EPA-420-P-98-023
 

Nonroad Engine Growth Estimates 

Report No. NR-008 

March 6, 1998
 

Gary J. Dolce
 

Nonroad Emissions Modeling Team
 

Assessment and Modeling Division
 

EPA, Office of Mobile Sources
 

Purpose 

Estimating accurate projections of future nonroad emissions inventories depends on 

estimations of future emission factors and future activity levels. This report focuses on the 

estimation of future activity levels. The purpose of this report is to document the proposed 

methodology for estimating growth in activity levels in the EPA NONROAD emission inventory 

model and to compare it to alternative methodologies. 

Background 

The emissions inventory for nonroad engines is a function of the emission factors and the 

amount of work or activity levels of these engines. Projections of future nonroad engine 

inventories must take into account expected changes in emission factors and activity levels. 

Future changes in emission factors will primarily be the result of future regulations and are 

discussed in separate reports (NR-009 and NR-010). Future changes in activity level will be the 

result of complex interactions between human population growth, changes in national and local 

economic factors, and changes in the markets for nonroad engines and the products they are used 

to produce. 

Historically, EPA has often used projections of economic indicators as surrogates for 

growth in activity for the purpose of estimating future emissions for a wide variety of sources. 

When applying this approach to nonroad equipment, the underlying assumption is that engine 

usage is a constant proportion of earnings for a given sector. The most commonly used 

compilation of economic indicators is provided by the Department of Commerce's Bureau of 

Economic Analysis (BEA). The most recent projections were published in July, 1995 . 1 BEA 

provides economic indicators by state or as a national average for numbers of employees, 

inflation adjusted national dollars of earnings, and inflation adjusted aggregate gross state 

products (GSP) dollars of earnings. In the past, BEA growth forecasts for major sectors of the 

economy (e.g., construction, farm, forestry, manufacturing, etc.) have been applied to all nonroad 

equipment that might be used in that sector of the economy. 

However, the use of economic indicators to predict growth in nonroad activity has some 

drawbacks. Economic indicators may not be able to adequately predict the effects of substitution 

of equipment for labor in the market. Also, economic models in recent years have tended to 
overestimate inflation rates. As a result of both of these factors, economic indicators may tend to 

under-predict growth in nonroad equipment populations and activity. Evidence that this is 

2 indeed the case can be found in an analysis done by E.H. Pechan and Associates which

compared BEA estimates of growth between 1990 and 1996 to estimates of actual 1990 and 1996 

populations of nonroad equipment from the Power Systems Research (PSR) PartsLink database. 

The Pechan analysis indicated that the projected 1996 population based on the BEA growth 

estimate under-predicted the estimates of actual population developed by PSR in 1996 by 7.4%. 

Overall, the total projected BEA growth from 1990 to 1996 was 9.3%, while PSR estimated that 

actual nonroad equipment populations grew 18.1% over that same period. 

There is a second drawback to using economic indicators that may be as important to 

estimation of emissions projections as the under prediction problem. Because economic 

indicators at best can only predict growth in broad sectors of the economy, they cannot be used to 

identify market trends within sectors. For example, economic indicators would not predict 

differential rates of growth of diesel equipment relative to gasoline equipment in nonroad 

applications, or changes in the horsepower distribution within nonroad applications. Because 

diesel and gasoline engines have very different emissions characteristics, the accurate prediction 

of changes in the relative distribution of different types of engines is very important to the 

accurate estimation of future emissions. 

An alternative approach which would be able to factor in market trends would be to base 

growth estimates on the historical trend in growth in nonroad equipment activity. Because total 

activity is never directly measured, the historical trend in population must be used as a surrogate. 

This seems reasonable given that capital costs of nonroad equipment are high compared to 

operating costs, in general. As a result, owners of such equipment have a strong incentive to get 

the most out of the equipment they own and a disincentive to purchase new equipment that will 

not be fully utilized. 

Although the use of historical population growth may have limitations, it is the only 

approach that will allow estimation of the impact of market shifts on emission projections. 

For these reasons, we propose to base growth projections in EPA’s NONROAD emissions model 

on a time series analysis of historical nonroad engine populations 

Methodology 

We analyzed historical engine population estimates for 1989 through 1996 taken from the 

PSR PartsLink database, the same source used to determine 1996 baseline engine populations as 

described in Report No. NR-006. The PSR database contains detailed information about each 

engine family sold in the United States. This information could be used to segregate nonroad 

engines for purposes of growth estimation at by several different factors, including market sector 

(agricultural, construction, etc.), application type (farm tractors, combines, etc.), fuel type 

(gasoline, diesel, etc.), and horsepower. As a result, one could in principle estimate separate 

growth factors for each combination of application type and fuel type, in discrete horsepower 

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categories. However, there are some limitations to this approach. In many cases, equipment 

populations become small enough, when broken down by all of these factors, that even small 

errors in the PSR database would result in large errors in growth estimation. In addition, the 

number of individual growth rates would become unwieldy considering the number of different 

application types, fuel types, and horsepower categories, as well as the fact that each state would 

have its own unique set of growth factors. 

We invite comment on whether or not we should move to that level of detail in the final 

version of NONROAD. For the current version, we have chosen to segregate nonroad engines by 

market sector and fuel type. Individual applications in the PSR database were assigned to broad 

market sectors as shown in Appendix A of Report No. NR-006. For example, excavators, 

graders, backhoes, dozers, etc. were all assigned to the Construction market sector (SCC category 

2260002xxx). Total market sector populations, segregated by fuel type, were calculated for each 

year from 1989 through 1996. An exponential curve was fit to each of these to determine the 

growth rate over the period from 1989 to 1996. We also estimated the growth rate for the total of 

all engines of all fuel types in each market sector for purposes of comparison with BEA 

estimates. 

Results 

Table 1 compares projected annual growth rates from BEA with those derived from a 

historical analysis of the PSR database (actual populations are given in the Appendix). With the 

exception of the logging and recreational sectors, the PSR estimates are significantly higher than 

the BEA estimates. The PSR database also indicates very large differences in growth rates for 

different fuel types. In most cases, the rate of growth for diesel equipment is substantially higher 

than that for gasoline equipment. In the industrial and light commercial categories LPG and 

CNG engines also show higher than average rates of growth (categories with no growth rates for 

LPG or CNG had populations that were either zero or negligible; i.e. less than 0.1% of the total 

population for that category). 

Table 1. Projected Average Annual Growth Rate Comparison 

Sector BEA 

PSR 

Total Diesel Gasoline LPG CNG 

Airport Service 5.5% 8.2% 9.4% 1.4% 

Construction 1.0% 2.6% 3.6% 0.3% 

Farm 2.4% 2.8% 3.2% 2.0% -7.7% 

Industrial 1.9% 3.1% 4.4% -3.5% 4.1% 

Lawn & Garden 1.0% 2.7% 9.6% 2.6% 

Light Commercial 1.9% 4.9% 5.5% 4.7% 14.2% 5.1% 

Logging 7.4% 5.2% -0.8% 5.9% 

Railway -0.9% 2.7% 5.1% 1.3% 

Recreational 1.0% 0.9% 3.9% 0.9% 

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It is obvious from the PSR data that a substantial shift from gasoline to diesel engines is 

occurring in most of the market sectors. Given the high rates of growth for diesel engines in 

most sectors compared to the overall sector growth rates, it is reasonable to ask whether or not 

these growth rates due to market shifting are sustainable. However, there is a more basic 

problem with the use of the fuel-specific growth rates for projecting future growth. In future 

years, the sum of the all of the projected fuel-specific populations will be greater than the 

projected total population using the total growth rate for the particular market sector. This is an 

unreasonable result. The total growth in any market sector should be determined by the historical 

total growth in that sector, not by market shifts occurring within the sector. 

The best solution to this problem may be to use total market sector growth factors to 

determine future total populations and to create a separate input (i.e., % share of diesel, gasoline, 

LPG, and CNG engines) to predict changes in fuel market share. Although the current version of 

the model can easily handle multiple growth rates, this solution would involve model coding 

changes that we will not be able to complete before release of the Beta version of NONROAD, 

and may not be able to complete in time for the final release of this version of NONROAD. As 

an interim solution for the Beta release, we have two options on which we request comment. 

The first option would be to only incorporate the total market sector growth factors in this 

version of the model. Under this option, output from the Beta release of the model would not 

reflect market shifts in fuel use. 

The second option would be to scale the individual fuel-specific growth factors so that 

projected total population when the individual fuel-specific populations are summed does not 

exceed the projected total population. This option could be implemented as follows: 

1. project total population using the total growth rate and fuel-specific populations using 

fuel specific growth rates for each market sector out to 2020 (or some other projection 

year). 

2. sum the fuel-specific populations for each year and calculate the fraction of those 

summed populations contributed by each fuel type. 

3. multiply those fractions by the projected total population derived from the total growth 

rate to determine projected populations by each fuel type scaled to the projected total 

populations. 

This option offers a relatively crude method for adjusting the projected fuel-specific populations, 

and we invite comment on more appropriate statistical analyses that might be used instead of this 

approach. However, under this option, Beta users would be able to see model results that do 

reflect estimates of changes in fuel market share. Table 2 shows the original and scaled 

population growth estimates by fuel type for each market sector. 

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We invite comment on which of the two options to incorporate into the Beta release, but 

caution that we may have to implement the first option in the Beta release due to time 

constraints. 

Table 2. Projected Average Annual Growth Rates with Fuel-Specific Growth Rates Scaled 

to PSR Total Growth Rates 

Sector 

BEA 

PSR 

Total Diesel Diesel 

Scaled 

Gasoline Gasoline 

Scaled 

LPG LPG 

Scaled 

CNG CNG 

Scaled 

Airport Service 5.5% 8.2% 9.4% 8.3% 1.4% 0.8% 

Construction 1.0% 2.6% 3.6% 3.3% 0.3% 0.0% 

Farm 2.4% 2.8% 3.2% 3.1% 2.0% 1.9% -7.7% -8.1% 

Industrial 1.9% 3.1% 4.4% 3.6% -3.5% -4.3% 4.1% 3.3% 

Lawn & 

Garden 1.0% 2.7% 9.6% 9.1% 2.6% 2.5% 

Light 

Commercial 1.9% 4.9% 5.5% 5.3% 4.7% 4.6% 14.2% 13.2% 5.1% 5.0% 

Logging 7.4% 5.2% -0.8% -1.2% 5.9% 5.4% 

Railway -0.9% 2.7% 5.1% 4.5% 1.3% 0.8% 

Recreational 1.0% 0.9% 3.9% 3.8% 0.9% 0.8% 

1. “BEA Regional Projections to 2045: Vol. 1, States”, U.S. Department of Commerce, Bureau 

of Economic Analysis, July 1995, available on the World Wide Web at 

www.bea.doc.gov/bea/ar1.htm 

2. “Comparison of Methods for Projecting Nonroad Equipment Activity Levels”, E.H. Pechan 

and Associates, Inc., Prepared for U.S. Environmental Protection Agency, Office of Mobile 

Sources, Ann Arbor, MI, September 1997 

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Appendix - Engine Populations by Year, Market Sector, and Fuel Type 

1989 1990 1991 1992 1993 1994 1995 1996 

Airport Service Diesel 

Gasoline 

8,325 

1,904 

9,516 

1,699 

10,688 

1,583 

11,800 

1,548 

12,862 

1,617 

13,962 

1,701 

15,087 

1,851 

16,199 

2,042 

Total 10,229 11,215 12,271 13,348 14,479 15,663 16,938 18,241 

Construction Diesel 

Gasoline 

1,445,011 

746,147 

1,515,056 

750,523 

1,563,077 

744,661 

1,614,190 

740,852 

1,671,812 

740,747 

1,740,599 

746,487 

1,810,301 

757,411 

1,869,003 

766,264 

Total 2,191,176 2,265,603 2,307,767 2,355,077 2,412,600 2,487,185 2,567,862 2,635,454 

Farm Diesel 

Gasoline CNG 

2,624,347 

1,200,445 

17,457 

2,764,773 

1,231,311 

16,355 

2,881,337 

1,258,131 

15,526 

2,992,660 

1,282,338 

14,671 

3,051,566 

1,306,827 

13,609 

3,114,436 

1,332,163 

12,449 

3,270,810 

1,355,539 

11,255 

3,302,604 

1,382,342 

10,050 

Total 3,842,504 4,012,671 4,155,212 4,289,868 4,372,171 4,459,200 4,637,746 4,695,124 

Industrial Diesel 

Gasoline LPG 

652,656 

176,736 

84,314 

683,015 

177,063 

91,092 

708,222 

172,120 

91,545 

735,321 

165,380 

91,062 

765,152 

153,632 

94,866 

805,322 

150,339 

104,450 

849,118 

148,457 

114,569 

892,852 

140,950 

110,292 

Total 913,706 951,185 971,949 991,887 1,013,826 1,060,293 1,112,351 1,144,322 

Lawn & Garden Diesel 

Gasoline 

327,626 

98,583,888 

365,587 

102,100,138 

398,010 

104,940,288 

437,044 

107,515,906 

483,345 

109,594,695 

532,684 

112,415,996 

587,132 

115,937,367 

645,149 

119,490,009 

Total 98,911,514 102,465,725 105,338,298 107,952,950 110,078,040 112,948,680 116,524,499 120,135,158 

Light Commercial Diesel 

Gasoline LPG CNG 

897,686 

4,185,087 

4,128 

37,947 

953,629 

4,376,324 

4,849 

40,571 

1,008,575 

4,537,560 

5,603 

42,651 

1,062,662 

4,701,324 

6,508 

44,611 

1,120,187 

4,912,338 

7,489 

46,767 

1,185,848 

5,185,707 

8,588 

49,122 

1,254,203 

5,520,270 

9,849 

51,944 

1,320,233 

5,868,886 

11,128 

55,098 

Total 5,124,864 5,375,388 5,594,404 5,815,120 6,086,799 6,429,289 6,836,298 7,255,386 

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1989 1990 1991 1992 1993 1994 1995 1996 

Logging Diesel 

Gasoline 

51,430 

337,267 

50,381 

366,182 

48,758 

395,921 

47,261 

427,873 

46,634 

449,011 

47,149 

471,027 

48,348 

492,469 

49,032 

511,778 

Total 388,697 416,563 444,679 475,134 495,645 518,176 540,817 560,810 

Railway Diesel 

Gasoline 

5,686 

10,508 

6,117 

11,285 

6,511 

11,730 

6,856 

11,898 

7,199 

11,900 

7,537 

11,840 

7,867 

11,863 

8,175 

11,816 

Total 16,194 17,402 18,241 18,754 19,099 19,377 19,730 19,991 

Recreational Diesel 

Gasoline 

83,258 

8,797,673 

86,988 

8,727,791 

90,304 

8,632,439 

93,758 

8,678,772 

97,433 

8,654,282 

101,342 

8,815,925 

105,559 

9,119,795 

110,169 

9,424,489 

Total 8,906,281 8,839,961 8,747,216 8,796,325 8,763,104 8,918,613 9,225,906 9,535,762 

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