Excerpt from: http://vista.cira.colostate.edu/TSS/Results/Emissions.aspx

Emissions Methods: Fugitive Dust Emissions

Fugitive Dust Emission Source Categories

Fugitive dust emissions, as represented in the WRAP modeling inventories, include 

the following general source categories:

 Agricultural Operations 

 Construction and Mining Operations

 Road Dust

 Windblown Dust from Vacant lands

In general, each of these emissions source categories includes more specific subcategories, as described below. For each, a brief description characterizing the source 

and the general methodology used to estimate emission rates are provided. For the most 

part, the estimation methodologies are based on AP-42 guidance. In the case of the 

WRAP inventory development, specific modifications and/or deviations from these 

general methodologies are noted. 

Agricultural Operations

Dust emissions from agricultural operations result from the disturbance of soil inherent in 

the preparation of agricultural lands for planting and after harvest activities. These 

include discing, leveling, and other mechanical operations. Dust emissions from this 

category exhibit a seasonal pattern as planting and harvesting generally occur in the 

spring and fall, respectively. In addition, agricultural practices and planting and 

harvesting calendars are crop-specific in many cases. In addition to operations associated 

with agricultural land preparation and harvesting, this emission source category includes 

dust emissions arising from the transport of agricultural crops as well as dust from 

agricultural feedlots or confined animal feeding operations (CAFOs). 

While the current version of AP-42 guidance (5th Edition) does not include estimation 

methodologies for this dust emission category, guidance was provided in previous 

versions. However, the California Air Resource Board has developed procedures for 

estimating PM10 dust emissions from agricultural activities, and these procedures were 

adopted for development of the WRAP modeling inventories, as describe below.

Particulate dust emissions from agricultural operations are estimated as the product of 

crop-specific emission factors and appropriate activity data. Emission factors vary as a 

function of the specific soil preparation operation used for a particular crop, while the 

activity data is based on harvested acreage, modified by factors to account for the typical 

number of passes per acre required to prepare a field for planting. The activity data used 

for estimating land preparation emissions are based on state summaries of crop acreage 
harvested, further spatially allocated by county and crop type for the each state. 

Acre-passes (the total number of passes typically performed to prepare land for planting 

during a year) are used to compute crop specific emission factors for land preparation. 

These land preparation operations may occur following harvest or closer to planting, and 

can include discing, tilling, land leveling, and other operations. Each crop is different in 

the type of soil operations performed and when they occur; crop profiles from similar 

crops are used for cases where specific crop data has not been updated. For updating 

acre-pass data, specific information on when agricultural operations occur is used to 

create detailed temporal profiles for PM emissions from agricultural land preparations.

Operation specific PM10 emission factors used to estimate the crop specific emissions for 

agricultural land preparations are based on data developed by the University of California 

Davis. Five emission factors were developed using 1995 to 1998 test data measured in 

cotton and wheat fields in California. Operations tested included root cutting, discing, 

ripping and subsoiling, land planing and floating, and weeding. The PM2.5/PM10 ratio 

for agricultural tilling dust used by CARB is 0.222.

PM dust emissions from agricultural activities were developed for the WRAP by Eastern 

Research Group (ERG). A detailed discussion of the development and data sources used 

by ERG can be found in ERG, 2006.

Construction Operations

Construction operations are significant source of dust emissions that may have a 

substantial temporary impact on local air quality. This emission source category includes 

both residential and non-residential construction as well as road construction. Dust 

emissions during the construction of buildings or roads are associated with land clearing, 

drilling and blasting, ground excavation, and cut and fill operations (i.e., earth moving). 

Dust emissions can vary substantially from day to day, depending on the level of activity, 

the specific operations, and the prevailing meteorological conditions. A significant 

amount of the dust emissions result from construction vehicle traffic over temporary 

roads at construction sites.

Residential Construction 

PM dust emissions from residential construction are a function of the total acres of land 

disturbed and the volume of soil excavated. The volume of soil excavated also varies by 

type of structure under construction. County-level housing starts by structure type are 

used to estimate the disturbed acreage for construction. These data can be obtained from 

the US Census Bureau and the Department of Commerce. Volume of soil excavated is 

estimated based on assumed characteristics of single-family homes and whether the 

structures include basements. 

Emission factors are estimated based on structure type and duration of construction. For 

single family houses, construction duration is assumed to be 6 months; for apartment 
buildings, 12-month construction duration is assumed. The emissions factors vary from 

approximately 0.011 tons PM10/acre-month to 0.11 tons PM10/acre-month. Additional 

adjustments are applied based on soil moisture, silt content and control efficiency. The 

ratio of PM2.5 to PM10, as documented in AP-42, is assumed to be 0.20.

Non-residential/Commercial Construction 

Dust emissions from non-residential and commercial construction are a function of the 

total acres of land disturbed. Activity data is based on the total value of the construction 

in $MM. Data for construction values are typically obtained on a national basis from the 

Department of Commerce. County-level data is allocated from national estimates using 

employment statistics. County-level valuation data is then used to estimate total acreages 

disturbed during construction. An assumed value of 1.55 acres/$MM is applied to the 

county-level valuation data, as specified in AP-42. 

An emission factor of 0.19 tons PM10/acre-month is used for the initial emissions 

estimate. The assumed construction duration is typically 11 months. As with residential 

construction, emission factors are adjusted to reflect variations in silt content, soil 

moisture and control efficiency. The ratio of PM2.5 to PM10, as documented in AP-42, 

is assumed to be 0.20.

Road Construction

PM dust emissions from road construction activities are a function of acres disturbed 

during construction. Activity data is based on data obtained from the4 Federal Highway 

Administration (FHWA) as a function of road type. State-level new miles of road 

constructed are estimated from 2002 FHWA state expenditures for capital outlay data, in 

thousands of dollars. These data are then converted to new miles of road constructed 

using 4/mile conversions from the North Carolina Department of Transportation 

(NCDOT) data. These data also vary by type of road. The new miles of road constructed 

is then used to estimate total acres disturbed using conversion factors for acres 

disturbed/mile of road constructed, as a function of road type. State-level acre disturbed 

are allocated top the county-level based on residential housing starts data. 

An emission factor of 0.42 tons PM10/acre-month is used to estimate PM10 dust 

emission from road construction activities. A construction duration of 12 months is 

typically assumed. Adjustments are applied for variations in silt content, soil moisture 

and control efficiency

PM dust emissions from construction activities were developed for the WRAP by Eastern 

Research Group (ERG). A detailed discussion of the development and data sources used 

by ERG can be found in ERG, 2006.

Paved Road Dust
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 emissions from 

vehicles in the form of exhaust, brake wear and tire wear emissions, and resuspension of 

loose material on the road surface. In general terms, resuspended particulate emissions 

from paved roads originate from, and result in the depletion of the loose material present 

on the surface (i.e., the surface loading). In turn, that surface loading 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. 

Dust emissions from paved roads have been found to vary with 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 [μm] in physical diameter) per unit area of the travel surface. The total road 

surface dust loading consists 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.” 

The surface silt loading (sL) provides a means of characterizing seasonal variability in a 

paved road emission inventory. In many areas of the country, road surface silt loadings 

are heaviest during the late winter and early spring months when the residual loading 

from snow/ice controls is greatest. Once replenishment of fresh material is eliminated, the 

road surface silt loading can be expected to reach an equilibrium value, which is 

substantially lower than the late winter/early spring values.

Particulate emissions from road surfaces due to vehicle travel on a dry paved road may be 

estimated using the following empirical expression:

where, 

E = particulate emission factor (having units matching the units of k),

k = particle size multiplier for particle size range,

sL = road surface silt loading (grams per square meter, g/m2),

W = average weight (tons) of the vehicles traveling the road, and

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

Unpaved Road Dust 

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 quantity of dust emissions from a given segment of unpaved 

road varies linearly with the volume of traffic. Dust emissions also 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 [μm] in physical diameter) in the road surface 

materials. As the silt content of a rural dirt road will vary with geographic location, it 

should be measured for use in projecting emissions. For a conservative approximation, 

the silt content of the parent soil is often 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. 

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 important in determining differences in 

emission levels between a hot desert environment and a cool moist location.

The PM10 emission factors presented below are based on stepwise linear regressions of 

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

amount of information available for PM2.5, the expression for that particle size range has 

been scaled against the PM10 results. The following empirical expressions may be used 

to estimate the quantity of size-specific particulate emissions from an unpaved road in 

pounds (lb) per vehicle mile traveled (VMT). For vehicles traveling on unpaved surfaces 

at industrial sites, emissions are estimated from the following equation:

E = k (s/12)a(W/3)b

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

emissions may be estimated from the following equation:

where k, a, b, c and d are empirical constants, and

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

s = surface material silt content (%)

W = mean vehicle weight (tons)

M = surface material moisture content (%)

  C

c

a d

(M/0.5)

k (s/12) (S/30) E
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. 

For the WRAP, paved and unpaved road dust emissions were estimated using updated 

VMT for the base and future years provided by state and local contacts as part of the base 

and future year survey work. Any updated road dust controls provided were also 

incorporated into the estimates. It is important to note that since the previous WRAP 

road dust emissions estimates were prepared, EPA’s guidance on estimating paved and 

unpaved road dust emissions was updated; see 

http://www.epa.gov/ttn/chief/ap42/ch13/index.html. The WRAP Emissions Forum opted 

to update the road dust emissions only to reflect updated VMT and controls, and not to 

reflect the updated EPA guidance methodology. 

A more detailed discussion of the development of paved and unpaved road dust 

emissions can be found in Pollack, et al., 2006

Windblown Dust from Vacant lands

Fugitive dust from wind erosion of agricultural and vacant lands represents a significant 

source of particulate matter emissions, particularly throughout the Western US. For 

agricultural windblown dust, emission factors may be estimated using the USDA wind 

erosion equation (WEQ) (ARB, 1997) which relates the PM10 emission factors to 

various parameters characterizing the specific crops, soil erodibility, surface roughness, 

vegetative cover and climatic factors. PM10 emissions are obtained by multiplying the 

resulting emission factor by the total crop acreage in units of tons/acre/yr. For nonagricultural vacant lands, numerous wind tunnel studies have been conducted to estimate 

appropriate emission factors based on soil types, surface conditions and threshold friction 

velocities. 

Windblown fugitive dust emissions have not been estimated by EPA in previous national 

emission inventories. ENVIRON has recently completed the development of a 

windblown dust model for use in WRAP regional haze modeling efforts (Mansell, et. al, 

2006). A description of the model development and the most recent results for the WRAP 

states can be found at http://www.wrapair.org/forums/dejf/fderosion.html. The model 

estimates fugitive PM dust emissions from vacant lands given wind speed data. All 

vacant land types are considered; mechanically disturbed lands, e.g., agricultural tilling, 

are not included. The current version of the model is set up to use the regional-scale land 

use databases for characterizing vacant lands, and also requires specification of soil 

characteristics, specifically soil texture. The model provides hourly gridded emission 

estimates that can be easily summarized on a county level. A complete detailed 

description of the model development and requisite input databases is included in the 

project Final Report and related documentation (Mansell, et al., 2006)
Emissions Modeling for Fugitive Dust Sources 

For regional air quality modeling, the county-level, annual (or seasonal/monthly) PM 

dust emissions are spatially allocated to the modeling grid and temporally allocated 

hourly. In addition, fugitive dust transport fractions are applied to the PM dust emissions 

estimates prior to their use in the air quality model. The WRAP RMC utilized the 

SMOKE emissions processing system to develop the necessary air quality model-ready 

dust emissions data. 

Similar to emissions modeling for other source sectors, the fugitive dust emissions were 

extracted from the point, area and mobile source inventory data files and processed 

separately through SMOKE. Dust emissions were extracted from the inventory files 

based on SCCs. Processing the dust emissions separately allows for more efficient 

quality assurance of the data and the direct application of the fugitive dust transport 

fractions. The application of transport fractions is discussed in more detail below. With 

the exception of the windblown dust emissions, transport fractions are applied using the 

growth and control modules of SMOKE. The windblown dust emission models 

incorporate the transport fractions directly in the estimation methodologies used. Note 

that, except for the gridded emissions summaries, the data presented in the summaries 

below do not reflect the application of transport fractions. 

The final step in preparation of PM dust emissions for air quality modeling involves the 

spatial and temporal allocation of annual, county-level emissions estimates. The PM10 

emissions estimates are also speciated as PMC (=PM10–PM2.5) and PMFINE (=PM2.5). 

Speciation and spatial and temporal allocation is performed based on detailed SCCs. The 

revised PM2.5/PM10 ratios, developed by MRI (MRI, 2005), were applied the final 

versions of the gridded dust emission inventories presented below. 

Fugitive Dust SCCs and PM2.5/PM10 Ratios

The development of the WRAP Base02b fugitive dust emissions inventory were based on 

the specific SCCs extracted from the area and point source inventory data used in the 

SMOKE emissions processing. As noted in Mansell (2006), several detailed source 

category codes that were either not included in the initial list of SCCs for fugitive dust 

processing, or were found to be reported using the most general SCC descriptions. For 

example, in some counties in Arizona, construction dust emissions were reported in terms 

of the general “all processes” SCC and were not included extracted from the area source 

inventory files. Likewise, agricultural dust emissions in California were provided 

separately from other fugitive dust source categories and were therefore initially not 

processed as fugitive dust within the SMOKE emissions modeling. 

The ratio of PM2.5 to PM10, as reported in the inventory data were evaluated for the 

Base02b fugitive dust emission inventory (Mansell, 2006). The PM2.5/PM10 ratios are 

generally consistent with AP-42 guidance documents, although some exceptions were 

found in the Base02b inventory. Table 1 summarizes these ratios based on AP-42 and 

also presents the revised factors as recommended by MRI. In 2005, the DEJF initiated a 
project to evaluate the fine fraction of particulate matter in fugitive dust. The result 

of this study indicated that the analysis procedures and findings on which the EPA's 

AP-42 Guidance is based may be biased by as much as a factor of 2. The completed 

DEJF study (MRI, 2005) provided recommended revisions, by dust emission source 

category, and are included in Table 1.

Table 2 presents the complete listing of fugitive dust emission source category codes 

used by the RMC for extracting data from area and point source inventory data files. 

Also included in Table 2 are the original and revised PM2.5/PM10 ratios used in the 

SMOKE processing. Note that several SCCs listed were not included in the 

development of the Base02b modeling inventories. Based on the initial review of 

emissions data for the Base02b inventory, these SCCs have subsequently been 

included in the current SMOKE processing procedures and are reflected in the 

Plan02b and Base18a fugitive dust emissions inventory summaries described below. 

Table 1. AP-42 PM2.5/PM10 ratios and recommended ratios from MRI, 2005.

Source Category AP-42 Section PM2.5/PM10 Ratio

Current Proposed

Paved Roads 13.2.1 0.25 0.15

Unpaved Roads 13.2.2 0.15 0.10

Construction & 

Demolition

-- 0.208 0.10

Aggregate 

Handling/Storage Piles

13.2.4 0.314 0.10 (traffic)

0.15 (transfer)

Industrial Wind 

Erosion

13.2.5 0.40 0.15

Agricultural Tilling -- 0.222 0.20

Table 2. Fugitive dust emission SCCs extracted from area and point source emissions 

inventory data files. 

SCC Description

PM2.5/PM10 

Original 

PM2.5/PM10 

Revised

2801000001 Agriculture Production - Crops;Agriculture - Crops;Land Breaking 0.222 0.2

2801000002 Agriculture Production - Crops;Agriculture - Crops;Planting 0.222 0.2

2801000003 Agriculture Production - Crops;Agriculture - Crops;Tilling 0.222 0.2

2801000004 Agriculture Production - Crops;Agriculture - Crops;Defoliation 0.222 0.2

2801000005 Agriculture Production - Crops;Agriculture - Crops;Harvesting 0.222 0.2

2801000006 Agriculture Production - Crops;Agriculture - Crops;Drying 0.222 0.2
SCC Description

PM2.5/PM10 

Original 

PM2.5/PM10 

Revised

2801000007 Agriculture Production - Crops;Agriculture - Crops;Loading 0.222 0.2

2801000008 Agriculture Production - Crops;Agriculture - Crops;Transport 0.222 0.2

2805000000 Agriculture Production - Livestock;Agriculture - Livestock;Total 0.222 0.2

2805001000 Agriculture Production - Livestock;Beef Cattle Feedlots;Dust Kicked-up by Hooves 0.222 0.2

2805001001 Agriculture Production - Livestock;Beef Cattle Feedlots;Feed Preparation 0.222 0.2

2805005000 Agriculture Production - Livestock;Poultry Operations;Total (use 2805030000) 0.222 0.2

2805005001 Agriculture Production - Livestock;Poultry Operations;Feed Preparation 0.222 0.2

2805010000

Agriculture Production - Livestock;Dairy Operations;Total (use 2805020000 and 

subsets) 0.222 0.2

2805010001 Agriculture Production - Livestock;Dairy Operations;Feed Preparation 0.222 0.2

2805015000 Agriculture Production - Livestock;Hog Operations;Total (use 2805025000) 0.222 0.2

2805015001 Agriculture Production - Livestock;Hog Operations;Feed Preparation 0.222 0.2

2805020000 Agriculture Production - Livestock;Cattle and Calves Waste Emissions;Total 0.222 0.2

2805025000 Agriculture Production - Livestock;Hogs and Pigs Waste Emissions;Total 0.222 0.2

2805030000 Agriculture Production - Livestock;Poultry Waste Emissions;Total 0.222 0.2

2805035000 Agriculture Production - Livestock;Horses and Ponies Waste Emissions;Total 0.222 0.2

2805040000 Agriculture Production - Livestock;Sheep and Lambs Waste Emissions;Total 0.222 0.2

2805045001 Agriculture Production - Livestock;Goats Waste Emissions;Total 0.222 0.2

2275085000 Aircraft;Unpaved Airstrips;Unpaved Airstrips n/a 0.1

2311000000 Construction: SIC 15 - 17;All Processes;Total 0.208 0.1

2311000010 Construction: SIC 15 - 17;All Processes;Land Clearing 0.208 0.1

2311000040 Construction: SIC 15 - 17;All Processes;Ground Excavations 0.208 0.1

2311000050 Construction: SIC 15 - 17;All Processes;Cut and Fill Operations 0.208 0.1

2311000060 Construction: SIC 15 - 17;All Processes;Construction 0.208 0.1

2311000070 Construction: SIC 15 - 17;All Processes;Vehicle Traffic 0.208 0.1

2311010000 Construction: SIC 15 - 17;General Building Construction;Total 0.208 0.1

2311010010 Construction: SIC 15 - 17;General Building Construction;Land Clearing 0.208 0.1

2311010040 Construction: SIC 15 - 17;General Building Construction;Ground Excavations 0.208 0.1

2311010050 Construction: SIC 15 - 17;General Building Construction;Cut and Fill Operations 0.208 0.1

2311010060 Construction: SIC 15 - 17;General Building Construction;Construction 0.208 0.1

2311010070 Construction: SIC 15 - 17;General Building Construction;Vehicle Traffic 0.208 0.1

2311020000 Construction: SIC 15 - 17;Heavy Construction;Total 0.208 0.1

2311020010 Construction: SIC 15 - 17;Heavy Construction;Land Clearing 0.208 0.1

2311020040 Construction: SIC 15 - 17;Heavy Construction;Ground Excavations 0.208 0.1

2311020050 Construction: SIC 15 - 17;Heavy Construction;Cut and Fill Operations 0.208 0.1

2311020060 Construction: SIC 15 - 17;Heavy Construction;Construction 0.208 0.1

2311020070 Construction: SIC 15 - 17;Heavy Construction;Vehicle Traffic 0.208 0.1

2311030000 Construction: SIC 15 - 17;Road Construction;Total 0.208 0.1

2311030010 Construction: SIC 15 - 17;Road Construction;Land Clearing 0.208 0.1

2311030040 Construction: SIC 15 - 17;Road Construction;Ground Excavations 0.208 0.1

2311030050 Construction: SIC 15 - 17;Road Construction;Cut and Fill Operations 0.208 0.1

2311030060 Construction: SIC 15 - 17;Road Construction;Construction 0.208 0.1

2311030070 Construction: SIC 15 - 17;Road Construction;Vehicle Traffic 0.208 0.1

2311040000 Construction: SIC 15 - 17;Special Trade Construction;Total 0.208 0.1

2305000000 Industrial Processes;Mineral Processes: SIC 32;All Processes;Total n/a 0.1

2305070000

Industrial Processes;Mineral Processes: SIC 32;Concrete, Gypsum, Plaster 

Products;Total n/a 0.1
SCC Description

PM2.5/PM10 

Original 

PM2.5/PM10 

Revised

2305080000 Industrial Processes;Mineral Processes: SIC 32;Cut Stone and Stone Products;Total n/a 0.1

2325020000 Industrial Processes;Mining and Quarrying: SIC 14;Crushed and Broken Stone;Total n/a 0.1 

2325030000 Industrial Processes;Mining and Quarrying: SIC 14;Sand and Gravel;Total n/a 0.1

2325040000

Industrial Processes;Mining and Quarrying: SIC 14;Clay, Ceramic, and 

Refractory;Total n/a 0.1

2530000020 Storage and Transport;Bulk Materials Storage;All Storage Types;Cement n/a 0.1

2530000100 Storage and Transport;Bulk Materials Storage;All Storage Types;Limestone n/a 0.1 

2530000120 Storage and Transport;Bulk Materials Storage;All Storage Types;Sand n/a 0.1

2325000000 Mining and Quarrying: SIC 14;All Processes;Total n/a 0.1

2294000000 Paved Roads;All Paved Roads;Total: Fugitives 0.25 0.12

2294000001 Paved Roads;All Paved Roads;Total: Average Conditions - Fugitives 0.25 0.12

2294000002 Paved Roads;All Paved Roads;Total: Sanding/Salting - Fugitives 0.25 0.12

2294005000 Paved Roads;Interstate/Arterial;Total: Fugitives 0.25 0.12

2294005001 Paved Roads;Interstate/Arterial;Total: Average Conditions - Fugitives 0.25 0.12

2294005002 Paved Roads;Interstate/Arterial;Total: Sanding/Salting - Fugitives 0.25 0.12

2294010000 Paved Roads;All Other Public Paved Roads;Total: Fugitives 0.25 0.12

2294010001 Paved Roads;All Other Public Paved Roads;Total: Average Conditions - Fugitives 0.25 0.12

2294010002 Paved Roads;All Other Public Paved Roads;Total: Sanding/Salting - Fugitives 0.25 0.12

2294015000 Paved Roads;Industrial Roads;Total: Fugitives 0.25 0.12

2294015001 Paved Roads;Industrial Roads;Total: Average Conditions - Fugitives 0.25 0.12

2294015002 Paved Roads;Industrial Roads;Total: Sanding/Salting - Fugitives 0.25 0.12

2296000000 Unpaved Roads;All Unpaved Roads;Total: Fugitives 0.15 0.1

2296005000 Unpaved Roads;Public Unpaved Roads;Total: Fugitives 0.15 0.1

2296010000 Unpaved Roads;Industrial Unpaved Roads;Total: Fugitives 0.15 0.1

Fugitive Dust Transport Fractions

The concept of fugitive dust transport fractions has been considered and refined in recent 

years. It has been recognized that, due to various mechanisms, dust particles are subject 

to near source removal. These mechanisms include gravitational settling, particle 

deposition to the ground and impaction and removal due to particle capture by the 

surrounding vegetation canopy and other physical structures. The EPA for many years 

had promoted the “divide by four” approach for reducing the emission from fugitive dust 

sources to account for these processes. The idea is that only a limited amount of the dust 

emitted by a particular source is transported significantly to affect the total available 

emissions in the atmosphere for air quality grid modeling. 

Recent research has shown that the amount of fugitive dust captured in the surround 

canopy or on physical structures can be related to the physical characteristics of the land 

surface, i.e., land use/land cover. The EPA recently developed county-level transport 

fractions for use in emissions inventory development for air quality modeling (Pace, 

2003; 2005). The county-level transport fractions were based on the percentage of land 

use in each county. The transport fractions were calculated as a weighted sum of 

landuse-specific fractions for each landuse type. Previously, landuse percentages were 

derived from the BELD3 LULC database. In the WRAP fugitive dust emission 
inventory, transport fractions were revised to reflect a more current LULC database. The 

current gridded dust emissions for the WRAP are based on the 2000 North American 

Land Cover (2000 NALC) database. A description of the 2000 NALC database can be 

found in Mansell and Hoats, 2005. 

For the windblown dust emissions, transport fractions were developed and applied within 

the wind blown dust model based on the gridded landuse data used in the estimation 

methodology. A discussion of the application of the transport fraction for windblown 

dust emissions can be found in Mansell, et al., 2006. The original and revised transport 

fractions for each of the relevant land use types are presented in Table 3. 

Table 3. Fugitive dust transport fractions as a function of landuse.

Fugitive Dust Transport Fractions

LULC Category Original Revised

Urban 0.30 0.00

Agriculture 0.85 0.75

Grassland 0.70 0.75

Shrubland 0.60 0.75

Forest 0.30 0.00

Barren/Water 0.97 1.00

Gridded Fugitive Dust Emission Inventory Summaries

Summaries of the gridded fugitive dust source emissions for the Base02b, Plan02c and 

Base18b inventories by state and county, annual and seasonal periods, can be found on 

the TSS at: http://vista.cira.colostate.edu/tss/Results/Emissions.aspx. 

References

Countess Environmental, 2004. WRAP Fugitive Dust Handbook. Prepared for Western 

Governor’ Association, Western Regional Air Partnership. Prepared by Countess 

Environmental. Midwest Research Institute. November 15.

ERG, 2006. Documentation for Base2002 WRAP point and area inventories, not available until 

January, 2006. (PLACEHOLDER)

Mansell G., et al., 2006. Final Report: Fugitive Wind Blown Dust Emissions and Model 

Performance Evaluation, Phase II. Prepared for the Western Governors 

Association by ENVIRON International Corporation, Novato, CA. May 5. 

Mansell G., 2006. Summary of the WRAP Fugitive Dust Emissions Inventories. 

Technical Memorandum prepared for the Western Governors Association by 

ENVIRON International Corporation, Novato, CA. 22 September. 

MRI, 2005. Analysis of the Fine Fraction of Particulate Matter in Fugitive Dust. Draft 
Project Report. Prepared for Western Governor’ Association, Western Regional 

Air Partnership. Prepared by Midwest Research Institute. August 17.

Pace, T.G., 2003. A Conceptual Model to Adjust Fugitive Dust Emissions to Account for 

Near Source Particle Removal in Grid Model Applications. U.S. EPA. August 22.

Pace, T.G., 2005. Methodology to Estimate the Transportable Fraction (TF) of Fugitive 

Dust Emissions for Regional and Urban Scale Air Quality Analyses. U.S. EPA. 

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Pollack, A., et al., 2006. Final Report: WRAP Mobile Source Emission Inventories Update. . 

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