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Strategic Workplan for Particulate Matter Research: 2000 to 2004

Research Focus Areas, Goals and Priority Projects

This section identifies and describes the research project priorities for the transportation community. This Workplan recommends the implementation of the fourteen projects (referenced in Figure 3) falling under the five research focus areas discussed in Section 1 -- monitoring, characterization, sources, modeling, and control strategies.

The recommended research projects are diverse in scope, ranging from fairly specific research initiatives to broad programmatic initiatives involving multiagency or multistakeholder coordination. This range in scope reflects the complexity of the PM issue and the significant research gaps that currently exist. Figure 4 provides a lexicon for the recommended projects based on project scope.

Recommended Project Issue Specific Project Multi-Faceted Project Programmatic Initiative
P1: Conduct analysis of preliminary data from PM2.5 monitoring network to identify potential PM2.5 non-attainment areas X    
P2: Integrate critical transportation sector PM research concerns into EPA's "super site" PM research program     X
P3: Examine state-of-the-art techniques from measuring semi-volatiles X    
P4: Review and update transportation-related source profile information used in PM speciation analysis X    
P5: Utilize speciation monitoring data to provide an improved understanding of the relative contribution of transportation to PM   X  
P6: Conduct dynamometer studies of diesel fueled vehicles/engines that are representative of current fleet mix   X  
P7: Conduct dynamometer studies of sample vehicles to determine the impact of gross emitter gasoline powered vehicles   X  
P8: Conduct a re-entrained road dust study that identifies the extent to which re-entrained roadway dust contributes to PM2.5 in urban areas in the Eastern United States. X    
P9: Develop a coordinated model improvement program for incorporating new research on motor vehicle-related emissions into EPA's PM model on a timely basis.     X
P10: Identify improvements needed in travel data to improve the use of the PM emission model for inventory development and analysis   X  
P11: Develop ammonia emissions component for inclusion in one of EPA's models. X    
P12: Analyze the costs and effectiveness of existing transportation source PM control strategies   X  
P13: Develop a menu of transportation-source PM2.5 control strategies for regions to consider in air quality planning   X  
P14: Develop assessment of interactions between transportation source control strategies for PM and other air pollutants   X  

Figure 4. Classification of Projects in Terms of Scope

Research initiatives that involve specific activities, such as analyses of currently available monitoring data, have specific (often singular) objectives, can be conducted by a relatively small research team, and can fall under the auspices of a single sponsoring agency. In most cases, the results of focused initiatives will feed multifaceted projects or even broader programmatic initiatives.

Multi-faceted projects attempt to fill multiple research gaps and are designed to address various, although related, objectives. For instance, projects that strive to improve modeling methodologies likely will require multi-disciplinary research teams with expertise in air quality and transportation modeling. Such projects may be best conducted under the auspices of multi-agency collaborative efforts, and most likely address multiple objectives (such as enhanced data collection practices, model development, and model application for impact assessment). Similarly, recommended projects that in effect are programmatic initiatives involve multiple objectives and may require multi-agency collaboration.

The following sub-sections describe the recommended projects under each of the five research areas. First, existing research gaps are identified to set the context for the recommendations. This is followed by project descriptions that discuss how the selected projects will address research gaps.

Monitoring

Research Goal. Ensure that enhancements to the Nation's PM monitoring system improve understanding of the contribution of transportation to PM.

Overview

The EPA's ambient air quality monitoring program provides the data needed to track air quality throughout the United States. The data gathered by the PM monitoring system provide a major source of information for the designation of future nonattainment areas, as well as for tracking compliance with NAAQS, and developing emissions modeling tools, emissions inventories, and control programs.

EPA, in coordination with state air quality agencies, is presently expanding the PM monitoring system to support future NAAQS by establishing:

These networks will substantially improve the capability of the PM monitoring system to address the new PM2.5 NAAQS. In addition, EPA has established seven PM Supersites with the primary objective of improving the understanding of PM characterization. The monitoring systems, however, may not be adequate to provide data needed for accurate determination of transportation sector-related PM emissions. To improve the understanding, a monitoring system is needed for the counting and classification of vehicles contemporaneously with a PM monitoring network. The gaps or uncertainties that should be addressed by the correlated monitoring efforts are associated with the areas noted below.

Understanding the temporal variation of PM is important to the transportation sector since a portion of ambient PM concentration is reactive in which time plays a role in the PM formation, transport and deposition. Generally, short term time intervals (1-hour or less) are important to developing a sound understanding because chemical reactivity, transport, deposition and traffic volumes will change significantly over the course of a day. The short sampling periods should provide sufficient fidelity to correlate vehicle emissions and traffic volumes. Further, an improved understanding in temporal variations may identify episodic PM violations that are the result of unusual conditions.

Improved understanding in the spatial variation of PM refers to the variability of the pollutant composition from one geographical area to another. The spatial variation may be the result of "transport" from other regions or due to differences in locally generated PM emissions. Developing an improved understanding from a study which can determine the "transport" component associated with PM generated in one geographic region but carried by atmospheric processes to another location is essential since control strategy effectiveness will be highly dependent upon this determination. In general, the spatial variability in PM appears to be a strong function of the geographic location with the inter-mountain States in the Western United States typically having problems with fugitive dust, California with nitrates, the Midwest and northeast with sulfates and the South with secondary organic compounds. An understanding of these differences and the role transportation sources play must be improved.

Chemical transformation of the volatile emissions that may be present in PM is an important area for improved understanding as research has shown that PM from transportation sources has significant component of semi-volatile compounds (e.g., ammonium nitrate). In addition, current methods do not accurately reflect what may be actually inhaled due to limitation in current monitoring methods.

To accurately discern the transportation related ambient PM, networks should include measurements of traffic volume and vehicle classification. For example, "gross emitters" typically represent less than 10 percent of the regional fleets, but account for 50 percent of gasoline-fueled tailpipe vehicle emissions. Therefore, a transportation apportionment study will need to characterize the "gross emitters" in addition to counting their numbers. Failure to accurately account for these vehicles will harm efforts to curb tailpipe gasoline-fueled vehicle emissions by incorrectly targeting all gasoline-fueled vehicles in control strategies when only a fractional percentage are responsible for the PM tailpipe emissions.

A transportation related source apportionment study must consider both the regional traffic contribution as well as the local traffic contribution. Counting and vehicle classification are important components of correlating vehicle emissions with sampled PM concentrations. Studies have been conducted which include traffic monitoring methods, but these studies often are not correlated well with the sampling times of the PM samplers or the counts have not been conducted over a regional area with the purpose of relating the regional disperse individual site measurements to the region as a whole. This is important since PM is a pollutant that can be chemically-transformed, transported and deposited over significant distances and times and, therefore, regional traffic information must be incorporated into the local counting to provide a complete picture of vehicle PM emissions.

Finally, a transportation source apportionment study must include both local and regional-scale measures of meteorology. Areas having frequent winds (e.g., mountain valleys, river valleys, ridge tops) are the least likely to have pollution problems. This is because emissions are continually dispersed and transported and do not remain in the area where they were generated. However, the emissions may be channeled to other areas leading to possible PM problems. Because of this, it is important for sites to have meteorological instruments that can account for the local meteorology. Relying on weather data measured many miles away from a local site will only provide general information about the site of interest. This phenomenon has been widely seen for CO in which ambient CO monitor data often shows low concentrations at times when traffic volume is relatively high. However, as a result of transport, the peak carbon monoxide concentrations are often found to occur in the late night hours and not near the location of peak emissions.

The following priority research projects are designed to ensure that transportation issues are addressed within PM monitoring activities.

Priority Projects

Project P1: Conduct an analysis of preliminary data from the PM2.5 monitoring network to identify potential PM2.5 nonattainment areas.

No accurate estimates of the scale and geographic extent of ambient PM2.5 concentrations exist (USEPA, 1996). Data from the new PM2.5 monitoring network will provide the foundation for EPA's PM2.5 nonattainment designations across the United States and many areas that are presently unaffected by PM10 are anticipated to become PM2.5 nonattainment areas. PM2.5 nonattainment status will have significant regional transportation policy implications because transportation has been shown to be a significant contributor to PM2.5 (Wongphatarakul et al., 1998; Lawson and Smith, 1998; Schauer et al., 1996). This project will analyze preliminary data from the national PM2.5 monitoring network to identify potential PM2.5 problem areas around the Nation and to examine the extent of secondary PM formation in these regions.

Relevance to Transportation Community. Designation of PM2.5 nonattainment areas will have a profound impact on the transportation programs and policies of affected regions, particularly if secondary PM is found to make up a significant portion of total ambient PM2.5. This project will provide transportation agencies with advance identification of potential PM2.5 problem areas, and an understanding of the extent to which ambient PM2.5 results from secondary formation from precursor pollutants and from pollutants that are transported from other regions. This will provide an opportunity to shape future policy development, such as designation of nonattainment boundaries and implementation of conformity in PM nonattainment areas more effectively.

Project P2: Integrate critical transportation sector PM research concerns into EPA's Supersite PM research program.

The EPA's supersite PM research program consists of a set of special studies that extend beyond the national regulatory monitoring networks for PM to support development of SIPs. Key components of the program include:

In late January of 2000, EPA announced the final selection of a set of seven region-specific supersite PM study locations, each of which will feature research programs conducted by academic institutions. The studies are located in Fresno, CA; Los Angeles, CA; Houston, TX; St Louis, MO; Baltimore, MD; Pittsburgh, PA; and New York, NY (a pilot supersite in Atlanta, GA is close to completion). The studies, with the exception of the Fresno site that is already underway, were deployed in mid-2000 and are scheduled to conclude prior to 2005 when the earliest PM SIPs are due.

The supersite studies are a critical PM research opportunity that will yield an unparalleled array of data about PM characteristics, yet only the New York supersite presently includes a transportation-specific objective. At the New York Supersite, an evaluation of the emissions impacts of alternative fuel buses and after-engine bus emission control technology will be included as part of the research program. Inclusion of similar transportation-related components at other supersites will require greater involvement by the transportation community, but will help to expand consideration and awareness of transportation-related research concerns.

Relevance to Transportation Community. The EPA's supersites analysis will provide a primary focus for PM research in the United States over the next five years. This project will involve a coordinated effort to incorporate transportation issues into the development of Supersite monitoring programs. At a minimum, the transportation community should continuously track the Supersite research findings to assess their significance in the context of transportation concerns, and to communicate findings to transportation agencies. Consideration should also be given to developing a program of transportation research initiatives with specific Supersite teams. Topics for consideration might include relative source apportionment, highway related "hot-spot" analyses, and effectiveness of transportation-sector control strategies.

Project P3: Examine state-of-the-art techniques for measuring the semi-volatile component of PM.

Transportation sources in some major urban areas are an important contributor of semi-volatile compounds such as ammonium nitrate. However, according to recent research by Kim et al. (1999, 2000), and Pang et al. (2000), current PM mass monitoring techniques may not accurately measure the semi-volatile fraction of PM. Semi-volatiles may be underestimated by monitors as a result of evaporation caused by pressure change during sampling or as a result of decomposition and chemical reactions that occur during filter storage. Kim et al. and Pang et al. find that loss of nitrates may be significant, accounting for upwards of 20 percent of the total PM2.5 mass on some days and up to 10 percent of the annual average. Alternatively, overestimation of semi-volatiles may result from gaseous adsorption onto filters or from chemical reactions that occur during filter storage. Gains may also be significant, according to Kim et al., and Pang et al., with a 6 to 20 percent gain on an annual basis.

Monitoring of semi-volatiles is an emerging issue of concern both to academic researchers and to the regulated community. Development of practical semi-volatile monitoring methods that can be incorporated into the "federal reference method" for monitoring techniques will require discussion between EPA, industry experts, regulated agencies, and academic researchers. This project will include development of a research forum to facilitate such a dialogue.

Relevance to Transportation Community. The contribution of semi-volatiles to total PM represents a basic knowledge gap in the PM monitoring science. Since the transportation sector is a major source of semi-volatiles, improved monitoring techniques that facilitate assessment of the relative contribution of semi-volatiles to total PM will ensure that the transportation sector's contribution to PM is estimated accurately, that emission control programs are designed accordingly, and that appropriate credit is granted for integrating strategies related to semi-volatiles.

Characterization

Research Goal - Advance understanding of the spatial occurrence of PM and its sources, with an emphasis on PM2.5 and secondary PM formation.

Overview

Characterization of PM draws on spatial and chemical analysis of monitoring data to improve understanding of where PM problems occur and how they are caused. Accurate characterization of PM can help to ensure that equitable and effective control strategies are developed. At present, however, understanding of the spatial and chemical characteristics of PM2.5 is based on a small number of region-specific studies, such as work by Eldred and Cahill (1994) on remote sites; work by Lipfert (1998) on clusters of urban fine particles; and work by EPA (1996, 1999) on data collected from the rural-focused visibility monitoring network. This research does not fully address key PM characterization concerns that are relevant to transportation agencies, such as the likely extent of areas that will be affected by PM2.5 regulations, the magnitude of secondary PM formation and transport, and the relative contribution of transportation sources to PM2.5. The transport of PM from one region to another is not well understood and it will be more important for PM2.5 than PM10. Targeted analysis of the data collected by improvements in the PM2.5 monitoring network will be vital to answering these questions.

Several critical research gaps exist in the understanding of the characterization of PM and its sources, and in particular for PM2.5 and secondary PM.

The following priority research projects are designed to advance the understanding of the spatial occurrence of PM and its sources.

Priority Projects

Project P4: Review and update transportation-related source profile information used in PM speciation analysis.

EPA and others have devoted considerable effort to the design and implementation of a nationwide network of PM speciation monitors that identify the chemical constituents present in PM. The chemical speciation data generated by the new network of speciation monitors will be combined with source profile information to determine the relative apportionment of PM emissions. Outdated source profile information, however, may hamper the accuracy of source apportionment estimates derived from new speciation monitor data.

As fuels, technologies, and use patterns have changed from 1970 to the present, so have the chemical profiles for many transportation-sector emissions sources. For example, catalytic converters on spark-ignition vehicles and improved diesel engine technologies have substantially reduced carbon emissions from these sources. Source profiles must be updated to reflect changing technology and to ensure that the value of the speciation network is maximized.

The first phase of this research project will review the adequacy of source profile information to determine the extent to which transportation-sector source profiles are out-of-date. In the second phase of the project, updated source profile information will be developed for use in conjunction with speciation monitor data.

Relevance to Transportation Community. Variations in the chemical composition of PM reflect the relative contribution of source categories. Accurate information about the chemical speciation characteristics of PM is therefore critical to determining future emission control strategies. The data generated through the speciation-monitoring network will greatly improve understanding of the relative contribution of different emissions source categories, such as diesel engines versus industrial sources and will help to focus future control strategy development.

Project P5: Utilize speciation monitoring data to provide an improved understanding of the relative contribution of transportation to PM.

Current estimates of the contribution of transportation to PM are based on a small number of region-specific studies that do not provide insight on variations in the relative share of transportation's contribution to PM from region to region, or the significance of secondary PM. The chemical speciation-monitoring network that is currently under development will provide a substantial amount of additional data on the relative source apportionment of PM in different regions of the country. This project will analyze data from the monitoring network to determine issues such as how the contribution of transportation to PM varies across the country, as well as the culpability of key transportation sources such as diesel trucks, and the potential for regional transport of PM.

Relevance to Transportation Community. As analysis of spatial, chemical and temporal variations in the characteristics of PM advances, this information will form a critical foundation for developing appropriate State and regional mitigation approaches. Nonattainment area designations must reflect the extent of contributing sources to PM NAAQS violations, while control strategy development must reflect the types of PM that are prevalent. For example, in regions where coarse mode (PM2.5 to PM10) size particles dominate, control strategies that focus on reducing resuspended agricultural or street dust may be most appropriate. In areas where PM2.5 particles are dominant, however, a focus on control of combustion sources may be more relevant.

Transportation Sources

Research Goal - Improve understanding of motor vehicle-related sources of PM and PM precursor emissions.

Overview

Despite several decades of regulation of PM emissions, relatively little is known about the operating variability of PM emissions from motor vehicles caused by factors such as changes in speed, engine deterioration, fuel characteristics and driving behavior. Recent studies on light-duty vehicles, such as those conducted by the Coordinating Research Council (CRC) and National Renewable Energy Laboratory (NREL), have begun to expand this knowledge (Cadle et al., 1998; Norbeck et al., 1998 and Whitney et al., 1998). Likewise, independent heavy-duty engine testing facilities in the US include West Virginia University and the California Center for Environmental Research and Technology (C-CERT).

Three broad categories of motor vehicle-related emissions are major contributors to ambient PM concentrations:

From these three broad categories the most relevant research gaps to improving the understanding of mobile source contribution to PM emissions are the following.

The following priority research projects have been designed to improve the understanding of motor vehicle-related sources of PM and PM precursor emissions.

Priority Projects

Project P6: Conduct dynamometer studies of diesel fueled vehicles/engines that are representative of current fleet mix to generate better data on the contribution of diesel vehicles to PM and PM precursor emissions.

Studies of in-use heavy-duty diesel emissions indicate that actual PM emissions may be considerably higher than current "PART5" and "EMFAC7G" emission factor models predict because factors such as engine deterioration, tampering and vehicle operating characteristics are poorly understood (Weaver et al., 1998). Although diesel vehicles manufactured since 1994 can have considerably lower emission rates because they incorporate advances in emission control technology, slow fleet turnover rates for diesel trucks reduce the impact of cleaner truck engines (Norbeck, et al., 1998).

This project will study diesel vehicle tailpipe emissions to determine the in-use characteristics of current diesel fleets nationwide. Such studies are typically conducted for a small sample of vehicles selected to be representative of fleet characteristics of interest, such as fuel type, vehicle age, and emissions control technology. Current monitoring techniques for measuring tailpipe PM emissions include direct measurements (light-duty vehicles on dynamometers); indirect measurements (heavy-duty engines on chassis-dynamometers combined with vehicle loads); tunnel measurements, and models that combine experimental measurement and physical approximations.

Relevance to Transportation Community. Until recently, PM regulations have focused on controlling PM10 problems that are localized, and that occur in a small number of locations in Western States. Control of PM2.5, in contrast, is likely to affect major urban areas in the Eastern United States as well as larger regions in the Western United States. In addition, combustion sources, particularly diesel-powered vehicles, are likely to be shown to be a significant contributor to PM2.5 emissions. Dynamometer studies of diesel vehicles will provide a better understanding of transportation's contribution to PM2.5.

Project P7: Conduct dynamometer studies of sample vehicles to determine the impact of gross emitter gasoline powered vehicles on PM emissions.

In-use PM emission rates of less than 3 mg/mile are typical for newer (post-1991) model light duty gasoline autos and trucks (Cadle et al., 1998; Norbeck et al., 1998; and Whitney et al., 1998). As vehicles age and accumulate mileage, however, deterioration of engine operating characteristics and emission control components can result in higher emission rates. In a recent CRC and NREL series of studies, high gaseous emitter gasoline vehicles were found to have approximately 5 to 10 times the particulate emission rates of normal emitter vehicles (Cadle et al., 1998; Norbeck et al., 1998; and Whitney et al., 1998). This project will study gasoline vehicles to determine the impact of gross emitters.

Relevance to Transportation Community. As diesel vehicle emissions improve with fleet turnover and use of cleaner fuels, the relative significance of gross-emitter gasoline vehicle-related PM emissions will increase. Studies to determine the impact of gasoline vehicles on PM are needed.

Project P8: Conduct a re-entrained road dust study that identifies the extent to which re-entrained roadway dust contributes to PM2.5 in urban areas in the Eastern United States.

There have been extensive studies of the impact of re-entrained dust in the Western United States, (Cowherd, 1997; Cowherd et al., 1998; Kinsey, 1995; Light et al., 1998; Moen et al., 1996) however, very little is known about the extent of re-entrained dust in the Eastern United States. Research on re-entrained dust from roadways has primarily been confined to analysis of sites in the Western United States where arid climatic conditions prevail. Some researchers suggest that current models that rely on existing research, overestimate re-entrained dust from roadways by as much as a factor of 10. (Larson and Silva, 1997, Light et al., 1998, Moen, et al., 1996, and Venkatram and Fitz, 1999). Research should focus on developing a better understanding of the contribution of re-entrained PM in eastern, urban areas, and determining the sources of re-entrained dust (i.e., sand, tire wear, crustal material, etc). There are large fluctuations in the level of re-entrained particulate emissions because of the sporadic nature of materials handling and the effects of precipitation and wind.

Relevance to Transportation Community. Lack of understanding about the significance of re-entrained roadway dust in major urban areas of the eastern United States, and in-use diesel engine emissions make existing emissions models inadequate for air quality planning. Future research must focus on developing information about transportation sources that enhances emissions factor models.

Modeling

Research Goal - Improve PM emission modeling for transportation sources.

Overview

The PART5 model is EPA's accepted motor vehicle PM emissions model, and is required in the development of PM10 inventories and analyses. The model is used to calculate emission factors (in grams per mile) for gasoline and diesel-powered motor vehicles for particle sizes up to 10 microns (PM10 and PM2.5). The model is capable of estimating emission rates for PM from vehicle exhaust, exhaust components, brakewear, tirewear, and re-entrained road dust. The State of California uses its own emissions model, EMFAC, to estimate PM emissions because of the unique regulations on vehicles in that State.

The accuracy of emission factor models is important because these models are used to develop emission inventories and to evaluate the emission effects of transportation projects and control strategies. The quality and accuracy of user inputs to the models, such as vehicle travel data, are also important for accurate inventory development and analysis.

It is widely recognized that the PART5 model contains a number of weaknesses that limit its accuracy (Graboski, 1997; Turner, 1995, 1998; Weaver et al.,1999). These weaknesses then limit the usefulness to which the modeling results can be used to establish accurate emission inventories and set emission budgets for PM, and in particular for PM2.5 and secondary PM.

Although various projects relevant to the transportation community can be identified, the following priority research project areas are designed to fill the most important research gaps in modeling techniques to the transportation community.

Specific priority research projects under the three areas listed above follow.

Priority Projects

Project P9: Develop a coordinated model improvement program for incorporating new research on motor vehicle-related emissions into EPA's PM model on a timely basis or developing new models as necessary.

The PART5 model was developed in the early 1990s and released in August 1994; the model was re-released in February 1995 with updates to correct a few problems identified with the initial release. Since that time, there has been a great deal of research that has advanced understanding of PM emissions from motor vehicles, yet this improved understanding of PM has not been incorporated into the PART5 model. As a result, the PART5 model does not adequately account for many factors that affect PM10 emission rates. In particular, recent research findings regarding factors that affect tailpipe emission rates such as in-use engine deterioration (Cadle et al., 1998, Norbeck et al., 1998, Weaver et al., 1998, Whitney et al., 1998), and factors that affect brake and tire wear such as weight and vehicle class (Cooper et al., 1995); and research on re-entrained road dust (Cowherd, 1998; Cowherd et al., 1998b; NCHRP 25-18, 1999) have not been incorporated into PART5.

The development of a coordinated model improvement program will ensure that existing research understanding is incorporated into the PART5 model and that future research findings are incorporated into new versions of the model in a timely manner. The model improvement program will be used to identify whether there is enough evidence and consensus in the research community to warrant incorporating research findings into the model.

Relevance to Transportation Community. The transportation community needs to have a PM model that includes state-of-the-art information to improve the accuracy of inventories and to improve the analysis of control strategies. Flawed or oversimplified modeling procedures limit the ability to estimate emissions accurately and could lead to improper or unnecessary efforts to reduce motor vehicle emissions.

Project P10: Identify improvements needed in travel data to improve the use of the PM emission model for inventory development and analysis.

Travel data inputs are an important input to the PART5 model, particularly information on the portion of vehicle travel by various classes of heavy-duty diesel vehicles and their age. Recent changes in new diesel engine control technologies are resulting in rapid changes in emissions. In addition, the newest heavy-duty diesel vehicles have much longer engine life cycles. These factors will vary widely both by facility types and within regions and will not be accurately reflected on the gross national average fleet mix. The model allows users to provide customized inputs of the percent of VMT for 12 vehicle categories and by vehicle age or registration. Travel data collected by State and local planning agencies, however, typically do not match the data needed for emissions models. For example, traffic count data typically do not identify the fuel used by vehicles (e.g., gasoline or diesel). While this issue is a problem common for modeling all criteria pollutants, there are certain travel data issues specific to modeling PM. For example, heavy-duty diesel vehicles are important contributors to PM, and the PART5 model accounts for three different classes of heavy-duty diesel vehicles (e.g., light heavy-duty diesels, medium heavy-duty diesels, and heavy heavy-duty diesels). Most traffic count data, however, do not distinguish among different categories of heavy-duty vehicles, limiting the accuracy of emission estimates that can be developed. This project will identify the travel data needs and develop a set of recommendations for improving travel data collection to improve the accuracy of PM emissions modeling.

Relevance to Transportation Community. Transportation agencies are responsible for collecting travel data for use in transportation emission models and need accurate local-level data in order to accurately establish emission inventories and to analyze transportation projects and controls.

Project P11: Develop an approach to ammonia emissions component for possible inclusion in one of EPA's motor vehicle emission factor models (PART or MOBILE).

PART5 calculates exhaust emission factors for primary emitted particulates, brake and tire wear emissions, and re-entrained road dust emissions. However, the PART5 model does not provide emission estimates for gas phase emissions that form as a result of chemical reactions in the atmosphere. These PM precursor emissions are at times a significant contributor to ambient PM in some regions (Turner, 1998). While EPA's "MOBILE" model does estimate some PM precursor emissions (such as VOC and NOX), the MOBILE model does not estimate emissions of ammonia that is an important PM precursor.

This project will involve developing modeling procedures to estimate ammonia emissions and to incorporate these procedures into the MOBILE or PART5 models. Although work is still being undertaken on developing an air quality model that can accurately estimate the effects of precursor emissions on ambient PM, this project will help to provide the foundation for estimating the transportation contribution to all major PM precursors.

Relevance to Transportation Community. Ammonia is an important PM precursor emitted by transportation sources that is not currently included in emission models. If secondary formation is a major contributor to PM, planners need to estimate the impacts of transportation projects on PM precursor emissions and air quality.

Control Strategies

Research Goal - Improve understanding of the costs and effectiveness of PM control strategies for transportation sources.

Overview

Transportation and air quality agencies in states with PM10 nonattainment areas have examined and implemented a number of transportation-related strategies to reduce PM air quality problems. Several recent reports provide an overview of potential PM control strategies for transportation sources. (MECA, 1999, EPA, 1990, STAPPA, 1996). These control strategies can be grouped into three categories:

With the potential for a significant number of new PM2.5 nonattainment areas under the new NAAQS, there is an increased need to improve understanding of potential control measures for transportation. States will be required to develop SIPs that identify how they will move toward attainment of the NAAQS. Many of these areas will have had limited experience with PM and will differ markedly in terms of climate, geography, and other conditions from parts of the country that have been the focus of earlier efforts. In areas where transportation sources contribute a significant share of PM, transportation control strategies will need to be examined for potential inclusion in the SIP.

A number of critical research gaps exist in the understanding of PM-related control strategies for transportation sources:

Priority research projects designed to improve the understanding of the costs and effectiveness of PM control strategies for transportation sources are described below.

Priority Projects

Project P12: Analyze the costs and effectiveness of existing transportation source PM control strategies at reducing PM and PM-precursor emissions.

PM10 nonattainment areas around the country have implemented local-level transportation-related control strategies for PM, such as, use of roadway surface treatments and road construction dust controls. Only a limited understanding exists, however, of the costs and effectiveness of these PM control strategies particularly in terms of how these measures contribute toward meeting the PM2.5 NAAQS since areas have not had to address this smaller size fraction.

This project would involve a set of case studies of existing transportation PM control strategies to identify the full costs of implementing these measures and to measure effects at reducing PM10 emissions, PM2.5 emissions, and PM-precursor emissions. The estimated reductions would be compared with the reductions required within the SIPs. Emission reductions would also be compared with estimates of the effects of improvements in diesel fuels and vehicle technologies to assess the relative contribution of these strategies.

Relevance to Transportation Community. This project would provide transportation decisionmakers with a better understanding of the extent to which existing, locally implemented control strategies contribute to attainment of the PM NAAQS. Transportation officials need to come to the table with an understanding of the costs and effectiveness of potential strategies when working with air quality officials to develop SIP measures.

Project P13: Develop a menu of transportation-source PM2.5 control strategies for regions to consider in air quality planning, including an evaluation of costs and effectiveness in different geographic settings.

State and local transportation and air quality agencies have limited knowledge of the full range of options to reduce PM2.5 from transportation sources. Existing control strategies in use in PM10 non-attainment are targeted towards the coarse mode fraction and are unlikely to be sufficient or appropriate for control of PM2.5 in many parts of the country designated as nonattainment under the new PM2.5 standard.

This project involves developing a menu of control strategies to help inform decisionmakers about the full range of options available for PM control. The emissions effects of each option will be assessed quantitatively using emission models in a range of different geographic settings (e.g., areas with different temperatures, road types, vehicle fleet mixes). Issues of concern to transportation decisionmakers will also be identified, including estimated costs, implementation issues, effects on other transportation goals (e.g., safety, mobility), and locational factors.

Relevance to Transportation Community. Transportation decisionmakers need to have information to help them select the most appropriate control measures for transportation sources if required. This project goes beyond the first project by examining the potential of measures in regions where PM controls have not yet been implemented or considered.

Project P14: Evaluate the interactions between transportation-related PM, ozone, air toxics, climate change, and other air pollutant control strategies.

The effect of control strategies on both PM and ozone is important because many areas of the country expected to be designated as nonattainment for PM2.5 are ozone nonattainment or maintenance areas. The effect of control strategies on both PM and ozone is important because many areas of the country expected to be designated as nonattainment for the 24-hour PM2.5 are ozone nonattainment or maintenance areas. This is because in many locations (particularly in the Eastern half of the United States) similar meteorological conditions conducive to high ozone formation also lead to high levels of PM2.5. As a result, State and local decisionmakers need to understand the implications of control strategies on both PM2.5 and ozone as well as the implications on air toxics and greenhouse gases.

Some control strategies may be beneficial in reducing both PM and ozone pollution. Since the ozone precursors, VOC and NOX, are also precursors for secondary PM, ozone controls may already be working to reduce secondary PM formation. On the other hand, some ozone control strategies may result in increased PM as well as other effects on air toxics and greenhouse gases. For example, an increase in transit bus service provision could increase PM emissions since diesel buses have high PM emission rates compared to other classes of vehicles. This would in addition increase air toxic emissions since diesel is considered a significant air toxic. Conversely, carbon dioxide would decrease as the transit bus service produces significantly less carbon dioxide than gasoline fueled vehicles.

This project involves modeling the impacts of transportation control strategies on both PM and ozone as well as their impact on air toxics and greenhouse gases using emission factor models and urban air shed models.

Relevance to Transportation Community. Transportation decisionmakers need to understand the implications of proposed controls on both PM and ozone to address conformity issues for these pollutants.

Updated: 07/06/2011
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