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

Emissions M ethods : 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 V acant lands

In general, each of these emissions source categories includes more specific sub

categories, 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 f

rom 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

categor y 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 (5 th 

### 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 emiss ion 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

nu mber 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 sta te.

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 b een 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 estim ate 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. Opera tions 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 WR AP 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 tem porary 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,

dri lling 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 s ignificant 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

t he 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 d uration 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 n on

- 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 Departm ent 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

c ounty

- 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 o f 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 capit al 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 roa d 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 star ts 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 m oisture 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 resus pension 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 surfac e 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 t ravel 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 su rface 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 var iability 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 mat erial 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 ma y 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/m 2 

### ),

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

c auses 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 r oad 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 f ound to vary directly with the fraction of silt (particles smaller than 75 micrometers [ μ m] 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 ar e 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 i n 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 unpave d 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, d ominated 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 (%)

### 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 e mission 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 E PA 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 rep resents 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 emissio n 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 t ons/acre/yr. For non

agricultural 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 developme nt 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; mechanicall y 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 relate d 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 allocate d 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

- rea dy

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 discu ssed 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 estimatio n 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 i nvolves 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 detail ed 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 e missions 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 ini tial 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 SMO KE 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, altho ugh 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, t he 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 inventor y, 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 fr om 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 (tran sfer)

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

i nventory data files.

SCC Description PM2.5/PM10 Original PM2.5/PM10

Revised

28010 00001 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 0.2SCC Description PM2.5/PM10 Original PM2.5/PM10

Revised

2801000007 Agricul ture 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 2805 030000) 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 Agric ulture 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 E missions;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 Constructi on: 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

- 1 7;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

231 1010070 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 0.1SCC 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: SI C 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 Ma terials 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;A ll 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/Ar terial;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 Othe r 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 Roa ds;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



### F ugitive D ust T ransport F ractions

The concept of fugitive dust transport fractions has been considered and refined in recent years. I t 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

surroundi ng 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

e mitted 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 physica l 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 e stimation 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 Ta ble 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/Wa ter 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, Wes tern 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 Em issions 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 Repo rt. 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 G rid 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.

June 2.

Pollack, A., et al., 2006. Final Repo rt: WRAP Mobile Source Emission Inventories Update. . Prepared for the Western Governors Association by ENVIRON International Corporation, Novato, CA. June 8.