11/06 Miscellaneous Sources 13.2.2-1

13.2.2 Unpaved Roads

13.2.2.1 General

When a vehicle travels an unpaved road, the force of the wheels on the road surface causes

pulverization of surface material. Particles are lifted and dropped from the rolling wheels, and the road

surface is exposed to strong air currents in turbulent shear with the surface. The turbulent wake behind

the vehicle continues to act on the road surface after the vehicle has passed.

The particulate emission factors presented in the previous draft version of this section of AP-42,

dated October 2001, implicitly included the emissions from vehicles in the form of exhaust, brake wear,

and tire wear as well as resuspended road surface material25. EPA included these sources in the emission

factor equation for unpaved public roads (equation 1b in this section) since the field testing data used to

develop the equation included both the direct emissions from vehicles and emissions from resuspension of

road dust. 

This version of the unpaved public road emission factor equation only estimates particulate

emissions from resuspended road surface material 23, 26. The particulate emissions from vehicle exhaust,

brake wear, and tire wear are now estimated separately using EPA’s MOBILE6.2 24. This approach

eliminates the possibility of double counting emissions. Double counting results when employing the

previous version of the emission factor equation in this section and MOBILE6.2 to estimate particulate

emissions from vehicle traffic on unpaved public roads. It also incorporates the decrease in exhaust

emissions that has occurred since the unpaved public road emission factor equation was developed. The

previous version of the unpaved public road emission factor equation includes estimates of emissions

from exhaust, brake wear, and tire wear based on emission rates for vehicles in the 1980 calendar year

fleet. The amount of PM released from vehicle exhaust has decreased since 1980 due to lower new

vehicle emission standards and changes in fuel characteristics.

13.2.2.2 Emissions Calculation And Correction Parameters1-6

The quantity of dust emissions from a given segment of unpaved road varies linearly with the

volume of traffic. Field investigations also have shown that emissions depend on source parameters that

characterize the condition of a particular road and the associated vehicle traffic. Characterization of these

source parameters allow for “correction” of emission estimates to specific road and traffic conditions

present on public and industrial roadways.

Dust emissions from unpaved roads have been found to vary directly with the fraction of silt

(particles smaller than 75 micrometers [:m] in diameter) in the road surface materials.1

 The silt fraction

is determined by measuring the proportion of loose dry surface dust that passes a 200-mesh screen, using

the ASTM-C-136 method. A summary of this method is contained in Appendix C of AP-42. Table

13.2.2-1 summarizes measured silt values for industrial unpaved roads. Table 13.2.2-2 summarizes

measured silt values for public unpaved roads. It should be noted that the ranges of silt content vary over

two orders of magnitude. Therefore, the use of data from this table can potentially introduce considerable

error. Use of this data is strongly discouraged when it is feasible to obtain locally gathered data.

Since the silt content of a rural dirt road will vary with geographic location, it should be measured

for use in projecting emissions. As a conservative approximation, the silt content of the parent soil in the

area can be used. Tests, however, show that road silt content is normally lower than in the surrounding

parent soil, because the fines are continually removed by the vehicle traffic, leaving a higher percentage

of coarse particles.
13.2.2-2 EMISSION FACTORS 11/06

Other variables are important in addition to the silt content of the road surface material. For

example, at industrial sites, where haul trucks and other heavy equipment are common, emissions are

highly correlated with vehicle weight. On the other hand, there is far less variability in the weights of

cars and pickup trucks that commonly travel publicly accessible unpaved roads throughout the United

States. For those roads, the moisture content of the road surface material may be more dominant in

determining differences in emission levels between, for example a hot, desert environment and a cool,

moist location.

The PM-10 and TSP emission factors presented below are the outcomes from stepwise linear

regressions of field emission test results of vehicles traveling over unpaved surfaces. Due to a limited

amount of information available for PM-2.5, the expression for that particle size range has been scaled

against the result for PM-10. Consequently, the quality rating for the PM-2.5 factor is lower than that for

the PM-10 expression.
11/06 Miscellaneous Sources 13.2.2-3

Table 13.2.2-1. TYPICAL SILT CONTENT VALUES OF SURFACE MATERIAL

ON INDUSTRIAL UNPAVED ROADSa

Industry

Road Use Or

Surface Material

Plant

Sites

No. Of

Samples

Silt Content (%)

Range Mean

Copper smelting Plant road 1 3 16 - 19 17

Iron and steel production Plant road 19 135 0.2 - 19 6.0

Sand and gravel processing Plant road 1 3 4.1 - 6.0 4.8

Material storage

area 1 1 - 7.1

Stone quarrying and processing Plant road 2 10 2.4 - 16 10

Haul road to/from

pit 4 20 5.0-15 8.3

Taconite mining and processing Service road 1 8 2.4 - 7.1 4.3

Haul road to/from

pit

1 12 3.9 - 9.7 5.8

Western surface coal mining Haul road to/from

pit

3 21 2.8 - 18 8.4

Plant road 2 2 4.9 - 5.3 5.1

Scraper route 3 10 7.2 - 25 17

Haul road

 (freshly graded) 2 5 18 - 29 24

Construction sites Scraper routes 7 20 0.56-23 8.5

Lumber sawmills Log yards 2 2 4.8-12 8.4

Municipal solid waste landfills Disposal routes 4 20 2.2 - 21 6.4

a

References 1,5-15.
13.2.2-4 EMISSION FACTORS 11/06

(1a)

(1b)

The following empirical expressions may be used to estimate the quantity in pounds (lb) of

size-specific particulate emissions from an unpaved road, per vehicle mile traveled (VMT):

For vehicles traveling on unpaved surfaces at industrial sites, emissions are estimated from the following

equation:

and, for vehicles traveling on publicly accessible roads, dominated by light duty vehicles, emissions may

be estimated from the following:

where k, a, b, c and d are empirical constants (Reference 6) given below and 

E = size-specific emission factor (lb/VMT)

s = surface material silt content (%)

W = mean vehicle weight (tons)

M = surface material moisture content (%) 

 S = mean vehicle speed (mph)

 C = emission factor for 1980's vehicle fleet exhaust, brake wear and tire wear.

The source characteristics s, W and M are referred to as correction parameters for adjusting the emission

estimates to local conditions. The metric conversion from lb/VMT to grams (g) per vehicle kilometer

traveled (VKT) is as follows:

1 lb/VMT = 281.9 g/VKT

The constants for Equations 1a and 1b based on the stated aerodynamic particle sizes are shown in

Tables 13.2.2-2 and 13.2.2-4. The PM-2.5 particle size multipliers (k-factors) are taken from

Reference 27.
11/06 Miscellaneous Sources 13.2.2-5

Table 13.2.2-2. CONSTANTS FOR EQUATIONS 1a AND 1b

Constant

Industrial Roads (Equation 1a) Public Roads (Equation 1b)

PM-2.5 PM-10 PM-30* PM-2.5 PM-10 PM-30*

k (lb/VMT) 0.15 1.5 4.9 0.18 1.8 6.0

a 0.9 0.9 0.7 1 1 1

b 0.45 0.45 0.45 - - -

c - - - 0.2 0.2 0.3

d --- 0.5 0.5 0.3

Quality Rating BBBBBB

*Assumed equivalent to total suspended particulate matter (TSP)

“-“ = not used in the emission factor equation

Table 13.2.2-2 also contains the quality ratings for the various size-specific versions of Equation 1a and

1b. The equation retains the assigned quality rating, if applied within the ranges of source conditions,

shown in Table 13.2.2-3, that were tested in developing the equation:

Table 13.2.2-3. RANGE OF SOURCE CONDITIONS USED IN DEVELOPING EQUATION 1a AND

1b

Emission Factor

Surface Silt

Content, %

Mean Vehicle

Weight

Mean Vehicle

Speed Mean

No. of

Wheels

Surface

Moisture

Content,

Mg ton km/hr mph %

Industrial Roads

(Equation 1a) 1.8-25.2 1.8-260 2-290 8-69 5-43 4-17a 0.03-13

Public Roads

(Equation 1b)

1.8-35 1.4-2.7 1.5-3 16-88 10-55 4-4.8 0.03-13

a

 See discussion in text.

As noted earlier, the models presented as Equations 1a and 1b were developed from tests of

traffic on unpaved surfaces. Unpaved roads have a hard, generally nonporous surface that usually dries

quickly after a rainfall or watering, because of traffic-enhanced natural evaporation. (Factors influencing

how fast a road dries are discussed in Section 13.2.2.3, below.) The quality ratings given above pertain to

the mid-range of the measured source conditions for the equation. A higher mean vehicle weight and a

higher than normal traffic rate may be justified when performing a worst-case analysis of emissions from

unpaved roads. 

The emission factors for the exhaust, brake wear and tire wear of a 1980's vehicle fleet (C) was

obtained from EPA’s MOBILE6.2 model 23. The emission factor also varies with aerodynamic size range
13.2.2-6 EMISSION FACTORS 11/06

as shown in Table 13.2.2-4

Table 13.2.2-4. EMISSION FACTOR FOR 1980'S VEHICLE FLEET 

EXHAUST, BRAKE WEAR AND TIRE WEAR

Particle Size Rangea

C, Emission Factor for

Exhaust, Brake Wear

and Tire Wearb

lb/VMT

PM2.5 0.00036

PM10 0.00047

PM30

c 0.00047

a Refers to airborne particulate matter (PM-x) with an aerodynamic diameter equal to or less

than x micrometers.

b Units shown are pounds per vehicle mile traveled (lb/VMT). c PM-30 is sometimes termed "suspendable particulate" (SP) and is often used as a surrogate

for TSP.

It is important to note that the vehicle-related source conditions refer to the average weight,

speed, and number of wheels for all vehicles traveling the road. For example, if 98 percent of traffic on

the road are 2-ton cars and trucks while the remaining 2 percent consists of 20-ton trucks, then the mean

weight is 2.4 tons. More specifically, Equations 1a and 1b are not intended to be used to calculate a

separate emission factor for each vehicle class within a mix of traffic on a given unpaved road. That is, in

the example, one should not determine one factor for the 2-ton vehicles and a second factor for the 20-ton

trucks. Instead, only one emission factor should be calculated that represents the "fleet" average of 2.4

tons for all vehicles traveling the road. 

Moreover, to retain the quality ratings when addressing a group of unpaved roads, it is necessary

that reliable correction parameter values be determined for the road in question. The field and laboratory

procedures for determining road surface silt and moisture contents are given in AP-42 Appendices C.1

and C.2. Vehicle-related parameters should be developed by recording visual observations of traffic. In

some cases, vehicle parameters for industrial unpaved roads can be determined by reviewing maintenance

records or other information sources at the facility.

In the event that site-specific values for correction parameters cannot be obtained, then default

values may be used.In the absence of site-specific silt content information, an appropriate mean value

from Table 13.2.2-1 may be used as a default value, but the quality rating of the equation is reduced by

two letters. Because of significant differences found between different types of road surfaces and

between different areas of the country, use of the default moisture content value of 0.5 percent in

Equation 1b is discouraged. The quality rating should be downgraded two letters when the default

moisture content value is used. (It is assumed that readers addressing industrial roads have access to the

information needed to develop average vehicle information in Equation 1a for their facility.)

The effect of routine watering to control emissions from unpaved roads is discussed below in

Section 13.2.2.3, “Controls”. However, all roads are subject to some natural mitigation because of

rainfall and other precipitation. The Equation 1a and 1b emission factors can be extrapolated to annual
11/06 Miscellaneous Sources 13.2.2-7

(2)

average uncontrolled conditions (but including natural mitigation) under the simplifying assumption that

annual average emissions are inversely proportional to the number of days with measurable (more than

0.254 mm [0.01 inch]) precipitation:

where: 

Eext = annual size-specific emission factor extrapolated for natural mitigation, lb/VMT

E = emission factor from Equation 1a or 1b

P = number of days in a year with at least 0.254 mm (0.01 in) of precipitation (see

below)

Figure 13.2.2-1 gives the geographical distribution for the mean annual number of “wet” days for the

United States.

Equation 2 provides an estimate that accounts for precipitation on an annual average basis for the

purpose of inventorying emissions. It should be noted that Equation 2 does not account for differences in

the temporal distributions of the rain events, the quantity of rain during any event, or the potential for the

rain to evaporate from the road surface. In the event that a finer temporal and spatial resolution is desired

for inventories of public unpaved roads, estimates can be based on a more complex set of assumptions. 

These assumptions include: 

1. The moisture content of the road surface material is increased in proportion to the quantity of

water added;

2. The moisture content of the road surface material is reduced in proportion to the Class A pan

evaporation rate;

3. The moisture content of the road surface material is reduced in proportion to the traffic

volume; and

4. The moisture content of the road surface material varies between the extremes observed in the

area. The CHIEF Web site (http://www.epa.gov/ttn/chief/ap42/ch13/related/c13s02-2.html) has a file

which contains a spreadsheet program for calculating emission factors which are temporally and spatially

resolved. Information required for use of the spreadsheet program includes monthly Class A pan

evaporation values, hourly meteorological data for precipitation, humidity and snow cover, vehicle traffic

information, and road surface material information.

It is emphasized that the simple assumption underlying Equation 2 and the more complex set of

assumptions underlying the use of the procedure which produces a finer temporal and spatial resolution

have not been verified in any rigorous manner. For this reason, the quality ratings for either approach

should be downgraded one letter from the rating that would be applied to Equation 1. 

13.2.2.3 Controls18-22

A wide variety of options exist to control emissions from unpaved roads. Options fall into the

following three groupings:

1. Vehicle restrictions that limit the speed, weight or number of vehicles on the road;
13.2.2-8 EMISSION FACTORS 11/06

2. Surface improvement, by measures such as (a) paving or (b) adding gravel or slag to a dirt

road; and

3. Surface treatment, such as watering or treatment with chemical dust suppressants.

Available control options span broad ranges in terms of cost, efficiency, and applicability. For example,

traffic controls provide moderate emission reductions (often at little cost) but are difficult to enforce. 

Although paving is highly effective, its high initial cost is often prohibitive. Furthermore, paving is not

feasible for industrial roads subject to very heavy vehicles and/or spillage of material in transport. 

Watering and chemical suppressants, on the other hand, are potentially applicable to most industrial roads

at moderate to low costs. However, these require frequent reapplication to maintain an acceptable level of

control. Chemical suppressants are generally more cost-effective than water but not in cases of temporary

roads (which are common at mines, landfills, and construction sites). In summary, then, one needs to

consider not only the type and volume of traffic on the road but also how long the road will be in service

when developing control plans. 

Vehicle restrictions. These measures seek to limit the amount and type of traffic present on the

road or to lower the mean vehicle speed. For example, many industrial plants have restricted employees

from driving on plant property and have instead instituted bussing programs. This eliminates emissions

due to employees traveling to/from their worksites. Although the heavier average vehicle weight of the

busses increases the base emission factor, the decrease in vehicle-miles-traveled results in a lower overall

emission rate. 
11/06 Miscellaneous Sources 13.2.2-9 Figure 13.2.2-1. Mean number of days with 0.01 inch or more of precipitation in United States.
13.2.2-10 EMISSION FACTORS 11/06

Surface improvements. Control options in this category alter the road surface. As opposed to the

“surface treatments” discussed below, improvements are relatively “permanent” and do not require

periodic retreatment. 

The most obvious surface improvement is paving an unpaved road. This option is quite

expensive and is probably most applicable to relatively short stretches of unpaved road with at least

several hundred vehicle passes per day. Furthermore, if the newly paved road is located near unpaved

areas or is used to transport material, it is essential that the control plan address routine cleaning of the

newly paved road surface. 

The control efficiencies achievable by paving can be estimated by comparing emission factors for

unpaved and paved road conditions. The predictive emission factor equation for paved roads, given in

Section 13.2.1, requires estimation of the silt loading on the traveled portion of the paved surface, which

in turn depends on whether the pavement is periodically cleaned. Unless curbing is to be installed, the

effects of vehicle excursion onto unpaved shoulders (berms) also must be taken into account in estimating

the control efficiency of paving.

Other improvement methods cover the road surface with another material that has a lower silt

content. Examples include placing gravel or slag on a dirt road. Control efficiency can be estimated by

comparing the emission factors obtained using the silt contents before and after improvement. The silt

content of the road surface should be determined after 3 to 6 months rather than immediately following

placement. Control plans should address regular maintenance practices, such as grading, to retain larger

aggregate on the traveled portion of the road. 

Surface treatments refer to control options which require periodic reapplication. Treatments fall

into the two main categories of (a) “wet suppression” (i. e., watering, possibly with surfactants or other

additives), which keeps the road surface wet to control emissions and (b) “chemical stabilization/

treatment”, which attempts to change the physical characteristics of the surface. The necessary

reapplication frequency varies from several minutes for plain water under summertime conditions to

several weeks or months for chemical dust suppressants. 

Watering increases the moisture content, which conglomerates particles and reduces their

likelihood to become suspended when vehicles pass over the surface. The control efficiency depends on

how fast the road dries after water is added. This in turn depends on (a) the amount (per unit road surface

area) of water added during each application; (b) the period of time between applications; (c) the weight,

speed and number of vehicles traveling over the watered road during the period between applications; and

(d) meteorological conditions (temperature, wind speed, cloud cover, etc.) that affect evaporation during

the period. 
11/06 Miscellaneous Sources 13.2.2-11

Figure 13.2.2-2 presents a simple bilinear relationship between the instantaneous control

efficiency due to watering and the resulting increase in surface moisture. The moisture ratio "M" (i.e., the

x-axis in Figure 13.2.2-2) is found by dividing the surface moisture content of the watered road by the

surface moisture content of the uncontrolled road. As the watered road surface dries, both the ratio M and

the predicted instantaneous control efficiency (i.e., the y-axis in the figure) decrease. The figure shows

that between the uncontrolled moisture content and a value twice as large, a small increase in moisture

content results in a large increase in control efficiency. Beyond that, control efficiency grows slowly with

increased moisture content.

Given the complicated nature of how the road dries, characterization of emissions from watered

roadways is best done by collecting road surface material samples at various times between water truck

passes. (Appendices C.1 and C.2 present the sampling and analysis procedures.) The moisture content

measured can then be associated with a control efficiency by use of Figure 13.2.2-2. Samples that reflect

average conditions during the watering cycle can take the form of either a series of samples between

water applications or a single sample at the midpoint. It is essential that samples be collected during

periods with active traffic on the road. Finally, because of different evaporation rates, it is recommended

that samples be collected at various times during the year. If only one set of samples is to be collected,

these must be collected during hot, summertime conditions.

When developing watering control plans for roads that do not yet exist, it is strongly

recommended that the moisture cycle be established by sampling similar roads in the same geographic

area. If the moisture cycle cannot be established by similar roads using established watering control

plans, the more complex methodology used to estimate the mitigation of rainfall and other precipitation

can be used to estimate the control provided by routine watering. An estimate of the maximum daytime

Class A pan evaporation (based upon daily evaporation data published in the monthly Climatological

Data for the state by the National Climatic Data Center) should be used to insure that adequate watering

capability is available during periods of highest evaporation. The hourly precipitation values in the

spreadsheet should be replaced with the equivalent inches of precipitation (where the equivalent of 1 inch

of precipitation is provided by an application of 5.6 gallons of water per square yard of road). 

Information on the long term average annual evaporation and on the percentage that occurs between May

and October was published in the Climatic Atlas (Reference 16). Figure 13.2.2-3 presents the

geographical distribution for "Class A pan evaporation" throughout the United States. Figure 13.2.2-4

presents the geographical distribution of the percentage of this evaporation that occurs between May and

October. The U. S. Weather Bureau Class A evaporation pan is a cylindrical metal container with a depth

of 10 inches and a diameter of 48 inches. Periodic measurements are made of the changes of the water

level.

The above methodology should be used only for prospective analyses and for designing watering

programs for existing roadways. The quality rating of an emission factor for a watered road that is based

on this methodology should be downgraded two letters. Periodic road surface samples should be

collected and analyzed to verify the efficiency of the watering program.

As opposed to watering, chemical dust suppressants have much less frequent reapplication

requirements. These materials suppress emissions by changing the physical characteristics of the existing

road surface material. Many chemical unpaved road dust suppressants form a hardened surface that binds

particles together. After several applications, a treated road often resembles a paved road except that the

surface is not uniformly flat. Because the improved surface results in more grinding of small particles,

the silt content of loose material on a highly controlled surface may be substantially higher than when the

surface was uncontrolled. For this reason, the models presented as Equations 1a and 1b cannot be used to

estimate emissions from chemically stabilized roads. Should the road be allowed to return to an
13.2.2-12 EMISSION FACTORS 11/06

uncontrolled state with no visible signs of large-scale cementing of material, the Equation 1a and 1b

emission factors could then be used to obtain conservatively high emission estimates. 

Figure 13.2.2-2. Watering control effectiveness for unpaved travel surfaces

0

25

50

75

100

012345

Moisture Ratio, M 

Control Efficiency (%)
11/06 Miscellaneous Sources 13.2.2-13

The control effectiveness of chemical dust suppressants appears to depend on (a) the dilution rate

used in the mixture; (b) the application rate (volume of solution per unit road surface area); (c) the time

between applications; (d) the size, speed and amount of traffic during the period between applications;

and (e) meteorological conditions (rainfall, freeze/thaw cycles, etc.) during the period. Other factors that

affect the performance of dust suppressants include other traffic characteristics (e. g., cornering, track-on

from unpaved areas) and road characteristics (e. g., bearing strength, grade). The variabilities in the

above factors and differences between individual dust control products make the control efficiencies of

chemical dust suppressants difficult to estimate. Past field testing of emissions from controlled unpaved

roads has shown that chemical dust suppressants provide a PM-10 control efficiency of about 80 percent

when applied at regular intervals of 2 weeks to 1 month. 
13.2.2-14 EMISSION FACTORS 11/06

Figure 13.2.2-3. Annual evaporation data.
11/06 Miscellaneous Sources 13.2.2-15 Figure 13.2.2-4. Geographical distribution of the percentage of evaporation occurring between May and Oc
13.2.2-16 EMISSION FACTORS 11/06

Table 13.2-2-5. EXAMPLE OF AVERAGE CONTROLLED EMISSION FACTORS

FOR SPECIFIC CONDITIONS

Period

Ground Inventory,

gal/yd2

Average Control

Efficiency, %a

Average Controlled

Emission Factor,

lb/VMT

May 0.037 0 7.1

June 0.073 62 2.7

July 0.11 68 2.3

August 0.15 74 1.8

September 0.18 80 1.4

a From Figure 13.2.2-5, #10 :m. Zero efficiency assigned if ground inventory is less than 0.05 gal/yd2

.

1 lb/VMT = 281.9 g/VKT. 1 gal/yd2

 = 4.531 L/m2.

Petroleum resin products historically have been the dust suppressants (besides water) most widely

used on industrial unpaved roads. Figure 13.2.2-5 presents a method to estimate average control

efficiencies associated with petroleum resins applied to unpaved roads.20 Several items should be noted:

1. The term "ground inventory" represents the total volume (per unit area) of petroleum resin

concentrate (not solution) applied since the start of the dust control season.

2. Because petroleum resin products must be periodically reapplied to unpaved roads, the use of

a time-averaged control efficiency value is appropriate. Figure 13.2.2-5 presents control efficiency values

averaged over two common application intervals, 2 weeks and 1 month. Other application intervals will

require interpolation.

3. Note that zero efficiency is assigned until the ground inventory reaches 0.05 gallon per square

yard (gal/yd2

). Requiring a minimum ground inventory ensures that one must apply a reasonable amount

of chemical dust suppressant to a road before claiming credit for emission control. Recall that the ground

inventory refers to the amount of petroleum resin concentrate rather than the total solution.

As an example of the application of Figure 13.2.2-5, suppose that Equation 1a was used to

estimate an emission factor of 7.1 lb/VMT for PM-10 from a particular road. Also, suppose that, starting

on May 1, the road is treated with 0.221 gal/yd2

 of a solution (1 part petroleum resin to 5 parts water) on

the first of each month through September. Then, the average controlled emission factors, shown in

Table 13.2.2-5, are found.

Besides petroleum resins, other newer dust suppressants have also been successful in controlling

emissions from unpaved roads. Specific test results for those chemicals, as well as for petroleum resins

and watering, are provided in References 18 through 21.
1

1/06 Miscellaneous Sources 13.2.2-17Figure 13.2.2-5. Average control efficiencies over common application intervals.
13.2.2-18 EMISSION FACTORS 11/06

13.2.2.4 Updates Since The Fifth Edition

The Fifth Edition was released in January 1995. Revisions to this section since that date are

summarized below. For further detail, consult the background report for this section (Reference 6).

October 1998 (Supplement E)– This was a major revision of this section. Significant changes to

the text and the emission factor equations were made.

October 2001 – Separate emission factors for unpaved surfaces at industrial sites and publicly

accessible roads were introduced. Figure 13.2.2-2 was included to provide control effectiveness estimates

for watered roads.

December 2003 – The public road emission factor equation (equation 1b) was adjusted to remove

the component of particulate emissions from exhaust, brake wear, and tire wear. The parameter C in the

new equation varies with aerodynamic size range of the particulate matter. Table 13.2.2-4 was added to

present the new coefficients. 

January 2006 – The PM-2.5 particle size multipliers (i.e., factors) in Table 13.2.2-2 were

modified and the quality ratings were upgraded from C to B based on the wind tunnel studies of a variety

of dust emitting surface materials.

References For Section 13.2.2

1. C. Cowherd, Jr., et al., Development Of Emission Factors For Fugitive Dust Sources,

EPA-450/3-74-037, U. S. Environmental Protection Agency, Research Triangle Park, NC,

June 1974.

2. R. J. Dyck and J. J. Stukel, "Fugitive Dust Emissions From Trucks On Unpaved Roads",

Environmental Science And Technology, 10(10):1046-1048, October 1976.

3. R. O. McCaldin and K. J. Heidel, "Particulate Emissions From Vehicle Travel Over Unpaved

Roads", Presented at the 71st Annual Meeting of the Air Pollution Control Association, Houston,

TX, June 1978.

4. C. Cowherd, Jr, et al., Iron And Steel Plant Open Dust Source Fugitive Emission Evaluation,

EPA-600/2-79-013, U. S. Environmental Protection Agency, Cincinnati, OH, May 1979.

5. G. Muleski, Unpaved Road Emission Impact, Arizona Department of Environmental Quality,

Phoenix, AZ, March 1991.

6. Emission Factor Documentation For AP-42, Section 13.2.2, Unpaved Roads, Final Report, Midwest

Research Institute, Kansas City, MO, September 1998.

7. T. Cuscino, Jr., et al., Taconite Mining Fugitive Emissions Study, Minnesota Pollution Control

Agency, Roseville, MN, June 1979.

8. Improved Emission Factors For Fugitive Dust From Western Surface Coal Mining Sources,

2 Volumes, EPA Contract No. 68-03-2924, Office of Air Quality Planning and Standards, U. S.

Environmental Protection Agency, Research Triangle Park, NC.
11/06 Miscellaneous Sources 13.2.2-19

9. 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.

10. Size Specific Emission Factors For Uncontrolled Industrial And Rural Roads, EPA Contract

No. 68-02-3158, Midwest Research Institute, Kansas City, MO, September 1983.

11. C. Cowherd, Jr., and P. 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.

12. PM-10 Emission Inventory Of Landfills In The Lake Calumet Area, EPA Contract 68-02-3891, Work

Assignment 30, Midwest Research Institute, Kansas City, MO, September 1987.

13. Chicago Area Particulate Matter Emission Inventory — Sampling And Analysis, EPA Contract

No. 68-02-4395, Work Assignment 1, Midwest Research Institute, Kansas City, MO, May 1988.

14. PM-10 Emissions Inventory Data For The Maricopa And Pima Planning Areas, EPA Contract

No. 68-02-3888, Engineering-Science, Pasadena, CA, January 1987.

15. Oregon Fugitive Dust Emission Inventory, EPA Contract 68-D0-0123, Midwest Research Institute,

Kansas City, MO, January 1992.

16. Climatic Atlas Of The United States, U. S. Department Of Commerce, Washington, DC, June 1968.

17. National Climatic Data Center, Solar And Meteorological Surface Observation Network 1961-1990;

3 Volume CD-ROM. Asheville, NC, 1993.

18. 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.

19. G. E. Muleski, et al., Extended Evaluation Of Unpaved Road Dust Suppressants In The Iron And

Steel Industry, EPA-600/2-84-027, U. S. Environmental Protection Agency, Cincinnati, OH,

February 1984.

20. C. Cowherd, Jr., and J. S. Kinsey, Identification, Assessment And Control Of Fugitive Particulate

Emissions, EPA-600/8-86-023, U. S. Environmental Protection Agency, Cincinnati, OH, August

1986.

21. G. E. Muleski and C. Cowherd, Jr., Evaluation Of The Effectiveness Of Chemical Dust Suppressants

On Unpaved Roads, EPA-600/2-87-102, U. S. Environmental Protection Agency, Cincinnati, OH,

November 1986.

22. Fugitive Dust Background Document And Technical Information Document For Best Available

Control Measures, EPA-450/2-92-004, Office Of Air Quality Planning And Standards, U. S.

Environmental Protection Agency, Research Triangle Park, NC, September 1992.

23. Written communication (Technical Memorandum) from P. Hemmer, E.H. Pechan & Associates,

Inc., Durham, NC to B. Kuykendal, U. S. Environmental Protection Agency, Research Triangle

Park, NC, August, 21, 2003.
13.2.2-20 EMISSION FACTORS 11/06

24. MOBILE6 User Guide, United States Environmental Protection Agency, Office of Transportation

and Air Quality. EPA420-R-02-028, October 2002.

25. Written communication (Technical Memorandum) from G. Muleski, Midwest Research Institute,

Kansas City, MO, to B. Kuykendal, U. S. Environmental Protection Agency, Research Triangle

Park, NC, Subject “Unpaved Roads”, September 27, 2001.

26. Written communication (Technical Memorandum) from W. Kuykendal, U. S. Environmental

Protection Agency, to File, Subject “Decisions on Final AP-42 Section 13.2.2 Unpaved Roads”,

November 24, 2003.

27. C. Cowherd, Background Document for Revisions to Fine Fraction Ratios &sed for AP-42 Fugitive

Dust Emission Factors. Prepared by Midwest Research Institute for Western Governors Association,

Western Regional Air Partnership, Denver, CO, February 1, 2006.