Real-World Vehicle Emissions: A Summary of the Ninth Coordinating Research Council On-Road Vehicle Emissions Workshop

ABSTRACT

In April 1999, the Coordinating Research Council sponsored a workshop focusing on our understanding of real-world emissions from motor vehicles. This summary presents the latest information on in-use light- and heavy-duty vehicle tailpipe and evaporative emissions, the effects of fuels on emissions, field programs designed to understand the contribution of mobile sources to emission inventories, efforts to evaluate and improve mobile source emission models, progress of vehicle inspection/ maintenance programs, and topics for future research. While significant progress has been made in understanding in-use vehicle emissions, further improvements are necessary. Moreover, the impact of current and future changes in emission control technologies and control programs will have to be monitored for effectiveness and incorporated into the emission factor models.     

Real-World Vehicle Emissions: A Summary of the Sixth Coordinating Research Council On-Road Vehicle Emissions Workshop

The Coordinating Research Council (CRC) has conducted a series of workshops on real-world vehicle emissions. This article summarizes findings from the most recent research regarding on-road emissions from mobile sources, presented at the CRC workshop held in March 1996. Among the topics discussed were efforts to improve and update emission models, results from field studies designed to understand the contribution of mobile sources to emission inventories, results from gas-and particle-phase emissions studies from in-use motor vehicles, and areas of future research.

The Sixth Coordinating Research Council (CRC) On-Road Vehicle Emissions Workshop was held March 18-20, 1996, in San Diego, CA. More than 160 representatives from academia, industry, government, and consulting firms in the United States, Canada, and Europe participated in the three-day meeting. The objective of the Workshop was to present the most recent information from research programs on:

mobile source contributions to the emission inventory

emission factor models and activity data

model comparison and development

emission reduction programs

new developments in remote sensing

studies of on-road vehicle exhaust and non-tailpipe emissions

off-cycle Federal Test Procedure (FTP) studies and revisions to the FTP

particle emissions from the light- and heavy-duty fleets

future research needs

Nine sessions were devoted to vehicle emissions models, improvements to the emission inventory, on-road and tunnel studies, off-cycle emissions, non-tailpipe and diesel emissions, emission reduction programs, and remote sensing. Overall workshop coordination was provided by Timothy Belian and the CRC staff, with Steven Cadle and Robert Gorse serving as cochairmen. Individual session chairmen were Brent Bailey (National Renewable Energy Laboratory), Mark Carlock (California Air Resources Board), Harold Haskew (General Motors), Kenneth Knapp and Philip Lorang (U.S. Environmental Protection Agency), Douglas Lawson (Colorado State University), Alan Lloyd (Desert Research Institute), Robert Slott (Shell Oil), and Timothy Truex (University of California, Riverside). In addition, during the Workshop, Lesha Hrynchuk of the California Air Resources Board (CARB) presented a hands-on demonstration using the Internet to obtain motor vehicle emissions information from groups throughout the world. The complete Workshop proceedings are available from the Coordinating Research Council, 219 Perimeter Center Parkway, Atlanta, GA 30346; phone: (770) 396-3400; fax: (770) 396-3404. The following summarizes each session and includes a short synopsis of all the papers that were presented.     

A Fuel-Based Motor Vehicle Emission Inventory

Abstract

A fuel-based methodology for calculating motor vehicle emission inventories is presented. In the fuel-based method, emission factors are normalized to fuel consumption and expressed as grams of pollutant emitted per gallon of gasoline burned. Fleet-average emission factors are calculated from the measured on-road emissions of a large, random sample of vehicles. Gasoline use is known at the state level from sales tax data, and may be disaggregated to individual air basins. A fuel-based motor vehicle CO inventory was calculated for the South Coast Air Basin in California for summer 1991. Emission factors were calculated from remote sensing measurements of more than 70,000 in-use vehicles. Stabilized exhaust emissions of CO were estimated to be 4400 tons/day for cars and 1500 tons/day for light-duty and medium- duty trucks, with an estimated uncertainty of ±20% for cars and ±30% for trucks. Total motor vehicle CO emissions, including incremental start emissions and emissions from heavy-duty vehicles were estimated to be 7900 tons/day. Fuelbased inventory estimates were greater than those of California's MVEI 7F model by factors of 2.2 for cars and 2.6 for trucks. A draft version of California's MVEI 7G model, which includes increased contributions from high-emitting vehicles and off-cycle emissions, predicted CO emissions which closely matched the fuel-based inventory. An analysis of CO mass emissions as a function of vehicle age revealed that cars and trucks which were ten or more years old were responsible for 58% of stabilized exhaust CO emissions from all cars and trucks.     

Modeling In-Use Vehicle Emissions and the Effects of Inspection and Maintenance Programs

Different ways for modeling the impact of vehicle emission inspection and maintenance programs on fleet hydrocarbon emissions are examined. A dynamic model is developed for forecasting fleet emissions in which individual vehicle performance is modeled as a stochastic process and vehicle emissions are tracked over time. Emissions inspection and repair are incorporated into the model, allowing for the stochastic aspects of both testing and repair. This model is compared to EPA’s model for evaluating the impact of vehicle emissions inspection and maintenance. We find that the way vehicle emission equipment deterioration overtime is modeled is important for forecasting emissions from the fleet and for assessing the success of inspection and maintenance programs. For inspection programs, we find that factors such as the proportion of vehicles tested, and repair effectiveness and duration have the greatest impact on emission reductions. The ability of different emission testing regimes to identify polluting vehicles has less impact on a program’s overall potential for emissions reduction. Policy recommendations for I&M testing and predictions of emission reduction credits from these tests will depend in important ways on the methods used in the underlying emissions models.     

Real-World Vehicle Emissions: A Summary of the Tenth Coordinating Research Council On-Road Vehicle Emissions Workshop

ABSTRACT

The Coordinating Research Council (CRC) held its tenth workshop in March 2000, focusing on results from the most recent real-world vehicle emissions research. In this paper, we summarize the presentations from researchers who are engaged in improving our understanding of the contribution of mobile sources to emission inventories. Participants in the workshop discussed efforts to improve mobile source emission models and emission inventories, results from gas- and particle-phase emissions studies from spark-ignition and diesel-powered vehicles, new methods for measuring mobile source emissions, improvements in vehicle emission control systems (ECSs), and evaluation of motor vehicle inspection/maintenance (I/M) programs, as well as topics for future research.     

Locating the Offender

Abstract

The Coordinating Research Council held its thirteenth Vehicle Emissions Workshop in April 2003, when results of the most recent on-road vehicle emissions research were presented. Ongoing work from researchers who are engaged in improving understanding of the contribution of mobile sources to ambient air quality and emission inventories is summarized here. Participants in the workshop discussed efforts to improve mobile source emission models, the role of on-board diagnostic systems in inspection and maintenance programs, light- and heavy-duty vehicle emissions measurements, on- and off-road emissions measurements, effects of fuels and lubricating oils on emissions, as well as topics for future research.     

Real-world vehicle emissions: a summary of the Ninth Coordinating Research Council On-Road Vehicle Emissions Workshop

In April 1999, the Coordinating Research Council sponsored a workshop focusing on our understanding of real-world emissions from motor vehicles. This summary presents the latest information on in-use light- and heavy-duty vehicle tailpipe and evaporative emissions, the effects of fuels on emissions, field programs designed to understand the contribution of mobile sources to emission inventories, efforts to evaluate and improve mobile source emission models, progress of vehicle inspection/maintenance programs, and topics for future research. While significant progress has been made in understanding in-use vehicle emissions, further improvements are necessary. Moreover, the impact of current and future changes in emission control technologies and control programs will have to be monitored for effectiveness and incorporated into the emission factor models.     

Reducing the Risk of Accidental Death Due to Vehicle-Related Carbon Monoxide Poisoning

ABSTRACT

Emissions of carbon monoxide (CO) from motor vehicles cause several hundred accidental fatal poisonings annually in the United States. The circumstances that could lead to fatal poisonings in residential settings with motor vehicles as the source of CO were explored. The risk of death in a garage (volume = 90 m³) and a single-family dwelling (400 m³) was evaluated using a Monte Carlo simulation with varying CO emission rates and ventilation rates. Information on emission rates was obtained from a survey of motor vehicle exhaust gas composition under warm idle conditions in California, and information on ventilation rates was obtained from a summary of published measurements in the U.S. housing stock. The risk of death ranged from 16 to 21% for a 3-hr exposure in a garage to 0% for a 1-hr exposure in a house. Older vehicles were associated with a disproportionately high risk of death. Removing all pre-1975 vehicles from the fleet would reduce the risk of death by one-fourth to two-thirds, depending on the exposure scenario. Significant efforts have been made to control CO emissions from motor vehicles with the goal of reducing CO concentrations in outdoor air. Substantial public health benefit could also be obtained if vehicle control measures were designed to take account of acute CO poisonings explicitly.     

Comparison of the MOVES2010a,MOBILE6.2, and EMFAC2007 mobile source emission models with on-road traffic tunnel and remote sensing measurements

The Desert Research Institute conducted an on-road mobile source emission study at a traffic tunnel in Van Nuys, California, in August 2010 to measure fleet-averaged, fuel-based emission factors. The study also included remote sensing device (RSD) measurements by the University of Denver of 13,000 vehicles near the tunnel. The tunnel and RSD fleet-averaged emission factors were compared in blind fashion with the corresponding modeled factors calculated by ENVIRON International Corporation using U.S. Environmental Protection Agency's (EPA's) MOVES2010a (Motor Vehicle Emissions Simulator) and MOBILE6.2 mobile source emission models, and California Air Resources Board's (CARB's) EMFAC2007 (EMission FACtors) emission model. With some exceptions, the fleet-averaged tunnel, RSD, and modeled carbon monoxide (CO) and oxide of nitrogen (NO_x) emission factors were in reasonable agreement (±25%). The nonmethane hydrocarbon (NMHC) emission factors (specifically the running evaporative emissions) predicted by MOVES were insensitive to ambient temperature as compared with the tunnel measurements and the MOBILE- and EMFAC-predicted emission factors, resulting in underestimation of the measured NMHC/NO_x ratios at higher ambient temperatures. Although predicted NMHC/NO_x ratios are in good agreement with the measured ratios during cooler sampling periods, the measured NMHC/NO_x ratios are 3.1, 1.7, and 1.4 times higher than those predicted by the MOVES, MOBILE, and EMFAC models, respectively, during high-temperature periods. Although the MOVES NO_x emission factors were generally higher than the measured factors, most differences were not significant considering the variations in the modeled factors using alternative vehicle operating cycles to represent the driving conditions in the tunnel. The three models predicted large differences in NO_x and particle emissions and in the relative contributions of diesel and gasoline vehicles to total NO_x and particulate carbon (TC) emissions in the tunnel.

Implications: Although advances have been made to mobile source emission models over the past two decades, the evidence that mobile source emissions of carbon monoxide and hydrocarbons in urban areas were underestimated by as much as a factor of 2–3 in past inventories underscores the need for on-going verification of emission inventories. Results suggest that there is an overall increase in motor vehicle NMHC emissions on hot days that is not fully accounted for by the emission models. Hot temperatures and concomitant higher ratios of NMHC emissions relative to NO_x both contribute to more rapid and efficient formation of ozone. Also, the ability of EPA's MOVES model to simulate varying vehicle operating modes places increased importance on the choice of operating modes to evaluate project-level emissions.     

Motor Vehicle Lead Embssbons Bo the Unfed States: An Analysis of Important Determinants,Geographic Patterns and Future Trends

This paper presents a simple method which utilizes composite emission factors to estimate motor vehicle lead emissions for large areas. Composite emission factors incorporate information on vehicle lead emission rates, sales-weighted average fuel economies, annual vehicle travel fractions, and average gasoline lead concentrations. The lead emissions estimation procedure takes as given estimates of motor vehicle travel and, hence, can be applied to any region or road system for which current or projected travel estimates are available. Estimates of motor vehicle lead emissions for major highway systems in individual states and national forecasts of motor vehicle lead emissions for six potential scenarios regarding the future use of lead additives in gasoline are presented to demonstrate the application of the method.     

Particulate matter speciation profiles for light-duty gasoline vehicles in the United States

Representative profiles for particulate matter particles less than or equal to 2.5 µm (PM_2.5) are developed from the Kansas City Light-Duty Vehicle Emissions Study for use in the U.S. Environmental Protection Agency (EPA) vehicle emission model, the Motor Vehicle Emission Simulator (MOVES), and for inclusion in the EPA SPECIATE database for speciation profiles. The profiles are compatible with the inputs of current photochemical air quality models, including the Community Multiscale Air Quality Aerosol Module Version 6 (AE6). The composition of light-duty gasoline PM_2.5 emissions differs significantly between cold start and hot stabilized running emissions, and between older and newer vehicles, reflecting both impacts of aging/deterioration and changes in vehicle technology. Fleet-average PM_2.5 profiles are estimated for cold start and hot stabilized running emission processes. Fleet-average profiles are calculated to include emissions from deteriorated high-emitting vehicles that are expected to continue to contribute disproportionately to the fleet-wide PM_2.5 emissions into the future. The profiles are calculated using a weighted average of the PM_2.5 composition according to the contribution of PM_2.5 emissions from each class of vehicles in the on-road gasoline fleet in the Kansas City Metropolitan Statistical Area. The paper introduces methods to exclude insignificant measurements, correct for organic carbon positive artifact, and control for contamination from the testing infrastructure in developing speciation profiles. The uncertainty of the PM_2.5 species fraction in each profile is quantified using sampling survey analysis methods. The primary use of the profiles is to develop PM_2.5 emissions inventories for the United States, but the profiles may also be used in source apportionment, atmospheric modeling, and exposure assessment, and as a basis for light-duty gasoline emission profiles for countries with limited data.

Implications: PM_2.5 speciation profiles were developed from a large sample of light-duty gasoline vehicles tested in the Kansas City area. Separate PM_2.5 profiles represent cold start and hot stabilized running emission processes to distinguish important differences in chemical composition. Statistical analysis was used to construct profiles that represent PM_2.5 emissions from the U.S. vehicle fleet based on vehicles tested from the 2005 calendar year Kansas City metropolitan area. The profiles have been incorporated into the EPA MOVES emissions model, as well as the EPA SPECIATE database, to improve emission inventories and provide the PM_2.5 chemical characterization needed by CMAQv5.0 for atmospheric chemistry modeling.     

Methods of characterizing the distribution of exhaust emissions from light-duty, gasoline-powered motor vehicles in the U.S. fleet

Mobile sources significantly contribute to ambient concentrations of airborne particulate matter (PM). Source apportionment studies for PM10 (PM < or = 10 microm in aerodynamic diameter) and PM2.5 (PM < or = 2.5 microm in aerodynamic diameter) indicate that mobile sources can be responsible for over half of the ambient PM measured in an urban area. Recent source apportionment studies attempted to differentiate between contributions from gasoline and diesel motor vehicle combustion. Several source apportionment studies conducted in the United States suggested that gasoline combustion from mobile sources contributed more to ambient PM than diesel combustion. However, existing emission inventories for the United States indicated that diesels contribute more than gasoline vehicles to ambient PM concentrations. A comprehensive testing program was initiated in the Kansas City metropolitan area to measure PM emissions in the light-duty, gasoline-powered, on-road mobile source fleet to provide data for PM inventory and emissions modeling. The vehicle recruitment design produced a sample that could represent the regional fleet, and by extension, the national fleet. All vehicles were recruited from a stratified sample on the basis of vehicle class (car, truck) and model-year group. The pool of available vehicles was drawn primarily from a sample of vehicle owners designed to represent the selected demographic and geographic characteristics of the Kansas City population. Emissions testing utilized a portable, light-duty chassis dynamometer with vehicles tested using the LA-92 driving cycle, on-board emissions measurement systems, and remote sensing devices. Particulate mass emissions were the focus of the study, with continuous and integrated samples collected. In addition, sample analyses included criteria gases (carbon monoxide, carbon dioxide, nitric oxide/nitrogen dioxide, hydrocarbons), air toxics (speciated volatile organic compounds), and PM constituents (elemental/organic carbon, metals, semi-volatile organic compounds). Results indicated that PM emissions from the in-use fleet varied by up to 3 orders of magnitude, with emissions generally increasing for older model-year vehicles. The study also identified a strong influence of ambient temperature on vehicle PM mass emissions, with rates increasing with decreasing temperatures.     

Characterization of Real-World Activity,Fuel Use,and Emissions for Selected Motor Graders Fueled with Petroleum Diesel and B20 Biodiesel

Abstract

Motor graders are a common type of nonroad vehicle used in many road construction and maintenance applications. In-use activity, fuel use, and emissions were measured for six selected motor graders using a portable emission measurement system. Each motor grader was tested with petroleum diesel and B20 biodiesel. Duty cycles were quantified in terms of the empirical cumulative distribution function of manifold absolute pressure (MAP), which is an indicator of engine load. The motor graders were operated under normal duty cycles for road maintenance and repair at various locations in Wake and Nash Counties in North Carolina. Approximately 3 hr of quality-assured, second-by-second data were obtained during each test. An empirical modal-based model of vehicle fuel use and emissions was developed, based on stratifying the data with respect to ranges of normalized MAP, to enable comparisons between duty cycles, motor graders, and fuels. Time-based emission factors were found to increase monotonically with MAP. Fuel-based emission factors were mainly sensitive to differences between idle and non-idle engine operation. Cycle average emission factors were estimated for road “resurfacing”, “roading,” and “shouldering” activities. On average, the use of B20 instead of petroleum diesel leads to a negligible decrease of 1.6% in nitric oxide emission rate, and decreases of 19– 22% in emission rates of carbon monoxide, hydrocarbons, and particulate matter. Emission rates decrease significantly when comparing newer engine tier vehicles to older ones. Significant reductions in tailpipe emissions accrue especially from the use of B20 and adoption of newer vehicles.     

Development and Preliminary Evaluation of a Particulate Matter Emission Factor Model for European Motor Vehicles

ABSTRACT

Although modeling of gaseous emissions from motor vehicles is now quite advanced, prediction of particulate emissions is still at an unsophisticated stage. Emission factors for gasoline vehicles are not reliably available, since gasoline vehicles are not included in the European Union (EU) emission test procedure. Regarding diesel vehicles, emission factors are available for different driving cycles but give little information about change of emissions with speed or engine load. We have developed size-specific speed-dependent emission factors for gasoline and diesel vehicles. Other vehicle-generated emission factors are also considered and the empirical equation for re-entrained road dust is modified to include humidity effects. A methodology is proposed to calculate modal (accelerating, cruising, or idling) emission factors. The emission factors cover particle size ranges up to 10 um, either from published data or from user-defined size distributions.

A particulate matter emission factor model (PMFAC), which incorporates virtually all the available information on particulate emissions for European motor vehicles, has been developed. PMFAC calculates the emission factors for five particle size ranges [i.e., total suspended particulates (TSP), PM₁₀, PM₅, PM₂₅, and PM₁] from both vehicle exhaust and nonexhaust emissions, such as tire wear, brake wear, and re-entrained road dust. The model can be used for an unlimited number of roads and lanes, and to calculate emission factors near an intersection in user-defined elements of the lane. PMFAC can be used for a variety of fleet structures. Hot emission factors at the user-defined speed can be calculated for individual vehicles, along with relative cold-to-hot emission factors. The model accounts for the proportions of distance driven with cold engines as a function of ambient temperature and road type (i.e., urban, rural, or motorway).

A preliminary evaluation of PMFAC with an available dispersion model to predict the airborne concentration in the urban environment is presented. The trial was on the A6 trunk road where it passes through Loughborough, a medium-size town in the English East Midlands. This evaluation for TSP and PM₁₀ was carried out for a range of traffic fleet compositions, speeds, and meteorological conditions. Given the limited basis of the evaluation, encouraging agreement was shown between predicted and measured concentrations.     

Particulate Emission Rates for Unpaved Shoulders along a Paved Road

ABSTRACT

This paper reports the first empirical estimate of particle emissions from unpaved shoulders along paved roads.¹ Its objectives are to develop and demonstrate an emission rate measurement methodology that can be applied in different areas; identify the mechanisms that suspend dust from unpaved shoulders and the observables related to this suspension process; and quantify PM₁₀ mass emissions in the form of an emission rate. To achieve these objectives, fast-response observations from nephelometers and a sonic anemometer were used to characterize shortlived dust plumes generated by passing vehicles. In addition, detailed soil surface measurements determined the mechanical properties of the shoulder surfaces.

Large traffic-induced turbulence events that led to significant dust entrainment were almost exclusively caused by “large” vehicles such as trucks, semis, and vehicles pulling trailers, all traveling 50-65 mph. PM₁₀ emission rates for these large, fast-traveling vehicles were determined to be 8 ± 4 grams per vehicle kilometer traveled under dry conditions. Emissions due to smaller vehicles such as cars, vans, and sport utility vehicles were negligible for normal on-road driving. These results indicate that the majority of PM₁₀ emissions from unpaved shoulders is caused by relatively few vehicles.     

Emissions Variability Processor (EMVAP): Design,evaluation, and application

Emissions of pollutants such as SO₂ and NOx from external combustion sources can vary widely depending on fuel sulfur content, load, and transient conditions such as startup, shutdown, and maintenance/malfunction. While monitoring will automatically reflect variability from both emissions and meteorological influences, dispersion modeling has been typically conducted with a single constant peak emission rate. To respond to the need to account for emissions variability in addressing probabilistic 1-hr ambient air quality standards for SO₂ and NO₂, we have developed a statistical technique, the Emissions Variability Processor (EMVAP), which can account for emissions variability in dispersion modeling through Monte Carlo sampling from a specified frequency distribution of emission rates. Based upon initial AERMOD modeling of from 1 to 5 years of actual meteorological conditions, EMVAP is used as a postprocessor to AERMOD to simulate hundreds or even thousands of years of concentration predictions. This procedure uses emissions varied hourly with a Monte Carlo sampling process that is based upon the user-specified emissions distribution, from which a probabilistic estimate can be obtained of the controlling concentration. EMVAP can also accommodate an advanced Tier 2 NO₂ modeling technique that uses a varying ambient ratio method approach to determine the fraction of total oxides of nitrogen that are in the form of nitrogen dioxide. For the case of the 1-hr National Ambient Air Quality Standards (NAAQS, established for SO₂ and NO₂), a “critical value” can be defined as the highest hourly emission rate that would be simulated to satisfy the standard using air dispersion models assuming constant emissions throughout the simulation. The critical value can be used as the starting point for a procedure like EMVAP that evaluates the impact of emissions variability and uses this information to determine an appropriate value to use for a longer term (e.g., 30-day) average emission rate that would still provide protection for the NAAQS under consideration. This paper reports on the design of EMVAP and its evaluation on several field databases that demonstrate that EMVAP produces a suitably modest overestimation of design concentrations. We also provide an example of an EMVAP application that involves a case in which a new emission limitation needs to be considered for a hypothetical emission unit that has infrequent higher-than-normal SO₂ emissions.

ImplicationsEmissions of pollutants from combustion sources can vary widely depending on fuel sulfur content, load, and transient conditions such as startup and shutdown. While monitoring will automatically reflect this variability on measured concentrations, dispersion modeling is typically conducted with a single peak emission rate assumed to occur continuously. To realistically account for emissions variability in addressing probabilistic 1-hr ambient air quality standards for SO₂ and NO₂, the authors have developed a statistical technique, the Emissions Variability Processor (EMVAP), which can account for emissions variability in dispersion modeling through Monte Carlo sampling from a specified frequency distribution of emission rates.     

Toxic Emissions from Mobile Sources: A Total Fuel-Cycle Analysis for Conventional and Alternative Fuel Vehicles

ABSTRACT

Mobile sources are among the largest contributors of four hazardous air pollutants—benzene, 1,3-butadiene, acetal-dehyde, and formaldehyde—in urban areas. At the same time, federal and state governments are promoting the use of alternative fuel vehicles as a means to curb local air pollution. As yet, the impact of this movement toward alternative fuels with respect to toxic emissions has not been well studied. The purpose of this paper is to compare toxic emissions from vehicles operating on a variety of fuels, including reformulated gasoline (RFG), natural gas, ethanol, methanol, liquid petroleum gas (LPG), and electricity. This study uses a version of Argonne National Laboratory's Greenhouse Gas, Regulated Emissions, and Energy Use in Transportation (GREET) model, appropriately modified to estimate toxic emissions. The GREET model conducts a total fuel-cycle analysis that calculates emissions from both downstream (e.g., operation of the vehicle) and upstream (e.g., fuel production and distribution) stages of the fuel cycle. We find that almost all of the fuels studied reduce 1,3-buta-diene emissions compared with conventional gasoline (CG). However, the use of ethanol in E85 (fuel made with 85% ethanol) or RFG leads to increased acetaldehyde emissions, and the use of methanol, ethanol, and compressed natural gas (CNG) may result in increased formaldehyde emissions. When the modeling results for the four air toxics are considered together with their cancer risk factors, all the fuels and vehicle technologies show air toxic emission reduction benefits.     

Effects of improved spatial and temporal modeling of on-road vehicle emissions

Numerous emission and air quality modeling studies have suggested the need to accurately characterize the spatial and temporal variations in on-road vehicle emissions. The purpose of this study was to quantify the impact that using detailed traffic activity data has on emission estimates used to model air quality impacts. The on-road vehicle emissions are estimated by multiplying the vehicle miles traveled (VMT) by the fleet-average emission factors determined by road link and hour of day. Changes in the fraction of VMT from heavy-duty diesel vehicles (HDDVs) can have a significant impact on estimated fleet-average emissions because the emission factors for HDDV nitrogen oxides (NOx) and particulate matter (PM) are much higher than those for light-duty gas vehicles (LDGVs). Through detailed road link-level on-road vehicle emission modeling, this work investigated two scenarios for better characterizing mobile source emissions: (1) improved spatial and temporal variation of vehicle type fractions, and (2) use of Motor Vehicle Emission Simulator (MOVES2010) instead of MOBILE6 exhaust emission factors. Emissions were estimated for the Detroit and Atlanta metropolitan areas for summer and winter episodes. The VMT mix scenario demonstrated the importance of better characterizing HDDV activity by time of day, day of week, and road type. More HDDV activity occurs on restricted access road types on weekdays and at nonpeak times, compared to light-duty vehicles, resulting in 5-15% higher NOx and PM emission rates during the weekdays and 15-40% lower rates on weekend days. Use of MOVES2010 exhaust emission factors resulted in increases of more than 50% in NOx and PM for both HDDVs and LDGVs, relative to MOBILE6. Because LDGV PM emissions have been shown to increase with lower temperatures, the most dramatic increase from MOBILE6 to MOVES2010 emission rates occurred for PM2.5 from LDGVs that increased 500% during colder wintertime conditions found in Detroit, the northernmost city modeled.