United States
Environmental Protection
Agency
Air and Energy Engineering
Research Laboratory
Research Triangle Park NC 27711
Research and Development
EPA/600/S7-85/051 Jan. 1986
c/EPA Project Summary
Size Specific Particulate
Emission Factors for Industrial
and Rural Roads: Source
Category Report
Chatten Cowherd, Jr. and Phillip J. Englehart
Over the past few years traffic-
generated dust emissions from un-
paved and paved industrial roads have
become recognized as a significant
source of atmospheric particulate emis-
sions, especially within industries in-
volved in the mining and processing of
mineral aggregates. Although a consid-
erable amount of field testing of indus-
trial roads has been performed, most
studies have focused on total sus-
pended particulate (TSP) emissions, be-
cause the current air quality standards
for particulate matter are based on TSP.
Only recently, in anticipation of an air
quality standard for particulate matter
based on particle size, has the empha-
sis shifted to the development of size-
specific emission factors.
This study was undertaken to derive
size-specific particulate emission fac-
tors for industrial paved and unpaved
roads and for rural unpaved roads from
the existing field testing data base. Re-
gression analysis is used to develop
predictive emission factor equations
which relate emission quantities to
road and traffic parameters. Separate
equations are developed for each road
type and for the following aerodynamic
particle size fractions: § 15, § io, and
£ 2.5 nm. Finally, recommendations
are made for inclusion of the resulting
emission factors in the EPA document,
Compilation of Air Pollutant Emission
Factors, AP-42.
This Project Summary was devel-
oped by EPA's Air and Energy Engineer-
ing Research Laboratory, Research Tri-
angle Park, NC, to announce key
findings of the research project that is
fully documented in a separate report
of the same title Isee Project Report or-
dering information at back).
Introduction
Over the past few years traffic-
generated dust emissions from un-
paved and paved industrial roads have
become recognized as a significant
source of atmospheric particulate emis-
sions, especially within industries in-
volved in the mining and processing of
mineral aggregates. Typically, road
dust emissions exceed emissions from
other open dust sources associated
with the transfer and storage of aggre-
gate materials. Therefore, the quantifi-
cation of industrial road dust emissions
is necessary to the development of ef-
fective strategies for the attainment and
maintenance of the national ambient air
quality standards (NAAQS) for particu-
late matter.
Although a considerable amount of
field testing of industrial roads has been
performed, most studies have focused
on total suspended particulate (TSP)
emissions, because the current NAAQS
for particulate matter are based on TSP.
Those studies have produced emission
factors that are poorly defined with re-
gard to particle size. Although the high-
volume sampler, which is the reference
device for measurement of TSP concen-
tration, has a very broad capture effi-
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ciency curve, TSP is generally recog-
nized as consisting of particles smaller
than 30 n,m in aerodynamic diameter.
Only recently, in anticipation of a
NAAQS for paniculate matter based on
particle size, has the emphasis shifted to
the development of size-specific emis-
sion factors. The following particle size
fractions have been of interest in these
recent studies:
IP = Inhalable participate matter
consisting of particles equal
to or smaller than 15 (im in
aerodynamic diameter,
PM-10 = Paniculate matter consisting
of particles equal to or
smaller than 10 ^.m in aero-
dynamic diameter, and
FP = Fine paniculate matter con-
sisting of panicles equal to
or smaller than 2.5 |xm in
aerodynamic diameter.
In practice, these particle size fractions
have been determined in the field using
inertial sizing devices characterized by
calibrated values of 50% cutoff diameter
(Da,).
This study was undertaken to derive
size-specific particulate emission fac-
tors for industrial paved and unpaved
roads and for rural unpaved roads from
the existing field testing data base. In
addition, recommendations are made
for inclusion of the resulting emission
factors in the EPA document, Compila-
tion of Air Pollutant Emission Factors,
AP-42.
Data Review
Besides an emissions test report on
western surface coal mines released in
November 1981, the literature search
identified two additional reports di-
rected to size specific emission factors
for road dust emissions. The first report
(dated August 1982) dealt with paved
and unpaved roads in the iron and steel
industry, and the second (dated Decem-
ber 1982) presented size specific emis-
sion factors for paved and unpaved
roads in several industries (asphalt and
concrete batching, copper smelting,
sand and gravel processing, and stone
quarrying and processing) and for rural
unpaved roads. The reliability of the
particle size data presented in these
three reports is judged to be substan-
tially better than the data presented in
earlier reports for the following rea-
sons:
1. Measurement of particle size dis-
tribution was an essential part of
the exposure profiling strategies
used to quantify emissions in
these studies.
2. Particle size distribution was mea-
sured simultaneously at more than
one height in the road dust plume.
3. Inertial sizing devices were used to
obtain direct measurements of
aerodynamic particle size distribu-
tion.
Table 1 identifies the AP-42 source cate-
gories covered by the three test reports.
Multiple Regression Analysis
In deriving recommended AP-42 par-
ticulate emission factors for industrial
paved and unpaved roads, the first step
is to determine if size-specific emission
factors correlated with source parame-
ters and if these correlations crossed in-
dustry lines. Such correlations would
lead to predictive emission factor equa-
tions of greater reliability than single-
valued mean emission factors. Step-
wise Multiple Linear Regression (MLR)
is the basic method used to evaluate
source parameters for possible use as
correction factors in a predictive emis-
sion factor equation for a specific parti-
cle size fraction.
The independent variables evaluated
initially as possible correction factors
are silt content (%), silt loading (g/m2),
total loading (g/m2), average vehicle
speed (km/hr), average vehicle weight
(Mg), and average number of vehicle
wheels. Silt denotes that portion of
loose surface dust that passes a 200
mesh screen during standard dry siev-
ing.
Unpaved Roads
All three test reports contained data
sets for the development of IP and PM-
10 emission factor equations for un-
paved industrial roads. These data sets
are combined for the purpose of devel-
oping predictive emission factor equa-
tions.
Analysis of the residuals from regres-
sion indicates that the equations per-
form reasonably well for much of the
data base, but that they do not ade-
quately account for emissions variabil-
ity in the surface mining industry. The
equations tend to significantly overpre-
dict emissions from mine roads. This is
thought to be due to the high degree of
compaction of mine roads which are de-
signed to handle heavy mine vehicles.
In support of this reasoning, the silt
loadings on the test mine roads are
much lower than the loadings found in
other industries. Based on the above
considerations, the decision is made to
exclude the surface mining data set
from the data base.
The non-mining data base (26 tests) is
used to develop several different forms
of predictive emission factor equations.
A model which includes silt loading and
traffic-related parameters is found to ac-
count for the highest percentage of
emission factor variability. The result-
ing equations have precision factors of
1.60 and 1.64 for the IP and PM-10 emis-
sions, respectively. The precision factor
is defined such that the 68% confidence
interval for a predicted value (P) extends
from P/f to Pf. The precision factor is
determined by exponentiating the
standard deviation of the differences
(standard error of the estimate) be-
tween the natural logarithms of the pre-
dicted and actual emission factors. The
precision factor is interpreted as a mea-
sure of the "average" error in predicting
emissions from the regression equa-
tion. In addition, a non-parametric anal-
ysis of the residuals from the MLR indi-
cates that the equations do not show
any systematic predictive bias with re-
spect to industry category.
Alternative equations are developed
retaining the same form as the current
AP-42 equation but with adjustments to
both the coefficient and the exponents
of the correction terms based on regres-
sion analysis against the study data
Table 1.
AP-42
Section No.
7.3
7.5
8.1
8.10
8.19
8.20
8.24
1 1.2. 1
11.2.6
Primary Test Reports by AP-42 Section Number
Industrial source category
Copper smelting
Iron and steel production
Asphaltic concrete plants
Concrete batching
Sand and gravel processing
Stone quarrying and processing
Western surface coal mining
Unpaved roads
Paved roads
Test report
date
12/82
8/82
12/82
12/82
12/82
12/82
11/81
All three
8/82, 12/82
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base. The alternative equations, which
incorporate road surface silt percentage
rather than silt loading, are found to
have nearly the same predictive reliabil-
ity (precision factors of 1.81 and 1.76 for
IP and PM-10, respectively).
For the IP and PM-10 particle size frac-
tions, the equations incorporating silt
percentage are recommended over the
equations using silt loading, primarily
because of the much greater amount of
information available on the expected
range of percent silt for industrial roads.
To provide a comparable amount of in-
formation for the silt loading parameter,
it would be necessary to perform a con-
siderable amount of additional road
surface characterization work. For the
FP size fraction, the recommended
model incorporates silt content and is
also the most accurate model.
The recommended unpaved road
equations for all three particle size frac-
tions follows a single functional form:
where:
E = emission factor; i.e., the quantity of particu-
late emissions from an unpaved road per ve-
hicle kilometer of travel, kg/VKT
s = silt content of road surface material, %
S - mean vehicle speed, km/hr
W = mean vehicle weight, Mg
w = mean number of wheels
p = number of days with at least 0.254 mm 10.01
in.) of precipitation per year
The particle size multiplier (k) in Eq. (1)
is found to vary with aerodynamic parti-
cle size range as follows:
Aerodynamic Particle Size
Multiplier for Eq. (1)
§15
§10
§2.5 u,m
0.50
0.36
0.095
Equation (1) is assigned a quality rat-
ing of A for application within the
ranges of source conditions that were
tested in developing the equations, as
follows: silt content, 4 to 35%; mean ve-
hicle weight, 2 to 49 Mg; mean vehicle
speed, 8 to 64 km/hr; mean number of
wheels, 4 to 17. Also, to retain the qual-
ity rating of the equation applied to a
specific unpaved road, it would be nec-
essary that reliable correction parame-
ter values be determined for the specific
road in question.
Paved Roads
Two data sets were available for the
development of paved road IP and PM-
10 emission factor equations. These in-
clude test data (21 tests) collected for
the following industries: iron and steel
production, copper smelting, concrete
batching, and sand and gravel process-
ing. The independent variables consid-
ered initially as possible correction fac-
tors are the same as those in the
unpaved roads analyses.
Prior to the analysis, it is recognized
that the measured correction factors
would probably not account for a sub-
stantial portion of the variability in IP
and PM-10 emissions. One of the major
reasons for this is that any direct contri-
bution of paniculate from vehicle un-
derbodies, exposed haulage loads (i.e.,
aggregate materials), or vehicle exhaust
is not parameterized by the available
correction factors. Similarly, the influ-
ence of emissions from unpaved shoul-
ders generated by the wakes of large
vehicles is not considered in the correc-
tion parameters. Because of the lower
magnitude of paved road emissions
compared to those from unpaved
roads, the influence of these sources
would be potentially greater in paved
road emission factors. Previously pub-
lished equations for paved road
emissions used augmentation or judg-
ment factors in an attempt to partially
account for the influence of these
sources.
Based on analysis of the data set, the
decision is made to partition the paved
road data base into two subsets: Subset
1 includes tests for relatively heavily
loaded roads traveled by predominantly
light-duty vehicles (i.e., mean vehicle
weight <4 Mg); and Subset 2 includes
tests for roads with generally moderate
surface loadings and vehicle mixes that
can be considered more typical of in-
dustrial facilities (i.e., mean vehicle
weight ~ 16 Mg). The mean emission
factors (IP and PM-10) for Subset 1 are
less than 50% of those of Subset 2.
The correlation matrix based on Sub-
set 2 shows a reasonably strong rela-
tionship between roadway surface load-
ings and emissions. The emission factor
equations predict the data Subset 2 with
precision factors of 1.59 and 1.64 for IP
and PM-10 emissions, respectively.
An alternative, consisting of the exist-
ing AP-42 emission factor equation with
adjustments to the original coefficient
to approximate IP and PM-10 emission
factors, does not acceptably predict the
new emission factor data base. The rela-
tively poor performance of the scaled
AP-42 equation is attributed largely to
two factors: first, the proportionality
constants are based on limited particle
sizing information; and second (and
more important), the range of source
conditions that provided the basis for
the AP-42 equation is much smaller
than that of the new data base.
The recommended paved road equa-
tions for all three particle size fractions
follows a single functional form:
(2)
where
E = emission factor; i.e., the quantity
of paniculate emissions from a
paved road per vehicle-kilometer
of travel, kg/VKT
sL = road surface silt loading, g/m2
The panicle size multiplier (k) is found
to vary with aerodynamic size range as
follows:
Aerodynamic Panicle Size
Multiplier for Eq. (2)
515
S10
S2.5
0.28
0.22
0.081
Equation (2) is assigned a quality rat-
ing of A for application within the range
of source conditions that were tested in
developing the equation as follows: silt
loading, 2 to 240 g/m2; and mean vehi-
cle weight, 6 to 42 Mg. Also, to retain the
quality ratings of Eq. (2) applied to a
specific industrial paved road, it would
be necessary that reliable correction
parameter values for the specific road in
question be determined.
For roads that are traveled by pre-
dominantly light-duty traffic, the single-
value emission factors represented by
the geometric means for Subset 1,
should provide reasonable upper limits
for IP and PM-10 emissions, as follows:
Emission Factors for Light-Duty
Vehicles on Heavily Loaded Roads
§15
§10 \im
0.12 kg/VKT
0.093 kg/VKT
These emission factors are assigned a
quality rating of B for application within
the range of source conditions that were
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tested in developing the factors, as fol-
lows: silt loading, 15 to 400 g/m2; and
mean vehicle weight, <4 Mg (<4 tons).
Proposed AP-42 Sections
This report also contains the pro-
posed revisions to the AP-42 sections
for unpaved roads (Section 11.2.1) and
for industrial paved roads (Section
11.2.6), respectively. Updates for these
sections were recently included in Sup-
plement 14 to AP-42. To the extent pos-
sible, the format used in Supplement 14
is retained for the purpose of incorpo-
rating the size-specific particulate emis-
sion factors developed in this docu-
ment.
With regard to unpaved road emis-
sion factors for western surface coal
mining, it 43 recommended that the new
AP-42 Section 8.24 be used without
modification. That section already con-
tained predictive emission factor equa-
tions for specified particle size fractions.
C. Cowherd, Jr. and P. J. Englehart are with Midwest Research Institute, Kansas
City, MO 64110.
Dale L. Harmon is the EPA Project Officer (see below).
The complete report, entitled "Size Specific Particulate Emission Factors for
Industrial and Rural Roads: Source Category Report," (Order No. PB 86-122
61 I/AS; Cost: $11.95, subject to change) will be available only from:
National Technical Information Service
5285 Port Royal Road
Springfield, VA 22161
Telephone: 703-487-4650
The EPA Project Officer can be contacted at:
Air and Energy Engineering Research Laboratory
U.S. Environmental Protection Agency
Research Triangle Park, NC27711
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Agency
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