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Modifying Link-Level Emissions Modeling Procedures for Applications within the MOVES Framework

2.0 Preparation of MOVES Inputs

In order to answer the first two study questions listed previously, ERG began the process of re-creating, using MOVES, the emissions inventory for the 8-county Houston-Galveston-Brazoria (HGB) ozone nonattainment area 1 prepared by the Texas Transportation Institute (TTI) using MOBILE6 and other associated tools. We selected this inventory as the subject for the analysis based on the level of detail utilized in the current modeling, as well as our long standing relationship with the Texas Commission on Environmental Quality (TCEQ) and the Texas Transportation Institute (TTI), the parties responsible for developing the inventory for the Houston region.

TTI's inventory uses link-level travel demand model outputs obtained from the Houston-Galveston Area Council (H-GAC), which have been processed and combined with MOBILE6 factors for each of the model's 28 vehicle classes by TTI. TTI processing activities include application of vehicle miles traveled (VMT), volume, speed, time of day, and seasonal adjustment factors to the link-level H-GAC activity data to obtain hourly allocations, as well as preparation and execution of episode-specific MOBILE6 runs in order to develop final mass emissions estimates. The emissions inventory files, as well as all of the supporting data and documentation, used to support the 2006 Houston-Galveston-Brazoria ozone nonattainment SIP is posted on TCEQ's public ftp server 2.

The inventory scenario selected for re-creation was an ozone season non-school weekday. Each county in the HGB area was modeled independently. Data provided by TTI included tab delimited summary files containing travel demand model (TDM) based VMT, VMT mix, hours of operation, vehicle speed, and other parameters on an hourly basis for each county, which were used for development of the first set of MOVES model runs prepared for this analysis. HPMS-based VMT was also provided, and was used to develop the second set of MOVES modeling runs. In addition, TTI provided MOBILE6 input files, along with associated MOBILE6 VMT by hour, speed VMT, VMT by facility, registration distribution, and inspection and maintenance (I/M) inputs.

The TDM-based VMT data was processed using SAS 3 programs developed by ERG to obtain VMT estimates usable in MOVES. ERG developed other spreadsheet tools and methodology for conversion of HPMS-based VMT into MOVES format 4. MOVES spreadsheet tools developed by EPA specifically for conversion of MOBILE6 inputs into MOVES formats (available at were also used extensively. The methodology used in preparing inputs for execution in MOVES generally involved four steps:

The general data flow for the inputs required to the MOVES model is presented in Figure 2-1.

Figure 2-1. MOVES Input Data Flow

Flowchart depicting flow of raw data in creating inputs for the MOVES model. TDM_based VMT is processed with a SAS program to determine ramp fractions and VMT by class. These data, along with speed and age distributions from MOBILE6, are input to the appropriate EPA converter tools. Output from the EPA converter tools, along with MOBILE6 I/M program, fuel, and meteorological data and MOVES derived population data, are directly input to MOVES. MOVES then produces model output.

A description of the processes used in analysis of the data provided by TTI, along with documentation of the methodology employed in creating MOVES input and output files, is provided below.

2.1 VMT Pre-Processing

The first step in preparing data for input to MOVES is to ensure that the activity data that will be used is representative and complete. Correct application of VMT, whether obtained from a travel demand model, HPMS, or other sources, is crucial to ensure model outputs correctly estimate emissions for a given area. For the purposes of this study, we prepared activity data derived from both TDM and HPMS. In this section, we discuss procedures we undertook in preparing our activity data, prior to subsequent processing in EPA's VMT spreadsheet tools, which will be discussed later.

Processing of TDM-based VMT data

In the case of TDM-based VMT, TTI provided tab-delimited summary files that included VMT, VMT mix, hours of operation, vehicle speed, and other parameters on an hourly basis for each county of interest. An example of the tab-delimited VMT summary data we received is presented in Table 2-1.

Table 2-1. Example Harris County Tab-delimited 24-hour VMT (gasoline vehicles)

Urban Interstate 5234029 425653 1416995 423979 194975 47905 16793 6649 2387 6478 2131 2472 426
Urban Other Freeway 2325426 189130 629612 188396 86638 21108 7399 2930 1052 2855 939 1089 188
Toll Roads 3554228 289074 962325 287950 132419 32149 11270 4462 1602 4348 1430 1659 286
Ramps (Fwy/Toll/Frnt) 364309 32879 109453 33570 15438 4340 1521 602 216 587 193 224 39
Urban Prin. Art. 1648401 148801 495356 151937 69871 19876 6967 2759 990 2688 884 1026 177
Urban Other Art. 2948941 266194 886158 271797 124991 35163 12326 4880 1752 4755 1564 1814 313
Urban Collector 213299 24812 82600 26893 12367 4218 1479 585 210 570 188 218 38
Local (Cent. Conn.) 3902947 454054 1511540 492125 226314 76860 26942 10668 3829 10394 3419 3966 684
Rural Interstate 12238642 995312 3313381 991404 455917 111089 38941 15419 5534 15023 4942 5733 988
Rural Other Freeway 2521654 205085 682724 204286 93945 22873 8018 3175 1140 3093 1018 1180 203
Rural Prin. Art. 6175292 557389 1855542 569097 261710 73626 25808 10219 3668 9957 3275 3799 655
Rural Other Art. 15704998 1417602 4719178 1447400 665616 186714 65449 25914 9302 25250 8306 9635 1661
Rural Major Col. 801542 93251 310433 101070 46479 15690 5500 2178 782 2122 698 810 140
Rural Collector 473582 55099 183422 59718 27463 9224 3233 1280 460 1247 410 476 82
Local (Intrazonal) 138475 16113 53642 17464 8031 2729 956 379 136 369 121 141 24
TOTALS 58245767 5170448 17212360 5267087 2422176 663563 232601 92097 33059 89736 29518 34241 5902

It became apparent to us that for the purposes of this study, using a combination of the tab-delimited summary files and MOBILE6 inputs provided by TTI would be the most efficient way to create representative MOVES input files. We arrived at this conclusion after perusing the MOVES conversion tools made available by EPA, which rely primarily on existing MOBILE6 inputs for use in creating MOVES input files. 5 It is important to note that EPA's conversion tools are designed to accept activity data in NMIM 6 format, and data available in that format may require little to no additional processing on the part of the user. However, since activity data for a given region may be available in a variety of formats, users interested in preparing TDM-based VMT for input to MOVES for their own region may need to develop their own methods for processing VMT. In doing so, the primary consideration should be:

Each of these inputs are required for EPA's VMT processor, which is further described in Step 2.

Figure 2-2. Example Input of VMT to EPA Conversion Tool - Harris County

Screenshot depicting input VMT by road type and vehicle class, along with vehicle class descriptions, as presented in the EPA conversion tool spreadsheet.

For this study, ERG used a SAS program to process the VMT summary files provided by TTI, aggregated by MOBILE6 vehicle type and H-GAC roadway type. Table 2-2 presents the mapping ERG used for converting H-GAC roadway types to HPMS roadway types; a similar mapping will likely need to be developed for roadway types in other areas. The SAS program was written solely for use with the TDM output provided by TTI, and was intended as both a QC measure (to verify MOBILE6 inputs provided by TTI were consistent with the TDM outputs) and as a tool to generate ramp fractions and VMT for use in the EPA conversion tools. ERG's SAS program produced appropriately formatted VMT, ramp fractions, and other QC outputs 8 for each county, which were subsequently used as input to the EPA converter tools discussed later.

Table 2-2. H-GAC Road Types Mapped to HPMS Road Types

H-GAC Road Type Code H-GAC Road Type Description HPMS Road Type Code HPMS Area Type HPMS Road Type Description
1 Urban Interstate Freeways 23 Urban Interstate
2 Urban Other Freeways 25 Urban Other Freeways and Expressways
3 Toll Roads 25 Urban Other Freeways and Expressways
4 Ramps (Frwy/Toll/Frontage) Special Case, no direct link, must map by ramp fraction    
5 Urban Principal Arterials 27 Urban Other Principal Arterial
6 Urban Other Arterials 29 Urban Minor Arterial
7 Urban Collectors 31 Urban Collector
8 Locals (Centroid Connectors) 33 Urban Local
10 Rural Interstate Freeways 11 Rural Interstate
11 Rural Other Freeways 13 Rural Other Principal Arterial
12 Rural Principal Arterials 13 Rural Other Principal Arterial
13 Rural Other Arterials 15 Rural Minor Arterial
14 Rural Major Collectors 17 Rural Major Collector
15 Rural Collectors 19 Rural Minor Collector
40 Local (Intrazonals) 21 Rural Local

Processing of HPMS-based VMT data

In the case of HPMS-based VMT, a different set of procedures must be used to arrive at activity data that can be used as format to the EPA converter tools, and subsequently, to the MOVES model itself. The HPMS VMT, also provided by TTI, is simplified and streamlined relative to the TDM-based VMT discussed above. The TDM based-VMT was provided for a number of specific vehicle types and road types, across all 24 hours of a given ozone season weekday. The HPMS VMT used in this analysis, however, is organized only by road types and area types, as seen in Table 2-3, which are less specific that what is available in the TDM-based VMT, a sample of which is presented previously in Figure 2-2.

Table 2-3. Harris County HPMS VMT Example

Data Type Area Type Interstate Freeway Principal Arterial Minor Arterial Major Collector Minor Collector Local Total
Rural (<5,000) 681,075.940 0.000 886,330.630 776,455.580 531,412.352 133,798.075 492,808.352 3,501,880.929
Small Urban (5,000-49,999) 0.000 0.000 177,295.000 81,002.190 50,515.680 0.000 14,614.040 323,426.910
Large Urban (50,000-199,999) 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000
Urbanized (200,000+) 30,049,085.890 21,045,993.960 18,072,516.123 19,274,509.064 8,199,444.036 0.000 3,651,528.589 100,293,077.662
Total 30,730,161.830 21,045,993.960 19,136,141.753 20,131,966.834 8,781,372.068 133,798.075 4,158,950.981 104,118,385.501

Since MOVES requires VMT data formatted by source type, and the HPMS data provided was aggregated only by road type, it is necessary to convert the VMT basis for use in the model. This can be accomplished by extracting default VMT ratios from within MOVES itself , which can then be used to define the relationship between VMT by source type and VMT by road type, and thereby calculate representative VMT by HPMS source type.

In order to do this, ERG exported the HPMSVtypeYear table from the MOVES MySQL database and used the VMTGrowthFactor for the year of interest to project the 1999 HPMSBaseYearVMT to 2006. The general formula is shown here. A sample of the values calculated is shown in Table 2-4.

HPMSBaseYearVMT (2006) = HPMSBaseYearVMT (1999) * VMTGrowthFactor (2006).

Table 2-4. Default HPMS VMT, Growth Factors, and 2006 Projected VMT

HPMSVtypeID yearID VMTGrowthFactor HPMSBaseYearVMT
10 1999 10600000000
20 1999 1.56864E+12
30 1999 9.00735E+11
40 1999 7657000000
50 1999 70273700000
60 1999 1.32358E+11
10 2006 1.119 11861400000
20 2006 0.98953 1.55222E+12
30 2006 1.0398 9.36584E+11
40 2006 1.007 7710599000
50 2006 1.007 70765615900
60 2006 1.034 1.36858E+11

Next, ERG calculated the VMT fraction by HPMSVtypeID using the HPMSBaseYearVMT. The VMT fraction is equal to the HPMSBaseYearVMT for each HPMSVtypeID, divided by the sum of HPMSBaseYearVMT for all HPMSVtypeIDs, as illustrated by this equation. An example of the calculation is shown in tabular form in Table 2-5.

VMTfraction HPMSVtypeID = HPMSBaseYearVMT HPMSVtypeID / sum(HPMSBaseYearVMT).

Table 2-5. Default MOVES VMT Fractions

HPMSVtypeID yearID HPMSBaseYearVMT baseYearOffNetVMT VMT Fraction
10 2006 11861400000 0 0.004367237
20 2006 1.55222E+12 0 0.571508987
30 2006 9.36584E+11 0 0.344840023
40 2006 7710599000 0 0.002838958
50 2006 70765615900 0 0.026055122
60 2006 1.36858E+11 0 0.050389674
TOTAL 2.716E+12

ERG then applied the VMT fraction by HPMSVtypeID to the HPMS total VMT provided for each county by TTI, as shown in this equation, and in Table 2-6.

LOCALVMT HPMSVtypeID = HPMSTotalVMT county * VMTfraction HPMStypeID.

Table 2-6. HPMS VMT by Source Category

County Brazoria Chambers Fort Bend Galveston Harris Liberty Montgomery Waller
Total VMT -
VMT Fraction
10 0.004367237 25378.13745 11203.62384 36609.01799 25948.09112 454709.6702 10347.52624 44018.87574 8211.623797
20 0.571508987 3321054.817 1466137.891 4790759.597 3395640.566 59504593.02 1354106.538 5760434.532 1074596.306
30 0.344840023 2003875.083 884645.7974 2890673.088 2048879.014 35904186.42 817047.7457 3475760.522 648395.4289
40 0.002838958 16497.2635 7283.006285 23797.98822 16867.76649 295587.6986 6726.493117 28614.82618 5338.032462
50 0.026055122 151407.0453 66841.29538 218410.9553 154807.4131 2712817.194 61733.78077 262618.4812 48990.89615
60 0.050389674 292815.8144 129268.6764 422398.9816 299392.0041 5246491.498 119390.9257 507894.7567 94746.64222

Finally, ERG formatted the local VMT data by HPMS vehicle type for import into MOVES according to the MOVES template for VMT by vehicle type. (Note that baseYearOffNetVMT is always set to zero for this purpose.) The HPMS-based VMT derived in this way negates the use of the first VMT converter tool described under Step 2 below, in that at this point we have effectively calculated total VMT by county and top level HPMS source category.

When using HPMS-based VMT as a source of activity data for MOVES, users must not only assign appropriate source types to the VMT described above, but also derive road type distributions for the data. 9 In order to perform this calculation for the HPMS data, ERG mapped the Houston-Galveston Area Council (H-GAC) road types listed in the TTI tab files to the standard HPMS road types. In cases where the mapping was not transparent, ERG used its best engineering judgment to assign the H-GAC road types to the most appropriate HPMS road type category. Table 2-7 shows the mapping.

Table 2-7. H-GAC Road Types Mapped to HPMS Road Types

H-GAC Road Type Code H-GAC Road Type Description HPMS Road Type Code HPMS Area Type HPMS Road Type Description
1 Urban Interstate Freeways 23 Urban Interstate
2 Urban Other Freeways 25 Urban Other Freeways and Expressways
3 Toll Roads 25 Urban Other Freeways and Expressways
4 Ramps (Frwy/Toll/Frontage) Special Case, no direct link, must map by ramp fraction    
5 Urban Principal Arterials 27 Urban Other Principal Arterial
6 Urban Other Arterials 29 Urban Minor Arterial
7 Urban Collectors 31 Urban Collector
8 Locals (Centroid Connectors) 33 Urban Local
10 Rural Interstate Freeways 11 Rural Interstate
11 Rural Other Freeways 13 Rural Other Principal Arterial
12 Rural Principal Arterials 13 Rural Other Principal Arterial
13 Rural Other Arterials 15 Rural Minor Arterial
14 Rural Major Collectors 17 Rural Major Collector
15 Rural Collectors 19 Rural Minor Collector
40 Local (Intrazonals) 21 Rural Local

ERG assigned the HPMS VMT provided by TTI to the appropriate road types. The VMT for the urban HPMS road types (codes 23, 25, 27, 29, 31, and 33) was obtained by summing the HPMS VMT for small urban areas, large urban areas, and urbanized areas. Then, the HPMS road types were mapped to the MOVES road types. Table 2-8 illustrates the HPMS road type to MOVES road type mapping, which was derived from calculation sheets contained in the EPA converter tools discussed below in Section 2.2.

Table 2-8. HPMS Road Types Mapped to MOVES Road Types

11 Rural Interstate 2 Rural restricted access
13 Rural Other Principal Arterial 3 Rural unrestricted access
15 Rural Minor Arterial 3 Rural unrestricted access
17 Rural Major Collector 3 Rural unrestricted access
19 Rural Minor Collector 3 Rural unrestricted access
21 Rural Local 3 Rural unrestricted access
23 Urban Interstate 4 Urban restricted access
25 Urban Other Freeways and Expressways 4 Urban restricted access
27 Urban Other Principal Arterial 5 Urban unrestricted access
29 Urban Minor Arterial 5 Urban unrestricted access
31 Urban Collector 5 Urban unrestricted access
33 Urban Local 5 Urban unrestricted access

Once these mapping schemes were completed, ERG summed the VMT by MOVES road type. The next step in the process was to obtain the MOVES default VMT fraction by vehicle type, using the same methodology described above in the HPMS-based VMT Conversion section. After projecting 2006 VMT from 1999 base VMT using factors supplied in the HPMSVtypeYear table in MOVES, ERG calculated a VMT fraction by HPMS type using default VMT ratios, an example of which is shown in Table 2-9.VMT HPMSvehicletypeandMOVESroadtype = VMTFractionbyVehicleType MOVESdefault * VMT MOVESRoadType.

Table 2-9. Example MOVES Default VMT Fraction by Vehicle Type ID

HPMSVtypeID VMT Fraction
10 0.004367237
20 0.571508987
30 0.344840023
40 0.002838958
50 0.026055122
60 0.050389674

ERG then multiplied the default VMT fraction (by vehicle type) with the total VMT (by MOVES road type) to obtain the VMT aggregated by HPMS Vehicle type and MOVES road type, according to the following equation.


Following the equation for RoadTypeVMTFraction provided below, ERG then divided the VMT by HPMS vehicle type and MOVES road type with the sum of all VMT for a given HPMS vehicle type in order to obtain the VMT distribution by road type that is required for input to MOVES:

RoadTypeVMTFraction = VMT HPMSvehicletypeandMOVESroadtype / [Sum(VMT HPMSvehicletypeandMOVESroadtype)] HPMSvehicletype.

All road type distribution calculations performed in this section are provided for reference electronically in Appendix A in the "Calculate HPMS VMT by HPMS vehicle type" spreadsheet.

2.2 Use of EPA Spreadsheet Converter Tools

Because EPA understands that many users of MOVES will already be familiar with MOBILE6 and NMIM, and likely have on hand previously performed analyses for their areas of interest that use those models, the agency has developed a number of converter tools that allow for transition of older data to MOVES. These spreadsheet tools were most recently updated in February 2010, and are freely available at EPA's website 10. ERG made extensive use of these tools in adapting TTI's previously developed MOBILE6 files into a form usable in MOVES, and we expect that others users will want to do the same. Each of the converter tools used during this study have been included electronically in Appendix A, and are discussed in additional detail below.

VMT Converter Tool

Having processed the TDM-based VMT using SAS, ERG used the first of several EPA spreadsheet tools employed for this effort, the VMT Converter Tool, to prepare inputs for MOVES. The specific converter used 11 was based on translation of specific VMT by the 28 MOBILE6 vehicle types, listed under "Set 2" on EPA's Tools for MOVES page. This tool is necessary to convert both VMT and road type fractions from a MOBILE6 vehicle type basis to a MOVES source type basis 12. Note that although we used only one of the VMT converter tools EPA provides on the Tools for MOVES website, there are seven other such VMT converters available. These converters are designed to assist users with conversion of VMT on a number of vehicle type bases (either 28, 16, 12, or 8 vehicle types), and based on either specific VMT or VMT/road type fractions. Users of MOVES are encouraged to closely examine EPA's available converter tools to determine which is best suited for their own application.

A separate converter spreadsheet was created for each of the eight counties of interest for this effort. This particular tool requires as input ramp fractions, hourly VMT fractions, monthly VMT fractions, and VMT aggregated by vehicle class and road type, each of which are described below:

The output from the converter tool includes VMT by HPMS source type, monthly VMT fractions by source type, hourly VMT fractions by source type and vehicle type, road type distribution by source type, and a converted ramp fraction. The ramp fraction and road type distribution produced here were directly imported into MOVES, as described later. The monthly fractions produced, meanwhile, were ignored in favor of those produced by EPA's Average Annual Daily (AAD) VMT converter tool, because using the default monthly weighting provided in this tool for VMT in July (1.0871 in a non-leap year) would have over-estimated VMT for the scenario we were modeling. The calculated VMT itself, as shown in Figure 2-3, was in turn used as input to the AADVMT tool.

Figure 2-3. VMT Output from EPA Conversion Tool - Harris County

Screenshot depicting output VMT by HPMS source type, as presented in the EPA conversion tool spreadsheet.

AADVMT Calculator Tool

The AADVMT tool 13 is the second of EPA's tools ERG used to develop MOVES inputs. This tool is necessary to convert Average Annual Daily VMT, such as that provided to us by TTI, into annual VMT, which is required as input to MOVES whether a user is performing an annual analysis or not. The AADVMT tool calculates annual VMT based on provided AAD VMT, and weights the VMT appropriately across months and days (weekend or weekday) of interest. As before, a separate AADVMT spreadsheet was created for of the eight counties to be modeled.

To use the AADVMT tool, the HMPS VMT obtained from the HPMSvTypeYear output sheet in the VMT converter tool shown above was copied (per guidance in the Instructions sheet) to the Import HPMS AADVMT and Factors sheet in the AADVMT calculator. In addition, all of the monthly and weekend-day adjustment factors on that sheet were changed from their default values to 1.0 to reflect that, for this inventory, we are ultimately only attempting to model emissions for a single day in a single month (thus, our daily VMT did not need to be re-weighted on an monthly or weekend-day basis for conversion to annual VMT). An example of the inputs to the AADVMT tool is shown in Figure 2-4. The outputs from the AADVMT calculator (in the HPMSVTypeYear, monthVMTFraction-calculated, and dayVMTFraction-calculated sheets) were ultimately used for inputs to MOVES through the County Data Manager, which is described in more detail later in this document.

Figure 2-4. AADVMT Input - Harris County

Screenshot depicting AADVMT input VMT, along with monthly and weekend_day adjustment factors, as presented in the AADVMT EPA conversion tool spreadsheet.

Age Distribution

Yet another converter tool 14 provided by EPA facilitates the transformation of MOBILE6-formatted registration distribution data into MOVES-compatible vehicle age distribution data files. ERG input TTI's MOBILE6 registration data to the tool, which expands registration data across thirty-one years, applies the registration distribution to the vehicle count for the calendar year of interest, and maps the total vehicle counts, by age, to one of the thirteen appropriate MOVES source types. The vehicle counts are then renormalized for each of the thirteen source types. The outputs of the converter tool, formatted appropriately for import into MOVES to populate the SourceTypeAgeDistribution table, include source type, year, vehicle age, and vehicle distribution fraction.

Speed Distribution

EPA also provides a tool 15 that converts MOBILE6-formatted speed distribution files to the format required by MOVES. (We used the MOBILE6-based version of the tool, but EPA provides an NMIM-based version as well for users with NMIM-formatted speed distributions.) ERG input TTI's MOBILE6 speed distribution data to the tool, which expands MOBILE6 fourteen-bin, VMT-based speed distribution files to the MOVES sixteen-bin, time-based speed distribution format. The outputs of the speed distribution converter tool, formatted appropriately for import directly into MOVES to populate the AvgSpeedDistribution table, include source type, road type, hour and day, average speed bin, and speed distribution fraction.

2.3 Preparation of Other Inputs

In addition to the various outputs from the converter tools described in the previous section, other inputs are also necessary for calculating emissions inventories at the county level in MOVES. These include vehicle populations, inspection and maintenance (I/M) program parameters, fuel characteristics, and ambient meteorological conditions. These model inputs were developed by ERG, are provided electronically as part of the MOVES County Data Manager input databases included in Appendix A, and are described in the section that follows.

Vehicle Population

EPA's Technical Guidance 16 prescribes the use of state motor vehicle registration data for developing vehicle populations in MOVES, which are used to calculate both start and evaporative emissions. ERG obtained 2006 registration data for each county of interest in this study from the Texas Department of Motor Vehicles. This data was aggregated by MOBILE6 vehicle class. In order to prepare the data for modeling in MOVES, ERG converted the vehicle populations provided to MOVES source types by using the mapping ratios available in Table A.1 of the Appendix in the Technical Guidance.

Although usage of registration data to develop vehicle populations is suggested by EPA in the Technical Guidance, users should understand that the vehicles registered in a county for a given point in time do not necessarily correspond to the VMT driven over that same period in the county. For example, commuters living in Fort Bend county may drive a significant portion of their vehicle miles in Harris county. In this example, using registration data as a population surrogate may lead to overestimation of start and evaporative emissions in Fort Bend county, while underestimating those same emissions in Harris County. While a better alternative for determining representative source populations does not currently exist, it is an important issue for users to be aware of.

Ideally, users will be able to develop population data files for import into MOVES using state and local resources, such as state motor vehicle registration data, local transit authorities, and/or data provided by other stakeholders. However, it has been our experience that this data can sometimes be difficult to obtain at the level of disaggregation required for import into MOVES. If adequate resources for development of vehicle populations are lacking, users can follow section 3.3 of EPA's Technical Guidance to calculate local vehicle population based on their VMT data.

Because we originally had difficulty obtaining registration data ourselves, ERG went through the process of developing populations surrogates based on VMT. As described in the EPA Technical Guidance, the first step in deriving local population estimates based on local VMT data is to perform a MOVES modeling run using MOVES default population and VMT data. To do this, ERG selected "National" as the modeling domain, and "County" as the geographic selection type. We then selected the county of interest, along with the 2006 year, for the evaluation. For the cases being evaluated in this exercise, the selections for time span were a 24-hour period for a weekday in the month of July. All vehicle and fuel types (except the placeholder fuel type) were selected, as well as all road types for this modeling scenario. Since the only interest here is obtaining the default population to VMT ratio, selection of a particular pollutant is not relevant. However, the model required the selection of at least one pollutant, so Oxides of Nitrogen was selected for these runs. Finally, output data selections were made, which are important to ensure the required information for calculating the default MOVES population to VMT ratios is present. For the evaluations undertaken here, the following selections were made:

Once the model runs were complete, ERG exported the ActivityType table and the MOVESActivityOutput table from the output database generated by the model. Using this data, ERG calculated the MOVES default population to VMT ratio for each source type by dividing the MOVES default population by the MOVES default VMT in the outputs.

Next, ERG obtained the local VMT data, by source type, for the area of interest (which was obtained by summing the VMT by county as calculated in EPA's VMT Converter Tool spreadsheet). Finally, the local vehicle population, by source type, was calculated by applying the default MOVES population to default MOVES VMT ratio to the local VMT, by source type, by county. This calculated population is what can ultimately be used for input to MOVES if other sources of population data are unavailable.

I/M Programs

Information on I/M programs in the HGB area was also provided by TTI in the form of inputs to MOBILE6. Note that only five of the eight counties modeled are affected by I/M - Brazoria, Fort Bend, Galveston, Harris, and Montgomery. Although there are no converter tools provided by EPA to adapt MOBILE6 I/M information into a format usable by MOVES, doing so manually is a fairly straightforward process. However, there are a few issues to be aware of when doing so.

As specified in the MOVES User's Guide 17, the most straightforward approach to making changes to an I/M program in MOVES is to begin with the MOVES default I/M information for the particular county being modeled, and adapt the information in the defaults as necessary. This can be most easily done by exporting the default I/M values using the feature provided in the County Data Manager into an Excel Spreadsheet.

In order to most accurately represent the inventory modeled by TTI, ERG changed the test standards from default values to match those specified in MOBILE6 inputs. In doing so, we added new records to reflect the I/M parameters specified in MOBILE6 inputs and included a value of Y for the useIMyn field as suggested in the MOVES User's Guide. We changed the useIMyn field to N for existing records in the IM table. Specifically, we changed the testStandardsID from 24 to 23 for the exhaust I/M program affecting light duty vehicles, represented by source types 21, 31, and 32 in MOVES (passenger cars, passenger trucks, and light commercial trucks, respectively). This reflected the ASM 2525 Final Cutpoints being used in the MOBILE6 inputs, as opposed to the ASM 2525/5015 Phase-in Cutpoints in place in the MOVES defaults. Similarly, the testStandardsID was changed from 43 to 45 for an evaporative program affecting light-duty vehicles, which represented an OBD Evap and Gas Cap program, as opposed to only an Evap program. In addition, ERG also added an I/M program consisting of a two-mode, 2500 RPM/Idle Test for heavy duty source types 41, 42, 43, 51, 53, 54, 61, 62, in addition to the program that already existed for heavy-duty source type 52.

One of the challenges of applying I/M programs as specified in MOBILE6 is that MOBILE6 vehicle types do not map precisely with MOVES source types. In particular, MOVES source types 31 and 32 can encompass MOBILE6 source types LDGT1 all the way up to HDGV5. In section 3.10.6 of the Technical Guidance, EPA recommends calculating a compliance factor based not only on compliance rate and waiver rate (both provided in MOBILE6 inputs), but also on regulatory class coverage. Calculating the regulatory class coverage is now fairly straightforward, as the information in Table A.3 of the April 2010 Technical Guidance Appendix (Gasoline I/M Regulatory Coverage Adjustments) provides the proper conversion factors, along with example calculations.

Once users have appropriately modified the default I/M program for the modeling area of interest and appropriately calculated conversion factors for each I/M program, pollutant, source type, and model year combination, the spreadsheet created can be imported back into MOVES as described later.

Fuel Formulation and Supply

MOVES uses two tables to characterize information with respect to fuels. The first, Fuel Supply, lists fuel formulations, along with their respective market shares, on a monthly and yearly basis. The second table, Fuel Formulation, lists a number of descriptive parameters for the various fuel formulations. In order to populate these two tables, ERG initially culled information on fuels used in the preparation of TTI's inventory from their MOBILE6 input files, as well as the accompanying 2005/2006 On-Road Mobile Source, Ozone Episode Modeling Emissions Inventories for the HGB Eight-Hour Nonattainment Area report. Reid vapor pressures, oxygenate weight percentages, and sulfur content for both gasoline and diesel fuels were specified in the MOBILE6 runs.

MOBILE6 oxygenates are listed in terms of weight percent, and must be converted to volume percent for use in MOVES. This was done using ratios specified on page 166 of the User's Guide to MOBILE6.1 and MOBILE6.2 18. Sulfur content and RVP provided in MOBILE6 were directly input to the fuel formulation sheet. The other fields required in the fuel formulation sheet (e.g., aromatic content, e200, cetane index, and so forth) were populated using the existing fuel formulation defaults in MOVES. The fuel supply sheet was populated with two new fuel formulation IDs for July 2006, one representing gasoline and one diesel, each with 100% market share. We felt this most accurately reflected the data available in the TTI MOBILE6 inputs. Note that per the Technical Guidance, creating some sort of single average fuel to be representative of a given area is discouraged - rather, multiple fuels in use for a given area should be input, and market share adjusted appropriately for each of those fuels. In this case, however, ERG created a single fuel, since that most closely mirrored the inputs used in TTI's MOBILE6 input files.

This initial attempt to create a representative fuel supply and formulation uncovered a couple of notable bugs in MOVES2010. The first bug involved creation of new fuel formulation IDs for input to MOVES. When a user creates and imports new fuel formulation IDs, MOVES does not currently "zero out" the market share of existing fuel formulation IDs, which leads to overestimation (approximately two to four times) of pollutants in model calculations. To avoid this problem, EPA suggests that users should currently adjust data associated only with existing fuel formulation IDs, and not create new IDs.

The second bug that was discovered is related to fuel type IDs. ERG's initial import contained a fuel type ID of 12, which represents E10 fuel. The ethanol volume percentage associated with this fuel, as calculated from the MOBILE6 inputs, was 9.28%. This is less than the range of 10-20% that MOVES expects for that particular fuel type ID. Therefore, MOVES did not handle calculation of VOC emissions correctly, and underestimated them by approximately an order of magnitude 19. In this particular case, the workaround suggested by EPA was to use a different fuel type ID of 13, which corresponds to E8 fuel and has an expected ethanol range that includes the 9.28% specified.

Because of the issues surrounding emissions calculations related to fuel formulations in MOVES, EPA 20 recommended that ERG use the default Fuel Formulation and Fuel Supply provided in MOVES for the HGB area instead of importing or adjusting custom formulations, until the existing bugs are fixed. The most straightforward way to do this is to export MOVES default fuelformulation and fuelsupply tables via the interface, and then reimport them, as suggested in the MOVES User's Guide. In most cases, modeling with the default Fuel Formulation and Fuel Supply for a given area should provide representative outputs.

Meteorological Data

MOVES provides a template for importing hourly temperature and relative humidity data. ERG simply formatted the hourly temperature and relative humidity data from the MOBILE6 input files according to the template in an Excel spreadsheet. Although this is a fairly straightforward conversion that ERG performed manually, EPA also provides two meteorological data converter tools on their website (one for MOBILE6-formatted data, and one for NMIM-formatted data) for modelers to use.

2.4 MOVES Model Setup

The procedures used for setting up and configuring MOVES input files (also known as run specifications, or "runspecs") and input databases were fairly similar across all modeling scenarios performed, differing only in external inputs provided to the model. A separate MOVES input runspec and associated database was created for each county of interest, using default MOVES drive cycles, for both TDM-based VMT, as well as HPMS-based VMT. The same runs were re-created using ERG's drive cycles developed from the Kansas City Emissions Study (discussed in detail in Section 3 below). A total of 32 MOVES runs were performed.

Model Option Selection

The first step in setting up these runs was to make appropriate selections for each model option on the submenus listed in the main MOVES interface (see Figure 2-5). It is very important to note that model option selections for all of the submenus pictured below must be made before entering data via the County Data Manager, or the user may experience difficulties.

Figure 2-5. MOVES Interface Example

Screenshot depicting the MOVES model interface, with input categories and submenus present in the left-hand column.

Selections were made for each of the submenus pictured, and they are described below.

County Data Manager

The next step in the process is to create an input database, using appropriate descriptive nomenclature, that will store county-specific data for the model. This database must then be populated. We did so using the processed data described in the previous section, for each county and VMT basis modeled. Before a MOVES run can be performed, data must be imported into each of the tabs shown in the County Data Manager, pictured in Figure 2-6.

Figure 2-6. County Data Manager Example

Screenshot depicting the MOVES county data manager, with various allowable input categories listed across the top of the screen on tabs.

ERG used a number of different spreadsheets to populate the County Data Manager. These spreadsheets are listed in Table 2-10, and have been provided electronically in Appendix A for further reference. The naming convention used here is not particularly meaningful with respect to MOVES; any filename can be used during the import process. Because the County Data Manager requires a number of different inputs to be properly populated, users may find it helpful to use a table such as the one shown here for QC purposes in creating their own MOVES input databases.

Table 2-10. Summary of Inputs to County Data Manager

County Data Manager Input TTI VMT Basis Data Source HPMS VMT Basis Data Source
Ramp Fraction [County]-vmt-converter-veh28-20100209.xls
RoadType tab
Defaults Used
Road Type Distribution TTIRoadTypeDist.xls
[County] tab
MOVES[County] tab
Source Type Population TXDMV_Converted_Pop.xls
[County] tab
[County] tab
HPMSVTypeYear [County]aadvmtcalculator.xls
HPMSVTypeYear tab
HPMSVTypeYear tab
monthVMTFraction [County]aadvmtcalculator.xls
monthVMTFraction-calculated tab
monthVMTFraction-calculated tab
dayVMTFraction [County]aadvmtcalculator.xls
dayVMTFraction-calculated tab
dayVMTFraction-calculated tab
hourVMTFraction [County]-vmt-converter-veh28-20100209.xls
HourVMTFraction tab
hourVMTFraction-default tab
I/M Programs Revised_IM.xls
Age Distribution RegData_HGBarea.xls
[County]MOVES tab
[County]MOVES tab
Average Speed
[County] tab
[County] tab
Fuel Formulation Defaults Used Defaults Used
Fuel Supply FuelSupply_HGBArea.xls
[County] tab
[County] tab
Meteorology Data MetTemplate_HGBarea.xls
[County] tab
[County] tab

There are a few things to keep in mind when using the County Data Manager. First of all, MOVES sometimes will return errors during an import of data directly from certain sheets in the EPA VMT tool. This can be resolved by copying data from the VMT tool into a blank spreadsheet, and then importing that sheet instead. Secondly, Fuel Formulation data should be imported before Fuel Supply data; if not imported in that order, MOVES will return an error regarding unknown formulations. Finally, note that after importing all four of the VMT sheets required for the Vehicle Type VMT tab, the red X in the interface may not change to a green check, even when you've imported valid data. This is a known bug and is documented in the current MOVES2010 Errata/Information Sheet 21.

The above procedures describe the methodology for creating a single MOVES run - in this case, for a particular county and VMT basis. However, as previously discussed, 32 different MOVES runs were set up and executed for this analysis, and it would have been fairly tedious to set up all 32 of those runs manually within the MOVES interface. Fortunately, MOVES provides a tool to assist with import of numerous sets of county-specific data. This tool, which generates an XML file to assist with importing, can be accessed on the Tools tab of the County Data Manager by clicking the "Generate XML Importer File" button.

The XML generator was used to create an XML file, which was in turn used to import data into the input database for a given county outside of the MOVES interface, at the command line. When generating MOVES runs for multiple counties, ERG found that it is a fairly straightforward process to run the County Data Manager for a single county, use the XML generator tool to prepare an XML importer template, and then alter that template in a text editor to produce importers for multiple counties. These XML files can then be called from the command line, or in a batch file, to create multiple input databases at once. The procedure for doing so is documented in Appendix C of the MOVES User's Guide. ERG has provided example XML importers generated for this analysis, as well as the batch file created to perform multiple imports at once, in Appendix A of this document.

In addition to creating multiple input databases using the XML generator, it was also necessary for ERG to create the 32 MOVES runspecs described earlier. We found the most efficient way to do this was to start by creating a runspec for a given county using the MOVES graphical interface, and save that file, which is stored by MOVES in XML format. Next, ERG edited the XML runspec manually in a text editor for each county of interest. This is a simple process which involved changing a few references to the county modeled, as well as input and output database paths, within the XML runspec file. These runspec files are also included for reference in Appendix A.

Having created model runspecs and input databases for the 32 model runs, ERG prepared to execute each of the runs in MOVES. Figure 2-7 presents a summary of inputs necessary for preparing county-level MOVES runs, and issues to keep in mind while doing so.

Figure 2-7. MOVES Input Preparation Quick Reference

Inputs Needed For County-Level Inventory Calculations in MOVES

Issues to Keep in Mind During Model Input Development

1 2005/2006 On-Road Mobile Source, Ozone Episode Modeling Emission Inventories for the HGB Eight-Hour Nonattainment Area (TTI, 2007)

2 These files are available at the following URL:

3 SAS, or the Statistical Analysis System, is an integrated system of software products, developed by SAS Institute Inc., that ERG used in its data analysis during the course of this study. More information is available at

4 These tools are provided electronically in Appendix A, and described in more detail in Section 2.1.

5 Because many users of MOVES are likely to already have MOBILE6 input files and (other information based on MOBILE6 vehicle types) available to them, and because EPA is encouraging usage of their conversion tools, we feel this process reflects the application of what will likely be a common way of creating MOVES runspecs.

6 The National Mobile Inventory Model is, according to EPA, "a free, desktop computer application developed by EPA to help you develop estimates of current and future emission inventories for on-road motor vehicles and nonroad equipment". More information is available at

7 A procedure for calculating VHT is presented in section 3.6 of EPA's "Technical Guidance on the Use of MOVES2010 for Emission Inventory Preparation in State Implementation Plans and Transportation Conformity," EPA-420-B-09-042.

8 ERG's SAS program also independently calculated MOBILE6-format facility VMT, speed VMT, and VMT by hour files. These files were used for QC purposes, and were checked against similar files already provided by TTI, The result was that ERG's facility VMT and VMT by hour files for Harris County very closely resembled those provided by TTI. Speed VMT differed in that ERG's speeds were not as widely distributed across the speed range as TTI's - this was later determined to be caused by ERG's use of the VMT summary, whereas TTI was using link-level VMT as a basis for its speed distribution, which is more accurate. Subsequently, VMT by hour and speed VMT from TTI were used as input to EPA's converter tools for all subsequent MOVES runs.

9 For TTI-based VMT, the calculation of road type distribution was handled by the EPA converter tool, as discussed in the following section.



12 It is important to note that MOBILE6 vehicle types are developed primarily on a vehicle weight basis, while MOVES source types focus more on usage classification of a particular vehicle. This distinction arises often while converting information from a MOBILE6 basis to a format useable in MOVES.




16 "Technical Guidance on the Use of MOVES2010 for Emission Inventory Preparation in State Implementation Plans and Transportation Conformity," EPA-420-B-10-023. United States Environmental Protection Agency. April 2010. Available at

17 Available both at and through the MOVES graphical interface

18 EPA420-R-030-010, August 2003, available at

19 MOVES tables of interest related to this bug include etohbin and fuelsubtypeID.

20 Per multiple conversations with Sean Hillson

21 EPA-420-B-09-043, available at

Updated: 03/31/2014
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