Air and Radiation EPA420-R-05-021 

December 2005 

NR-014d 

Geographic Allocation of

Nonroad Engine Population

Data to the State and 

County Level 
EPA420-R-05-021 

December 2005 

Geographic Allocation of Nonroad Engine Population

Data to the State and County Level

NR-014d

Assessment and Standards Division 

Office of Transportation and Air Quality 

U.S. Environmental Protection Agency 

NOTICE

This technical report does not necessarily represent fi nal EPA decisions or positions.

It is intended to present technical analysis of issues using data that are currently available.

The purpose in the release of such reports is to facilitate the exchange of

technical information and to inform the public of technical developments which

may form the basis for a fi nal EPA decision, position, or regulatory action.
Purpose 

The purpose of this report is to discuss the methodology and data that the Environmental 

Protection Agency (EPA) uses in the NONROAD2005 model to allocate equipment populations 

from the national to the state and county level. 

Background 

EPA has developed a national nonroad air emissions inventory model called NONROAD. 

This model provides a tool for EPA, States, regional air pollution organizations, and local air 

pollution control agencies to use in estimating pollution from nonroad vehicles and equipment 

for State Implementation Plans (SIPs), as required by the 1990 Clean Air Act Amendments, and 

other regulatory needs. 

With some exceptions, the model uses national engine population or sales data from Power 

Systems Research (PSR), a company that tracks the sales and populations of all types of engines 

sold in the U.S. Since PSR also matches the engines to the equipment in which they are used, 

the term “equipment populations” will be used for the purpose of this report to describe the 

population of both nonroad equipment and the engines used to power that equipment. EPA 

believes that PSR provides the most comprehensive national nonroad equipment population data 

currently available. PSR updates these data on a yearly basis. However, in some cases, EPA has 

used population data from a source other than PSR when such a source is available and found to 

be more accurate than the PSR data. For some types of equipment (e.g., ATVs and 

snowmobiles) NONROAD uses equipment sales or population data from industry sources or 

state registration data. 

The PSR database also geographically allocates equipment populations from the national to 

the county level and then aggregates the county-level populations to generate state totals. 

However, the methods and data that PSR uses to perform these allocations have only been 

explained in general terms, since PSR considers their methods to be proprietary information. 

Since the EPA wants the methods that it uses to allocate equipment populations in NONROAD 

to be fully understood by EPA and the public, we have decided to use publicly available data as 

much as possible to serve as factors to allocate the national PSR equipment populations to the 

county level. State/local users may elect to substitute their own equipment population data, 

where such data is well-documented and specific to local conditions, for SIP purposes. These 

data may be derived from well-designed and executed surveys or other information sources. In 

order to be used as input data for NONROAD, these surveys or alternative sources of 

information should include the hours per year that the various types of equipment are used, as 

well as equipment populations. Using only local population data in NONROAD without the 

corresponding local activity data (or vice-versa) could result in distortions in the emission 

inventory estimates that NONROAD calculates. 

1 
Allocating Activity Versus Engine Population 

One central feature of the NONROAD model is that it uses the same methods to allocate 

equipment populations, equipment activity, and equipment emissions to specific geographic 

areas. To the extent that a given equipment type is operated at the same power level (load factor), 

operating cycle, and for the same number of hours in all areas, the distribution of the population 

of this equipment type will match the distribution of its activity and engine emissions. In general, 

population, activity, and emissions will tend to track one another, since emissions are a direct 

function of equipment activity and the conditions that stimulate increased engine activity are 

likely to stimulate increased engine populations. 

In reality, however, the geographic distribution of nonroad equipment may differ from the 

geographic distribution of emissions from these equipment. Because an equipment type’s 

operating cycle and load factor most likely do not vary significantly by geographic area, the 

difference between the distribution of population and emissions depends on variations in the 

amount of activity. The amount of activity that each piece of nonroad equipment of a given type 

experiences can vary from area to area as a result of variations in local economies, weather 

patterns, or other local conditions. For example, agricultural equipment and residential 

lawnmowers may experience more use per year in areas with longer growing seasons; 

construction equipment is likely to be used more intensively in areas experiencing an economic 

boom and less intensively where the economy is not as robust. 

Equipment activity may also be influenced by the age of the equipment. EPA has 

encountered some general information indicating that equipment activity declines as the 

equipment gets older. For example, older pieces of agricultural or construction equipment might 

be kept as spares to be used if newer equipment breaks down or if an extra piece of equipment is 

needed to complete a task once in awhile. Unfortunately, EPA has been unable to obtain precise 

quantifiable data to model this relationship for any type of nonroad equipment. EPA will 

continue to look for such data for the development of the nonroad portion of the MOVES model. 

Currently, the NONROAD2005 model is capable of handling only one activity level for each 

equipment type across all parts of the U.S. As a result, the model uses the same factors to 

allocate engine populations and their associated activity. Wherever possible, EPA has sought 

indicators related to engine activity, since it is engine activity that results in emissions (except for 

diurnal and hot soak emissions, which are more closely related to engine populations). In some 

cases, however, EPA was unable to find a suitable activity indicator and had to rely on 

population-related indicators as a surrogate for engine activity. In this report, the EPA has 

attempted to be explicit as to whether each equipment type’s geographic allocation factor is an 

activity-oriented indicator, a population-oriented indicator, or an indicator that is reasonable for 

both population and activity. 

EPA welcomes suggestions from the nonroad industry, state and local air quality agencies, 

and other interested parties concerning improved methods to allocate equipment categories to the 

county level. EPA also invites state and local air quality agencies to substitute adequately 

2 
documented local data for the national default allocation estimates, in accordance with EPA 

guidance, for any categories where the national default estimates may not adequately reflect local 

conditions. 

Through the EPA Office of Air and Radiation’s (OAR) Section 103/105 Grant Program, EPA 

has sought to encourage regional, state, and local air pollution organizations to develop and 

apply methods to collect local nonroad equipment population and activity data for categories of 

equipment that contribute significantly to the total nonroad emissions inventory. EPA awarded a 

grant to the Northeast States Coordinated Air Use Management Association (NESCAUM) in 

1999 to conduct a multi-year effort that generally includes the following: 

1) performing a review and analysis of known survey methods that have been used by state and 

local air agencies to collect local nonroad equipment activity data, 

2) choosing one of the survey methods reviewed and analyzed in part 1 or developing a new 

method to be included in EPA guidance to state and local air agencies, and 

3) applying the chosen method to selected areas to ensure that it works properly and produces 

reasonable and useful results. 

EPA also awarded a Section 103/105 grant to the California Air Resources Board (ARB) to 

conduct a lawn and garden equipment survey. This survey targeted potential residential, 

commercial, and municipal/institutional users of lawn and garden equipment. This project 

included a questionnaire about the number and type of equipment owned and used. In an attempt 

to develop better activity data, the ARB also distributed data loggers to willing volunteers to 

record the time and date of when the piece of equipment was started and shut off. The results of 

the work performed under this grant are available in a report at the following address on the 

California Air Resources Board web site. 

www.arb.ca.gov/msei/off-road/updates.htm 

EPA welcomes suggestions and comments about these efforts, as well as information about 

surveys of nonroad equipment that have been conducted in the past or are presently being 

conducted, from stakeholders and other interested parties. 

Methodology 

NONROAD is designed to use various types of economic and industry information that 

can be related to equipment population or activity to distribute national equipment populations 

and their associated activity to the state and county level. For example, commercial equipment is 

allocated in direct proportion to the number of wholesale employees in each county. This 

surrogate information constitutes a geographic allocation factor. The model can use a single 

allocation factor for entire categories of nonroad equipment, or it can use separate factors for one 

or more equipment types within a category. 

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The model calculations assume that each piece of equipment of a given type experiences 

the same annual activity (i.e., hours/year) 1. This reduces the allocation problem to one of 

allocating engine populations. In essence, the allocation factor serves as a measure of relative 

population and activity. 

To optimize model speed it is designed to only allocate down one level from the input 

level of equipment populations. I.e., to do a county level run, the model needs to start from state 

population files. Therefore national equipment populations are pre-allocated to state population 

input files outside of the model. Thus, when a state level model run is chosen, no additional 

allocation is needed during the model run, since that state population file can be used directly. 

For most equipment types, where the same allocation surrogate is used for both US-tostate and state-to-county levels of allocation, the state population files are developed by (a) 

adding up the state-to-county allocation factors for each surrogate and each state, and then (b) 

calculating the ratio of that state total to the US total for each surrogate (which is the US-to-state 

allocation factor), and finally (c) multiplying that US-to-state allocation factor by the US total 

population, using the appropriate surrogate for each type of equipment. This can be expressed as 

shown in the following equation. 

(Equip. Population)state = (Equip. Population)national X Sum(Surrogatescounties in state)

 Surrogatenational 

During a county level model run the state-to-county allocation factors are applied to the 

state equipment population inputs to calculate the output county-level equipment populations, as 

shown below. 

(Equip. Population)county = (Input Equip. Population)state X Surrogatecounty

 Surrogatestate 

There are a few equipment types that use a modified form of the above method. As 

explained in more detail below in the sections covering each equipment type, snowmobiles, 

ATV's, offroad motorcycles, and recreational marine equipment use an equipment-specific 

method to allocate from national to state (done outside of the model) and then use the above 

method to allocate from state to county within the model. 

Addition of Puerto Rico and U.S. Virgin Islands 

For NONROAD2005 a limited capability of modeling nonroad emissions in Puerto Rico 

(each of the 79 "municipios") and the U.S. Virgin Islands (St. Thomas, St. John, and St. Croix) 

has been added to the model. Allocation data at the territory and county level for these areas are 

available for many, but not all of the surrogates that are used for the rest of the country. An 

1

 The annual activity can be distributed differently throughout the year for different geographic regions. 

4 
additional complication is that the nationwide equipment populations that serve as the basis from 

which the state allocations are calculated do not include equipment from these U.S. territories. 

Therefore, the methodology described above for the 50 states, D.C., and their counties has been 

modified somewhat for these territories. 

In cases where comparable data exist for the territories as for the states, the allocation 

factors are computed exactly the same way as for the states, as the ratio of the territory or state 

indicator value (e.g., human population or harvested acres) to the value of the same indicator for 

the entire U.S. (sum of all 50 states plus D.C. but not the territories). This means that the sum of 

all state and territory allocations adds up to more than 1.0, since the territories are treated as 

incremental to the US total equipment populations. 

There were only a few indicators that were not available for the territories. In the case of 

offroad motorcycles and ATVs, the same per-capita equipment allocation was assumed as for 

Florida. The number of landscape service employees (used for commercial lawn and garden 

equipment) was assumed to be equal to Hawaii on a per-capita basis. Since a direct estimate of 

marine fuel consumption in the territories was not available to allocate boating activity, Coast 

Guard data on the number of registered boats in the territories relative to Florida was used to 

calculate the allocation inputs. An example of this calculation is shown below. The same basic 

method was used for motorcycles/ATVs, landscape service employees, and boating activity. 

Harvested acres is the allocation indicator used for farm equipment. Therefore, the farm 

equipment population of Puerto Rico is estimated as follows. 

MCATVPR = MCATVFL X POPPR / POPFL

 Where 

POP = Human population of Puerto Rico (PR) or Florida (FL) 

MCATV = Number of offroad motorcycles & ATVs in Puerto Rico or Florida 

For allocation from total territory to "county" area within the territory (i.e., municipio or 

island), a similar approach was used. If county level data for a given surrogate was available, it 

was used directly as the ratio of the county value to the territory value. If county level data was 

not available, the ratio of human population of each county to the territory total was used instead. 

Sources and Types of Data 

There are three basic types of data that are potentially useful as allocation factors: human 

population and its associated income and housing data, business activity, and geographic data. 

Most of these data are available from the U.S. Census Bureau or other federal agencies, except 

for data concerning construction activity and some industry-provided data for state populations 

of motorcycles and ATVs, which are discussed separately below. Information from the U.S. 

Census Bureau is especially attractive for use in the NONROAD model because census data 

undergo rigorous statistical analyses and quality assurance reviews. 

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Population Data 

The U.S. Census Bureau conducts a nationwide census on a decennial basis. The census 

includes data on population, housing (e.g., number of homes by type, number of occupants per 

home), and income. The most recent census available at the time these allocations were updated 

occurred in 2000, but the Census Bureau also produces annual estimates of human population 

and housing based on population growth trends. To be consistent with the latest CBP data, 

NONROAD2005 uses the 2002 population and housing estimates. 

Business Activity Data 

The U.S. Census Bureau publishes an annual report called County Business Patterns1 

(CBP), which tracks the number of establishments and employees for various types of businesses 

and industries at the national and county level categorized according to the North American 

Industry Classification System (NAICS). NONROAD2005 uses 2002 CBP data where 

available. Prior versions of NONROAD used CBP data that were based on the Standard 

Industrial Code (SIC) system of industry categorization. EPA also used County Business Pattern 

indicators for the 1991 Nonroad Engine and Vehicle Emissions Study2 (NEVES) to allocate 

state-level populations to the county level. 

The U.S. Census Bureau in cooperation with the U.S. Department of Agriculture also 

conducts a Census of Agriculture every five years in those years ending with "2" or "7," so the 

most recent surveys were done in 1997 and 2002. 

Geographic Data 

Geographic data include factors related to an area’s location or physical characteristics. 

Such factors include water or land surface area, weather data, and land use data. Such data are 

available from government agencies such as the U.S. Census Bureau, the National 

Oceanographic and Atmospheric Administration, and the U.S. Geological Survey. 

Handling of Counties with Withheld Source Data 

When using the US Census County Business Patterns data to allocate to the county level, 

there are sometimes a few counties in a state where the individual county data have been 

withheld to avoid disclosing data of individual companies. In such cases, the value is included in 

the state total, and in some cases the county entry will give a range, such as 100-249 employees. 

EPA was able to generate county allocations for the missing counties using the state total 

missing value (i.e., the state total value minus the sum of the available individual county values). 

This total missing value was then distributed to the appropriate counties using one of the 

following methods. If no ranges had been given in the source data, then the state total missing 

value was distributed equally to each of the counties where data had been withheld. If ranges 

were available, then the midpoint of the range for each county was assigned to the county (e.g., 

6 
175 for the 100-249 range), and then these values within each state were normalized to force the 

sum of the withheld county data to be equal to the total missing value for that state. 

Allocation of Specific Populations of Equipment Categories/Types 

The allocation indicators that EPA has examined and selected for use in NONROAD2005 

and prior versions of the NONROAD model are discussed below and summarized in Table 1 at 

the end of this report. 

Residential Lawn and Garden Equipment (except snowblowers) 

To allocate lawn and garden equipment used by private households, NONROAD uses 

U.S. Census data on one and two unit housing (i.e., single family homes and duplexes) by 

county. Structures containing more than two units tend to be condominiums or apartments that 

use commercial lawn care services. One and two unit housing information was used as an 

allocation factor in the NEVES, and an analysis of this set of data during the writing of the 

NEVES showed that it was a good predictor of lawn and garden equipment populations. In 

addition, EPA has not been able to find an alternative type of data to use as an allocation factor 

for residential lawn and garden equipment that offers the high quality, the necessary county-level 

detail, and the predictive strength of one and two unit housing data from the U.S. Census Bureau. 

One and two unit housing is most properly thought of as a population allocation factor for 

residential lawn and garden equipment. The population of such equipment in an area should be 

roughly proportional to the number of single and double housing units in the area, since the 

average household occupying such units would have the average probability of owning any 

given type of lawn and garden equipment. But the amount of use such equipment experiences 

may vary considerably from area to area based on such variables as the average size of yards, 

length of growing season, and amount of rainfall. Allocation factors based on residential lawn 

and garden equipment gasoline consumption, tons of yard waste removed, or the land area 

occupied by single and double housing units could, in principle, provide a more direct measure 

of activity. However, the information regarding such potential activity allocation factors are 

either not available, of questionable quality, or subject to confounding influences that make that 

potential allocation factor even less reliable than the one currently used in NONROAD. 

Therefore, the model continues to use one and two unit single family housing data and estimates 

from the Census Bureau. 

Commercial Lawn and Garden Equipment (except snowblowers) 

To allocate commercial lawn and garden equipment NONROAD2005 uses the number of 

employees in landscaping services (NAICS code 561730) from the 2002 CBP database. Earlier 

versions of NONROAD, as well as the 1991 NEVES study used number of employees in 

landscape and horticultural services (CBP SIC 78) to allocate commercial lawn and garden 

equipment. An analysis performed during the preparation of the NEVES showed the number of 

7 
employees in landscape and horticultural services to be a good predictor of commercial lawn and 

garden equipment populations. In addition, EPA does not know of any other sources to 

adequately serve as a geographic allocation factor for commercial lawn and garden equipment. 

The number of employees in landscape and horticultural services is better suited for 

allocating the population of commercial lawn and garden equipment than the activity associated 

with this type of equipment. The level of mechanization in the landscape services industry is 

likely to be reasonably constant from county to county. By contrast, the number of hours per year 

that the average piece of commercial lawn and garden equipment operates is likely to vary 

considerably from county to county as a result of different growing seasons and rainfall patterns. 

Reliable information on allocation factors more directly related to activity levels, such as gallons 

of fuel consumed per county and year by commercial lawn and garden equipment, are not 

available. 

One caveat for using the number of employees in landscape and horticultural services to 

geographically allocate commercial lawn and garden equipment populations is that this factor 

does not include municipal employees that perform landscape maintenance duties for schools, 

parks, and other properties owned and maintained by local governments. The implicit 

assumption used in NONROAD is that the population and activity level of such equipment is 

proportional to commercial lawn and garden equipment population and activity levels. EPA 

welcomes comments from interested parties concerning methods or sources of data that could 

better account for lawn and garden equipment used by municipal landscape employees. 

Snowblowers 

Allocating snowblower populations and activity levels requires the use of allocation 

factors that account for the impact of climatic differences among regions, in addition to the 

factors used to allocate residential and commercial lawn and garden equipment. Put simply, 

snowblower populations and activity levels depend on snowfall. Snowblower populations in 

warm-weather states like Florida, Louisiana, and Hawaii should be zero. Snowblowers may be 

present in parts of states such as Texas and California because part of their territories receive 

snow (e.g., Texas Panhandle, Sierra Nevada Mountains in California), while snowblower 

populations in other parts of the state should be zero. 

Therefore, the allocation of snowblowers in the NONROAD model involves estimating 

which counties in the U.S. receive enough snowfall to call for the use of snowblowers. This was 

done by overlaying a map of the U.S. from the National Oceanic and Atmospheric 

Administration (NOAA) showing ranges of long-term average snowfall amounts on top of a map 

of U.S. counties and making an informed judgment about the minimum annual amount of 

snowfall that would correspond to the use of snowblowers. EPA has chosen a minimum 

snowfall of fifteen inches based on discussions with a snowblower manufacturer and by the 

mapping process mentioned above. The same allocation factors that are used for other lawn and 

garden equipment types (i.e., the number of single and duplex family housing units for 

residential snowblowers and the number of employees in landscaping services for commercial 

8 
snowblowers) are used to allocate snowblowers, except that counties that do not receive at least 

15 inches of snow on average have their allocation factors set to zero so that no snowblowers are 

allocated to those counties or erroneously included in the total state populations. This is the 

same basic methodology that was used in draft versions of NONROAD since 2002. 

In the April 1999 (Tier 2) draft version of NONROAD the snowblower populations were 

allocated to states in proportion to the number of snowmobile registrations in each state 

according to data supplied by the International Snowmobile Manufacturer’s Association (ISMA). 

The model then allocated the snowblowers to the county level using the same factors used to 

allocate other types of lawn and garden equipment. In the original June 1998 draft version of 

NONROAD, due to time and resource constraints, snowblower populations at the state and 

county levels were simply set to zero to avoid misallocation problems, although that version of 

the model could calculate national annual snowblower emissions. 

Construction Equipment 

Initially, EPA planned to use the number of employees engaged in construction by county 

(CBP SIC 15) to geographically allocate construction equipment. However, early comments 

from some stakeholders correctly pointed out that using this indicator could lead to errors in 

estimating construction equipment population and activity in a county because construction 

employees and equipment move from project to project, often crossing county lines. In some 

parts of the country, such as the Northeast, construction employees and equipment may cross 

state lines quite frequently. The CBP data only reflect where construction employees and 

establishments are headquartered, not where they work. 

An alternative indicator of construction equipment activity is the dollar value of 

construction. The U.S. Census Bureau collects and maintains such data, but only at the level of 

metropolitan statistical areas (MSAs) instead of counties. However, EPA was able to obtain 

construction valuation data by county from McGraw-Hill Construction (formerly F.W. Dodge 

Company). 

Dollar value of construction provides a good reflection of activity, since there is a 

proportional relationship between the dollar value of construction and the amount of construction 

activity in a given area. Also, using the dollar value of construction by county as an allocation 

factor distributes construction equipment to where it is actually being used, as opposed to where 

it is headquartered. Furthermore, this indicator provides a reasonable allocation factor for 

construction equipment populations: competitive forces encourage construction companies to 

obtain the maximum return on their investments in costly pieces of construction equipment by 

maximizing their use as much as possible, thereby strengthening the correlation between 

construction activity and construction equipment population. Therefore, construction value was 

chosen as the best means available to allocate construction equipment activity to counties. 

For NONROAD2005 the construction allocation methodology has been enhanced by 

adjusting the construction value data to account for the different cost of construction in different 

9 
geographic areas. This has been done to address the issue that a given amount of construction 

activity in a high cost area (e.g., New York City or Alaska) would show up as greater 

construction value than the same amount of construction activity in a lower cost area. The data 

used for this adjustment process was the 2003 construction cost Area Modification Factors 

(AMFs) published by Craftsman3

. 

These construction AMFs are provided by Craftsman for many cities around the US and 

as averages for entire states, but they are not provided for every county. Since different counties 

within a state can have substantially different costs of construction (e.g., Queens County, New 

York City versus Chautauqua County at the western end of the state), it did not make sense to 

apply the state average to the entire state. Therefore AMFs were determined using a Geographic 

Information System (GIS) approach to apply data from the closest cities for each county. Each 

city value (for which Craftsman provided data) was assigned to a single point location (the 

population centroid defined by the US Census). Each US county was assigned to a single point 

location, also defined by the population centroid of the US Census. The AMF value for each 

county was then estimated from the city data by an oct-angle search. The area around each 

county was divided into eight equal angle sectors, and the eight cities closest to the county 

centroid (one city in each sector) were identified. The AMF value for the county was then 

estimated by weighting together the eight values using a weighting factor equal to the inverse of 

the distance squared, so that closer points were more heavily weighted. Following is an example 

of the allocation calculation for New York City (FIPS 36061). 

ALO = CONVAL x (1-(1/(1+100/AMF))) 

= 3,127,536 x (1-(1/(1+100/2.5))) 

= 3051255 

Where 

ALO = Allocation factor for New York County 

CONVAL = 2003 Value of construction for New York County 

AMF = Area Modification Factor (percent above or below the national 

average construction cost of materials for county) 

As part of this change in construction allocation methodology, a new analysis of 

nationwide data was done regarding whether to treat different types of construction differently4

. 

E.g., should the value of road construction be weighted differently from building construction as 

was done in prior versions of NONROAD? This analysis found that the weighting used in the 

model actually tended to decrease correlation with construction fuel use, data for which was 

available at the state level. Therefore, to simplify that aspect of the construction allocation the 

total dollar value of construction is now used as the basis from which geographic cost 

adjustments are made (per the Area Modification Factors described above) to arrive at the final 

adjusted relative values of construction, which serve as the geographic allocation factors for 

construction equipment. Although the fuel use data could have been used at the state level, EPA 

chose to use the construction value data at all levels for consistency, since there appeared to be 

good correlation between the fuel data and the construction value data. 

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For the June 1998 and April 1999 (Tier 2) draft versions of NONROAD, the total dollar 

value of construction for all types of construction was used directly to allocate construction 

equipment populations to the county level. 

For later draft versions of the model, through draft NONROAD2004, refinements to the 

method were applied in an attempt to account for different levels of equipment use in different 

types of construction. The Dodge data includes the dollar value of residential, commercial, and 

industrial building construction, as well as road and other public works-related heavy 

construction. The construction of the various types of buildings accounts for a large portion of 

the total dollar value of construction. However, according to a survey of construction activity in 

Houston conducted by Environ in 19985

, road and other types of heavy construction constituted a 

much larger share of actual equipment activity per dollar valuation compared to the construction 

of residential, commercial, and industrial buildings. This apparent discrepancy can be explained 

by the fact that, once the land is cleared and graded, heavy construction equipment is not used 

much in the construction of the actual building, which also usually accounts for the majority of 

the project’s cost. The trends in the Environ survey compared favorably to a study conducted by 

Sierra Research in 1993 that estimated the relative activity of construction equipment based on 

fuel cost per project dollar valuation derived from the 1987 Census of Construction Industries. 

Therefore, EPA weighted the various categories of the Dodge construction dollar value 

data based on the Environ survey of Houston construction activity. The equation that was used is 

shown below. 

Allocation Factorj = (SFHj + 3*OBLDGj + 18.4*R&Bj + 8.5*PWj) / 

(SFH + 3*OBLDG + 18.4*R&B + 8.5*PW) 

Where the variables are the dollar valuation for either the county (j) or national total 

SFH = single/double-family housing construction 

OBLDG = other building construction 

R&B = road and bridge construction 

PW = public works (sewer, water, and drainage) construction 

The heavier weighting given to road and other types of infrastructure construction generally 

tended to decrease the allocation of construction equipment to urban counties and increase the 

allocation of this equipment to suburban and adjacent rural counties. This stands to reason, since 

the road and other infrastructure systems in urban counties tend to be largely established but are 

still being developed in outlying counties where suburban sprawl continues to take place. 

One known shortcoming of the construction equipment allocation methodologies used in 

NONROAD is that the allocation does not account for the use of construction equipment in nonconstruction applications. Most notably, landfill and surface mining operations are known to be 

substantial users of certain types of construction equipment, such as wheel loaders, crawler11 
dozers, excavators, and off-highway trucks. These operations, especially surface mining, tend to 

be more geographically limited than construction operations, and they are also tend to involve 

intensive (often two-shift) ongoing (multi-year) operation, compared to construction projects that 

tend toward less continuous use of equipment with much shorter project duration. Thus, in 

counties where there are substantial landfill and/or surface mining operations, the NONROAD 

allocation methodology is likely to underestimate construction equipment emissions. 

Agricultural Equipment 

For this category, EPA considered using the number of employees involved in 

agricultural work by county as an allocation factor (CBP SIC 78), as was used in the NEVES. 

However, this allocation indicator may not correlate well with either agricultural activity or 

agricultural equipment populations. A small number of agricultural employees in a county could 

cause the model to underestimate the population and activity of agricultural equipment if the 

predominant type of farming in that county is highly automated or relies on migrant labor that is 

recorded as being based in a different county. Conversely, a large number of agricultural 

employees in a county could cause the model to overestimate the population and emissions of 

agricultural equipment if the predominant type of farming is labor intensive or if migrant labor is 

recorded as being based in the county. 

Instead of using farm employee data, EPA chose to use the acreage of cropland harvested 

by county to allocate agricultural equipment populations. This same indicator has been used in 

all versions of NONROAD. The data on harvested acres is obtained from the U.S. Census 

Bureau’s USA Counties6 database, or more recently from the Census Bureau web site. 

Using the amount of harvested cropland as an allocation factor provides a good predictor 

of agricultural equipment activity, since a proportional relationship generally exists between the 

amount of cropland harvested and how much equipment activity is needed to prepare the land 

and plant, maintain, and harvest the crops. However, the amount of cropland harvested does not 

necessarily provide as accurate a predictor of agricultural equipment population as it does for 

activity for several reasons. First, the same amount of cropland in a county can be plowed, 

planted and harvested by a few pieces of large equipment or several smaller ones. Second, the 

amount of equipment present in a county may be more dependent on the number of farms than 

on the amount of acreage harvested (although this source of inaccuracy in estimating populations 

may be mitigated by the presence of equipment-sharing arrangements in areas with smaller 

farms). Since the purpose of NONROAD is to estimate emission levels, and since emissions are 

more directly associated with activity levels than with equipment populations, EPA believes that 

the amount of harvested cropland is an appropriate allocation factor for the NONROAD model. 

In cases where a county only contains one or two farms the Census Bureau withholds the 

county level data to avoid disclosing data for individual farms. In such cases, as an estimate for 

use in NONROAD2005, the average number of harvested acres per undisclosed county was 

calculated by subtracting the sum of reported county acres from the state total acres, and dividing 

that by the number of undisclosed counties in the state. Although imprecise, EPA considers this 

12 
an improvement over previous versions of NONROAD in which such counties were simply 

assigned an allocation of zero harvested acres. 

One known shortcoming of the agricultural allocation methodology which should be 

addressed in the future is the treatment of irrigation equipment, since this is highly dependent on 

factors other than harvested acres. Data is available from the Census of Agriculture on the 

number of farms and land area being irrigated. Even more importantly the actual irrigation 

energy cost by type of energy is available at the state level, which would be a very good 

indicator of relative Hp-hours of nonroad engine activity, since electric powered equipment 

could be ignored. 

Recreational Marine Equipment 

Because the county in which the equipment is purchased, registered, and/or stored may 

not be the same county where the equipment is used, the geographic allocation of recreational 

marine equipment presents a significant challenge. An urban or suburban county where a boat is 

sold, registered, and/or stored may not contain a body of water that can support recreational 

marine traffic, or water bodies near where a boat owner lives may be overcrowded. Small and 

medium sized recreational marine craft, which constitute most of the recreational marine fleet, 

can be transported by trailer over a wide area, further complicating matters. Thus, sales and 

registration data are not sufficient to accurately allocate recreational marine equipment to the 

county level. Due to these complexities of allocating recreational boats, EPA developed a 

composite approach to make use of the best available data at each level of allocation. 

To allocate the national recreational boat population to the state level NONROAD uses 

data from a 1992 gasoline consumption distribution developed by the Oak Ridge National 

Laboratory (ORNL) for use in its 1994 Nonhighway Gasoline Use Estimator Model. The ORNL 

gasoline consumption distribution is also used by the Federal Highway Administration (FHWA) 

to estimate annual fuel consumption for boats in states for which no gasoline tax records are 

available. Because the fuel consumption distribution data directly relate to total boat activity and 

emissions, it would also be useful to apply it for state-to-county allocation, but the data are not 

available below the state level. 

To allocate the recreational boat population and activity from the state to county level 

NONROAD uses water surface area data by county from the U.S. Census Bureau. Additionally, 

since water surface area alone does not distinguish between the differences in usage patterns for 

the different types of boats (personal watercraft, outboards, and sterndrive/inboards), the water 

surface allocation factors are adjusted according to the differences in how far each kind of boat 

tends to operate from the shore. Public releases of the model starting with draft 

NONROAD2002 have assumed that personal watercraft and boats with outboard engines operate 

within a quarter mile off the coast, while boats with sterndrive/inboard engines operate up to two 

miles off the coast. The effect of this modification is to allocate a greater number of larger boats 

to coastal counties, while the allocation of personal watercraft and outboards will tend to shift 

toward rivers and lakes in inland counties. This compares to NEVES and the earlier (June 1998 

13 
and April 1999) draft releases of NONROAD, in which the general assumption was that all boats 

operate within one mile of the coast. 

In NONROAD2005 some corrections have been made to the calculation of coastal area 

water surface. It was discovered that in certain cases (especially Great Lakes states) the water 

area included in the basic county boundaries (prior to adding the 1/4 or 2 mile from the coast) 

actually already included a large portion of the coastal water body, well beyond the 2 mile 

intended maximum. A good example of this would be a county on the eastern shore of Lake 

Michigan, for which the legal county boundary is in the middle of Lake Michigan, roughly 50 

miles from the shore. This error was then worsened by adding on the additional 1/4 or 2 mile 

wide segment. This has been corrected using a different dataset that reflects the difference 

between inland versus coastal water areas. 

Even with the enhancements applied to the water surface area data, it should be noted that 

there are some limitations in the use of water surface as an allocation indicator. For instance, it 

does not make a distinction between navigable bodies of water and those that are too shallow for 

boating or have obstructions through which boats are unable to pass. Also, water surface area 

does not account for convenience of location (proximity to areas of significant population) or the 

recreational quality of the water body (which includes such factors as its attractiveness for 

fishing, its visual appeal, and its water quality), both of which could be expected to affect a body 

of water’s recreational marine activity per unit area. Another limitation is that water surface area 

alone does not account for access restrictions that may prevent boating or limit the number of 

boats permitted to operate on a given body of water. 

In earlier model releases prior to draft NONROAD2002 water surface area alone was 

used for recreational marine allocation at all levels, including national to state. One main reason 

EPA switched to the fuel consumption approach described above is that use of water surface area 

alone results in an over-allocation of boating equipment to some states that have long coastlines, 

such as Michigan. In addition, a highly disproportionate share of boating equipment had been 

allocated to Alaska, since much of its coastline and bodies of water are either inaccessible and/or 

inhospitable to recreational boating. 

The NEVES report estimated the population of boats actually being used in each of the 

24 urban nonattainment areas covered by the NEVES through the use of data from a 1991 

National Marine Manufacturers Association survey of boat owners. These data included where 

the boat owners said they primarily operated their boats, where the boats were registered, the 

boat owners’ estimates of the amount of hours they used their boats per boating season, and their 

estimates of the amount of fuel their boats consumed per boating season. In general terms, the 

data from these surveys were used to adjust registration-based boat populations so that only the 

boats actually operating within the nonattainment area (as opposed to boats registered in the 

nonattainment area but used elsewhere) were included when calculating the recreational marine 

emissions for each area addressed in the NEVES. In order to check the reasonableness of the 

NMMA-based results, the total square miles of water surface area in a nonattainment area, the 

estimated square miles of water surface area needed for a typical boat to operate, and the 

14 
maximum number of possible hours per boating season in each nonattainment area were used to 

ensure that the use of NMMA survey data did not result in a boat population estimate that 

exceeded the maximum number of boats that could theoretically operate during the boating 

season of a particular area. If the NMMA-based boat population estimate exceeded the 

theoretical maximum, then this population was adjusted downward. The NEVES method was 

not used in the NONROAD model mainly due to the lack of corresponding nationwide data at 

the county level, but at least some of its elements were adapted to the allocation of recreational 

marine equipment in NONROAD. 

EPA hopes to continue to investigate ways to improve upon the water surface area 

allocation method currently used in the model and also explore whether there might be other 

methods and data available to use in NONROAD to better allocate the population of recreational 

marine equipment for all of the counties in the U.S. Local surveys of recreational boating 

activity, focusing on factors such as marina and boat ramp usage, offer the most accurate means 

to assess boat populations and activity at the county level. One early stakeholder comment 

suggested using data on boating violations and accidents to allocate recreational marine 

equipment. Surveys better capture the actual activity on local lakes, rivers, and other waterways, 

as well as account for boats registered in one county but used in another. If States, regional air 

organizations, and local air pollution control districts have such types of data, then EPA is 

interested in learning about them. Furthermore, EPA encourages state, regional, and local air 

organizations to use these local data in the NONROAD model for county-level boat populations, 

subject to appropriate guidance. 

Recreational Equipment (except for snowmobiles and golf carts) 

The allocation of recreational equipment, such as all terrain vehicles (ATVs) and off-road 

motorcycles, shares the same challenge as the allocation of recreational boats, namely where the 

equipment is registered, purchased, serviced, and stored is usually not the location where the 

equipment is actually used. Because of convenience, people tend to purchase recreational 

equipment, like other products, near where they live. Hence, most recreational equipment is 

purchased in urban and suburban areas, where the majority of the U.S. population lives, and this 

equipment also is registered, stored and serviced in these areas. However, there are relatively few 

places in urban and suburban areas where it is possible and legal to operate recreational 

equipment. Generally speaking, recreational equipment usage tends to be concentrated in rural 

and semi-rural areas near a metropolitan area; such areas are conveniently accessible to the 

owners of most of the recreational equipment, have more area that is attractive for recreational 

equipment use, and tend to impose fewer restrictions on recreational equipment use than more 

densely populated areas. Due to these complexities of allocating recreational equipment, the 

NONROAD model applies a composite approach to make use of the best available data at each 

level of allocation. 

To allocate the national population of recreational equipment to the state level 

NONROAD2005 uses state equipment population estimates obtained from the Motorcycle 

Industry Council (MIC) for the combination of offroad motorcycles and ATVs. These estimates 

15 
are based on sales data and assumptions of equipment life expectancy as well as equipment 

registration data where that is available. This same method and data have been used since the 

April 2000 draft release of NONROAD. 

To allocate recreational equipment population and activity from the state to county level 

NONROAD2005 uses the number of RV (Recreational Vehicle) Parks and Recreational Camps 

(NAICS code 72121) from the 2002 CBP database. All prior draft releases of NONROAD used 

the comparable indicator: number of Camps and Recreational Vehicle Parks (CBP SIC 7030). 

The SIC 7030 data was also used to allocate from national to state in all draft NONROAD 

versions prior to the April 2000 release. 

This indicator CBP SIC 7030 (or NAICS 72121) includes sporting and recreational 

camps (other than sports instructional camps) as well as facilities providing short-term sites for 

recreational vehicles, trailers, campers, or tents, but not mobile home parks. The data subset 

from CBP SIC 7030 containing the number of establishments offers better coverage of the U.S. 

than the subset containing the number of camp and recreational vehicle park employees. The 

data subset containing the number of employees appears to be missing information for areas 

known to contain national and state parks, near which camps and recreational vehicle parks are 

likely to be located. EPA acknowledges that this approach may not adequately account for 

recreational equipment being used on private and public lands that are not associated with and/or 

adjacent to camps and recreational vehicle parks. In addition, using the number of camps and 

recreational vehicle parks as an allocation factor is only loosely correlated to the level of 

recreational equipment activity occurring in a county. At the present time, however, EPA is not 

aware of other allocation methods that are both practical and reasonably accurate to allocate from 

state to county population and activity. EPA welcomes suggestions of better alternative methods 

and data sources for allocation of recreational equipment. 

The NEVES report used CBP data for SIC 557 (number of motorcycle establishments) to 

allocate recreational equipment to the county level. However, this data is not available for one or 

more counties in some States. The NEVES report also used SIC 55 (number of employees in 

auto dealerships and service stations), of which SIC 557 is a subset. Neither of these data sets 

provide a reasonable allocation factor for recreational equipment, because most motorcycle 

establishments, auto dealerships and service stations are located in urban and suburban areas 

instead of rural and semi-rural areas where most recreational equipment activity occurs. 

Registration data also exist for ATVs in most States, but there may be some cases where 

these data are not available or up to date. Sales data also are available from Power Systems 

Research or manufacturers. However, using registration or sales data alone as allocation factors 

presents the same drawback as using the CBP data: the location of population does not correlate 

well with the location of recreational equipment activity outside of heavily urbanized or 

suburbanized areas. 

Alternative approaches for the allocation of recreational equipment have also been 

considered by EPA. One option considered was allocating recreational equipment population 

16 
and activity based on the inverse of population or population density (i.e., the higher the 

population or population density of a county, the less recreational equipment activity is allocated 

to that county). EPA has also considered allocating activity based on the amount of nonurbanized land area per county within a State. While these approaches would reduce the risk of 

overestimating urban activity, they would tend to overestimate activity in remote rural areas, 

such as the North Slope of Alaska, Michigan’s Upper Peninsula, the Mojave Desert, or the Texas 

Panhandle. Yet another approach would have used employment or Gross Domestic Product 

(GDP) economic activity directly associated with recreational equipment usage to allocate 

recreational equipment. However, EPA has been unable to locate these data at the county level. 

The CBP database does not include recreational equipment GDP data, and the Bureau of 

Economic Analysis (BEA) only tracks GDP data down to the state level. Even if it were 

available at the county level, it would have the same drawback as the CBP data: the location 

where GDP is generated does not correspond to the location of recreational equipment activity. 

Golf Carts 

Golf carts have a different pattern of usage from other types of equipment in the 

recreational category. Unlike ATVs or snowmobiles, golf carts are predominantly used in a 

central location (golf courses), which is usually within or close to an urban/suburban area. In 

NONROAD2005 golf carts are allocated according to the number of golf courses and country 

clubs (CBP NAICS code 713910). 

EPA had initially planned to use public golf course employees (CBP SIC 7992) as an 

allocation factor for this equipment type. However, these data were incomplete for many 

counties in the U.S. For example, no employees of golf courses were reported for the state of 

Colorado. Even so, due to time limitations the initial June 1998 draft version of NONROAD just 

used golf course employees as a temporary place-holder while additional analysis was being 

conducted. Then beginning with the April 1999 (Tier 2) version of NONROAD, the model used 

the number of golf courses (CBP SIC 7992) by county for allocating golf carts. 

Using the number of golf courses to allocate golf carts and their emissions to the county 

level does not provide a precise reflection of golf cart population or activity. Like the allocation 

factor that is used to allocate the other types of recreational equipment (the number of RV parks 

and recreational camps), the relationship between the number of golf courses on the one hand 

and the population and activity level of golf carts and on the other is a loose one. The population 

and activity of golf carts at a given golf course depends on the size, popularity, and type of 

course. A large, popular, 36-hole championship golf course will have more golf carts that are 

used more intensively than a small, less intensively used 9 hole course. The location of a golf 

course also affects golf cart activity. A golf course adjacent to an urban area or in a suburban 

area will tend to have more players than one located in a rural area, resulting in higher golf cart 

activity at the urban or suburban course. An additional complication is that many golf courses 

use electrically powered carts instead of carts using gasoline-powered engines. However, EPA 

does not know of any nationally applicable allocation factors that account for these influences. 

Therefore, EPA plans to continue using the number of golf courses as an allocation factor in the 

17 
NONROAD model, but is open to the use of other data that might better account for local nonelectric golf cart activity and population. 

Snowmobiles 

The allocation of snowmobile activity presents the same challenges as other recreational 

equipment (except golf carts), but it is further complicated by the need to take snowfall into 

account. Thus, a more complex hybrid allocation methodology is used, which takes into account 

snowmobile state registrations, human population density, county urbanization, and snowfall. 

The allocation of the national snowmobile population to states is based on 1998 

snowmobile registration data from the International Snowmobile Manufacturers Association 

(ISMA). This registration data was then modified on a state-by-state basis by ORNL7

 in an 

attempt to account for unregistered snowmobiles, since anecdotal information suggests that these 

may account for a significant portion of total snowmobile emissions, and some states do not even 

have a registration program. Using this sort of registration data automatically avoids allocating 

snowmobiles to states without significant snowfall. 

To allocate snowmobiles from the state to the county level in states other than Alaska, the 

model uses inverse human population as the basic allocation factor, placing more snowmobile 

activity in the more rural counties where snowmobile trails would be located. Additionally, to 

restrict snowmobile emissions to counties with sufficient snowfall the model applies a minimum 

average annual snowfall requirement of forty inches, such that allocation factors for counties 

receiving less than that much snow are set to zero, similar to the method used for snowblowers 

(discussed above). The annual average snowfall data are available from the National Oceanic 

and Atmospheric Administration (NOAA). As a final filter on the county allocations, counties 

that are considered to be partially or fully urban are excluded completely from the snowmobile 

allocation, even if they receive over 40 inches of snow, and even if some portion of the county is 

rural enough to support snowmobile use. 

An exception to the use of inverse human population and exclusion of urban counties has 

been made for Alaska, since using inverse human population would allocate snowmobiles to the 

numerous areas of Alaska that are uninhabited and largely inaccessible. Since most of the 

populated parts of Alaska are fairly rural to begin with, human population is used directly, rather 

than inversely. No counties are excluded, since all counties in Alaska average more than 40 

inches of snow per year. 

For NONROAD2005 the only update to the snowmobile allocations from the 2002 and 

2004 draft models is an update of the human population portion of the county allocation 

calculations. The model now uses 2002 US Census Bureau human population estimates, 

whereas the earlier models used 1996 census estimates. 

The April 1999 (Tier 2) draft version of the model also used snowmobile registration data 

for allocation to the states, but it was 1996 data and it did not include any adjustments to account 

18 
for unregistered snowmobiles. For state to county snowmobile allocation, this 1999 version of 

the model used the number of camps and recreational vehicle parks from the 1995 County 

Business Patterns (CBP) database. EPA realized that this county allocation indicator had serious 

limitations, since snowmobile allocation really needs to be focused on rural counties within a 

state that receive frequent snowfall that results in significant and persistent snow coverage. 

For the initial June 1998 draft version of NONROAD, time and resource constraints did 

not allow EPA to properly address snowmobile allocation. As a result, state and county 

snowmobile populations were simply set to zero in that version of the model, but the nationwide 

snowmobile population was included to allow calculation of snowmobile emissions at the 

national level. 

One alternative allocation methodology for snowmobiles was also considered. 

Snowmobile trail mileage by county presents an apparently logical method to allocate 

snowmobiles, since they are only located where the annual snowfall would support snowmobile 

use, and the amount of activity would be reflected by how many miles of trails a county would 

have. Most states where snowmobiles are used have trail maps, but these maps vary 

significantly in quality and may or may not be scaled accurately. In addition, EPA found that 

states with snowmobile trails do not keep track of the mileage of these trails by county. Trail 

mileage also does not necessarily provide an accurate reflection of activity, since it does not 

capture how intensively a given trail is used, and it does not account for off-trail snowmobiling. 

Airport Ground Support Equipment (GSE) 

The population and use of ground support equipment (GSE), such as baggage tractors, 

fuel carts, aircraft tow tractors, etc., is a function of the number of aircraft operations (landings & 

take-offs), the sizes of the aircraft, and how full they are of passengers or cargo. For 

NONROAD2005 EPA has chosen to allocate GSE in proportion to the estimated emissions of 

aircraft NOx, as reported in the 2002 National Emissions Inventory (NEI). The use of aircraft 

NOx provides a reasonable indication of the relative amounts of aircraft operations at different 

airports, with much greater weighting given to commercial aircraft, and especially larger 

commercial aircraft which would require most of the GSE. Additionally, by using the NEI data, 

any data submitted by state/local governments is included, which can be more accurate than the 

default data. 

For all prior draft versions of NONROAD through 2004 EPA used the number of people 

employed in air transportation by county (CBP SIC 4500) to allocate ground support equipment. 

However, this indicator can include employees that are not directly connected to aircraft 

operations, such as airline reservation staff and ticket agents. Using this factor may lead to an 

overestimation of aircraft ground support equipment population and activity, especially in 

counties that either have airports with one or more airline “hubs” or that do not have a 

commercial airport but have branch ticket offices for various airlines. 

19 
Industrial and Commercial Equipment 

Allocation of industrial and commercial equipment in NONROAD2005, and all prior 

verions of the model, is done using the same indicators as in the 1991 NEVES report. For 

industrial equipment, such as forklifts and sweepers/scrubbers, NONROAD uses the number of 

employees in manufacturing (NAICS codes 31xxxx, 32xxxx, 33xxxx, and 5111xx, formerly 

CBP SIC 20--, which included all SICs 2xxx and 3xxx). Commercial equipment, considered to 

include items such as generators, pumps, pressure washers and welders, is allocated according to 

the number of wholesale establishments (NAICS code 42, formerly CBP SIC 50--). 

Because these types of equipment are expected to remain close to a fixed central base of 

operations, unlike construction equipment that often crosses county or state boundaries, one 

would expect that the number of establishments or employees could be reasonable factors for 

allocation of commercial and industrial equipment. Analyses done for the NEVES report 

showed that these indicators were indeed reasonable predictors of commercial and industrial 

equipment populations. EPA acknowledges that the number of establishments may not be the 

best possible indicator of activity, since equipment activity would depend on the average size of 

establishment and the mix of establishment types, in addition to the absolute number of 

establishments. EPA is open to considering possible alternative sources of activity-related 

allocation factors such as the dollar value of commercial, wholesale, or industrial output, 

including their advantages and disadvantages relative to the number of employees and 

establishments. 

Logging Equipment 

In NONROAD2005 logging equipment activity is now allocated by county according to 

2002 Total Product estimates (cubic feet, without residues) in the Timber Product Output (TPO) 

database from the U.S. Forest Service (www.fia.fs.fed.us/program-features/tpo/). This is a 

change from the 2002 and 2004 versions of NONROAD, in which allocation of logging 

equipment was based on the number of employees in logging operations (1996 CBP SIC 2410). 

Although the number of logging employees would be expected to provide a reasonable reflection 

of logging equipment activity, peer review comments provided information on the TPO database, 

which is expected to correlate even better with equipment activity. 

In the original June 1998 and April 1999 (Tier 2) draft versions of NONROAD EPA used 

the number of employees in logging (CBP SIC 2410) combined with the number of employees in 

saw and planing mills (CBP SIC 2420). However, inclusion of saw and planing mill employees 

caused logging equipment populations to be allocated to unlikely places such as Southern 

California and various urban areas in Texas, where actual mobile logging equipment would not 

be found. 

20 
Oil Field Equipment 

To allocate oil field equipment population and activity, NONROAD2005 uses the 

number of employees in Oil & Gas Extraction (2002 CBP NAICS code 211xxx) plus the number 

of employees in Drilling Oil & Gas Wells (2002 CBP NAICS code 213111). 

All prior versions of NONROAD used the total number of employees in oil and gas 

extraction operations (CBP SIC 1300). That SIC category included employees in support 

activities for oil and gas operations, but under the newer NAICS system it became possible to 

exclude this particular subcategory since it would tend to involve more office activities rather 

than equipment-oriented field activities. 

Employment data provide reasonable allocation factors for oil field equipment activity 

because a proportional relationship is believed to exist between the number of employees and the 

amount of equipment they use. Furthermore, economic incentives to avoid leaving expensive 

equipment idle suggests that activity and equipment populations will be closely correlated. 

Finally, these types of equipment tend to remain within a given state and county (unlike 

construction equipment, for example), so the location of activity for oil field equipment usually 

coincides with the location where the employees are based. A production-based indicator, such 

as gallons of oil pumped, might be a better allocation factor, but EPA has been unable to find this 

type of activity-related data at the county level. 

Underground Mining Equipment 

To allocate underground mining equipment population and activity NONROAD2005 

uses tons of underground coal production, as reported in the Energy Information 

Administration's Annual Coal Report8. EPA considers this production-based indicator to be a 

better allocation factor for equipment use than the employment data used in prior versions of the 

model. 

In earlier draft versions of NONROAD, before finding the underground coal production 

data by county, mining employment data were used based on the same rationale described above 

for oil field equipment. In the 2002 and 2004 versions of the model EPA used the number of 

employees in all types of coal mining (CBP SIC 1200) as the indicator for underground mining 

equipment. This was not limited specifically to underground coal mining because there was no 

separation of SICs for underground versus surface mining of anthracite coal. 

In the June 1998 and the April 1999 (Tier 2) draft versions of NONROAD, allocation of 

underground mining equipment was based on the number of employees in metal mining (CBP 

SIC 1000). After further investigation EPA decided to switch from metal mining to coal mining 

employment data, since most metal mining in the U.S. is performed above ground through the 

excavation of large open pits. 

21 
Railroad Maintenance Equipment 

Rail maintenance equipment includes any type of nonroad equipment specific to railroad 

operation other than the locomotives themselves. This usually refers to rail maintenance 

machinery, whether designed to travel directly on the rails or be hauled to the job site. The 

population and activity of rail maintenance equipment in each county depend upon factors such 

as the number of miles of track in a county, the number of cargo and passenger rail trips within 

the county, the size of the trains used and how fully loaded they are, the age and condition of the 

track, and the resources available for maintenance. 

For NONROAD2005 EPA has chosen to allocate rail maintenance equipment in 

proportion to the estimated locomotive NOx emissions, as reported in the 2002 National 

Emissions Inventory (NEI). The use of locomotive NOx provides a reasonable indication of the 

relative amounts of train operation in different counties, with greater weighting given to 

operation of larger cargo trains and those operated in areas with greater grades. Additionally, by 

using the NEI data, data submitted by state/local governments is included, which can be more 

accurate than the default data. 

For all prior draft versions of NONROAD through 2004 the model simply used human 

population as the allocation factor for rail maintenance equipment. EPA acknowledged that 

human population is unlikely to correspond well to the location and usage of railroad 

maintenance equipment, but no applicable CBP business/employment category was found, nor 

any other reasonable alternative indicators, until the recent update to the NEI locomotive data. 

AC/Refrigeration Equipment 

Air conditioning and refrigeration equipment covered by the NONROAD model typically 

are units used on trucking trailers and refrigerated rail cars to keep food cold and fresh while it is 

transported to restaurants and markets. NONROAD2005 and all prior versions of the model use 

human population by county as the allocation factor for this equipment. The rationale for using 

human population as the indicator is that the number of units being used to transport food into or 

within a given county is likely to be directly related to the size of the human population in that 

county. However, EPA is open to consideration of better allocation factors that might, for 

example, account for refrigerated transport over longer distances outside of population centers. 

22 
Table 1

NONROAD Surrogate Allocation Factors

Nonroad 

Equipment 

Category 

Allocation Factor 

June 1998 Draft Version 

Allocation Factor 

April 1999 Draft Tier 2 Version 

Allocation Factor 

2002 Draft Version & Draft 

NR2004 

Lawn and Garden Residential (HOU) ??_HOUSE.ALO 

Number of single and double (duplex) family housing units from 1990 US Census by county. 

Number of single and double (duplex) family housing units from 1990 US Census by county adjusted by 1997 county human population estimates from U.S. Census Bureau. 

Same as April 1999 draft version. 

2002 singlhous

Lawn and Garden Commercial (LSC) ??_LSCAP.ALO 

Number of employees in landscape and horticultural services, County Bus. Patterns (CBP), Standard Industrial Code (SIC) 0780. 

Same as June 1998 draft version. Same as June 1998 draft 

version. 

Sam2002 Numland

Residential Snowblowers (SBR) ??_SBR.ALO 

Snowblowers set to zero pending implementation of proper allocation based on snowfall. 

Populations allocated to states based on snowmobile registration data by state, then allocated to counties using same factor as residential lawn and garden. 

Same as residential lawn and garden, but allocation factors for counties with snowfall less than 15 inches set to zero. 

Samand gfactoless 

Commercial Snowblowers (SBC) ??_SBC.ALO 

Snowblowers set to zero pending implementation of proper allocation based on snowfall. 

Populations allocated to states based on snowmobile registration data by state, then allocated to counties using same factor as commercial lawn and garden 

Same as commercial lawn and garden, but allocation factors for counties with snowfall less than 15 inches set to zero. 

Samand gfactoless 

23 
Nonroad 

Equipment 

Category 

Allocation Factor 

June 1998 Draft Version 

Allocation Factor 

April 1999 Draft Tier 2 Version 

Allocation Factor 

2002 Draft Version & Draft 

NR2004 

Construction (CON) ??_CONST.ALO 

Total dollar value of construction by county. 

Same as June 1998 Categories (e.g., housing, 

commercial buildings, public works construction) of F.W. Dodge construction dollar value data weighted by 1998 Environ survey of construction equipment activity in Houston, TX and then totaled. 

ALRdollacounConsDodconsdiffeConsModCraf

Agricultural (FRM) ??_FARMS.ALO 

1992 Harvested cropland (U.S. Census Bureau, USA Counties 

1998 database). 

Same as June 1998 draft version. Same as June 1998 draft 

version. 

2002 Cens

Recreational Marine (WOB - outboards, PWC) ??_WOB.ALO (WIB - inboards) ??_WOB.ALO 

Ratio of county water surface area to total national water surface area. 

Same as June 1998 draft version. Population will be allocated 

to states using ORNL fuel consumption distribution. Allocation to counties using water surface area with different operating limits from shore for personal watercraft, outboards, and inboards. 

BeinSamcorremeasthan whicLake

Recreational (except snowmobiles and golf carts) (RVP) ??_RVPRK.ALO 

Number of camps and recreational vehicle park establishments (CBP SIC 7030). 

Number of camps and recreational vehicle park establishments (CBP SIC 7030). 

State offroad motorcycle + ATV population estimates from MIC for national to state allocation and number of camps and recreational vehicle park establishments (CBP SIC 7030) for state to county allocation. 

Samupdacode RecrCamalloc

24 
Nonroad 

Equipment 

Category 

Allocation Factor 

June 1998 Draft Version 

Allocation Factor 

April 1999 Draft Tier 2 Version 

Allocation Factor 

2002 Draft Version & Draft 

NR2004 

Snowmobiles (SNM) ??_SNOWM.ALO 

Snowmobiles set to zero pending implementation of proper allocation based on snowfall. 

Populations allocated to states based on ISMA snowmobile registration data by state, then allocated to counties using the same factor as other recreational equipment, the number of RV park/camp establishments. 

Allocate to states per updated ISMA state snowmobile registration data plus estimate of unregistered Allocate to counties with at least 40 inches snowfall using inverse human population (or direct human population in Alaska). 

Sam2002 data. 

Golf Carts (GC) ??_GOLF.ALO 

Number of public golf course employees (CBP SIC 7992). 

Number of public golf courses (CBP SIC 7992). 

Same as April 1999 draft version. 

Sam2002 NumCoun

Aircraft Ground Support Equipment (AIR) ??_AIRTR.ALO 

Number of employees in air transportation (CBP SIC 4500). 

Same as June 1998 draft version. Same as June 1998 draft 

version. 

2002 invenallocLTO 

Commercial (COM) ??_HOLSL.ALO 

Number of wholesale establishments (CBP SIC 50--), which includes all SIC 50xx + 51xx, not just SIC 5000. 

Same as June 1998 draft version. Same as June 1998 draft 

version. 

Sam2002 Numestab

Industrial (MFG) ??_MNFG.ALO 

Number of employees in manufacturing (CBP SIC 20--), which includes all SIC 2xxx + 3xxx, not just SIC 20. 

Same as June 1998 draft version. Same as June 1998 draft 

version. 

Sam2002 32xxof em

Logging (LOG) ??_LOGGN.ALO 

Number of employees in logging plus saw and planing mills (CBP SIC 2410 and 2420). 

Same as June 1998 draft version. Number of employees in logging (CBP SIC 2410). 2002 

25 
Nonroad 

Equipment 

Category 

Allocation Factor 

June 1998 Draft Version 

Allocation Factor 

April 1999 Draft Tier 2 Version 

Allocation Factor 

2002 Draft Version & Draft 

NR2004 

Oil Field Equipment (OIL) ??_OIL.ALO 

Number of employees engaged in oil and gas extraction (CBP SIC 1300). 

Same as June 1998 draft version. Same as June 1998 draft 

version. 

Sam2002 and 2in Ooil & 

Underground Mining Equipment (MIN) ??_COAL.ALO 

Number of employees engaged in metals mining(CBP SIC 1000). 

Same as June 1998 draft version. Number of Employees in coal 

mining (CBP SIC 1200). 

UpdProdAnnu

Railroad Maintenance Equipment (POP) same as AC/Refrig ??_POP.ALO 

1990 human population. 1990 and 1996 human population. Might be revised using 

different allocation factor for final version, pending review. 

2002 invenallocmile

AC/Refrigeration Equipment (POP) same as RailMaint ??_POP.ALO 

1990 human population. 1990 and 1996 human population Will update with latest 

human population data available. 

Sam2002 Cens

26 
References 

1

 "County Business Patterns 1995-1996," U.S. Census Bureau, CD-CBP-95-96, issued 

January 1999. 

2

 "Nonroad Engine and Vehicle Emission Study," U.S. Environmental Protection 

Agency, Office of Air and Radiation. 21A-2001, November 1991. 

3

 "2003 National Construction Estimator," Craftsman Book Company (used for initial 

analysis of Area Modification Factors). 

4

 "Construction allocation data recommendations," memorandum from Jeremy Heiken, 

Air Improvement Resource, Inc. to Greg Janssen, EPA, May 24, 2004. File: 

[construction memo REVISION 1.doc] 

5

 "TNRCC Construction Equipment Emissions Project," Final Report, prepared for Texas 

Natural Resource Conservation Commission, by Environ International Corporation, 

February, 1999. File: [TNRCCFNL.pdf] 

6

 "USA Counties 1996," U.S. Census Bureau, CD-USA-1996, issued August 1996. 

7

 "Fuel Used for Off-Road Recreation: A reassessment of the Fuel Use Model," prepared 

for the Office of Highway Information Managment, Federal Highway Administration by 

Stacy Davis, Lorena Truett, Patricia Hu, Center for Transportation Analysis, Oak Ridge 

National Laboratory, ORNL/TM-1999/100, July 1999. 

8

 "Annual Coal Report 2002," Energy Information Administration, DOE/EIA-0584 

(2002). 

27