, instead of 2
million. The decimal point implies some level of
significant figures. Is that level really there?
3. Reference 1 in the background document should not be the Statistical Abstract but rather the 1987 Census of
Construction Industries. This will be corrected in any revision. The 1987 Census uses the expression "nearly 2.0
million construction establishments." Any subsequent version of the background document will incorporate that
phrasing.
4. Unless total value of business done is the way that
Statistical Abstract describes the information presented
on page 2-1 and 2-2, I'd say total revenue.
4. The Statistical Abstract reports "value of construction [contract]." The Census of Construction Industries uses the
term "value of construction work." Subsequent version of the background document will use "value of
construction work."
5. Page 2-5 "unpaved travel rates"? - middle of last
paragraph
5. This is a typographical error and should read "travel routes." The change will be made in a subsequent revision to
the background document.
Comments on Section 3
6. I think another criteria should be added to all reviews
and AP-42 chapter development efforts. All primary
source reports should contain sufficient information and
data so that all data reduction procedures and/or
calculations can be verified. Frequently, even when
information has been given in fugitive emission factor
development reports, the data cannot be used to give
reproducible results using the data reduction/calculation
methods presented.
6. Please see response 6 in the paved road comment log regarding independent calculation of exposure profiling test
results.
7. Page 3-1 near the bottom. The 1987 Censu s of
Construction Industries, United States Summary is
listed as reference 1, however, reference 1 is the
Statistical Abstract of the U.S. for 1992.
7. As noted in response 3, Reference 1 should read
U.S. Department of Commerce, Bureau of the Census. "1987 Census of Construction Industries." Geographic
Area Series, CC87-A-10. Washington, D. C. October 1990.
8. Page 3-6, change "unless the plume can be draw..." to
"unless the plume can be drawn"
Page 3-9, next to last sentence change "when characterize
source conditions" to "which characterize source conditions"
8. These changes will be made in any subsequent version of the background document.
-------
RESPONSE TO COMMENTS MADE IN ATTACHMENTS TO WILLIAM R. BARNARD LETTER OF MAY 12, 1993
CONSTRUCTION ACTIVITIES (continued)
COMMENT
RESPONSE
Comments on Section 4
9. All discussions of reviewed emission factors should
clearly delineate whether the emission factor being
discussed is for TSP or PM-10.
Page 4-5, last paragraph, says that upwind-downwind
sampling was used to determine TSP emission factors in
Table 4-2, but the table caption says they are PM-10 emission
factors.
9. The background document will be reviewed to identify points where PM10/TSP could be confused.
The entries are in fact PM-10 emission factors based on Referernce 12's reanalysis of TSP emission factors contained in
Test Report III. Statements will be corrected in any subsequent version of the background document.
10. Page 4-6, last sentence of first paragraph, says that a
minimum of 4 samplers are required but on Page 3-11
the minimum number is specified as 5.
10. MRI does not see the two statements as contradictory. Page 3-11 calls for "at least five ... with one device located
upwind." Consequently at least 4 should be deployed downwind. Page 4-6 states that "two samplers ... were used
downwind rather than the minimum of four."
11. Page 4-6, last paragraph before section 4.2.2, either give
it a B or a C rating. Probably deserves a C
11. MRI agrees that "C" is appropriate.
12. In the revised section for AP-42, the discussion
concerning equation 1 indicates that the emission factor
can be used for PM-10, but this is a TSP emission
factor. No discussion is provided to indicate what factor
should be applied to provide PM-10 emission estimates.
12. The intention in the revised AP-42 section is to allow readers to use Equation (1) to not only estimate TSP
emissions but also to conservatively estimate PM-10 emissions. The discussion on oase 11.2.4-2 recosnizes that
this approach may result in too high a PM-10 estimate and recommends estimating emissions on the basis of
component operations.
-------
COMMENTS MADE IN MAY 24, 1992, LETTER FROM DOUGLAS P. COLLINS, IDAHO DEQ PAVED ROADS
COMMENT
RESPONSE
The 90th percentile, as a worst case scenario, appears to overestimate emissions,
especially if used to generate a daily total emission rate. To assume that all streets, on
any day, would be carrying a 90th percentile silt loading seems unlikely.
MRI agrees that it is highly unlikely that all roads in an area will be at the 90th percentile at
once. As noted in the AP-42 section and the comments below, sL values specific to the site
and situation of interest would be preferred.
The temporal scale of January to June, and July to December, does not reflect annual
increase and decrease of silt loadings in Idaho. Increased silt loadings from the
application of anti skid materials starts with the first significant snow fall, usually in
November, and lasts until about April, when many road departments mechanically
remove excess road debris.
During the preparation of the AP-42 Section, MRI considered using different groupings, such
as winter/spring vs. summer/fall or November-through-March vs. April-through-October. The
other grouping schemes all failed to adequately account for differences seen in the sL values;
furthermore, the other schemes called for a subjective decision — such as: When does
"winter" begin at a specific site? — or failed to take into account weather patterns during a
particular sampling year — such as: Was November 1991 particularly snowy or warm?
Because the sL data base was a secondary objective in the program, project resources were
insufficient to devote much effort in resolving weather patterns. Consequently, calendar year
halves were selected to avoid subjective decisions.
Not all counties in Idaho require vehicle weights to be recorded with the title or
registration. Therefore it is a best guess as to what the average vehicle weight might
be. Some guidelines, references, or suggested values, or range of values would be
helpful.
For most public roads with "normal" mixes of cars, trucks and buses, one can probably expect
the average weight not vary outside the range of 2.0 to 2.5 tons.
The preferred method for determining silt loading value is to collect your own
representative samples. Appendices, in the past, have addressed how to take and
analyze the samples, but do not provide a methodology to set up a sampling study. A
methodology that lays out guidelines on the number of sites, number of samples,
precision and accuracy, QA/QC, meterological considerations, and other parameters
needed to conduct an adequate road silt sampling project would be of help. These
guidelines could address both larger studyies for determining specific silt loading
values, an a limited study for trying to narrow down the options presented in using the
50th to 90th percentile used in the revised AP-42.
MRI agrees that some sort of "case study" would be quite useful to the regulatory community.
The current version of Appendix D to AP-42 is necessarily vague on where and how many
samples should be collected and even on the type of equipment to be used in sampling,
because site-specific considerations may affect decisions. A case study that considered
• three different size cities (e.g., Phoenix, Reno, and Pocatello)
and,
• and 2 or 3 levels of effort (for example, a two-month long program for $10,000 versus a
multiyear program for $70,000).
would be of great practical benefit.
Use of the public paved road sL data base (not yet provided) would seem to be a good
intermediate choice between getting site specific data and using the the revised AP-42
values, providing the selection criteria used can adequately reflect the area of interest.
Selection information might include: the amount of anti-skid material used, percent of
silt in anti skid material, average number of applications per season, application
equipment used, application rate, and the size and location of the area where the data
was collected.
At present, the revised paved road section recognizes that end users of AP-42 are the most
capable in selecting roads in the data base that are similar to roads of interest in their
jurisdictions. Although site-specific sL values would be most preferred, MRI believes that the
new approach represents an improvement.
When compared to the current AP-42 section in use, selecting a winter time silt loading
value from the revised section feels more comfortable. The 50th to 90th percentile
range appears to accurately reflect the range of silt loadings that can be found on Idaho
roads, and even though the value range is fairly large, it does let you know when you
are in the ball park.
MRI agrees.
-------
COMMENTS MADE IN MAY 27, 1992, LETTER FROM GARY NEUROTH, ARIZONA DEQ PAVED ROADS
COMMENT
RESPONSE
The "MRI accepted" data base contains little, if any, data for relatively high volume,
high speed roads typically found in urban areas. For example, roads with daily traffic
volumes over 10,000 with speeds over 35 mph.
Figures 1 and 2 compare the speed/silt loading ranges in the AP-42 data base and data from
the PEI Denver study (Test Report I in the background document). As can be seen, the AP-42
data contains slightly more tests within the range of the PEI data.
This is not to say that the current paved road emission factor data base does not suffer from
certain limitations. As MRI has pointed out, the present paved road emission factor models do
not explicitly reference characteristics that are likely to influence emission levels, such as
• Vehicle mix — It is likely that particulate matter emission levels are higher for
roads/areas where diesel and/or poorly maintained older vehicles are prevalent. At
present, however, neither the current Section 11.2.5 or Section 11.2.6 PM10 emission
factor distinguishes between roads with different vehicle mixes. The recommended
revision, on the other hand, at least partially accounts for vehicle mix by the inclusion of
the "weight term." Still, no direct distinction is made for different diesel/gasoline ratios,
etc.
• Vehicle speed — As the comment points out, it is likely that, all other factors being equal,
high ADT roads should have different emission characteristics than low ADT roads.
However, both the AP-42 and the PEI baseline data bases show a very strong
interrelationship between silt loading and vehicle speed. Thus, the effects of high-speed
(and, by inference, high-ADT) are at least partially accounted for by the inclusion of silt
loading as an input parameter. (Also, please see the response to comment 4 in the log for
the letter from Pechan and Associates.
• Traffic flow characteristics — The AP-42 paved road data base and all current or revised
emission factor models apply only to freely flowing traffic; no provision is made for the
presumably higher emissions due to stop-and-go traffic.
As you are probably aware, the Federal Flighway Administration is presentaly funding
research conducted by Desert Research Institute (DRI) to characterize emissions from
paved roads. My staff is currently assisting DRI conducting roadside testing in
Scottsdale, Arizona. In October 1993, our Department plans to conduct roadside
PM1Q sampling at several locations in the Phoenix metro area using a 3-dimensional
sampling array similar to the MRI configuration. I've enclosed a copy of our proposed
study plan, which I believe has two inherent advantages that promise to yield a better
data base than that used to derive the AP-42 emission factors for urban areas: (1)
saqmpling will be conducted on roads selected to represent a majority of the urban
VMT (2) PM10 samples will be collected continuously using Tapedred Element
Oscillating Microbalance (TEOM) samplers which will provide a larger number of data
points with shorter averaging times allowing tighter specification on variables such as
wind and traffic.
In light of the above response, MRI certainly recognizes the need for additional field
investigation. Furthermore, MRI also recognizes the need that, as new information becomes
available, the paved road emission factor should be evaluated in terms of its performance in
estimatin
• evaluated in terms of its oerformance in estimatins indeoendent emissions data
• reformulated, as needed, deoendins uoon the results of the evaluation
-------
Plot of In (Speedl vs. in (Silt Loading)
5
65 mph -
55 mph -
45 mph -
- Range of values in PEI
data base
35 mph -
i n n n n n [ n
I I
I n n nn n 2nn
+ n—n-n—n n
15 mph -
n n 2 n
5 mph -
Pawod re-adl Oaiia Bas© used t
mw Soctolmi 13.2.1
l
LSL
0.02 0.05 0.1 0.2 0.5 1
Figure 1. PLOT OF AVERAGE VEHICLE SPEED vs. SILT LOADING IN THE
AP-42 PAVED ROAD EMISSION FACTOR DATA BASE (Fully logarithmic)
Al-9
-------
Plot of In (Speed) vs. In (Silt Loading)
5
Range of Values in PEI data base
(box repeated in Figure 1)
—+
PEI Denver Data Base
from "Test Report I"
+ n n n +
1
LSL
50 g/ra2
Figure 2. PLOT OF AVERAGE VEHICLE SPEED vs. SILT LOADING IN THE
PEI BASELINE EMISSION FACTOR DATA BASE (Fully logarithmic)
Al-10
-------
Attachment 2.
Public Paved Road Surface Loading
Presented as Appendix X in March 8,1993
Paved Road Background Document
-------
TABLE A2-1. PUBLIC PAVED ROAD SURFAC
LOADING DATA BASE (DETAILED INFORMATION)
STATE
CITY
STREET
CLASS
DATE
ADT
SILT LOADING
(g/m*m)
SILT %
TOTAL LOADING
(g/m*m)
SILT LOADING
SUMMARY
The following data from
Reference 1
MT
Billings
Rural
Apr-78
50
0.6
18.5
3.4
MT
Billings
Yellowstone
Residential
Apr-78
115
0.5
14.3
3.5
MT
Missoula
Bancroft
Residential
Apr-78
4000
8.4
33.9
24.9
MT
Butte
1st St
Residential
Apr-78
679
24.6
10.6
232.4
MT
Butte
N Park PI
Residential
Apr-78
60
103.7
7
1480.8
MT
Billings
Grand Ave
Collector
Apr-78
6453
1.6
19.1
13.05
2 samples, range: 1.0 - 2.2
MT
Billings
4th Ave E
Collector
Apr-78
3328
7.7
7.7
99.5
MT
Missoula
6th St
Collector
Apr-78
3655
26
62.9
6
MT
Butte
Harrison
Arterial
Apr-78
22849
1.9
5
37.3
MT
Missoula
Hiway 93
Arterial
Apr-78
18870
1.9
55.9
3.3
MT
Butte
Montana
Arterial
Apr-78
13529
0.8
6.6
11.9
MT
East Helena
Thurman
Residential
Apr-83
140
13.1
4.3
305.2
MT
East Helena
1st St
Local
Apr-83
780
4
13.6
29
MT
East Helena
Montana
Collector
Apr-83
2700
8.2
9.4
86.6
MT
East Helena
Main St
Collector
Apr-83
1360
4.7
8.4
55.3
MT
Libby
6th
Local
Mar-8 8
1310
14.8
MT
Libby
5th
Local
Mar-8 8
331
16.5
MT
Libby
Champion Int So g
Collector
Mar-8 8
800
27.5
MT
Libby
Mineral Ave
Collector
Mar-8 8
5900
7
16
43.5
MT
Libby
Main Ave btwn 6th
Collector
Mar-8 8
536
61
20.4
299.2
MT
Libby
California
Collector
Mar-8 8
4500
12.1
MT
Libby
US 2
Arterial
Mar-8 8
10850
12.3
MT
Butte
Garfield Ave
Residential
Apr-88
562
2.1
10.9
19.3
MT
Butte
Continental Dr
Arterial
Apr-88
5272
0.9
10.1
8.8
MT
Butte
Garfield Ave
Residential
Jun-89
562
1
8.7
11.2
MT
Butte
So Park Ave
Residential
Jun-89
60
2.8
10.9
25.5
MT
Butte
Continental Dr
Arterial
Jun-89
5272
7.2
3.6
197.6
MT
East Helena
Morton St
Local
Aug-89
250
1.7
6.8
24.6
MT
East Helena
Main St
Collector
Aug-89
2316
0.7
4.1
17
MT
East Helena
US 12
Arterial
Aug-89
7900
2.1
12.5
16.5
MT
Columbia Fall
7th St
Residential
Mar-90
390
9.5
MT
Columbia Fall
4th St
Residential
Mar-90
400
18.8
14.3
131.5
MT
Columbia Fall
3rd Ave
Residential
Mar-90
50
14.3
MT
Columbia Fall
4th Ave
Residential
Mar-90
1720
5.4
-------
TABLE A2-1. (continued)
>
to
I
to
STATE
CITY
STREET
CLASS
DATE
ADT
SILT LOADING
(g/m*m)
SILT %
TOTAL LOADING
(g/m*m)
SILT LOADING
SUMMARY
MT
Columbia Fall
CF Forest
Local
Mar-90
240
16.3
MT
Columbia Fall
12 th Ave
Collector
Mar-90
1510
8.8
MT
Columbia Fall
3rd St
Collector
Mar-90
1945
7
MT
Columbia Fall
Nucleus
Collector
Mar-90
4730
15.4
10
153.9
MT
Columbia Fall
Plum Creek
Collector
Mar-90
316
6.2
MT
Columbia Fall
6th Ave
Collector
Mar-90
1764
4.2
MT
Columbia Fall
US 2
Arterial
Mar-90
13110
2.7
18.7
14.6
MT
East Flelena
Morton
Residential
Jul-90
250
1.6
17
9.3
MT
East Flelena
Main St
Collector
Jul-90
2316
5.6
10.6
52.5
MT
East Flelena
US 12
Arterial
Jul-90
7900
3.2
15.4
20.9
MT
Columbia Fall
4th Ave
Local
Aug-90
400
1.5
4
37.7
MT
Libby
Main Ave 4th &
Collector
Aug-90
530
2.4
17.9
13.2
MT
Columbia Fall
Nucleus
Collector
Aug-90
5730
0.8
5.3
16
MT
Columbia Fall
US 2
Arterial
Aug-90
13039
0.2
7
2.9
MT
East Flelena
Morton
Local
Oct-90
250
3.4
10.2
33.6
MT
East Flelena
Main
Collector
Oct-90
2316
4.5
5.6
81.3
MT
East Flelena
US 12
Arterial
Oct-90
7900
0.6
13.9
4.3
MT
Columbia Fall
Nucleus
Collector
11/6/90
5670
5.2
13.5
38
MT
Columbia Fall
US 2
Arterial
11/6/90
15890
1.7
24.1
7.2
MT
Libby
US 2
Arterial
12/8/90
10000
21.5
9.6
223.9
MT
Libby
Main Ave 4th &
Collector
12/9/90
530
13.6
27.1
50.3
MT
Butte
Texas
Collector
12/13/90
3070
1
15.4
6.4
MT
East Flelena
King
Local
Jan-91
75
1
3.4
30.6
MT
East Flelena
Prickly Pear
Local
Jan-91
425
12
1.8
666.5
MT
East Flelena
Morton
Local
Jan-91
250
14.1
3.5
402.3
MT
East Flelena
Main St
Collector
Jan-91
2316
36.7
12.1
303.4
MT
East Flelena
US 12
Arterial
Jan-91
7900
0.8
14
5.6
MT
Thompson Fall
Preston
Local
1/23/90
920
9.2
9.9
93
MT
Thompson Fall
Highway 200
Collector
1/23/90
5000
33.3
27.2
122.2
MT
East Flelena
Seaver Park Rd
Local
Feb-91
150
21.6
7.1
304.7
MT
East Flelena
New Lake Flelena
D
Collector
Feb-91
2140
19.2
9
213.4
MT
East Flelena
Porter
Collector
Feb-91
850
74.4
7.7
966.8
MT
Libby
Main Ave 4th &
Collector
2/14/91
530
33.3
18.7
178.2
MT
Libby
US 2
Arterial
2/17/91
10000
69.3
21
330.3
MT
Butte
Texas
Collector
2/21/91
3070
1.2
11
10.9
-------
TABLE A2-1. (continued)
>
to
I
OJ
STATE
CITY
STREET
CLASS
DATE
ADT
SILT LOADING
(g/m*m)
SILT %
TOTAL LOADING
(g/m*m)
SILT LOADING
SUMMARY
MT
Butte
Flarrison
Arterial
2/21/91
22849
2.9
7.9
36.6
MT
Kalispell
3rd btwn Main & 1
Collector
2/24/91
2653
30.5
24.8
122.9
MT
Kalispell
Main
Arterial
2/24/91
14730
17.4
20.4
85.2
MT
Thompson Fall
Preston
Local
2/25/91
920
35.7
17.9
199.6
MT
Thompson Fall
Highway 200
Collector
2/25/91
5000
66.8
17.8
375.3
MT
Flelena
Montana
Arterial
Mar-91
21900
15.4
6.2
248.3
MT
Kalispell
3rd btwn Main & 1
Collector
3/9/91
2653
39.1
29.1
134.5
MT
Columbia Fall
Nucleus
Collector
Mar-91
5670
30.1
17
174.6
2 samples, range: 0.8 - 0.8
MT
Kalispell
Main
Arterial
3/9/91
14730
17.6
24.7
71.4
MT
Thompson Fall
Preston
Local
Mar-91
920
4.4
8.3
51
2 samples, range: 2.8 - 5.9
MT
Thompson Fall
Flighway 200
Collector
Mar-91
5000
4.3
15.5
28.9
2 samples, range: 1.0 - 7.5
MT
Libby
Main Ave 4th &
Collector
Mar-91
530
14.8
33.1
44.9
2 samples, range: 13.5 - 16.1
MT
Libby
US 2
Arterial
Mar-91
11963
20
19.5
111.9
3 samples, range: 11.4-32.4
MT
East Flelena
Morton
Local
Apr-91
250
4.3
8.8
48.7
MT
East Flelena
US 12
Arterial
Apr-91
7900
0.5
8.7
5.7
MT
Thompson Fall
Preston
Local
Apr-91
920
1.2
15.7
6.3
4 samples, range: 0.3 - 4.0
MT
Thompson Fall
Flighway 200
Collector
4/4/91
5000
2
13.4
14.7
2 samples, range: 1.1 - 2.2
MT
Libby
Main Ave 4th &
Collector
Apr-91
530
3.5
44
7.8
2 samples, range: 2.5 - 4.4
MT
Libby
US 2
Arterial
Apr-91
12945
11.8
20.5
57.2
4 samples, range: 1.2 - 22.9
MT
Kalispell
3rd btwn Main & 1
Collector
4/14/91
2653
15.1
37.1
40.9
MT
Columbia Fall
Nucleus
Collector
Apr-91
5670
9
19.8
47.6
MT
Kalispell
Main
Arterial
4/14/91
14730
13
44.5
29.4
MT
Columbia Fall
Nucleus
Collector
May-91
5670
2.4
17.5
15.9
4 samples, range: 1.3 - 3.8
MT
Columbia Fall
US 2
Arterial
May-91
14712
5.5
20.7
24.8
5 samples, range: 1.5 - 14.2
MT
Libby
Main Ave 4th &
Collector
5/19/91
530
1.7
31
5.7
MT
Libby
Main Ave 4th &
Collector
6/27/91
530
1.7
24.3
7.1
MT
Libby
US 2
Arterial
6/27/91
10000
3.8
12.6
30.6
MT
East Flelena
Morton
Local
Jul-91
250
1.7
11.4
15.3
MT
East Flelena
Main
Collector
Jul-91
2316
8.8
11
79.7
MT
Thompson Fall
Preston
Local
7/9/91
920
10.9
11
98.7
MT
Thompson Fall
Flighway 200
Collector
7/9/91
5000
2.1
8.1
25.9
MT
Flelena
Montana
Arterial
7/17/91
21900
0.9
4.7
19.4
MT
Butte
Texas
Collector
7/26/91
3070
2.5
28.2
8.9
MT
Butte
Flarrison
Arterial
7/26/91
22849
1.6
28.2
5.8
MT
Kalispell
3rd btwn Main & 1
Collector
8/3/91
2653
5.8
23
25.3
MT
Kalispell
Main
Arterial
8/3/91
14730
4
21
19.3
-------
TABLE A2-1. (continued)
>
to
I
-p^
STATE
CITY
STREET
CLASS
DATE
ADT
SILT LOADING
(g/m*m)
SILT %
TOTAL LOADING
(g/m*m)
SILT LOADING
SUMMARY
MT
Columbia Fall
US 2
Arterial
8/11/91
15890
0.1
5.6
2.3
MT
Missoula
Russel btwn 4th &
Road
8/30/91
5270
1.6
8.3
19.3
MT
East Helena
US 12
Arterial
8/30/91
7900
7
20.5
34.3
MT
Butte
Texas
Collector
10/3/91
3070
1
17.7
5.4
MT
Butte
Harrison
Arterial
10/3/91
22849
2.1
23.1
9.1
MT
Kalispell
3rd btwn Main & 1
Collector
10/6/91
2653
10
31.3
31.9
MT
Kalispell
Main
Arterial
10/6/91
14730
4.3
27.7
15.7
MT
East Helena
Morton
Local
10/16/91
250
1.8
31
5.9
MT
East Helena
Main St
Collector
10/16/91
2316
1.6
20.5
7.7
MT
East Helena
US 12
Arterial
10/16/91
7900
1
6.7
14.9
MT
Columbia Fall
Nucleus
Collector
10/20/91
5670
1.9
13.9
13.3
MT
Columbia Fall
US 2
Arterial
10/20/91
15890
1.2
11.3
10.2
MT
Kalispell 3r
d btwn Main & 1
Collector
11/6/91
2653
2.2
12.3
17.8
MT
Kalispell
Main
Arterial
11/28/91
14730
2.7
8.6
30.8
MT
Thompson Fall
Preston
Local
12/17/91
920
4
18.1
22.5
MT
Thompson Fall
Highway 200
Collector
12/17/91
5000
1.5
13.2
11.6
MT
Butte
Texas
Collector
2/2/92
3070
19.1
11.6
164.5
MT
Butte
Harrison
Arterial
2/2/92
22849
8.3
12
69.3
MT
East Helena
Morton
Local
2/3/92
250
78.3
9.5
824.7
MT
Libby
W 4th St
Local
2/3/92
350
36.3
56.3
64.5
MT
Libby
Main Ave 4th &
Collector
2/3/92
530
10.7
49.9
21.4
MT
East Helena
Main St
Collector
2/3/92
2316
57.9
14.8
391
MT
Columbia Fall
Nucleus
Collector
2/3/92
5670
29.2
20.1
145.4
MT
Columbia Fall
US 2
Arterial
Feb-92
12945
51.3
32.2
143.1
2 samples, range: 13.0 - 89.5
MT
East Helena
US 12
Arterial
2/3/92
7900
2.9
14.3
20.7
MT
Thompson Fall
Preston
Local
2/22/92
920
0.5
18
2.6
MT
Thompson Fall
Highway 200
Collector
2/22/92
5000
1.2
14.6
8.1
MT
Kalispell
3rd btwn 2nd & 3r
Local
3/15/92
450
40.2
11.9
338
MT
Kalispell
3rd btwn Main & 1
Collector
3/15/92
2653
81.1
37.3
217.3
MT
Kalispell
Main
Arterial
3/15/92
14730
16.5
32.1
51.3
MT
Thompson Fall
Preston
Local
Apr-92
920
0.43
14.9
3.2
MT
Thompson Fall
Highway 200
Collector
Apr-92
5000
0.8
18.2
4.7
3 samples, range: 0.4 -1.0
MT
Kalispell
3rd btwn 2nd & 3r
Local
4/26/92
450
20.9
45.8
45.5
MT
Kalispell
3rd btwn Main & 1
Collector
4/26/92
2653
19.2
50.9
37.7
MT
Kalispell
Main
Arterial
4/26/92
14730
10.7
33.5
32.1
MT
Kalispell
3rd btwn 2nd & 3r
Local
Mav-92
450
8.3
35.6
23.5
3 samples, range: 6.6 - 10.3
-------
TABLE A2-1. (continued)
>
to
I
'^1
STATE
CITY
STREET
CLASS
DATE
ADT
SILT LOADING
(g/m*m)
SILT %
TOTAL LOADING
(g/m*m)
SILT LOADING
SUMMARY
MT
Kalispell
3rd btwn Main & 1
Collector
May-92
2653
8.5
32.4
25.8
3 samples, range: 6.3 - 11.4
MT
Kalispell
Main
Arterial
May-92
14730
5.1
23.6
21.7
3 samples, range: 3.8 - 5.9
MT
Libby
W 4th St
Local
5/11/92
350
13.4
56.5
23.7
MT
Libby
Main Ave 4th &
Collector
5/11/92
530
5.6
58.9
9.4
MT
Libby
US 2
Arterial
May-92
12945
10.4
25.6
29.4
MT
East Helena
Morton
Local
5/15/92
250
6.9
6.7
103
MT
East Helena
Main St
Collector
5/15/92
2316
6.4
10.2
62.8
MT
East Helena
US 12
Arterial
5/15/92
7900
1.2
6.9
17
MT
Columbia Fall
Nucleus
Collector
5/25/92
5670
1
21.7
4.5
MT
Missoula
Inez btwn 4th & 5
Local
6/4/92
500
1
17.4
5.6
MT
Missoula
Russel btwn 3rd &
Collector
6/4/92
5270
15.2
14
108.4
MT
Missoula
3rd btwn Prince &
Arterial
6/4/92
12000
2
13.1
15.7
The following data from
Reference 2 & 3
CO
Denver
E. Colfax
Principal Arte
Mar-89
1994 *
0.21
2
19.9
4 samples, range: 0.04-0.47
CO
Denver
E. Colfax
Principal Arte
Apr-89
2228 *
0.73
1.7
106.7
18 samples, range: 0.08-1.78
CO
Denver
York St
Principal Arte
Apr-89
780 *
0.86
1.2
74.8
2 samples, range: 0.83 - 0.89
CO
Denver
E. Belleview
Principal Arte
Apr-89
0.07
4.2
2
3 samples, range: 0.03-0.09
CO
Denver
1-225
Expressway +
Apr-89
4731 *
0.02
3.6
0.4
3 samples, range: 0.01-0.02
CO
Denver
W. Evans
Principal Arte
May-89
1905 *
0.76
1.9
74
11 samples, range: 0.03 -
2.24
CO
Denver
W. Evans
Principal Arte
Jun-89
1655 *
0.71
1.2
66.1
12 samples, range: 0.07 -
3.34
CO
Denver
E. Louisiana
Minor Arterial
Jun-89
515 *
0.14
4.66
3.5
5 samples, range: 0.08 - 0.24
The following data from
Reference 4 & 3
CO
Denver
E. Louisiana
Minor Arterial
Jan-90
1.44 *
6 samples, range: 0.12-2.0
CO
Denver
E. Jewell Ave
Collector +
1/24/90
2.24 *
CO
Denver St
ate Highway 36
Expressway +
1/30/90
0.56 *
2 samples, range
0.56-0.56
CO
Denver St
ate Highway 36
Expressway +
2/1/90
1.92 *
4 samples, range
1.92-1.92
CO
Denver
W. Evans Ave
Principal Arte
2/3/90
1.64 *
2 samples, range
1.64-1.64
CO
Denver
E. Mexico St
Local +
2/7/90
2.58 *
3 samples, range
2.58-2.58
CO
Denver
E. Colfax Ave
Principal Arte
Feb-90
0.09 *
16 samples, range: 0.02 -
0.17
CO
Denver St
ate Highway 36
Expressway +
Mar-90
7 samples
CO
Denver E.
Louisiana Ave
Minor Arterial
3/10/90
3 samples
CO
Denver
W. Evans Ave
Principal Arte
Mar-90
1.27 *
5 samples, range: 0.07 - 3.38
-------
TABLE A2-1. (continued)
>
to
I
On
STATE
CITY
STREET
CLASS
DATE
ADT
SILT LOADING
(g/m*m)
SILT %
TOTAL LOADING
(g/m*m)
SILT LOADING
SUMMARY
CO
Denver
W. Colfax Ave
Principal Arte
Mar-90
0.41 *
21 samples, range: 0.04 -
2.61
CO
Denver
Parker Rd
Local +
Apr-90
0.05 *
6 samples, range: 0.01 - 0.11
CO
Denver
W. Byron PI
Principal Arte
Apr-90
0.3 *
6 samples, range: 0.21 - 0.35
CO
Denver
E. Colfax Ave
Principal Arte
4/18/90
0.21 *
The following data from
Reference 5
UT
Salt Lake Cou
700 East
Arterial
*
42340
0.137
11.5
1.187
4 samples, range: 0.107-
0.162
UT
Salt Lake Cou
State St
Collector
*
27140
0.288
17
1.692
4 samples, range: 0.212-
0.357
UT
Salt Lake Cou
1-80
Freeway
*
77040
0.023
21.4
0.1
5 samples, range: 0.011 -
0.034
UT
Salt Lake Cou
1-15
Freeway
*
146180
0.096
23.5
0.419
6 samples, range: 0.078 -
0.126
UT
Salt Lake Cou
400 East
Local
*
5000
1.967
4.07
46.043
14 samples, range: 0.177 -
5.772
The following data from
Reference 6
NV
Las Vegas
Lake Mead
Major
7/15/87
0.81
12.4
6.51
NV
Las Vegas
Perliter
Local
7/15/87
2.23
31.2
7.14
NV
Las Vegas
Bruce
Collector
7/15/87
1.64
26.1
6.3
NV
Las Vegas
Stewart
Major
9/29/87
0.38
24
1.63
3 samples, range: 0.24 - 0.46
NV
Las Vegas
Ambler
Local
9/29/87
1.38
23
6.32
3 samples, range: 0.64 - 2.00
NV
Las Vegas
28th St
Collector
9/29/87
0.52
15.8
3.4
3 samples, range: 0.51 - 0.54
NV
Las Vegas
Lake Mead
Major
10/7/87
0.19
14.9
1.26
2 samples, range: 0.17 - 0.20
NV
Las Vegas
Perliter
Local
10/7/87
1.5
31.9
4.76
2 samples, range: 1.48 - 1.52
NV
Las Vegas
Bruce
Collector
10/7/87
0.9
24.1
3.74
2 samples, range: 0.76 - 1.03
The following data from
Reference 7
AZ
Phoenix
Broadway
Arterial
*
0.127
12.2
1.071
AZ
Phoenix
South Central
Arterial
*
0.085
5
1.726
AZ
Phoenix
Indian School & 2
Arterial
*
0.035
3.1
1.021
AZ
Glendale
43rd & Vista
Arterial
*
0.042
3.9
1.049
AZ
Glendale
59th & Peoria
Arterial
*
0.099
8.2
1.183
AZ
Mesa
Mesa Drive
Arterial
*
0.099
8.9
1.085
AZ
Mesa
E. McKellips & Ol
Arterial
*
0.014
17
0.092
AZ
Phoenix
17th & Highland
Collector
*
0.028
13.4
0.232
-------
TABLE A2-1. (continued)
>
to
I
STATE
CITY
STREET
CLASS
DATE
ADT
SILT LOADING
(g/m*m)
SILT %
TOTAL LOADING
(g/m*m)
SILT LOADING
SUMMARY
AZ
Mesa
3rd & Miller
Collector
*
0.07
11.8
0.627
AZ
Phoenix
Avalon & 25th
Collector
*
0.528
11.1
4.79
AZ
Phoenix
Apache
Collector
*
0.282
6.4
4.367
AZ
Phoenix
28th St & E. G
Collector
*
0.035
2.3
1.479
AZ
Pima County
6th Ave
Collector
*
1.282
6.417
19.961
AZ
Pima County
Speedway Blvd
Arterial
*
0.401
8.117
4.937
AZ
Pima County
22nd St
Arterial
*
0.028
16.529
0.176
AZ
Pima County
Amklam Rd
Collector
*
0.014
5.506
0.197
AZ
Pima County
Fort Lowel Rd
Arterial
*
0.113
3.509
3.268
AZ
Pima County
Oracle Rd
Arterial
*
0.014
1.556
0.725
AZ
Pima County
Inn Rd
Arterial
*
0.021
18.756
0.127
AZ
Pima County
Orange Grove
Arterial
*
0.162
21.989
0.725
AZ
Pima County
La Canada
Arterial
*
0.106
3.975
2.571
The following data from
Reference 8
KS
Kansas City
7th
Arterial
Feb-80
0.29
6.8
4.2
3 samples, range: 0.15 - 0.46
MO
Kansas City
Volker
Arterial
Feb-80
0.67
20.1
3.5
3 samples, range: 0.43 -1.00
MO
Kansas City
Rockhill
Arterial
Feb-80
0.68
21.7
3.3
KS
Tonganoxie
4th
Collector
Mar-80
2.5
14.5
17.1
KS
Kansas City
7th
Arterial
Mar-80
0.29
12.2
2.4
MO
St. Louis
1-44
Expressway
May-80
0.02
4 samples, range: 0.02
MO
St. Louis
Kingshighway
Collector
May-80
0.08
10.9
0.7
3 samples, range: 0.05 - 0.11
IL
GraniteCity
24th
Arterial
May-80
0.78
6.4
12.3
2 samples, range: 0.73 - 0.83
IL
GraniteCity
Benton
Collector
May-80
0.93
8.6
10.8
The following data from
Reference 9
MN
Duluth
US53north
Highway
3/19/92
5000
0.23
28
1.94
8 samples, range: 0.04 - 0.77
MN
Duluth
US53south
Highway
2/26/92
5000
0.24
13.4
2.3
5 samples, range: 0.05 - 0.37
The following data from
Reference 10
CO
Aspen
Aspen
Local
3/18/92
3.56 *
24
14.81
* Samples said to be wet
sieved
CO
Aspen
Aspen
Collector
3/30/92
12.05 *
24
50.23
CO
Aspen
Aspen
Collector
4/1/92
5.97 *
21.1
29.16
8 samples, range: 2.65 - 9.10
CO
Aspen
Highway 82
Major Arterial
4/6/92
6.1 *
12
50.08
2 samples, range: 4.55 - 7.65
CO
Aspen
Knollwood
Local
4/1/92
7.9 *
8
96.01
2 samples, range: 5.21 -
10.59
-------
TABLE A2-1. (continued)
STATE
CITY
STREET
CLASS
DATE
ADT
SILT LOADING
(g/m*m)
SILT %
TOTAL LOADING
(g/m*m)
SILT LOADING
SUMMARY
CO
Aspen
Main
Major Arterial
4/2/92
7.68 *
21.7
35.9
3 samples, range: 5.58 - 9.30
CO
Aspen
Maroon Creek Rd
Minor Arterial
3/30/92
2.07 *
9
23.03
CO
Aspen
Maroon Creek Rd
Minor Arterial
4/1/92
2.78 *
8.9
30.35
7 samples, range: 0.96 - 6.41
CO
Aspen
South Mill
Collector
4/1/92
9.05 *
25
36.21
" denotes missing information.
-------
TABLE A2-2. PUBLIC PAVED ROAD SURFACE LOADING DATA BASE
STATE
CLASS
DATE
ADT
SL
SILT
TL
# SAMPLES
MT
1
Apr-7 8
50
0.6
18.5
3.4
1
MT
2
Apr-7 8
115
0.5
14.3
3.5
1
MT
2
Apr-7 8
4000
8.4
33.9
24.9
1
MT
2
Apr-7 8
679
24.6
10.6
232.4
1
MT
2
Apr-7 8
60
103.7
7
1480.8
1
MT
3
Apr-7 8
6453
1.6
19.1
13.05
MT
3
Apr-7 8
3328
7.7
7.7
99.5
1
MT
3
Apr-7 8
3655
26
62.9
6
1
MT
4
Apr-7 8
22849
1.9
5
37.3
1
MT
4
Apr-7 8
18870
1.9
55.9
3.3
1
MT
4
Apr-7 8
13529
0.8
6.6
11.9
1
MT
2
Apr-83
140
13.1
4.3
305.2
1
MT
5
Apr-83
780
4
13.6
29
1
MT
3
Apr-83
2700
8.2
9.4
86.6
1
MT
3
Apr-83
1360
4.7
8.4
55.3
1
MT
5
Mar-8 8
1310
14.8
1
MT
5
Mar-8 8
331
16.5
1
MT
3
Mar-8 8
800
27.5
1
MT
3
Mar-8 8
5900
7
16
43.5
1
MT
3
Mar-8 8
536
61
20.4
299.2
1
MT
3
Mar-8 8
4500
12.1
1
MT
4
Mar-8 8
10850
12.3
1
MT
2
Apr-8 8
562
2.1
10.9
19.3
1
MT
4
Apr-8 8
5272
0.9
10.1
00
00
1
MT
2
Jun-89
562
1
8.7
11.2
1
MT
2
Jun-89
60
2.8
10.9
25.5
1
MT
4
Jun-89
5272
7.2
3.6
197.6
1
MT
5
Aug-8 9
250
1.7
6.8
24.6
1
MT
3
Aug-8 9
2316
0.7
4.1
17
1
MT
4
Aug-8 9
7900
2.1
12.5
16.5
1
MT
2
Mar-90
390
9.5
1
MT
2
Mar-90
400
18.8
14.3
131.5
1
MT
2
Mar-90
50
14.3
1
MT
2
Mar-90
1720
5.4
1
MT
5
Mar-90
240
16.3
1
A2-9
-------
TABLE A2-2. (continued)
STATE
CLASS
DATE
ADT
SL
SILT
TL
# SAMPLES
MT
3
Mar-90
1510
00
00
1
MT
3
Mar-90
1945
7
1
MT
3
Mar-90
4730
15.4
10
153.9
1
MT
3
Mar-90
316
6.2
1
MT
3
Mar-90
1764
4.2
1
MT
4
Mar-90
13110
2.7
18.7
14.6
1
MT
2
Jul-90
250
1.6
17
9.3
1
MT
3
Jul-90
2316
5.6
10.6
52.5
1
MT
4
Jul-90
790
3.2
15.4
20.9
1
MT
5
Aug-90
400
1.5
4
37.7
1
MT
3
Aug-90
530
2.4
17.9
13.2
1
MT
3
Aug-90
5730
0.8
5.3
16
1
MT
4
Aug-90
13039
0.2
7
2.9
1
MT
5
Oct-90
250
3.4
10.2
33.6
1
MT
3
Oct-90
2316
4.5
5.6
81.3
1
MT
4
Oct-90
7900
0.6
13.9
4.3
1
MT
3
11/6/90
5670
5.2
13.5
38
1
MT
4
11/6/90
15890
1.7
24.1
7.2
1
MT
4
12/8/90
10000
21.5
9.6
223.9
1
MT
3
12/9/90
530
13.6
27.1
50.3
1
MT
3
12/13/90
3070
1
15.4
6.4
1
MT
5
Jan-91
75
1
3.4
30.6
1
MT
5
Jan-91
425
12
1.8
666.5
1
MT
5
Jan-91
250
14.1
3.5
402.3
1
MT
3
Jan-91
2316
36.7
12.1
303.4
1
MT
4
Jan-91
7900
0.8
14
5.6
1
MT
5
1/23/91
920
9.2
9.9
93
1
MT
3
1/23/91
5000
33.3
27.2
122.2
1
MT
5
Feb-91
150
21.6
7.1
304.7
1
MT
3
Feb-91
2140
19.2
9
213.4
1
MT
3
Feb-91
850
74.4
7.7
966.8
1
MT
3
2/14/91
530
33.3
18.7
178.2
1
MT
4
2/17/91
10000
69.3
21
330.3
1
MT
3
2/21/91
3070
1.2
11
10.9
1
A2-10
-------
TABLE A2-2. (continued)
STATE
CLASS
DATE
ADT
SL
SILT
TL
# SAMPLES
MT
4
2/21/91
22849
2.9
7.9
36.6
1
MT
3
2/24/91
2653
30.5
24.8
122.9
1
MT
4
2/24/91
14730
17.4
20.4
85.2
1
MT
5
2/25/91
920
35.7
17.9
199.6
1
MT
3
2/25/91
5000
66.8
17.8
375.3
1
MT
4
Mar-91
21900
15.4
6.2
248.3
1
MT
3
3/9/91
2653
39.1
29.1
134.5
1
MT
3
Mar-91
5670
30.1
17
174.6
2
MT
4
3/9/91
14730
17.6
24.7
71.4
1
MT
5
Mar-91
920
4.4
8.3
51
2
MT
3
Mar-91
5000
4.3
15.5
28.9
2
MT
3
Mar-91
530
14.8
33.1
44.9
2
MT
4
Mar-91
11963
20
19.5
111.9
3
MT
5
Apr-91
250
4.3
00
00
48.7
1
MT
4
Apr-91
7900
0.5
8.7
5.7
1
MT
5
Apr-91
920
1.2
15.7
6.3
4
MT
3
4/4/91
5000
2
13.4
14.7
2
MT
3
Apr-91
530
3.5
44
7.8
2
MT
4
Apr-91
12945
11.8
20.5
57.2
4
MT
3
4/14/91
2653
15.1
37.1
40.9
1
MT
3
Apr-91
5670
9
19.8
47.6
1
MT
4
4/14/91
14730
13
44.5
29.4
1
MT
3
May-00
5670
2.4
17.5
15.9
4
MT
4
50
14712
5.5
20.7
24.8
5
MT
3
5/19/91
530
1.7
31
5.7
1
MT
3
6/27/91
530
1.7
24.3
7.1
1
MT
4
6/27/91
10000
3.8
12.6
30.6
1
MT
5
Jul-91
250
1.7
11.4
15.3
1
MT
3
Jul-91
2316
00
00
11
79.7
1
MT
5
7/9/91
920
10.9
11
98.7
1
MT
3
7/9/91
5000
2.1
8.1
25.9
1
MT
4
7/17/91
21900
0.9
4.7
19.4
1
MT
3
7/26/91
3070
2.5
28.2
8.9
1
MT
4
7/26/91
22849
1.6
28.2
5.8
1
A2-11
-------
TABLE A2-2. (continued)
STATE
CLASS
DATE
ADT
SL
SILT
TL
# SAMPLES
MT
3
8/3/91
2653
5.8
23
25.3
1
MT
4
8/3/91
14730
4
21
19.3
1
MT
4
8/11/91
15890
0.1
5.6
2.3
1
MT
3
8/3/91
5270
1.6
8.3
19.3
1
MT
4
8/3/91
7900
7
20.5
34.3
1
MT
3
10/3/91
3070
1
17.7
5.4
1
MT
4
10/3/91
22849
2.1
23.1
9.1
1
MT
3
10/6/91
2653
10
31.3
31.9
1
MT
4
10/6/91
14730
4.3
27.7
15.7
1
MT
5
10/16/91
250
1.8
31
5.9
1
MT
3
10/16/91
2316
1.6
20.5
7.7
1
MT
4
10/16/91
7900
1
6.7
14.9
1
MT
3
10/20/91
5670
1.9
13.9
13.3
1
MT
4
10/20/91
15890
1.2
11.3
10.2
1
MT
3
11/6/91
2653
2.2
12.3
17.8
1
MT
4
11/28/91
14730
2.7
8.6
30.8
1
MT
5
12/17/91
920
4
18.1
22.5
1
MT
3
12/17/91
5000
1.5
13.2
11.6
1
MT
3
2/2/92
3070
19.1
11.6
164.5
1
MT
4
2/2/92
22849
8.3
12
69.3
1
MT
5
2/3/92
250
78.3
9.5
824.7
1
MT
5
2/3/92
350
36.3
56.3
64.5
1
MT
3
2/3/92
530
10.7
49.9
21.4
1
MT
3
2/3/92
2316
57.9
14.8
391
1
MT
3
2/3/92
5670
29.2
20.1
145.4
1
MT
4
Feb-92
12945
51.3
32.2
143.1
MT
4
2/3/92
7900
2.9
14.3
20.7
1
MT
5
Feb-92
920
0.5
18
2.6
1
MT
3
2/22/92
5000
1.2
14.6
8.1
1
MT
5
3/15/92
450
40.2
11.9
338
1
MT
3
3/15/92
2653
81.1
37.3
217.3
1
MT
4
3/15/92
14730
16.5
32.1
51.3
1
MT
5
Apr-92
920
0.43
14.9
3.2
1
MT
3
Apr-92
5000
0.8
18.2
4.7
3
A2-12
-------
TABLE A2-2. (continued)
STATE
CLASS
DATE
ADT
SL
SILT
TL
# SAMPLES
MT
5
4/26/92
450
20.9
45.8
45.5
1
MT
3
4/26/92
2653
19.2
50.9
37.7
1
MT
4
4/26/92
14730
10.7
33.5
32.1
1
MT
5
May-92
450
8.3
35.6
23.5
3
MT
3
May-92
2653
8.5
32.4
25.8
3
MT
4
May-92
14730
5.1
23.6
21.7
3
MT
5
5/11/92
350
13.4
56.5
23.7
1
MT
3
5/11/92
530
5.6
58.9
9.4
1
MT
4
May-92
12945
10.4
25.6
29.4
1
MT
5
5/15/92
250
6.9
6.7
103
1
MT
3
5/15/92
2316
6.4
10.2
62.8
1
MT
4
5/15/92
7900
1.2
6.9
17
1
MT
3
5/25/92
5670
1
21.7
4.5
1
MT
5
6/4/92
500
1
17.4
5.6
1
MT
3
6/4/92
5270
15.2
14
108.4
1
MT
4
6/4/92
12000
2
13.1
15.7
1
CO
6
Mar-89
1994
0.21
2
19.9
4
CO
6
Apr-89
2228
0.73
1.7
106.7
18
CO
6
Apr-89
780
0.86
1.2
74.8
2
CO
6
Apr-89
0.07
4.2
2
3
CO
7
Apr-89
4731
0.02
3.6
0.4
3
CO
6
May-8 9
1905
0.76
1.9
74
11
CO
6
Jun-89
1655
0.71
1.2
66.1
12
CO
8
Jun-89
515
0.14
4.66
3.5
5
CO
8
Oct-90
1.44
6
CO
3
1/24/90
2.24
1
CO
7
1/30/90
0.56
2
CO
7
2/1/90
1.92
4
CO
6
2/3/90
1.64
2
CO
5
2/7/90
2.58
3
CO
6
Feb-90
0.9
16
CO
7
Mar-90
7
CO
8
3/10/90
3
CO
6
Mar-90
1.27
5
A2-13
-------
TABLE A2-2. (continued)
STATE
CLASS
DATE
ADT
SL
SILT
TL
# SAMPLES
CO
6
Mar-90
0.41
21
CO
5
Apr-90
0.05
6
CO
6
Apr-90
0.3
6
CO
6
4/18/90
0.21
1
UT
4
42340
0.137
11.5
1.187
4
UT
3
27140
0.288
17
1.692
4
UT
9
77040
0.023
21.4
0.1
5
UT
9
146180
0.096
23.5
0.419
6
UT
5
5000
1.967
4.07
46.043
14
NV
10
7/15/87
0.81
12.4
6.51
1
NV
5
7/15/87
2.23
31.2
7.14
1
NV
3
7/15/87
1.64
26.1
6.3
1
NV
10
9/29/87
0.38
24
1.63
3
NV
5
9/29/87
1.38
23
6.32
3
NV
3
9/29/87
0.52
15.8
3.4
3
NV
10
10/7/87
0.19
14.9
1.26
2
NV
5
10/7/87
1.5
31.9
4.76
2
NV
3
10/7/87
0.9
24.1
3.74
2
AZ
4
0.127
12.2
1.071
1
AZ
4
0.085
5
1.726
1
AZ
4
0.035
3.1
1.021
1
AZ
4
0.042
3.9
1.049
1
AZ
4
0.099
8.2
1.183
1
AZ
4
0.099
8.9
1.085
1
AZ
4
0.014
17
0.092
1
AZ
3
0.028
13.4
0.232
1
AZ
3
0.07
11.8
0.627
1
AZ
3
0.528
11.1
4.79
1
AZ
3
0.282
6.4
4.367
1
AZ
3
0.035
2.3
1.479
1
AZ
3
1.282
6.417
19.961
1
AZ
4
0.401
8.117
4.937
1
AZ
4
0.028
16.529
0.176
1
AZ
3
0.014
5.506
0.197
1
A2-14
-------
TABLE A2-2. (continued)
STATE
CLASS
DATE
ADT
SL
SILT
TL
# SAMPLES
AZ
4
0.113
3.509
3.268
1
AZ
4
0.014
1.556
0.725
1
AZ
4
0.021
18.756
0.127
1
AZ
4
0.162
21.989
0.725
1
AZ
4
0.106
3.975
2.571
1
KS
4
Feb-80
0.29
6.8
4.2
3
MO
4
Feb-80
0.67
20.1
3.5
3
MO
4
Feb-80
0.68
21.7
3.3
1
KS
3
Mar-80
2.5
14.5
17.1
1
KS
4
Mar-80
0.29
12.2
2.4
1
MO
7
May-80
0.02
4
MO
3
May-80
0.08
10.9
0.7
3
IL
4
May-80
0.78
6.4
12.3
2
IL
3
May-80
0.93
8.6
10.8
1
MN
11
3/19/92
5000
0.23
28
1.94
8
MN
11
2/26/92
5000
0.24
13.4
2.3
5
CO
5
3/18/92
3.56
24
14.81
1
CO
3
3/30/92
12.05
24
50.23
1
CO
3
4/1/92
5.97
21.1
29.16
8
CO
10
4/6/92
6.1
12
50.08
2
CO
5
4/1/92
7.9
8
96.01
2
CO
10
4/2/92
7.68
21.7
35.9
3
CO
8
3/30/92
2.07
9
23.03
1
CO
8
4/1/92
2.78
8.9
30.35
7
CO
3
4/1/92
9.05
25
36.21
1
A2-15
-------
Attachment 3
New Silt Loading Data Set Used to Develop Revised Default Silt Loading Values
-------
TABLE A3-1. N
EW PUBLIC PAVE
D ROAD SILT LOADING DATA SET
State
Reference
Location
Date
Silt loading,
g/m2
ADT
Posted speed
limit
Road/Comments
NV
BACM11
Las Vegas
Apr-95
0.084
LOW
NA
Composite of 4 roads of the same class
NV
BACM11
Las Vegas
Jun-95
0.097
LOW
NA
Repeat sample of above roads
NV
BACM11
Las Vegas
Apr-95
0.052
HIGH
NA
Composite of 4 roads of the same class
NV
BACM11
Las Vegas
Jun-95
0.033
HIGH
NA
Repeat sample of above roads
NV
BACM12
Las Vegas
Jun-95
1.270
LOW
NA
Composite of 4 roads of the same class
NV
BACM12
Las Vegas
Jun-95
0.029
HIGH
NA
Composite of 4 roads of the same class
NV
BACM13
Las Vegas
Jun-95
0.280
LOW
NA
Composite of 4 roads of the same class
NV
BACM13
Las Vegas
Jun-95
0.200
HIGH
NA
Composite of 4 roads of the same class
CA
BACM21
South Coast
Apr-95
0.184
LOW
NA
Composite of 4 roads of the same class
CA
BACM21
South Coast
Jun-95
0.054
LOW
NA
Repeat sample of above roads
CA
BACM21
South Coast
Apr-95
0.012
HIGH
NA
Composite of 4 roads of the same class
CA
BACM21
South Coast
Jun-95
0.015
HIGH
NA
Repeat sample of above roads
CA
BACM22
South Coast
Jun-95
0.170
LOW
NA
Composite of 4 roads of the same class
CA
BACM22
South Coast
Jun-95
0.011
HIGH
NA
Composite of 4 roads of the same class
CA
BACM23
South Coast
Jun-95
0.140
LOW
NA
Composite of 4 roads of the same class
CA
BACM23
South Coast
Jun-95
0.046
HIGH
NA
Composite of 4 roads of the same class
CA
BACM31
Bakersfield
Apr-95
0.520
LOW
NA
Composite of 4 roads of the same class
CA
BACM31
Bakersfield
Jul-95
0.190
LOW
NA
Repeat sample of above roads
CA
BACM31
Bakersfield
Apr-95
0.054
HIGH
NA
Composite of 4 roads of the same class
CA
BACM31
Bakersfield
Jul-95
0.015
HIGH
NA
Repeat sample of above roads
CA
BACM32
Bakersfield
Jul-95
0.940
LOW
NA
Composite of 4 roads of the same class
CA
BACM32
Bakersfield
Jul-95
0.051
HIGH
NA
Composite of 4 roads of the same class
CA
BACM33
Bakersfield
Jul-95
0.410
LOW
NA
Composite of 4 roads of the same class
CA
BACM33
Bakersfield
Jul-95
0.039
HIGH
NA
Composite of 4 roads of the same class
CA
BACM41
Coachella Valley
Apr-95
2.040
LOW
NA
Composite of 4 roads of the same class, visible trackout signs present
CA
BACM41
Coachella Valley
Jul-95
0.420
LOW
NA
Repeat sample of above roads
CA
BACM41
Coachella Valley
Apr-95
0.027
HIGH
NA
Composite of 4 roads of the same class
CA
BACM41
Coachella Valley
Jul-95
0.037
HIGH
NA
Repeat sample of above roads
CA
BACM42
Coachella Valley
Jul-95
0.350
LOW
NA
Composite of 4 roads of the same class
CA
BACM42
Coachella Valley
Jul-95
0.082
HIGH
NA
Composite of 4 roads of the same class
CA
BACM43
Coachella Valley
Jul-95
0.200
LOW
NA
Composite of 4 roads of the same class
CA
BACM43
Coachella Valley
Jul-95
0.030
HIGH
NA
Composite of 4 roads of the same class
-------
TABLE A3-1. (continued)
>
OJ
I
to
State
Reference
Location
Date
Silt loading,
g/m2
ADT
Posted speed
limit
Road/Comments
CA
SCAQMD
South Coast
Mar-90
0.117
MIXED
NA
Composite of 10 to 12 roads within a 5 km x 5 km area
CA
SCAQMD
South Coast
Mar-90
0.236
MIXED
NA
Composite of 10 to 12 roads within a 5 km x 5 km area
CA
SCAQMD
South Coast
Mar-90
0.720
MIXED
NA
Composite of 10 to 12 roads within a 5 km x 5 km area
CA
SCAQMD
South Coast
Mar-90
0.207
MIXED
NA
Composite of 10 to 12 roads within a 5 km x 5 km area
CA
SCAQMD
South Coast
Mar-90
0.438
MIXED
NA
Composite of 10 to 12 roads within a 5 km x 5 km area
CA
SCAQMD
South Coast
Mar-90
0.139
MIXED
NA
Composite of 10 to 12 roads within a 5 km x 5 km area
CA
SCAQMD
South Coast
Mar-90
0.180
MIXED
NA
Composite of 10 to 12 roads within a 5 km x 5 km area
CA
SCAQMD
South Coast
Mar-90
0.348
MIXED
NA
Composite of 10 to 12 roads within a 5 km x 5 km area
CA
SCAQMD
South Coast
Mar-90
0.112
MIXED
NA
Composite of 10 to 12 roads within a 5 km x 5 km area
CA
SCAQMD
South Coast
Mar-90
0.283
MIXED
NA
Composite of 10 to 12 roads within a 5 km x 5 km area
CA
SCAQMD
South Coast
Mar-90
1.830
MIXED
NA
Composite of 10 to 12 roads within a 5 km x 5 km area
CA
SCAQMD
South Coast
Mar-90
0.907
MIXED
NA
Composite of 10 to 12 roads within a 5 km x 5 km area
CA
SCAQMD
South Coast
Mar-90
0.260
MIXED
NA
Composite of 10 to 12 roads within a 5 km x 5 km area
OR
LAGRD
La Grande
May-91
0.770
MIXED
NA
Composite of 10 to 12 roads within the inventory area
OR
KFALLS
Klamath Falls
May-91
0.370
MIXED
NA
Composite of 10 to 12 roads within the inventory area
OR
GRPASS
Grants Pass
May-91
0.810
MIXED
NA
Composite of 10 to 12 roads within the inventory area
NV
RENO
Reno
Jan-95
0.520
2778
25
Purina
NV
RENO
Reno
Feb-95
0.810
2778
25
Purina
NV
RENO
Reno
Mar-95
0.400
2778
25
Purina
NV
RENO
Reno
Apr-95
0.690
2778
25
Purina
NV
RENO
Reno
May-95
0.890
2778
25
Purina
NV
RENO
Reno
Jun-95
0.910
2778
25
Purina
NV
RENO
Reno
Jul-95
0.550
2778
25
Purina
NV
RENO
Reno
Aug-95
1.520
2778
25
Purina
NV
RENO
Reno
Sep-95
0.920
2778
25
Purina
NV
RENO
Reno
Oct-95
0.290
2778
25
Purina
NV
RENO
Reno
Nov-95
0.390
2778
25
Purina
NV
RENO
Reno
Dec-95
0.330
2778
25
Purina
NV
RENO
Reno
Jan-95
0.300
511
25
Lonetree
NV
RENO
Reno
Feb-95
0.100
511
25
Lonetree
NV
RENO
Reno
Mar-95
0.330
511
25
Lonetree
NV
RENO
Reno
Apr-95
0.270
511
25
Lonetree
NV
RENO
Reno
May-95
0.200
511
25
Lonetree
-------
TABLE A3-1. (continued)
State
Reference
Location
Date
Silt loading,
g/m2
ADT
Posted speed
limit
Road/Comments
NV
RENO
Reno
Jun-95
0.120
511
25
Lonetree
NV
RENO
Reno
Jul-95
0.120
511
25
Lonetree
NV
RENO
Reno
Aug-95
0.120
511
25
Lonetree
NV
RENO
Reno
Sep-95
0.090
511
25
Lonetree
NV
RENO
Reno
Oct-95
0.130
511
25
Lonetree
NV
RENO
Reno
Nov-95
0.170
511
25
Lonetree
NV
RENO
Reno
Dec-95
1.050
511
25
Lonetree
NV
RENO
Reno
Jan-95
0.260
1978
25
Forest
NV
RENO
Reno
Feb-95
0.160
1978
25
Forest
NV
RENO
Reno
Mar-95
0.100
1978
25
Forest
NV
RENO
Reno
Apr-95
0.180
1978
25
Forest
NV
RENO
Reno
May-95
0.250
1978
25
Forest
NV
RENO
Reno
Jun-95
0.140
1978
25
Forest
NV
RENO
Reno
Jul-95
0.190
1978
25
Forest
NV
RENO
Reno
Aug-95
0.110
1978
25
Forest
NV
RENO
Reno
Sep-95
0.280
1978
25
Forest
NV
RENO
Reno
Oct-95
0.160
1978
25
Forest
NV
RENO
Reno
Nov-95
0.110
1978
25
Forest
NV
RENO
Reno
Dec-95
0.110
1978
25
Forest
NV
RENO
Reno
Jan-95
0.230
1978
25
Forest
NV
RENO
Reno
Feb-95
1.310
2155
25
Freeport
NV
RENO
Reno
Mar-95
0.420
2155
25
Freeport
NV
RENO
Reno
Apr-95
2.890
2155
25
Freeport
NV
RENO
Reno
May-95
0.330
2155
25
Freeport
NV
RENO
Reno
Jun-95
0.720
2155
25
Freeport
NV
RENO
Reno
Jul-95
0.810
2155
25
Freeport
NV
RENO
Reno
Aug-95
1.030
2155
25
Freeport
NV
RENO
Reno
Sep-95
0.850
2155
25
Freeport
NV
RENO
Reno
Oct-95
0.420
2155
25
Freeport
NV
RENO
Reno
Nov-95
0.910
2155
25
Freeport
NV
RENO
Reno
Dec-95
0.680
2155
25
Freeport
NV
RENO
Reno
Jan-95
1.510
1578
25
Cashill
NV
RENO
Reno
Feb-95
6.820
1578
25
Cashill
-------
TABLE A3-1. (continued)
>
OJ
I
-p^
State
Reference
Location
Date
Silt loading,
g/m2
ADT
Posted speed
limit
Road/Comments
NV
RENO
Reno
Mar-95
0.630
1578
25
Cashill
NV
RENO
Reno
Apr-95
0.480
1578
25
Cashill
NV
RENO
Reno
May-95
0.340
1578
25
Cashill
NV
RENO
Reno
Jun-95
0.340
1578
25
Cashill
NV
RENO
Reno
Jul-95
0.270
1578
25
Cashill
NV
RENO
Reno
Aug-95
0.140
1578
25
Cashill
NV
RENO
Reno
Sep-95
0.150
1578
25
Cashill
NV
RENO
Reno
Oct-95
0.190
1578
25
Cashill
NV
RENO
Reno
Nov-95
0.430
1578
25
Cashill
NV
RENO
Reno
Dec-95
0.550
1578
25
Cashill
NV
RENO
Reno
Feb-95
5.090
509
25
Ralston
NV
RENO
Reno
Mar-95
2.100
509
25
Ralston
NV
RENO
Reno
Apr-95
1.340
509
25
Ralston
NV
RENO
Reno
May-95
1.630
509
25
Ralston
NV
RENO
Reno
Jun-95
1.630
509
25
Ralston
NV
RENO
Reno
Jul-95
2.170
509
25
Ralston
NV
RENO
Reno
Aug-95
1.730
509
25
Ralston
NV
RENO
Reno
Sep-95
2.250
509
25
Ralston
NV
RENO
Reno
Oct-95
0.790
509
25
Ralston
NV
RENO
Reno
Nov-95
1.120
509
25
Ralston
NV
RENO
Reno
Dec-95
1.000
509
25
Ralston
NV
RENO
Reno
Jan-95
0.240
2396
25
Mayberry
NV
RENO
Reno
Apr-95
0.200
2396
25
Mayberry
NV
RENO
Reno
Jul-95
0.220
2396
25
Mayberry
NV
RENO
Reno
Oct-95
0.320
2396
25
Mayberry
NV
RENO
Reno
Jan-95
0.110
5135
25
Patriot
NV
RENO
Reno
Feb-95
0.860
5135
25
Patriot
NV
RENO
Reno
Mar-95
0.340
5135
25
Patriot
NV
RENO
Reno
Apr-95
0.460
5135
25
Patriot
NV
RENO
Reno
May-95
0.710
5135
25
Patriot
NV
RENO
Reno
Jun-95
0.230
5135
25
Patriot
NV
RENO
Reno
Jul-95
0.400
5135
25
Patriot
NV
RENO
Reno
Aug-95
0.370
5135
25
Patriot
-------
TABLE A3-1. (continued)
State
Reference
Location
Date
Silt loading,
g/m2
ADT
Posted speed
limit
Road/Comments
NV
RENO
Reno
Sep-95
0.520
5135
25
Patriot
NV
RENO
Reno
Oct-95
0.450
5135
25
Patriot
NV
RENO
Reno
Nov-95
0.550
5135
25
Patriot
NV
RENO
Reno
Dec-95
0.460
5135
25
Patriot
NV
RENO
Reno
Jan-95
0.630
5135
25
W. 4th
NV
RENO
Reno
Apr-95
1.020
5135
25
W. 4th
NV
RENO
Reno
Jul-95
0.380
5135
25
W. 4th
NV
RENO
Reno
Oct-95
0.280
5135
25
W. 4th
NV
RENO
Reno
Jan-95
0.140
10170
35
Mill
NV
RENO
Reno
Apr-95
0.290
10170
35
Mill
NV
RENO
Reno
Jul-95
0.140
10170
35
Mill
NV
RENO
Reno
Oct-95
0.200
10170
35
Mill
NV
RENO
Reno
Jan-95
0.170
10521
45
Vista
NV
RENO
Reno
Apr-95
0.190
10521
45
Vista
NV
RENO
Reno
Jul-95
0.090
10521
45
Vista
NV
RENO
Reno
Oct-95
0.080
10521
45
Vista
NV
RENO
Reno
Jan-95
0.050
14441
45
N. McCarran
NV
RENO
Reno
Apr-95
0.050
14441
45
N. McCarran
NV
RENO
Reno
Jul-95
0.020
14441
45
N. McCarran
NV
RENO
Reno
Oct-95
0.010
14441
45
N. McCarran
NV
RENO
Reno
Jan-95
0.400
15566
50
Kietzke-G
NV
RENO
Reno
Apr-95
0.250
15566
50
Kietzke-G
NV
RENO
Reno
Jul-95
0.080
15566
50
Kietzke-G
NV
RENO
Reno
Oct-95
0.250
15566
50
Kietzke-G
NV
RENO
Reno
Jan-95
0.210
17425
25
Prater
NV
RENO
Reno
Apr-95
0.070
17425
25
Prater
NV
RENO
Reno
Jul-95
0.040
17425
25
Prater
NV
RENO
Reno
Oct-95
0.110
17425
25
Prater
NV
RENO
Reno
Jan-95
0.110
17854
40
S. McCarran
NV
RENO
Reno
Apr-95
0.250
17854
40
S. McCarran
NV
RENO
Reno
Jul-95
0.160
17854
40
S. McCarran
NV
RENO
Reno
Oct-95
0.330
17854
40
S. McCarran
NV
RENO
Reno
Jan-95
0.470
25199
40
Kietzke-P
-------
TABLE A3-1. (continued)
State
Reference
Location
Date
Silt loading,
g/m2
ADT
Posted speed
limit
Road/Comments
NV
RENO
Reno
Apr-95
0.530
25199
40
Kietzke-P
NV
RENO
Reno
Jul-95
0.210
25199
40
Kietzke-P
NV
RENO
Reno
Oct-95
0.200
25199
40
Kietzke-P
NV
PM2.5 Study
Reno
Jun-96
0.082
HIGH
45
Virginia, North of Parr
NC
PM2.5 Study
Raleigh
May-96
0.060
HIGH
45
Western (3600 block)
NA = not applicable; shown for composite samples from several roads
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