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Sample Methodologies for Regional Emissions Analysis in Small Urban and Rural Areas

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4.3 Vehicle Age Distribution

The vehicle age distribution determines the fraction of vehicles operating within each emissions control requirement standard and the deterioration of the emission control technology. Emission rates vary widely between new and older vehicles. Thus, even small changes in fleet age, particularly for older vehicles, may result in large changes in emission totals.

The MOBILE6 model requires estimates of a distribution of registered vehicles by age and vehicle category for current and future years. MOBILE6 default values were developed using national level vehicle registration data by age and class for July 1, 1996. EPA developed a methodology to convert the July 1, 1996 registration profile into a general registration distribution by age and by vehicle category for some 6 composite (gasoline and diesel) vehicle types plus motorcycles (see Table below). To project future changes, EPA evaluated general sales growth and vehicle scrappage trends for the total light-duty vehicle in-use fleet and the total heavy-duty vehicle in-use fleet, and made minor adjustments, where possible, to reflect some of the differences between vehicle categories.

MOBILE6 U.S. Vehicle Fleet Distribution of Registration Fractions by age as of July 1

Vehicle age LDV ALL LDT 0 -6,000 LDT 6,001-8,500 HDV 2B-3 8,501-14,000 HDV 4-8B 14,001+ HD School Bus (All) HD Transit. Bus (All) MC
1* 0.0530 0.0581 0.0594 0.0503 0.0364 0.0368 0.0307 0.1440
2 0.0706 0.0774 0.0738 0.0916 0.0728 0.0736 0.0614 0.1680
3 0.0706 0.0769 0.0688 0.0833 0.0681 0.0688 0.0614 0.1350
4 0.0705 0.0760 0.0640 0.0758 0.0637 0.0642 0.0614 0.1090
5 0.0703 0.0745 0.0597 0.0690 0.0596 0.0600 0.0614 0.0880
6 0.0698 0.0723 0.0556 0.0627 0.0557 0.0561 0.0614 0.0700
7 0.0689 0.0693 0.0518 0.0571 0.0521 0.0524 0.0614 0.0560
8 0.0676 0.0656 0.0482 0.0519 0.0487 0.0489 0.0614 0.0450
9 0.0655 0.0610 0.0449 0.0472 0.0456 0.0457 0.0614 0.0360
10 0.0627 0.0557 0.0419 0.0430 0.0426 0.0427 0.0613 0.0290
11 0.0588 0.0498 0.0390 0.0391 0.0399 0.0399 0.0611 0.0230
12 0.0539 0.0436 0.0363 0.0356 0.0373 0.0373 0.0607 0.0970
13 0.0458 0.0372 0.0338 0.0324 0.0349 0.0348 0.0595 0.0000
14 0.0363 0.0309 0.0315 0.0294 0.0326 0.0325 0.0568 0.0000
15 0.0288 0.0249 0.0294 0.0268 0.0305 0.0304 0.0511 0.0000
16 0.0228 0.0195 0.0274 0.0244 0.0285 0.0284 0.0406 0.0000
17 0.0181 0.0147 0.0255 0.0222 0.0267 0.0265 0.0254 0.0000
18 0.0144 0.0107 0.0237 0.0202 0.0250 0.0248 0.0121 0.0000
19 0.0114 0.0085 0.0221 0.0184 0.0234 0.0231 0.0099 0.0000
20 0.0090 0.0081 0.0206 0.0167 0.0219 0.0216 0.0081 0.0000
21 0.0072 0.0078 0.0192 0.0152 0.0204 0.0202 0.0066 0.0000
22 0.0057 0.0075 0.0179 0.0138 0.0191 0.0189 0.0054 0.0000
23 0.0045 0.0072 0.0167 0.0126 0.0179 0.0176 0.0044 0.0000
24 0.0036 0.0069 0.0155 0.0114 0.0167 0.0165 0.0037 0.0000
25 0.0103 0.0360 0.0732 0.0499 0.0799 0.0783 0.0115 0.0000

Note: age 1 = 75% of age 1 as predicted by the curve fit analysis to reflect a July 1 population of age 1 vehicle.

Estimating Vehicle age Distribution

Method 1: Use MOBILE6 Model Defaults

Scale of 1-5(lowest to highest) - Availability of Data:5 ; Ease of Application:5 ; Technical Robustness:1 ; Policy Sensitivity:2

Description
The MOBILE model requires estimates of a distribution of registered vehicles by age and vehicle category for current and future years. This approach uses the national default registration distribution in MOBILE6.
Method Applicability
This method is most applicable in a nonattainment or maintenance area where it is believed that the vehicle fleet age is similar to the national default. This is most likely the case in areas that parallel national socioeconomic statistics. This assessment should include all on-road vehicles in the area including those outside the nonattainment or maintenance area if a considerable portion of vehicles in the on-road fleet come from outside the area.
Data Sources and Procedures

This approach involves using the national default registration distribution that comes with the MOBILE6 model. A review of the national registration data should be made in order to verify the appropriateness of the national default data. This review could look at the most important classes of vehicles: light-duty gas vehicles and heavy-duty diesel vehicles.

Also, an assessment should be made as to the projected trends in sales growth and scrappage trends to determine if the default trends used in MOBILE6 are appropriate. The extent to which the growth and scrappage trends diverge from the national default in the future is an important factor that will affect estimates of future emissions.

Advantages
  • Uses a readily available, nationally recognized source of data that requires little effort for the user to apply.
  • Use of the national average facilities comparisons to other regions using the national averages for the vehicle age distribution.
Limitations
  • Area may have a VMT age distribution that varies significantly from the national default. Thus, the approach may not provide a valid representation of the actual fleet age distribution.
  • Sensitivity tests conducted by EPA[15] found that only a 20% age shift to older vehicles can increase emissions for hydrocarbons and CO by as much as 50% depending on the calendar year of evaluation and up to 40% for NOx.
  • Approach does not include local adjustments for changes in local scrappage or sales rates. Localized shifts in these trends may have substantial impact on emissions.
  • Use of national defaults may have important implications on policy decisions if vehicle registration fees are tied to age of vehicle (i.e., as done in many counties to help reduce emissions a policy could be made to increase license fees as the vehicle ages to encourage people to use newer low-emitting vehicles)
Example Location

This methodology has been applied in Portneuf Valley, Bannock County, Idaho. However, efforts were underway to obtain a VIN decoder that would enable them to use a county specific fleet age distribution because of concerns about using the national default values for this small urban area of Pocatello and Chubbuck.

References:

Bannock Planning Organization, "FY2004 Draft Transportation Improvement Program Conformity Determination," August 15, 2003.

Estimating Vehicle age Distribution

Method 2: Use Local Vehicle Registration Data for In-Use Fleet

Scale of 1-5(lowest to highest) - Availability of Data:3 ; Ease of Application:2 ; Technical Robustness:4 ; Policy Sensitivity:3

Description
The MOBILE model requires estimates of a distribution of registered vehicles by age and vehicle category for current and future years. This approach uses local vehicle registration data to develop these inputs.
Method Applicability
This approach is most applicable in areas where there are significant differences in the local vehicle fleet age distribution relative to the national average. It is most applicable where the local registration data can be assembled and are representative of the nonattainment or maintenance area. Ideally, registration data at the local level can be used to estimate vehicle age distribution. However, adjustments may be needed if a significant portion of on-road motor vehicles is from outside the nonattainment area.
Data Sources and Procedures

This approach involves using local vehicle registration data. This is typically available at the county level, but may also be applied using statewide data from the state motor vehicle registration office. The fleet age should be representative of the vehicle fleet over the small urban or rural area under question. If the pollutants of concern are ozone precursors, then the data should reflect the July 1st date. For CO, the January 1st date should be used.

Also, an assessment should be made as to the projected trends in sales growth and scrappage trends to determine if the default trends used in MOBILE6 are appropriate when using this local vehicle registration data for baseline age distribution. The extent to which the growth and scrappage trends diverge from the baseline is an important factor that will affect estimates of future year emission estimates.

Advantages
  • Uses locally specific registration data, which is likely more representative of the local area than the national default.
  • Requires minimal additional resources, particularly if data is readily available at the county or local level from the State department of motor vehicle registration.
  • Recommended by EPA and generally is encouraged as a preferred approach over the national default approach.
Limitations
  • May include vehicles owned, but not operated in the local area.
  • Registration data does not differentiate between seasonal usage differences in vehicles. For example, in some locations LDGT are operated more frequently in the winter months with the need for better traction in winter driving conditions. Conversely, more LDGV are used in summer months when driving conditions are less demanding.
  • Does not include local adjustments for changes in local scrappage or sales rates. Localized shifts in these trends may have substantial impact on emissions.
Example Location

The basic methodology has been applied in several locations, including Cheshire County, NH and in Missoula County, MT.

In Berks County in Pennsylvania, the Pennsylvania Department of Transportation used the same approach, except for heavy-duty vehicles, where the distribution was estimated using the internal MOBILE6 age distributions, since much of Pennsylvania's heavy-duty vehicle traffic is through traffic and therefore not registered in the state.

The Bay Lake Regional Planning Commission in Wisconsin used the same approaches but distributions were only made at the highest level for the three major vehicle classes of LDGT, LDGT and HDDV. Also, data were only applied using state registration distributions.

For small urban and rural areas in North Carolina, the North Carolina Department of Transportation developed age distributions based on registration data for the eight vehicle types for those portions of the state outside the state's three major urban areas.

References:

Bay-Lake Regional Planning Commission, "Assessment of Conformity of the Year 2025 Sheboygan Area Transportation Plan and the 2004-2007 Sheboygan Metropolitan Planning Area Transportation Improvement Program with Respect to the State of Wisconsin Air Quality Implementation Plan," 2003.

New Hampshire Department of Transportation, "Procedure to Determine VMT Percentages by Vehicle Type in New Hampshire", August 2, 2002.

Montana Department of Environmental Quality, Vehicle Fractions by Functional Roadway Classifications, February 25, 2004.

Pennsylvania Department of Environmental Protection, "The 2002 Pennsylvania Statewide Inventory Using MOBILE6, An Explanation of Methodology," Prepared by Michael Baker, Jr., Inc. November 2003.

4.4 Percent of VMT on Freeway Ramps

In the MOBILE6 model, there are four sets of driving cycles that are modeled separately, representing different types of functional classes of roadways:

The fraction of vehicle miles traveled (VMT) by highway functional system (also called "roadway type" or "facility type") varies from area to area and can have a significant effect on overall emissions from highway sources. For SIP-related highway vehicle emission inventory development in moderate and above non-attainment areas, EPA expects states to develop and use their own specific estimates of VMT by highway functional system. Each driving cycle may be run separately, with analysis results combined outside of the MOBILE6 model, or the user may use the ability of MOBILE6 to combine the results into a single composite emission rate.

It is important for transportation agencies to understand what the MOBILE roadway classifications represent since each driving cycle set implies different assumptions about vehicle activity and different emission estimates in MOBILE6. These classifications may not always match with definitions used by transportation agencies. In particular, most transportation agencies do not explicitly account for freeway ramp VMT separately. Since freeway ramp activity is not included in MOBILE6 in the freeway driving cycle set, freeway VMT must include a corresponding amount of freeway ramp VMT in MOBILE6 to account for acceleration and deceleration to and from freeway speeds. MOBILE6 models freeway ramp VMT based on the assumption that freeway ramps are 8% of all VMT assigned to both freeways and freeway ramps. MOBILE6 models all freeway ramps at a fixed average speed of 34.6 miles per hour. If the freeway ramp VMT is accounted for in other driving cycle sets (i.e., collector roadways), then the VMT in those roadways must be reduced by the amount of VMT assigned to the freeway and freeway ramp combination.

If the user does not choose to provide these percentages, MOBILE6 uses the following default values.

While areas should use local data to estimate the VMT on each classification, given that most areas do not collect specific estimates of VMT on freeway ramps, a default percentage of 8 percent of freeway VMT on ramps (3 percent/34 percent) is generally recommended for use by EPA. This percentage, however, is a national average, and rural areas may have a lower percentage of VMT on freeway ramps due to the limited number of interchanges and large distances between interchanges in comparison to more urban areas. As a result, it may be useful for an area to consider a local study to estimate the freeway ramp percentage. This approach is described below.

Addressing Percent VMT on Freeway Ramps

Method: Use Local Data on Percent of Freeway Traffic on Ramps

Scale of 1-5(lowest to highest) - Availability of Data:3 ; Ease of Application:5 ; Technical Robustness:5 ; Policy Sensitivity:2

Description
This methodology involves collecting data on route mileage of ramps and vehicle travel on ramps from local traffic counts in order to develop a better estimate of the percent of freeway VMT on ramps.
Method Applicability
This method is most applicable in an area where there is reason to believe that the percent of freeway VMT on ramps is significantly different from the MOBILE6 default. This is most likely to be the case in rural areas with few interchanges.
Data Sources and Procedures
This approach involves collecting data on ramp traffic from a ramp count survey and collecting detailed data on the route mileage of ramps compared to the highway itself. This estimated percentage of the area's interstate/freeway VMT that occurs on freeway ramps is then used to estimate total VMT on freeway ramps. An emissions factor for the freeway ramps is then developed and applied to the VMT to estimate emissions on freeway ramps.
Advantages
  • Simplicity of the approach.
  • Uses local data to better characterize travel activity.
  • Requires limited amount of new data collection.
Limitations
  • Requires collection of additional data.
Example Location

This methodology has been applied in rural areas of Kentucky. The Kentucky Transportation Cabinet (KYTC) conducted a rural ramp count survey over a 3-week period, and found that ramp VMT was roughly 1.5 percent of interstate VMT in rural areas. This estimate was significantly below the level assumed in the MOBILE6 default, and had implications on the emissions results since MOBILE6 assumes that average ramp speed is 34.6 miles per hour, which is significantly lower than the average speed on rural highways.

Reference: Phone conversation with Jesse Mayes and Barry House, Kentucky Transportation Cabinet, Jesse.Mayes@ky.gov, February 20, 2004.

4.5 I/M Participation

Many areas have implemented inspection and maintenance (I/M) programs to reduce mobile source emissions. Many of the choices for these I/M program specifications are at the discretion of the local agency depending upon the severity of the air pollution problem and the air pollutant of concern. The types of vehicles in the program as well as the types of I/M program may have significant impacts on the estimated emission rates. For example, areas that have employed the most stringent level of I/M program (IM240) have found on-road emission reductions for CO of 45%, hydrocarbon (HC) as large as 35%, and up to 12% for NOx relative to conditions without the I/M program.[16] For the more minimal I/M programs (biennial emission idle test), reduction benefits are estimated at 19% for CO, 17% for HC, and 0.5% for NOx. Thus, the choice of program may have potentially significant changes in emission totals.

MOBILE6 is capable of modeling the impact of up to seven different exhaust and evaporative emission I/M programs on emission factors. By defining multiple I/M emission reduction programs, the user can model different requirements on different types and ages of vehicles or different requirements in different calendar years. MOBILE6 also allows users to enter a number of I/M program parameters to better model specific I/M program features. These parameters include:

In addition, the mere presence of an I/M program is expected to act as a deterrent to tampering. Thus, in areas with an I/M program, MOBILE6 will reduce the tampering rates even if there is no anti-tampering program. All 1996 and newer model year vehicles are assumed to have negligible tampering effects in MOBILE6. As a result, there is no tampering reduction benefit associated with the 1996 and newer vehicles.

Addressing I/M Participation

Method 1: Apply Type of I/M Program to Area of Analysis

Scale of 1-5(lowest to highest) - Availability of Data:4 ; Ease of Application:4 ; Technical Robustness:5 ; Policy Sensitivity:5

Description
This methodology uses the local I/M program requirements to define the on-road vehicle fleet that is participating in I/M programs. The approach allows the user to define the local I/M program through the application of the MOBILE6 model. For regions that have significant numbers of vehicles subject to other I/M programs, the MOBILE6 model will need to be applied separately for each I/M program.
Method Applicability
This method is most applicable in a nonattainment or maintenance area where the I/M participation rate in the on-road vehicle fleet is essentially the same as the percentage of vehicles registered in the jurisdiction subject to I/M. In regions where a significant portion of the on-road fleet is from outside the local I/M area, an estimate must be made for the fraction of those vehicles outside the local region (see Method #2).
Data Sources and Procedures

This approach involves running the local specific I/M program requirements through the MOBILE6 model to estimate the effects of the I/M program. If, through the use of local survey data, a significant fraction of the on-road fleet is found to be registered outside the jurisdiction of the local I/M program then the procedure should be modified, as described in Method #2.

In order to forecast emissions, the analysis can account for a change in the counties or local areas where I/M programs will be required in the future. The extent to which I/M program requirements change in the future is an important factor that will affect estimates of future emissions.

Advantages
  • Uses the local specific I/M program requirements as defined in local regulations.
  • Approach is straightforward and would generally be considered an acceptable approach providing it can be demonstrated that the approach is representative.
  • Relatively simple to apply and can be modified easily to account for non-I/M effects through the use of survey data.
Limitations
  • The local I/M participation rate may be an invalid representation of the on-road fleet. For example, a number of vehicles from outside the region may pass through the local area, particularly in donut shaped areas, and may therefore cause the local I/M participation rate not to be representative of the local on-road emission rate.
  • If survey data is used to estimate the on-road fleet fraction outside the local I/M program control, it may not be representative if an inadequate number of survey days are sampled.
Example Location

This methodology has been applied in both Pennsylvania's Berks County and Wisconsin's Bay Lake Regional Planning Commission.

In Berks County the I/M program began in 2003 for LDGV and LDGT vehicles only. 1996 and newer vehicles had their OBD computer checked, for 1975 to 1995 model year cars an anti-tampering program with seven inspections is performed and for all years a gas cap pressure check is done.

For Wisconsin, emission factors included different model year vapor recovery programs and more basic inspection maintenance procedures. Five vehicle classes were subject to the program: LDGV, LDGT (1 thru 4), and HDGV2B.

References:

Bay-Lake Regional Planning Commission, Wisconsin DOT, and Wisconsin Department of Natural Resources, Assessment of conformity of the Year 2025 Sheboygan Area Transportation and the 2004-2007 Sheboygan Metropolitan Planning Area Transportation Improvement Program (TIP) with Respect to the State of Wisconsin Air Quality Implementation Plan, Fall 2003.

Michael Baker, Jr., Inc., "The 2002 Pennsylvania Statewide Inventory, Using MOBILE6, An Explanation of Methodology," November 2003.

Addressing I/M Participation

Method 2: Use Accident or Other Data Sources to Estimate Proportion of Traffic Subject to I/M

Scale of 1-5(lowest to highest) - Availability of Data:3 ; Ease of Application:2 ; Technical Robustness:4 ; Policy Sensitivity:5

Description
This methodology uses vehicle accident data, or other vehicle data, to estimate the proportion of vehicles in the on-road vehicle fleet that are participating in Inspection & Maintenance (I/M) programs. The approach is unique in that it accounts for the fact that some vehicles traveling in a jurisdiction are registered in another jurisdiction that may not be subject to the same requirements.
Method Applicability
This method is most applicable in a nonattainment or maintenance area where there is reason to believe that the I/M participation rate in the on-road vehicle fleet is significantly different than the percentage of vehicles registered in the jurisdiction subject to I/M (for example, if a jurisdiction does not have an I/M program but a considerable portion of vehicles in the on-road fleet come from other jurisdictions that do, or alternatively, if the jurisdiction has an I/M program and considerable traffic comes from other jurisdictions that do not). This would be particularly important where an I/M program is not statewide and if there is a high level of inter-county or interstate travel.
Data Sources and Procedures

This approach involves using accident data in order to estimate the proportion of vehicles in the on-road fleet that are from jurisdictions subject to I/M program requirements. Accident data are used to determine the county in which vehicles on the road are registered. Based on place of registration, the proportion of vehicles on the road that are subject to I/M programs can be determined.

The MOBILE model is run twice-once with an I/M program and once without an I/M program. A weighted emissions factor is then calculated by multiplying the MOBILE emissions factor with I/M by the percent of vehicles from jurisdictions subject to I/M, plus the MOBILE emissions factor without I/M by the percent of vehicles from jurisdictions without I/M requirements.

To forecast emissions, the analysis can account for a change in the counties where I/M programs will be required in the future. The extent to which I/M program requirements change in the future is an important factor that will affect estimates of future emissions.

Advantages
  • Uses a readily available source of data on a county-by-county level. Virtually all counties collect accident data due to its obvious uses related to improving safety in high accident areas.
  • Use of the data to estimate the proportion of vehicles subject to I/M is an innovative approach to using existing data for new purposes.
  • Relatively simple to operationalize and improves the quality of data used in analysis (i.e., national defaults or local inputs).
Limitations
  • Accident data may not provide a valid representation of the proportion of in area vs. out-of-area vehicles.
  • The quality of the accident data may create biases. For example, if many accidents occur at nighttime, the mix of vehicles on the road could be very different than during an average day.
Example Location

This methodology has been applied in North Carolina. This methodology was selected since an I/M program currently is limited to nine counties and there is significant county-to-county commuting. The NCDOT assumes that the I/M program in the State will be in force in 48 counties in 2007.

This methodology was used across North Carolina for six urban and six rural road types. It was used primarily for adjusting the vehicle classification mix to reflect the change in fleet mix for higher light-duty truck fraction than the national average using recent historical HPMS data.

References:

Phone conversation with Behshad Norowzi, North Carolina DOT, bnorowzi@dot.state.nc.us), February 17, 2004.

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