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### Air Pollution Emissions from Highway Vehicles: What MOVES Tells Us

Megan Beardsley, Jim Warila, Gary Dolce, John Koupal U.S. Environmental Protection Agency 2000 Traverwood Drive, Ann Arbor, Michigan 48015 mobile@epa.gov

ABSTRACT

The U.S. Environmental Protection Agen cy is developing the Motor Vehicle Emission Simulator (MOVES) to estimate air pollution emissions from cars, trucks and other mobile sources. When complete , MOVES will replace EPA's MOBILE and
NONROAD models. The EPA has created a draf t version of MOVES that incorporates extensive new data and advanced algorithms to better estimate highway vehicle emissions of greenhouse gases, criteria polluta nts and selected air toxics. This paper
summarizes how MOVES differs from MOBILE 6 in terms of capabilities, inputs, and preliminary results.

INTRODUCTION

Since 1978, the U.S. Environmental Protec tion Agency has used computer models to estimate emissions from cars, trucks and other mobile sources. The initial MOBILE model was expanded many times over the years to incorporate new data on vehicle emissions, new vehicle emission standards a nd to better address new policy questions, 1

but the basic structure of the model has remain ed constant. MOBILE uses average gram per mile emission rates and a series of corr ection factors to estimate emissions over a wide range of driving conditions.

MOBILE6.2 2 , finalized in 2004, is EPA's current official model for highway
vehicle emissions. It is used for EPA inte rnal policy analyses and is required for use (outside California) in th e evaluation of State Implementation Plans (SIPs) and transportation confor mity determinations. 3

A number of analysts have critique d the MOBILE series of models. 4 In 2000, the National Research Council prepared an eval uation that recommended a number of design changes for MOBILE. 5 They suggested that EPA develop a modeling "toolkit" that would better serve the range of uses for high way vehicle modeling, including consistent modeling at the aggregate scal e, mesoscale, and microscale analysis. The model should integrate the modeling of criteria pollutant s, air toxics, greenhouse gases and fuel consumption.

In response to these and other concerns , EPA has developed the Motor Vehicle Emissions Simulator (MOVES). MOVES incorp orates extensive new data and advanced2 algorithms to better estimate highway vehicle emissions of greenhouse gases, criteria pollutants and selected air toxics at the na tional, regional and proj ect level. A draft version of MOVES is planned for release in spring 2009. A final version for highway vehicles is planned for release in December 2009.

MOVES CAPABILITIES

MOVES greatly extends the capabilities of MOBILE6, allowing significantly greater flexibility in modeling choices and offering a variety of tools designed to ease the use of the model in a variety of use ca ses. Draft MOVES2009 calculates highway vehicle emissions of greenhouse gases, criteria pol lutants and selected air toxics. It also calculates energy consumption. Emissions ar e calculated for all the significant vehicle emission processes: running emissions, star t emissions, evaporativ e emissions, extended idle emissions, crankcase emissions, tirewear and brakewear.

In response to criticisms of MOBILE, MOVES was designed to allow easier incorporation of large amounts of in-use data from a variety of sources. MOBILE was written in Fortran, and many data elements were hard-coded, making them difficult to update. MOVES is written in Java and MYSQL, and data elemen ts are stored in database
tables.

Like MOBILE6, MOVES adjusts emissions to account for changes in vehicle mix, fuel properties, temper atures, and speeds. Unlike MOBILE6, MOVES is designed to estimate emissions at multiple geographic scales. MOBILE6 emissions rates were based on regional-scale trip pattern, while MOVES emissions are based on operating modes, and thus can be customized to the uni que driving patterns in a particular region or project area.

MOVES has a menu-driven interface to guide users as they set up and execute MOVES runs. The interface includes graphical display to help users define their desired model run and a variety of data importers to help users creat e appropriate input files.
MOVES also includes a command-line interface to facilitate batch r uns. MOVES can be run on a single computer, or set up in a "master/worker" configuration, allowing distributed processing. Users can model th e impacts of particular policy options using built-in tools. Current policy tools include vehicle inspection/maintenance (I/M) programs, retrofits of vehicle equipment, and the phase-in of alternative fuels and advanced technology vehicles.

MOVES allows users to output emissions either in MOBILE6-like gram-per-mile emission factors or in total mass for a given area and time. Users can select the desired level of output detail th rough the user interface, and can apply database processing tools to further customize reports.3 MOVES INPUTS

In MOBILE6, emissions were calculated fro m default information in block data, supplemented with information provided by the user in input text files. In MOVES,
default information is contained in a default input database. Hypothetically, users can run MOVES using all default data , all new data, or anything in-between. In reality, the inputs that users bring to the model will de pend on the situation being modeled and the purpose of the modeling. EPA is prepar ing detailed technical guidance on the requirements for users running the model to prepare SIP inventories and conformity
determinations.

Generally, users are not expected to m odify the default MOVES emission rates. The default rates were developed by assessing millions of vehicles. For Light Duty Vehicles, emission rates for hydrocarbons (H C), carbon monoxide (CO) and oxides of nitrogen (NOx) from existing vehicles were derived from ten years of second-by-second data from Arizona's Inspecti on/Maintenance (I/M), with comparisons to other I/M programs and remote sensing da ta. Particulate Matter (P M) emissions were derived from a major new EPA study in Kansas City 6 . Heavy Duty emissions were derived from
more than 300 in-use vehicles in a number of detailed studies.

Many of user inputs expected by MOVES are similar to those previously used in MOBILE6. For example, information on age distributions, local fuels and local temperatures are essential inputs for any accu rate estimate of emi ssions. MOVES differs however, in that the categories for these i nputs have changed. For example, MOBILE6 has 28 vehicle categories, generally based on vehicle weight ratings, while MOVES has only 13 categories, based on observable charact eristics (e.g. combination vs. single unit trucks) and typical use (e.g. long haul vs. shor t haul). The EPA is developing converters to allow users to automatically convert MOBILE6 inputs into MOVES formats.

MOVES new capabilities also require new i nputs. In particular, because MOVES can calculate inventories as well as gram per mile emission rates, MOVES relies on input of Vehicle Miles Travelled (VMT). The MOVES design also recognizes that vehicle starts and evaporative activity may not be well correlated with VMT, and thus relies on vehicle population estimates to calculate these emissions.

In another example of how new capa bilities require new inputs, MOBILE6 allowed users to enter a speed distribution or an average speed for a run. MOVES also allows input of a speed distribution, but it can also accept specific driving cycles or operating mode distributions, allowing the user to model emissions resulting from changes in driving behavior.

MOVES can work with inputs at the nati onal level, with allocation to specific counties if desired; or MOVES can work at the county or project level, with inputs specific to that time and place.4 PRELIMINARY RESULTS

MOVES updated data and advanced capab ilities enhance our un derstanding of vehicle emissions. To begin to understand how MOVES emissions differ from MOBILE6 emissions, we ran some simple comparisons with a preliminary draft version of MOVES. Comparing MOVES and MOBILE6 is better done for specific local areas, as it is easier to align the inputs for the two models on a smaller scale, and b ecause national default inputs in MOVES would not fully capture th e individual variation between nonattainment

areas.

To best characterize the comparison most relevant for U.S. nonattainment areas, we ran the preliminary draft version of MOVES for three sample cities: a medium-sized city in the western U.S., a large city in th e north central U.S., and a large city in the Southeast. For these preliminary runs, we used local data submitted to the U.S. EPA as part of the National Emission Inventory effort . This data included local information on the age distribution of the fleet , the fraction of light-duty and heavy-duty VMT, local fuel characteristics, and temperature data. This allowed us to match the activity and other inputs between MOVES and MOBILE and to simula te local data that would be used in a SIP. However, the inputs were simplified a nd may not be complete ly consistent with data that the state would actually use in preparing a SIP for the city.

For 2008, 2015 and 2020, we ran this data through the MOBILE6.2 model (using the National Mobile Inventory Model (NMIM )) and through MOVES, adjusting inputs as necessary to fit MOVES data categories. Ou r results were generally consistent between the three cities, with decreases or little chan ge in hydrocarbon (HC) emissions, moderate increases in nitrogen oxides (NOx) and significant increases in particulate matter (PM). Figures 1-3 illustrate these trends for the northern city in our sample.

Figure 1. Hydrocarbon emissions in example northern city



### City A - HC

0 10000 20000 30000 40000 50000 60000



### 2008 2015 2020**Annual Tons M6** 

**M6 M6**  **MOVES**

**MOVES MOVES**  **HD**

**HD**

**LD LD**5 Figure 2. Nitrogen Oxide emissions in example northern city

Figure 3. Particulate Matter emissions in example northern city

CONCLUSIONS

The results of our preliminary comparisons were consistent with our understanding of the changes in underlying e mission rates. In MOVES, light duty cars
and trucks tend to have similar or lower HC emissions than in MOBILE6. This is because new exhaust and evaporative emissi ons test data has demonstrated that MOBILE6 was overly pessimistic in estimating how emissions from mid-1990s and later 

### City A - NOx

0 10000 20000 30000 40000 50000 60000 70000 80000 90000



### 2008 2015 2020**Annual Tons**

**MOVES MOVES**  **MOVES**

**M6 M6**  **M6**

**HD**

**HD**

**LD LD** 



### City A - PM2.5

0 1000 2000 3000 4000



### 2008 2015 2020**Annual Tons**

**MOVES MOVES**  **MOVES**

**M6 M6**  **M6**

**HD HD** 

**LD LD** 6 vehicles would increase with age. Light dut y trucks tend to have higher NOx emissions than forecast by MOBILE6, and heavy duty trucks tend to have higher NOx than estimated from the engine certification tests used in the MOBILE6 analysis – in part due to higher brake-specific emissions from in-use trucks, and in part due to the differences between real-world operation and the certifica tion test. Extended idle NOx emissions were also given a much more careful treatment in MOVES than in MOBILE6; given default assumptions about extended idle activ ity and the projected lack of control from
NOx aftertreatment devices dur ing extended idle operation, they are projected to form a large portion of the future-year heavy duty NOx inventory. The growth in light-duty PM
emissions from MOBILE6 to MOVES reflect s the higher emissions and strong temperature dependence that we saw in the Kansas City study. 7,8 The growth in heavyduty PM reflects new information on in-use vehicles 9 and new analysis of emission deterioration. MOVES also adjusts PM e missions for speed, which MOBILE6 did not do, which leads to a very large difference in emissions between the two models at lower speeds typical of congested urban operation.

The implications of the changes in emission estimates for SIPs will depend on local conditions and regulatory requireme nts. Higher NOx and PM emissions from mobile sources will impact local air quality modeling and will increase the role of mobile
source control measures in atta inment demonstrations. Howe ver, it is important to note that for attainment analysis, a key measure is the percent reduction in emissions from the analysis base year. In our limited analysis, we saw a greater percent reduction for PM in MOVES than in MOBILE6, but a lower percent reduction for NOx.

Table 1. Percent Reduction in On-Road Emissions, 2008 to 2015

City A City B City C

MOVES MOBILE6 MOVES MOBILE6 MOVES MOBILE6
HC 50% 50% 39% 32% 38% 31%

NOx 54% 56% 40% 52% 36% 53%

PM2.5 57% 40% 52% 40% 38% 23%

REFERENCES

1 U.S. Environmental Protection Agency, Description and History of the MOBILE Highway Vehicle Emission Factor Model , February 2004. http://www.epa.gov/otaq/models/mob_hist.txt

2 U.S. Environmental Protec tion Agency, MOBILE6.2, March 2006. http://www.epa.gov/otaq/models/mobile6/mobile62.zip7 3 Oge, M.T. and Page, S., Memorandum to EPA Regional Air Division Directors, Policy
Guidance on the Use of MOBILE6.2 and the December 2003 AP-42 Method for ReEntrained Road Dust for SIP Developm ent and Conformity, February 24, 2004.

4 Pollack, A.K.; et al., Evaluation of the U.S. EPA MOBILE6 Highway Vehicle Emission Factor Model, Coordinating Research C ouncil Project E-64, March 2004.

5 National Research Council. Modeling Mobile-Source Emission , Committee to Review EPA's Mobile Source Emissions Factor (M OBILE) Model, Board on Environmental Studies and Toxicology, Trans portation Research Board. 2000.

6 Nam, E.; et al., Analysis of Particulate Matter Emissions from Light-Duty Gasoline Vehicles in Kansas City, EPA420-R-08-010, April 2008 http://www.epa.gov/otaq/emission-factors-research/420r08010.pdf

7 U.S. Environmental Protection Agency, Kansas City PM Characterization Study, EPA420-R-08-009, April 2008. http:// www.epa.gov/otaq/emission-factorsresearch/420r08009.pdf

8 Nam, E.; et al., Analysis of Particulate Matter Emissions from Light-Duty Gasoline Vehicles in Kansas City, EPA420-R-08-010, April 2008 http://www.epa.gov/otaq/emission-factors-research/420r08010.pdf

9 Clark, N; et al, Heavy-Duty Vehicle Chassis Dyna mometer Testing for Emissions Inventory, Air Quality Modeling, Source Apportionment and Air Toxics Emissions Inventory , Coordinating Research Counc il Report No. E-55/59, August, 2007. http://www.crcao.org/reports/recentstudies2007/E-55-59/E55_59_Final_Report_23AUG2007.pdf