September 15, 2006
Vol. 40, Iss. 18

Particulate Matter: A Strategic Vision for Transportation-Related Research

In a collaborative effort sponsored by the U.S. Federal Highway Administration, regulators, researchers, and consultants identify and prioritize research needs for the transportation community.

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Most individuals have witnessed a bus or large truck emitting a thick smoke plume as it accelerates away from an intersection. Or they have seen the occasional car trailing a smoke cloud in its wake. When cars and trucks emit visible smoke, their contribution to air pollution is obvious. However, on-road vehicles, or “mobile sources”, emit a range of pollution. Some pollutants, such as carbon monoxide (CO) and soot from diesel-powered trucks, are emitted straight from the tailpipe. Other vehicle emissions, like volatile organic compounds (VOCs), NO_x, and ammonia, interact in the atmosphere to form “secondary” pollutants, such as ozone or ammonium nitrate.

Small solid or liquid particles, either directly emitted or formed in the atmosphere, are referred to as particulate matter (PM). These tiny particles can scatter or absorb visible light, thus creating the hazy appearance associated with urban air pollution. PM also contributes to global climate change and acid rain. Small particles are easily inhaled and have been linked to asthma, strokes, and decreased life expectancy (1, 2). Over the past decade, PM has emerged as one of the most important air-quality problems, and research shows that on-road vehicles are a major PM source. However, knowledge gaps exist about the science and control of PM pollution from on-road vehicles. This article summarizes the results of recent work sponsored by the U.S. Federal Highway Administration (FHWA) to assess recent literature and ongoing research pertinent to transportation and PM and to develop a strategic research plan for the transportation community. The priorities identified in a workshop that included members of the transportation, research, and regulatory communities formed the basis of the PM plan, which complements research plans focused on other pollutants, such as air toxics and ozone (3, 4), and PM research plans sponsored by other agencies (5, 6).

PM regulatory framework

In the U.S., National Ambient Air Quality Standards (NAAQS) regulate mass concentrations of 2 PM sizes: particles with diameters <2.5 µm (PM_2.5, or the “fine” fraction) and those with diameters <10 µm (PM₁₀; PM_2.5 is a subset of PM₁₀). Transportation contributes to both PM₁₀ and PM_2.5. For example, vehicles disturb road dust that contributes significantly to PM₁₀ (picture the plume behind a car on a dirt road) and a lesser amount to PM_2.5. Combustion pollutants exiting exhaust pipes are usually much smaller than dust particles and contribute to PM_2.5 both directly and through formation of secondary pollutants. Mobile sources in urban areas in the U.S. generally contribute 10–65% of total PM_2.5 mass; typical values are ~35% (7). Disturbed road dust can contribute substantially to PM₁₀ concentrations near roads, but it is thought to deposit on the ground within short distances and time periods (8).

The U.S. EPA has proposed to modify the PM NAAQS to create a standard for PM_10–2.5, or a “thoracic coarse particle”, that excludes PM_2.5 mass (9). It will take many years, perhaps until 2013, for EPA to designate areas that violate thoracic course particle standards and even longer before the transportation community will be required to comply with the new standards (10).

U.S. transportation planning agencies, including FHWA, state departments of transportation (DOTs), and metropolitan planning organizations (MPOs), have a vested interest in understanding PM problems and contributing to their effective control. In the U.S., nonattainment areas—where air-pollution levels persistently exceed the NAAQS—are required to develop state implementation plans (SIPs). A SIP is an air-quality management strategy that documents efforts to reduce emissions and to demonstrate future attainment of air-quality standards. SIPs include regional budgets for allowable PM and PM precursor emissions from transportation sources. MPOs and DOTs are required to demonstrate that transportation plans and programs conform to SIP emissions budgets and that projects do not create or exacerbate air-quality standards violations; these regulations are known as “transportation conformity”. Conformity is a regulatory prod to ensure that transportation and air-quality agencies collaborate. Conformity failure halts receipt of federal highway funds—an impact with political ramifications, because large metropolitan areas receive hundreds of millions of dollars in federal transportation support. Conformity is demonstrated by using emissions models to show that regional emissions are within budgets and dispersion models to show that transportation projects do not cause or contribute to localized, or hot-spot, air-quality problems. The National Environmental Policy Act (NEPA) also requires project-level air-quality analyses.

From the perspective of the U.S. transportation community, required analyses are driven by existing health-based standards. The U.S. PM NAAQS are currently mass-based, an approach that is retained in the proposed NAAQS revisions (9). Recent literature also associates adverse health effects with exposure to increased numbers of ultrafine particles with aerodynamic diameters <100 nm (11, 12). In response, European regulators are weighing the adoption of number-based PM emissions standards for new vehicles (13). However, in the U.S. no corollary regulatory effort is under development, and PM research priorities are motivated by mass-based concentrations. One reason that mass is still the preferred metric is that it is difficult to establish experimental conditions that quantify source production of ultrafine PM as a number count. In the laboratory, the PM number count from engines is strongly influenced by the nature of exhaust dilution, whereas in the real world, the count is influenced by varying atmospheric conditions.

Given the importance of PM air pollution, conformity, and NEPA mandates, FHWA worked with transportation and air-quality experts from public, private, and academic organizations to develop a strategic research plan to address transportation-related PM. This article summarizes the resulting Strategic Plan for Particulate Matter Research: 2005–2010 (14). Details about the strategic planning process, the scientific literature assessed, and the research findings are available from FHWA (7, 15).

Identifying research priorities

Transportation analysts are most interested in applied air-quality research, which yields tools or information that can be used to complete conformity and NEPA assessments or mitigate the impacts of roadway projects. However, the transportation community also depends on the basic science that influences policy decisions affecting PM nonattainment areas (e.g., measurements of PM, assessments of background concentrations) and provides an estimate of the contribution of mobile sources to PM concentrations. FHWA examined candidate research topics in five categories: ambient monitoring of PM and precursors; characterization of PM with modeling tools used to link emissions sources to ambient concentrations; measurements of vehicle emissions; modeling tools to calculate emissions or localized concentrations; and control strategies, including efficacy of emissions controls and associated cost-effectiveness information. Figure 1 illustrates the relationships among the five research topics and agency tasks.

Figure 1. Relationships among research topics and agency tasks

Air-quality agency tasks are green; transportation agency tasks are gray.

FHWA used a three-step process to identify and prioritize PM research needs for the transportation community. First, recent and ongoing research (7), including other PM research plans (5, 16–19), were assessed. Second, the agency sponsored a workshop in which ~50 members of the academic, government, industry, and consulting communities, including MPO and DOT representatives, discussed and prioritized research issues (15). The literature assessment and workshop discussions yielded 23 candidate research issues, spread among the 5 topic areas in Figure 1. Third, the literature assessment and workshop results were synthesized into a strategic plan (14).

Table 1. Prioritized research needs within candidate topic areas

Each issue is numbered in rank order (e.g., M1 is the highest medium priority and M10 is the lowest medium priority). Ranks are based on participant feedback from a workshop held April 7, 2005. DOT: state department of transportation; MOBILE6.2: the U.S. EPA’s MOBILE emissions model, version 6.2; MPO: metropolitan planning organization; PM: particulate matter.
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Table 1 summarizes the key research issues that were identified. During the workshop, a clear consensus emerged that 4 of the 23 research issues were high-priority and that 9 were low-priority. The remaining 10 issues were identified as medium-priority by at least 1 subset of workshop participants.

Other strategic research documents (5, 6, 17) have placed a strong emphasis on monitoring concentrations, measuring emissions, developing air-quality models, and assessing exposure—all goals that are reinforced by this FHWA effort. These research issues are included, directly or indirectly, in Table 1. For the transportation community, high-priority research issues are generally those most relevant to improving the tools and analyses used to meet current and near-term regulatory deadlines. These transportation-community-specific issues have been largely ignored in previous strategic research plans.

To help understand the difference in research focus between the transportation and air-quality management communities, we consider secondary organic aerosols (SOAs). Recent research suggests that motor-vehicle or other anthropogenic sources may be a greater contributor to SOAs than predicted by current modeling (20). From an air-quality management perspective, uncertainty about SOA sources is a key problem, because SIPs must address important sources to reduce PM concentrations. Research plans (5, 17) and the literature assessment supporting this research plan (7) point to the need for further development of methods to measure and apportion SOA. However, from a transportation management perspective, uncertainty over SOA sources is not as compelling a research need as other topics. For example, a planner evaluating a highway project must estimate the incremental contribution of that project to localized PM concentrations. Although background PM concentrations are important for project analyses, the project analyst has a limited need to understand the sources that contribute to background conditions. A more pressing need for the analyst is to estimate project-specific emissions, their effect on localized PM concentrations, and whether mitigation can reduce impacts.

The discussion that follows describes the high-priority research issues included in FHWA’s strategic PM research plan. Although the research topics focus on PM, many of the same needs have been identified for air toxics (3). The research program described here should not be read in isolation; multiple opportunities exist to simultaneously evaluate PM and toxics. For example, field programs that monitor PM, toxics, and other criteria pollutants can improve our understanding of how various mobile-source pollutant concentrations change with distance from the road. For each issue, we provide background, identify research gaps, and suggest ways to fill those gaps.

Monitoring near roadways. A growing body of literature shows that adverse health effects decrease with increasing distance from major roadways. For example, epidemiological studies have linked exposure to traffic with asthma, stroke mortality, and decreased life expectancy (21, 22). Health studies have shown that high particle number concentrations may be responsible for some of the adverse health effects (23–25); however, no definitive studies identify which pollutants (gases, particles, ultrafine particles, or pollutant mixtures) are responsible for the health effects. Some evidence suggests that near roadways, the health effects of diesel-vehicle emissions are much greater than those of gasoline vehicles (26). EPA’s air-quality monitoring program is not designed to study air quality near roadways. Specialized monitoring studies have shown only slightly elevated concentrations of PM_2.5 mass on and near roads, whereas concentrations of black carbon and CO are highly elevated, as is the number of ultrafine particles (27–30).

Near-roadway monitoring data can be used to evaluate concentrations of PM and PM precursors, understand physical and chemical transformations of PM from mobile-source emissions, evaluate hot-spot modeling tools, and support health-effects research. The research will help DOTs and MPOs understand how PM concentrations vary with changes in traffic volumes, speed, vehicle age distributions, diesel-vehicle fractions, and congestion levels. Monitoring concentrations of PM and its precursors near specific roadways before and after implementation of a transportation project will also allow quantitative evaluation of pollution-control strategies and roadway-project effects.

Evaluating hot-spot dispersion models. Hot-spot modeling tools are necessary for transportation agencies to complete environmental impact reports and project-level analyses. Historically, transportation project hot-spot (within 500 m) modeling has focused on CO, which is inert on hot-spot scales. Models used to evaluate CO have incorporated the effects of dispersion caused by dilution and air movement, but they do not account for any chemical or physical processes; these considerations are important for PM on hot-spot spatial scales. For example, new particle formation, condensation, and evaporation are important on hot-spot spatial scales (31). In addition, road dust and other larger particles (such as PM from brake and tire wear) may need to be modeled separately from exhaust PM, which is substantially different in size, deposition rate, and resuspension.

EPA currently recommends the use of specialized dispersion models to evaluate CO hot spots: the CALINE model for free-flow roadways and the CALINE-based CAL3QHC model that accounts for queuing at intersections. Past studies have evaluated CO modeling tools (32); both CALINE and CAL3QHC perform poorly for CO when the wind is nearly parallel to the roadway (33). Recently developed models (ROADWAY-2 and HYROAD) show agreement with measured pollutant concentrations for multiple wind directions (32, 34). Although initial work has been done to evaluate whether CALINE can be used to assess PM (35), further analysis is needed to assess the accuracy of these models for PM.

EPA has promulgated regulations to require MPOs and DOTs to estimate PM hot-spot impacts of transportation projects (36). However, as discussed by EPA in its final hot-spot rule, modeling tools to meet hot-spot requirements are still under development.

Hot-spot modeling tools do not exist to adequately characterize gradients in concentrations of PM, PM components (such as black carbon), and PM precursors near roadways (36). Until appropriate tools exist, project-level, near-roadway NEPA and conformity PM analyses will be qualitative at best and “paper exercises” at worst. New research will assess the limitations of using existing CO modeling tools to assess PM conditions and will define model development needs where current tools prove inadequate.

Improving PM emissions models. Currently, all MPOs and DOTs are required to use the EPA MOBILE emissions model, or the EMFAC emissions model in California, to make conformity determinations. However, these existing models do not accurately estimate on-road PM emissions. For example, MOBILE characterizes vehicle activity in terms of average speed and roadway type only, ignoring the impacts of acceleration or grade on emissions. MOBILE’s emission factors for PM and ammonia are independent of speed and roadway type, assume no deterioration over time, and are sensitive only to vehicle age and type. Speed correction factors and deterioration rates exist in other emissions models but have not been extensively evaluated. MOBILE has fixed emission factors for tire and brake wear, independent of driving conditions, based on data from the mid-1980s; the data may not be representative of the current vehicle fleet (37–45). These deficiencies show that the currently required emissions models are insufficient to accurately handle project-level assessments for PM.

EPA is devoting its resources to developing a new emissions model, named MOVES, to replace MOBILE. However, MOVES will not be available to create PM_2.5 SIPs, which are due in 2008. Therefore, MOBILE must be used to prepare PM_2.5 SIPs and establish allowable PM_2.5 conformity emissions budgets. The MOVES model will address some of MOBILE’s deficiencies by better characterizing emissions as a function of vehicle activity. Beta versions of the MOVES model are being evaluated by the Coordinating Research Council (CRC), a government-industry research consortium; however, the transportation community needs additional evaluations specific to highway projects and conformity applications (46). In addition, other researchers have developed or are developing tools to estimate on-road emissions of PM precursor pollutants (40, 47–51). These emerging tools should be evaluated to determine whether they are robust and whether they can be used by the transportation community for project- or regional-scale analyses.

Emissions data are needed for specific roadways and traffic conditions, to complete project-level analyses. Research that improves link-level (facility-specific) base emission rates and speed correction factors will improve the ability of existing tools to model travel behavior at the project scale, especially for heavy-duty diesel vehicles. If MOVES predicts much lower or higher PM emissions than MOBILE, that could complicate conformity, especially if MOVES emissions estimates are compared with SIP emissions budgets created with MOBILE. Therefore, PM emissions estimates from MOBILE should be compared with results from MOVES and with results from emissions testing to screen for possible systematic biases in emissions budgets from MOBILE that may be written into 2008 SIPs.

Research to evaluate newly developed emissions models is especially important for regional-scale ammonia emissions analyses. Ammonia emissions have not been modeled by the transportation community in the past; ammonia’s contribution to formation of secondary PM and the anticipation that ammonia emissions budgets will be established by SIPs mean that research on ammonia modeling tools will substantially improve the transportation community’s ability to perform regional conformity emissions assessments.

Evaluating control-strategy programs. Planning agencies are already familiar with an array of control measures that reduce VOC or NO_x emissions; these are typically implemented to reduce ozone. However, a knowledge gap exists about the cost-effectiveness of transportation controls that reduce PM problems (52). Existing research shows that the cost-effectiveness of controls varies by several orders of magnitude (52–54). Some of the variation reflects the measures themselves; for example, some controls are less effective at the local or regional level because their impacts are diluted by interstate and interregional travel. Controls that attempt to modify travel behavior often achieve more limited emissions reductions than technology-based controls, and technology-based measures are implemented on regional, state, or national scales (55). In addition, some of the variability observed in the literature is caused by differences in evaluation methods. For example, some methods are based on costs to consumers, while others are based on costs to manufacturers. Implementation costs are often excluded, particularly those incurred by regulatory agencies.

Given the lack of PM-specific control information and the wide range in cost-effectiveness of control measures, a need exists to research and document the cost-effectiveness of transportation controls related to PM. Studies that identify cost-effective PM control measures across the broad spectrum of control options will help close the gap between current needs and existing information.

There are six candidate control measure research topic areas. New-vehicle technologies are controls that are implemented at the time a vehicle is manufactured; examples include improved emissions control systems or use of inherently low-emitting engine designs, such as hybrid gasoline–electric engines. Vehicle retrofits are controls used to reduce emissions on existing vehicles; examples include adding catalytic converters or particulate filters. Inspection and maintenance programs screen the in-use vehicle fleet to reduce the number of high-emitting vehicles and encourage routine maintenance. Fuels and lubricants can also be altered to reduce in-use vehicle emissions; examples include reformulated and oxygenated gasoline or low-sulfur diesel fuel. The use of low-sulfur diesel is especially important because it facilitates the installation of retrofit control devices and the use of catalyzed diesel particulate filters to meet the 0.01 g/hp·h U.S. 2007 standard. Transportation demand management programs alter existing use of ground transportation; examples include ride-sharing, increased transit service, park-and-ride lots, and bike paths. Finally, traffic system management programs change the flow of vehicles, which can reduce emissions from stop-and-go driving or congestion; examples include road modifications such as left-turn lanes and traffic-signal-light synchronization.

Studies that address some or all of the six categories will accomplish two things. First, the findings will help regional officials determine the cost-effectiveness of national and state measures. Second, they will assist officials in identifying the cost-effectiveness of control options that could be implemented at the local level.

Given the near-term SIP deadline, transportation and air-quality planning professionals are disquietingly uncomfortable about our understanding of PM_2.5 control measures. And, with looming PM_2.5 conformity analyses, which will determine the fate of hundreds of millions of dollars in federal highway funds for major metropolitan areas, they are concerned that appropriate analysis tools do not yet exist. Some workshop participants predicted that, if analysis tools are not improved, PM_2.5 conformity analyses risk becoming mere paper exercises. The strategic PM research plan summarized here should provide impetus to government, private-sector, and academic organizations to close these important information gaps over the next 5 years.

Michael C. McCarthy is a senior air-quality analyst at Sonoma Technology, Inc. (STI). Douglas S. Eisinger is the director of transportation policy and planning at STI and the program manager of the University of California, Davis-Caltrans Air Quality Project. Hilary R. Hafner is the vice president of the Air Quality Analysis Division at STI. Lyle R. Chinkin is the president of STI. Paul T. Roberts is the executive vice president and chief scientific officer of STI. Kevin N. Black is an air quality specialist for the U.S. Federal Highway Administration’s Air Quality Team. Nigel N. Clark is the George Berry Chair and professor of mechanical and aerospace engineering at West Virginia University. Peter H. McMurry is a professor of mechanical engineering at the University of Minnesota. Arthur M. Winer is a distinguished professor of environmental health sciences at the University of California, Los Angeles. Address correspondence about this article to Eisinger at doug@sonomatech.com.

Acknowledgments

The authors thank Todd Tamura for his assistance on this project and all the workshop participants for their individual contributions.

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