Air and Radiation EPA420-R-05-021
December 2005
United States NR-014d
Environmental Protection
Agency
Geographic Allocation of
Nonroad Engine Population
Data to the State and
County Level
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EPA420-R-05-021
December 2005
Of
to the County
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 final 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 final EPA decision, position, or regulatory action.
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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.
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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
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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)l. 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-to-
state 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)nationai X Sum(Surrogatescounties jn state)
SulTOgatenational
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 Surrogatecountv
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.
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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 = MCATVpL 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.,
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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
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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
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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
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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 =CONVALx(l-(l/(l+100/AMF)))
= 3,127,536 x (l-(l/(l+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 non-
construction applications. Most notably, landfill and surface mining operations are known to be
substantial users of certain types of construction equipment, such as wheel loaders, crawler-
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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
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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
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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
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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
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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
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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 non-
urbanized 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
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NONROAD model, but is open to the use of other data that might better account for local non-
electric 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
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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.
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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 Slxxxx, 32xxxx, 33xxxx, and Slllxx, 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.
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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 21 Ixxx) plus the number
of employees in Drilling Oil & Gas Wells (2002 CBPNAICS code 213 111).
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.
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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/Refriaeration 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.
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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
Allocation Factor
NR2005
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 US Census data for number of
single and double (duplex) family
housing units.
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.
Same as NR2004, but updated per
2002 CBP (NAICS Code 561730)
Number of employees in
landscaping services.
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.
Same as NR2005 residential lawn
and garden above, but allocation
factors for counties with snowfall
less than 15 inches set to zero.
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.
Same as NR2005 commercial lawn
and garden above, but allocation
factors for counties with snowfall
less than 15 inches set to zero.
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Nonroad
Equipment
Category
Allocation Factor
June 1998 Draft Version
Allocation Factor
April 1999 Draft Tier 2 Version
Allocation Factor
2002 Draft Version & Draft
NR2004
Allocation Factor
NR2005
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.
ALREADY DONE. 2003 total
dollar value of construction by
county from McGraw-Hill
Construction (formerly F.W.
Dodge), adjusted for geographic
construction material cost
differences per 2003 National
Construction Estimator, Area
Modifications Factors (published by
Craftsman).
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 Harvested cropland (USDA
Census of Agriculture) acres.
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.
Being handled in Task le:
Same basic method as NR2004, but
corrected county boundaries to
measure distance from shore rather
than distance from legal boundary,
which could be in middle of a Great
Lake.
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.
Same method as NR2004, but
updated per 2002 CBP (NAICS
code 721211) Number of
Recreational Vehicle Parks and
Campgrounds for the state-to-county
allocation.
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Nonroad
Equipment
Category
Allocation Factor
June 1998 Draft Version
Allocation Factor
April 1999 Draft Tier 2 Version
Allocation Factor
2002 Draft Version & Draft
NR2004
Allocation Factor
NR2005
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).
Same as NR2004, but updated per
2002 US Census human population
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.
Same as NR2004, but updated per
2002 CBP (NAICS code 713910)
Number of Golf Courses and
Country Clubs.
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 NEI aircraft NOx emission
inventory estimates, which are
allocated mainly according to FAA
LTD data.
Commercial
(COM)
?? HOLSL.ALO
Number of wholesale
establishments (CBP SIC 50-),
which includes all SIC 50xx +
5 Ixx, not just SIC 5000.
Same as June 1998 draft version.
Same as June 1998 draft
version.
Same as NR2004, but updated per
2002 CBP (NAICS code 42)
Number of Wholesale
establishments.
Industrial
(MFC)
?? 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.
Same as NR2004, but updated per
2002 CBP (NAICS codes Slxxxx,
32xxxx, 33xxxx, 5111xx) Number
of employees in manufacturing.
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 Timber Product Output.
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Nonroad
Equipment
Category
Allocation Factor
June 1998 Draft Version
Allocation Factor
April 1999 Draft Tier 2 Version
Allocation Factor
2002 Draft Version & Draft
NR2004
Allocation Factor
NR2005
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.
Same as NR2004, but updated per
2002 CBP (NAICS codes 211xxx
and 213111) Number of employees
in Oil & gas extraction, and Drilling
oil & gas wells.
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).
Updated per Underground Coal
Production tons, DOE/EIA 2002
Annual Coal Report.
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 NEI locomotive NOx emission
inventory estimates, which are
allocated mainly by railroad ton-
miles.
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.
Same as NR2004, but updated per
2002 human population from US
Census.
26
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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 l.doc]
5 "TNRCC Construction Equipment Emissions Project," Final Report, prepared for Texas
Natural Resource Conservation Commission, by Environ International Corporation,
February, 1999. File: [JNRCCFNL.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).
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