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Suggested Citation:"Chapter 2 - Context of the CMAQ Program." Transportation Research Board. 2002. The Congestion Mitigation and Air Quality Improvement Program: Assessing 10 Years of Experience -- Special Report 264. Washington, DC: The National Academies Press. doi: 10.17226/10350.
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2
CONTEXT OF THE CMAQ PROGRAM

As noted in Chapter 1, the primary policy goal of the CMAQ program is to improve air quality; congestion mitigation is another program objective to the extent that it supports this goal. In this chapter, the role of the CMAQ program in meeting both goals is discussed. The chapter begins with a brief overview of the air quality problem in the United States, its effect on human health and the environment, the contribution of transportation to the problem, the costs imposed by motor vehicle pollution, and the regulatory and planning process for pollution control. Within this broader context, the specific role of the CMAQ program in helping meet air quality standards is addressed. The discussion then turns to the role of the CMAQ program in reducing congestion. Congestion is defined, measurement of the extent and costs of congested travel on U.S. highways is reviewed, the link between congestion and air quality is examined, and the specific role of the CMAQ program in helping alleviate traffic congestion is discussed. In a final section, the changing air quality and travel context within which the CMAQ program operates and the effect of this context on the future direction of the program are considered. The chapter ends with conclusions and a review of implications for evaluation of the CMAQ program.

THE CMAQ PROGRAM AND AIR QUALITY IMPROVEMENT

Air Quality Standards

Protection of public health is the primary purpose of air quality regulation. The Clean Air Act Amendments (CAAA) of 1970 (Public Law 91-604, 84 Stat. 1676) required, and the U.S. Environmental Protection Agency (EPA) developed, National Ambient Air Quality Standards (NAAQS) for six criteria pollutants considered harmful to

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Suggested Citation:"Chapter 2 - Context of the CMAQ Program." Transportation Research Board. 2002. The Congestion Mitigation and Air Quality Improvement Program: Assessing 10 Years of Experience -- Special Report 264. Washington, DC: The National Academies Press. doi: 10.17226/10350.
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public health—carbon monoxide (CO), lead, nitrogen dioxide (NO2), ozone, particulate matter (PM10),1 and sulfur dioxide (SO2). Primary standards were established that set allowable concentrations of and exposure limits for these criteria pollutants to protect public health with “an adequate margin of safety” (NRC 2000, 16). Secondary standards were also established to protect the public welfare against environmental and property damage (NRC 2000, 16). EPA is required to review and update the NAAQS for major air pollutants every 5 years on the basis of the latest scientific evidence.

Another category of pollutants, known as hazardous air pollutants or air toxics, is also regulated under the Clean Air Act. Air toxics are emitted from thousands of sources, such as electric utilities, automobiles, and dry cleaners. The CAAA of 1990 mandated the development of technology-based emission standards for the 188 relevant pollutants, as well as an assessment of remaining risks (EPA 2001a, 80). According to the most recent EPA inventory, highway vehicles are responsible for about 30 percent of the 4.6 million tons of air toxics released nationwide (EPA 2001a, 82). The inventory does not include diesel particulate matter, which EPA recently listed as a mobile source air toxic and is addressing in several regulatory actions discussed in the final section of this chapter.

In 1997 EPA revised the NAAQS for ozone and PM on the basis of a review of the adverse health effects of exposures to ambient pollutant levels allowed by the then-current standards. The new standard for ozone extended the exceedance period from a 1-hour averaging time to an 8-hour standard to protect against longer exposure periods, and also tightened the standard for most nonattainment areas, changing from a 1-hour daily maximum of 0.12 parts per million (ppm) ozone concentration to a 0.08 ppm 8-hour standard (Federal Register 1997a, 38,856).2 Moreover, whereas prior standards focused on PM10, the new standards for PM targeted PM2.5 for the first time

1

 PM10 is composed of coarse particles (i.e., between 2.5 and 10 micrometers in mean aerodynamic diameter) and fine particles (PM2.5) with mean aerodynamic diameter of less than 2.5 micrometers.

2

The new 8-hour standard is not a daily maximum, like the 1-hour standard, but instead is based on the 3-year average of the fourth-highest daily maximum 8-hour average.

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Suggested Citation:"Chapter 2 - Context of the CMAQ Program." Transportation Research Board. 2002. The Congestion Mitigation and Air Quality Improvement Program: Assessing 10 Years of Experience -- Special Report 264. Washington, DC: The National Academies Press. doi: 10.17226/10350.
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on the basis of epidemiological studies that revealed associations between ambient PM concentrations and various adverse health effects, including mortality (Federal Register 1997b, 38,652). The 24-hour averaging standard for PM10 was also made more stringent. Challenges to the new standards in the Appellate and Supreme Courts have stalled the initial phase of implementation, but these standards were not to take full effect until 2012 and 2018 for ozone and PM2.5, respectively. As of this writing, EPA still needs to satisfy the Court that its new ozone standard can be implemented in a manner compatible with the 1990 CAAA.3

As of September 2000, the most recent period for which data are available, 101 million people, slightly more than one-third (35 percent) of the U.S. population, were living in 114 areas designated as being in nonattainment for at least one of the criteria pollutants (EPA 2001a, 76).

Health and Environmental Effects of Criteria Pollutants and Air Toxics

Concentrations of criteria pollutants that exceed regulated levels are believed to contribute significantly to adverse health effects, which can range from illness to premature death. The adverse health effects of CO and ozone have been known for some time. CO enters the blood stream and links to hemoglobin, reducing delivery of oxygen to the body’s organs and tissues. The health threat from lower levels of CO is most serious for those who suffer from cardiovascular disease (EPA 2001a, 11). However, impairment of cognitive skills, vision, and work capacity may occur with elevated CO levels in healthy individuals (EPA 2001a, 11). The health effects associated with exposure to levels of ozone above the 1-hour standard range from short-term effects, such as chest pain, decreased lung function, and increased susceptibility to respiratory infection, to possible long-term consequences, such as premature lung aging and chronic respiratory illnesses (EPA 2001a, 29).

3

The issue is that requirements for controls in nonattainment areas depend on the areas’ classification (e.g., moderate, serious, severe, extreme), which is keyed to the 0.12 ppm standard in the CAAA. If the standard changes, it is not clear how areas should be classified.

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Suggested Citation:"Chapter 2 - Context of the CMAQ Program." Transportation Research Board. 2002. The Congestion Mitigation and Air Quality Improvement Program: Assessing 10 Years of Experience -- Special Report 264. Washington, DC: The National Academies Press. doi: 10.17226/10350.
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New epidemiological evidence, obtained largely during the 1990s, led to the promulgation of revised PM standards in 1997 and intense scrutiny concerning PM’s adverse health effects, including premature death (NRC 1998, ix). Both coarse and fine particulates can accumulate in the respiratory system. Coarse particles aggravate respiratory conditions such as asthma. Fine particles are also associated with exacerbation of asthma and other respiratory-tract diseases, decreased lung function, increased hospitalization for cardiopulmonary diseases, and premature death (EPA 2001a, 41).4 Air toxics are known to cause or are suspected of causing cancer and having other serious human health effects (EPA 2001a, 79). Relative to criteria pollutants, however, less information is available about the health and environmental impacts of individual hazardous air pollutants (EPA 2001b, 26).

Pollutant deposition can also have adverse effects on ecosystems. SO2 is a well-known precursor to acid deposition (acid rain), as is the ozone precursor NO2 (EPA 2001a, 61). Acids are delivered to ecosystems through the deposition of dry particles and gases (such as nitric acid vapor); rain and snow; and, in coastal and high-elevation areas, clouds or fog. Although nitrogen is an essential plant nutrient, deposition of atmospheric nitrogen in some regions of the United States contributes to acidification of sensitive soils and surface waters; groundwater pollution; and eutrophication5 of downstream waters, such as estuaries and near-coastal ecosystems (Driscoll et al. 2001).

4

The issuance of new standards for PM2.5 has focused considerable attention on the need to review the science that underlies the standards. For example, Congress directed the EPA Administrator to arrange for an independent study by the National Research Council (NRC) on the most important research priorities relevant to setting PM standards, among other tasks, and added substantial funds to EPA’s budget to support the expansion of PM research. Three NRC reports addressing this issue have been published to date (NRC 1998; NRC 1999; NRC 2001a). In addition, EPA has funded five national centers to conduct PM research. The Health Effects Institute, a nonprofit independent research institute that addresses the health effects of air pollution caused by motor vehicles, has also conducted several major reviews and reanalyses of a number of key studies (HEI Perspective 2001), and the American Lung Association has published a review of recent peer-reviewed studies on the health effects of PM air pollution (ALA 2000).

5

The process by which a body of water acquires a high concentration of nutrients, especially phosphates and nitrates, that lead to excessive algae growth and depletion of oxygen in the water.

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Suggested Citation:"Chapter 2 - Context of the CMAQ Program." Transportation Research Board. 2002. The Congestion Mitigation and Air Quality Improvement Program: Assessing 10 Years of Experience -- Special Report 264. Washington, DC: The National Academies Press. doi: 10.17226/10350.
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For example, approximately 30 percent of the nitrogen loading to the Chesapeake Bay and the New York Bay caused by human action is due to atmospheric deposition (Hinga et al. 1991; Fisher and Oppenheimer 1991). Ozone and its precursors can also affect sensitive vegetation and ecosystems. Specifically, they can lead to reduced crop and commercial forest yields and increased plant susceptibility to disease, pests, and the adverse effects of harsh weather (EPA 2001a, 29). Overall, acidic deposition can significantly affect the cycling of nutrients and the acidity of land or water ecosystems. In addition, fine particulates are a major cause of haze and poor visibility in a number of areas, including many national parks (EPA 2001a, 41).

Formation of Criteria Pollutants

Air pollutants either are directly emitted from sources (“primary” pollutants) or are formed in the atmosphere through physical and chemical processes (“secondary” pollutants), resulting in ambient concentrations that can adversely affect the health of exposed populations. Of the six criteria pollutants, CO, SO2, and lead are primary pollutants; NO2 has both primary and secondary origins; and ozone is a secondary pollutant formed by the action of sunlight and chemical reactions involving volatile organic compounds (VOCs) and oxides of nitrogen (NOx)6 (NRC 2000, 16–17). Airborne PM is a combination of primary and secondary pollutants (NRC 2000, 17). Carbonaceous particles from combustion sources (i.e., motor vehicles; utilities; industrial, commercial, and institutional boilers; and area source combustion) and windblown dust account for most of the primary PM. Ammonium sulfate and ammonium nitrate from the oxidation of SO2 and NOx, respectively, are important components of secondary particles, though a significant fraction of organic carbon PM can also result from the chemical reactions of VOCs. Other important constituents of airborne PM include heavy metals and polycyclic aromatic hydrocarbons (PAH).

The distinction between primary and secondary pollutants is important in designing appropriate pollution control strategies. For

6

NOx emissions from motor vehicles, the primary focus of this report, consist of a mixture of NO and NO2 (TRB 1995, 44).

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Suggested Citation:"Chapter 2 - Context of the CMAQ Program." Transportation Research Board. 2002. The Congestion Mitigation and Air Quality Improvement Program: Assessing 10 Years of Experience -- Special Report 264. Washington, DC: The National Academies Press. doi: 10.17226/10350.
×

example, emissions of transportation-related PM, CO, and NO2—primary pollutants—tend to be concentrated on and near congested highways and at other locations where traffic densities are high. Thus targeted improvements, such as relieving traffic bottlenecks or otherwise reducing emissions (e.g., substituting cleaner-burning fuels) can reduce CO, NO2, and PM. In contrast, ozone and secondary fine particles typically are regional problems, not amenable to geographically targeted projects. Furthermore, ambient concentrations of secondary pollutants are not always proportional to their source emissions because the rates at which they form are not necessarily proportional to quantities of precursor gases. In the case of ozone, knowing the relative concentrations of precursor VOCs and NOx is critical to selecting appropriate abatement strategies. For example, in regions with low levels of VOCs relative to NOx, characteristic of some highly polluted urban areas, strategies that lower VOCs will reduce peak ozone concentrations; however, lowering NOx can lead to lower or higher ozone in the urban center, depending on the relative concentrations of VOC and NOx, the specific mix of VOCs present, and the proximity to NOx emissions, as well as the effects of local meteorology on transport and dispersion. These processes are complex and depend on many meteorological and chemical variables, which are described in more detail in Appendix B.

Contribution of Transportation to Pollutant Formation

The principal sources of polluting emissions are as follows:

  • Transportation (on- and off-road vehicles);

  • Stationary sources (e.g., fuel combustion by utilities and industrial, commercial, and residential sources);

  • Industrial process sources (e.g., chemical manufacturing, petroleum refining, solvents, and waste disposal); and

  • Other sources [e.g., biogenic emissions from natural and agricultural sources and from other combustion (NRC 2000, 17)].

In 1999, the most recent year for which data are available, emissions from transportation sources, also known as mobile source emissions, contributed to more than half (53 percent) of nationwide

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Suggested Citation:"Chapter 2 - Context of the CMAQ Program." Transportation Research Board. 2002. The Congestion Mitigation and Air Quality Improvement Program: Assessing 10 Years of Experience -- Special Report 264. Washington, DC: The National Academies Press. doi: 10.17226/10350.
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emissions of EPA’s criteria pollutants (see Table 2-1). Nearly two-thirds (64 percent) of mobile source emissions are from highway (on-road) vehicles, although the range is considerable for each pollutant source (see Figure 2-1). For example, highway vehicles are the dominant source of U.S. CO emissions. In 1999 highway vehicles contributed 51 percent of total CO emissions nationwide (see Table 2-1 and Figure 2-1). In many urban areas, mobile sources account for more than 90 percent of total CO emissions, for example, as documented in the emission inventories for the San Francisco Bay Area and the South Coast Air Quality Management District (Los Angeles area). Nevertheless, in 1999 CO levels were the lowest recorded in the last 20 years; currently there are only six areas of the country with CO levels violating the NAAQS (EPA 2001a, 2). More specifically, CO emissions from highway vehicles have decreased by approximately 50 percent during the past 20 years despite nearly a 60 percent increase in vehicle-miles traveled (VMT) (EPA 2001a, 13).

TABLE 2-1 Contribution of Transportation to Emissions of Criteria Pollutants in the United States, 1999 (millions of short tons)

Source Category

Pollutant

Total

CO

NOx

VOCs

PM10

Lead

SO2

Transportation

Total

75.1

14.1

8.5

0.8

0.5

1.3

100.3

Highway vehicle share

49.9

8.6

5.3

0.3

0.02

0.4

64.5

Fuel combustion

5.3

10.0

0.9

1.0

0.5

16.1

33.8

Industrial processes

7.6

0.9

8.0

1.3

3.2

1.5

22.5

Miscellaneous

9.4

0.3

0.7

20.6a

0.0

0.01

31.0

Total

97.4

25.3

18.1

23.7

4.2

18.9

187.6

Share of total (percent)

All transportation

77.0

56.0

47.0

3.0

12.0

7.0

53.0

Highway vehicles

51.0

34.0

29.0

1.3

0.5

2.1

34.0

Note: CO = carbon monoxide; VOCs = volatile organic compounds; NOx = oxides of nitrogen; PM10 = particulate matter (with mean aerodynamic diameter less than 10 micrometers); SO2 = sulfur dioxide.

aIncludes windblown dust and natural sources (i.e., wind erosion).

Source: EPA (2001a).

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Suggested Citation:"Chapter 2 - Context of the CMAQ Program." Transportation Research Board. 2002. The Congestion Mitigation and Air Quality Improvement Program: Assessing 10 Years of Experience -- Special Report 264. Washington, DC: The National Academies Press. doi: 10.17226/10350.
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FIGURE 2-1 Sources of criteria air pollutants. Estimated total annual emissions of criteria pollutants from stationary sources, industrial processes, transportation (on-road and nonroad), and miscellaneous sources for 1999. Emissions are shown in thousands of short tons except for lead, which is shown in short tons. (Source: EPA 2001a, Appendix A.)

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Suggested Citation:"Chapter 2 - Context of the CMAQ Program." Transportation Research Board. 2002. The Congestion Mitigation and Air Quality Improvement Program: Assessing 10 Years of Experience -- Special Report 264. Washington, DC: The National Academies Press. doi: 10.17226/10350.
×

During the last 20 years, ozone levels (1-hour and 8-hour) have improved considerably (EPA 2001a, 29). Urban ozone levels, historically the most severe, have shown marked improvement in response to stringent control programs (EPA 2001a, 29). Mobile source emissions are a major source of VOCs and NOx—the precursors of ozone and fine particulate matter. In 1999 highway vehicles contributed 29 percent of VOCs and 34 percent of NOx emissions nationwide. VOC emissions from highway vehicles declined 18 percent during the past 10 years, but NOx emissions increased by 19 percent during the same period (EPA 2001a, 37). This poor performance of NOx emissions may reflect the lack of attention paid to the role of this important pollutant in ozone formation until relatively recently (NRC 1991).

According to the national emissions inventory for 1999, tailpipe emissions from highway vehicles represented a small share (1.3 percent and 3.4 percent) of directly emitted (i.e., primary) PM10 and PM2.5, respectively, from all sources (see Figure 2-1). However, tailpipe emissions account for a substantially higher portion of PM in urban areas, where the majority of mobile source emissions occur. For example, ambient source apportionment studies show that particulate emissions in motor vehicle exhaust account for nearly 40 percent of the fine PM in Denver and Los Angeles (Watson et al. 1998; Fujita et al. 1998; Schauer et al. 1996). Including dust from paved roads and secondary ammonium nitrate from NOx emissions, motor vehicles may contribute as much as 50 to 75 percent of the fine PM in Denver and Los Angeles. In contrast, windblown dust from unpaved roads and, to a lesser extent, agriculture and forestry, wildfires, and managed burns occurs mainly in rural areas. Coarse particles are relatively short-lived in the atmosphere, tending to be removed rapidly or deposited within a short distance from the point of their release.7 Carbonaceous fine particles from combustion sources and secondary particles (i.e., nitrates, sulfates, and organic carbon formed in the atmosphere from the conversion of gaseous NOx, SO2, and VOCs), which range in size from 10 nanometers to 1 micrometer, are much longer lived and

7

Little is known, however, about the influence of exposure to road dust on the risks of mortality and disease.

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Suggested Citation:"Chapter 2 - Context of the CMAQ Program." Transportation Research Board. 2002. The Congestion Mitigation and Air Quality Improvement Program: Assessing 10 Years of Experience -- Special Report 264. Washington, DC: The National Academies Press. doi: 10.17226/10350.
×

are transported longer distances than coarse particles. Fine and ultra-fine particles also occur in far greater numbers than coarse particles. The greater numbers and longer lifetimes in the atmosphere of fine and ultrafine particles, as well as their ability to be inhaled into the deep lung, result in greater human exposure and potential health impacts than is the case for coarse particles.

Transportation is a minor source of SO2 and no longer accounts for a large share of pollution from lead. Highway vehicles currently account for less than 1 percent of total lead emissions, primarily because of the use of unleaded gasoline (see Table 2-1 and Figure 2-1). Highway vehicles contribute about 2 percent of directly emitted SO2; coal-burning power plants are consistently the largest contributor (see Table 2-1). However, these percentages are somewhat misleading. Similar to emissions of NOx, SO2 emissions from motor vehicles react in the atmosphere to form sulfate aerosols and hence are an important precursor to PM2.5 (EPA 2001a, 61).

The transportation sector also contributes to the formation of greenhouse gases. Approximately one-third of total U.S. anthropogenic emissions of CO2 comes from the transportation sector (NRC 2000, 20).8 About one-quarter of the total is attributable to highway vehicles (NRC 2000, 20).

Emissions from highway vehicles vary by vehicle and fuel type. The primary emissions of gasoline-powered vehicles—passenger vehicles and panel trucks—are CO, VOCs, NOx, and SO2, although research is under way to characterize PM emissions from high-emitting gasoline vehicles (see Figure 2-2).9 The primary emissions of diesel vehicles—mainly heavy trucks and buses—are NOx, CO, PM, VOCs, and SO2 (see Figure 2-2). Emissions of NOx and PM from heavy trucks and buses are of greatest concern. Heavy-duty vehicles are a dominant source of directly emitted fine and ultrafine particles

8

Note, however, that there is no air quality standard for CO2—the principal green-house gas—because CO2 is not toxic and therefore has no direct negative health effects.

9

Estimates of PM emissions from light-duty vehicles are highly uncertain. They are generally based on EPA’s PART5 model, which a recent NRC study characterized as “seriously out of date” (NRC 2000, 70).

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Suggested Citation:"Chapter 2 - Context of the CMAQ Program." Transportation Research Board. 2002. The Congestion Mitigation and Air Quality Improvement Program: Assessing 10 Years of Experience -- Special Report 264. Washington, DC: The National Academies Press. doi: 10.17226/10350.
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FIGURE 2-2 Estimated mobile source emissions by vehicle and fuel type. MOBILE5 and PART5 estimates of 1999 emissions from the on-road motor vehicle fleet. It is likely that MOBILE5 underestimates gasoline VOC and diesel NOx emissions. Emissions are shown in thousands of short tons. (Source: EPA 2001a, Appendix A.)

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Suggested Citation:"Chapter 2 - Context of the CMAQ Program." Transportation Research Board. 2002. The Congestion Mitigation and Air Quality Improvement Program: Assessing 10 Years of Experience -- Special Report 264. Washington, DC: The National Academies Press. doi: 10.17226/10350.
×

(PM2.5), and PM from diesel exhaust was recently declared an air toxic (EPA 2001a, 79; ARB).10 Because of the high sulfur content of diesel fuel, emissions of SO2 from heavy-duty vehicles are also of concern; moreover, the high sulfur content defeats diesel engine control measures. As discussed subsequently, tighter exhaust emission standards for heavy-duty diesel engines and a related rule on low-sulfur diesel fuel should go a long way toward reducing these pollutant sources.

Emissions from highway vehicles in specific nonattainment areas may represent much greater pollutant contributions than the national averages. Ozone precursors are a good example. In the South Coast Air Basin, which includes some of the most polluted areas of the Los Angeles region, emissions of VOCs and NOx from highway vehicles account for 52 percent and 72 percent, respectively, of emissions from all sources on the basis of 1997 data provided by the South Coast Air Quality Management District; the national averages at that time were 28 percent and 34 percent, respectively (EPA 2001a, Appendix A).

Costs of Motor Vehicle–Related Air Pollution

Several attempts have been made to estimate the economic cost of the health impacts of pollution. However, far fewer studies have focused specifically on the health costs of motor vehicle emissions.11 Estimating health costs requires a complex set of steps: estimating emissions related to motor vehicle use; estimating changes in exposure to air pollution; relating these changes to changes in physical health effects; and finally relating those effects to changes in

10

See the California Air Resources Board website (www.arb.ca.gov) for more information on California’s approach to diesel PM emissions.

11

Small and Kazimi (1995) estimate the health costs of PM and ozone from motor vehicles for the Los Angeles area. Krupnick et al. (1996, 338) summarize the literature from the United States and Europe on the primary social costs of air pollution from transportation sources, present the results of a more complete life-cycle analysis of the air pollution–related damages from all major refinery emissions and from vehicular emissions contributing to particulate concentrations, and discuss key issues in estimating health damages. Several of these studies either appear or are discussed in Greene et al. (1997).

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Suggested Citation:"Chapter 2 - Context of the CMAQ Program." Transportation Research Board. 2002. The Congestion Mitigation and Air Quality Improvement Program: Assessing 10 Years of Experience -- Special Report 264. Washington, DC: The National Academies Press. doi: 10.17226/10350.
×

economic welfare, including placing a value on reduction of mortality risk and illness (McCubbin and Delucchi 1999, 254). The most recent comprehensive analysis of the costs of the health effects of criteria pollutants from all emission sources related to motor vehicle use in the United States was conducted by the Federal Highway Administration (FHWA) as an addendum to its 1997 Federal Highway Cost Allocation Study (FHWA 2000). According to that analysis, the economic cost of motor vehicle–related air pollution was estimated at approximately $40 billion (in 1990 dollars) using methods developed by EPA in a cost–benefit study (EPA 1997).12 Cost ranges could not be developed from the EPA data, but a high and low estimate of the costs of air pollution attributable to motor vehicle use, ranging from about $30 billion to $349 billion (in 1991 dollars), was taken from a study by McCubbin and Delucchi (1998, 55) to reflect the very large uncertainties of the estimates.

The absolute levels of cost are surely open to challenge; however, what the results show about the relative importance of the various cost elements is perhaps of greater interest. Both the FHWA and McCubbin and Delucchi studies cited here show that the majority of the costs are attributable to PM, reflecting the serious health consequences related to PM inhalation. In addition, diesel vehicles are estimated to cause more damage per mile than gasoline vehicles because heavy-duty diesel vehicles account for a greater share of PM emissions (FHWA 2000; McCubbin and Delucchi 1999, 253).

Regulation of Mobile Source Emissions

Requirements of the 1990 Clean Air Act Amendments13

As noted earlier, in 1990 Congress enacted a series of amendments to the Clean Air Act to intensify air pollution control efforts across the nation and overhaul planning provisions in those areas that did not meet the NAAQS. The 1990 CAAA strengthened requirements

12

If EPA’s higher mortality valuation is used, the costs increase to approximately $65 billion (in 1990 dollars) (FHWA 2000). In both cases, the costs of road dust (a major source of PM10) and air toxics, mortality costs for ozone, and other environmental costs (e.g., crop damage) are excluded from the analyses.

13

This section draws heavily on Special Report 245 (TRB 1995, 14–17).

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Suggested Citation:"Chapter 2 - Context of the CMAQ Program." Transportation Research Board. 2002. The Congestion Mitigation and Air Quality Improvement Program: Assessing 10 Years of Experience -- Special Report 264. Washington, DC: The National Academies Press. doi: 10.17226/10350.
×

for reducing emissions from transportation sources. Strict monitoring and sanctions for nonperformance were designed to bring nonattainment areas into compliance. The legislation specified deadlines for reaching attainment that varied with the severity of air quality problems. Areas classified as being in marginal nonattainment had 3 years from the baseline year (1990) to reach attainment; moderate areas, 6 years; serious areas, 9 years; severe areas, 17 years; and extreme areas—only one, Los Angeles—20 years.

Required levels of effort also varied with the severity of air quality problems. Nonattainment areas with ozone classifications of moderate or worse had to submit plans showing reductions of at least 15 percent in the emissions that create ozone within 6 years from the 1990 baseline, net of any growth in emissions during that period. In addition, with the exception of moderate nonattainment areas, these areas had to achieve additional emission reductions of 3 percent per year until attainment was achieved. Nonattainment areas classified as severe or extreme had to adopt transportation control measures (TCMs) aimed at decreasing automobile travel.

Moderate or worse nonattainment areas with only CO designations were required to forecast VMT annually beginning in 1992, and if actual VMT exceeded that forecast, to be ready to adopt contingency TCMs. The latter were required for CO nonattainment areas designated as serious.

Conformity Requirements

Conformity serves as the primary tool for ensuring that transportation activities in nonattainment and maintenance areas are consistent with the achievement of air quality standards. The concept of transportation conformity, introduced in the CAAA of 1977, was made considerably more rigorous in the 1990 CAAA (FHWA 1997, 2). The latter required metropolitan planning organizations (MPOs) and the U.S. Department of Transportation (USDOT) to demonstrate that transportation plans, programs, and projects would not cause or contribute to any new violations of air quality standards, increase the frequency or severity of existing violations, or delay timely attainment of the NAAQS (FHWA 1997, 2). This requirement applied to all local

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Suggested Citation:"Chapter 2 - Context of the CMAQ Program." Transportation Research Board. 2002. The Congestion Mitigation and Air Quality Improvement Program: Assessing 10 Years of Experience -- Special Report 264. Washington, DC: The National Academies Press. doi: 10.17226/10350.
×

transportation projects funded or approved by FHWA or the Federal Transit Administration (FTA).14

Conformity determinations require a set of planning activities that involve both the states and MPOs. The 1990 CAAA required each state to develop a state implementation plan (SIP) addressing each pollutant for which the state had failed to meet the NAAQS and indicating how the state intended to meet the standards on schedule (FHWA 1997, viii). The SIP assigns emission reduction targets to each source category, primarily stationary sources and mobile source emissions. The mobile source emissions budget included in an SIP represents the highest level (or ceiling) of emissions allowed from all projects included in local-area transportation plans in a state.15

At the local level, MPOs are responsible for demonstrating that transportation plans and programs conform to the emissions budgets in the SIP.16 The Intermodal Surface Transportation Efficiency Act (ISTEA) of 1991 complemented the CAAA by strengthening metropolitan-area planning requirements to help make these conformity determinations. Under ISTEA, MPOs must have long-range (20-year) transportation plans in place. Shorter-term (typically 6-year) transportation improvement programs (TIPs)—prioritized multiyear lists of projects for which funds must be available or committed for the first 2 years—when analyzed, must show emissions consistent with those allowed in the SIP mobile source emissions budget for that nonattainment area (FHWA 1997, 1). Under ISTEA’s metropolitan planning requirements, projects cannot be approved, funded, advanced through the planning process, or implemented unless they

14

Conformity analysis must also include regionally significant transportation projects— projects on a facility that serves regional transportation needs and would normally be included in the modeling of a metropolitan area’s transportation network—that are not funded or approved by FHWA or FTA, but are sponsored by recipients of FHWA/FTA funds.

15

These budgets are developed on the basis of emission inventories in the SIP, which in turn are based on the number of vehicles in a region, their age, the rate of fleet turnover to newer and cleaner vehicles, seasonal temperatures, and projections of travel activity (FHWA 1997, 3).

16

In rural areas, conformity determinations are the responsibility of USDOT and the project sponsor, which is usually the state DOT (FHWA 1997, 2). The latter is often responsible for conformity determinations in PM nonattainment areas, which tend to be rural or small city areas.

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Suggested Citation:"Chapter 2 - Context of the CMAQ Program." Transportation Research Board. 2002. The Congestion Mitigation and Air Quality Improvement Program: Assessing 10 Years of Experience -- Special Report 264. Washington, DC: The National Academies Press. doi: 10.17226/10350.
×

are in a fiscally constrained and conforming transportation plan and TIP (FHWA 1997, vii). If a conformity determination cannot be made by modifying either the TIP or the SIP to offset the excess emissions, or if more than 3 years passes before a new conformity determination is made, the determination lapses, and no new projects may advance (FHWA 1997, 5).

Contribution of CMAQ to Meeting Air Quality Attainment Goals

CMAQ Projects and Air Quality Improvement

As noted earlier, the primary focus of the CMAQ program has been on ozone and its precursors—VOCs and NOx—and CO, reflecting the pollutants of greatest concern at the time the 1990 CAAA and ISTEA were passed. Projects aimed at reducing PM10 emissions became explicitly eligible for funding under the reauthorization of the CMAQ program in the Transportation Equity Act for the 21st Century (TEA-21), reflecting increased concern about the adverse health effects of PM. However, PM is still not recognized directly as a factor in the CMAQ funding allocation formula (see Table 3-2 in Chapter 3).

CMAQ regulations (FHWA 1999, 10) give first priority for funding to transportation activities in approved SIPs and maintenance plans and then to the TCMs included in the CAAA, with the exception of vehicle scrappage programs. All CMAQ projects must be included in an area’s TIP and meet conformity requirements.

As discussed in Chapter 1, the type of pollutant for which areas are in nonattainment may influence CMAQ project selection. Areas with CO problems may select traffic flow improvements to eliminate CO hotspots. On the other hand, areas that have an NOx problem may not choose traffic flow improvements, at least not those that would significantly increase vehicle speeds, which would in turn increase NOx emissions.

Of course, CMAQ is not the only revenue source for dealing with local transportation strategies to improve air quality. For example, Maryland chooses to use state funds to pay for regional TCMs needed to help the Washington metropolitan area stay within its SIP budgets. Simply focusing on Maryland’s CMAQ expenditures would result in underestimating that state’s spending on air quality improvement projects in the Washington area.

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Benefits of Air Quality Improvement Projects

CMAQ program recipients must demonstrate expected emission reductions for each project funded under the program. States are required to report annually on the potential reductions of each relevant pollutant (CO, VOCs, NOx, and PM10) for inclusion in FHWA’s national CMAQ database (FHWA 1999, 22). No attempt is made to take the next step to determine how these projects actually affect pollutant concentrations or public health.

Estimating the emission benefits of TCMs and other CMAQ-eligible projects requires the use of models or model inputs whose results are highly uncertain. Pollutant emissions from highway vehicles are currently estimated using a mobile source emission factor model, such as the MOBILE and PART5 models developed by EPA and the motor vehicle emission inventory (MVEI) suite of models developed by the California Air Resources Board. A recent NRC (2000) report provides a comprehensive evaluation of the MOBILE model, reviewing the accuracy and uncertainties of modeled emission estimates, as well as other modeling techniques. The MOBILE and MVEI models are intended for use in deriving emission inventories for entire regions.17 They are not well suited to evaluating smaller-scale operational improvements, such as many typical CMAQ projects.

THE CMAQ PROGRAM AND CONGESTION MITIGATION

Defining Congestion

Economists observe that when a scarce and valued good is free or underpriced, demand will outstrip supply, creating shortages (TRB 1994, 27). This phenomenon is readily seen in the nation’s metropolitan areas each day as motorists attempt to commute to work at desired peak travel times, creating levels of demand that exceed road capacity (i.e., congested conditions). In the absence of pricing or

17

These models provide emission factors separately for classes of vehicles and technology classes. To estimate total on-road emissions in a given area, either the vehicle class emission factor is multiplied by estimates of vehicle travel distances by vehicle class for the area and summed, or the fleet-average emission factor is multiplied by total travel distance for the area. In addition to vehicle class and travel distances, model inputs (some required and some optional) include ambient temperature, average vehicle speed by vehicle class, fuel characteristics, vehicle inspection and maintenance parameters, and vehicle age distributions.

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rationing, the primary incentive for individual motorists to travel is guided by the costs each experiences directly, known as private costs—vehicle operating expenses and the value of that driver’s travel time. The travel decision, however, is not affected by the delay costs imposed on others (known as social costs) as a result of the decisions of individual motorists to travel at a particular time, although individual drivers are affected by the total delay they encounter. The increment of delay added by any one motorist may be small. When increments are accumulated over all the motorists that follow, however, the delay can be substantial (TRB 1994, 28–29). For example, if traffic density is already near the facility capacity, delays will mount rapidly and service will decline markedly, resulting in the stop-and-start conditions so common during peak travel periods (TRB 1994, 28). Of course, if delays become bad enough, some motorists will change their behavior even in the absence of pricing, by either changing the times of their trips or canceling their trips. However, these shifts are rarely adequate to reduce congestion appreciably without additional incentives (TRB 1994, 28).

The socially optimal level of travel on a highway facility at peak travel times occurs when the marginal benefits of additional trips just equal the total costs they impose on all motorists (TRB 1994, 29). From an efficiency perspective, some amount of congestion is desirable, even at socially optimal traffic levels. The reason is that some motorists knowingly choose to travel even at congested times. Thus, they are willing to pay a portion of the social costs of the trip because the expected trip benefits exceed the private costs for these travelers.

A key attribute of congested travel is delay, which is often characterized as either recurring or nonrecurring. Recurring delay refers to the reduced driving speeds and resulting delays that typically occur each day during peak travel times. The delays are attributable to high volumes of traffic relative to roadway capacity. Nonrecurring delay occurs because of incidents—crashes, breakdowns, or other occurrences—that temporarily reduce highway capacity. A recent study of congestion on freeways and principal arterial streets in 68 urban areas revealed that, on average, incident delays accounted for more than half (54 percent) of total delays in these areas (Schrank and

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Suggested Citation:"Chapter 2 - Context of the CMAQ Program." Transportation Research Board. 2002. The Congestion Mitigation and Air Quality Improvement Program: Assessing 10 Years of Experience -- Special Report 264. Washington, DC: The National Academies Press. doi: 10.17226/10350.
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Lomax 2001, 8).18 The distinction between recurring and nonrecurring congestion is important because different strategies are often deployed to address the two.

Costs of Congestion

The two primary costs of congestion are vehicle operating costs and the value of travel time. Valuing vehicle operating costs—primarily fuel costs—is relatively straightforward. Valuing travel time is more complex, and a large literature exists on the topic.19 Evidence suggests that different population subgroups value time differently (Small 1999, 148). As previously noted, some drivers are more willing than others to drive in congested conditions. Another complication arises from the fact that not all trips are valued equally. For example, the time spent commuting to work typically is valued at a higher rate than that spent on discretionary trips.20 The value of time also depends on trip characteristics, including length and total amount of time spent traveling (Small 1999, 149). For example, there is some evidence that people value travel time savings more on medium-length trips than on short or long trips (Small 1999, 148). In addition to estimating the costs of congestion to commuters, a full accounting requires consideration of the costs imposed on businesses and consumers by delays in freight movement.

18

This estimate was developed separately for freeway and arterial travel. The freeway figure is based on a detailed methodology developed by FHWA and updated for the Schrank and Lomax report to estimate the ratio of recurring to incident delay on freeways. The resulting 1.4 ratio was multiplied by the amount of recurring freeway delay in each urban area. Incident delay on arterial streets was estimated as a constant 1.1 ratio of recurring delay on these roads. Crash rates are higher on arterials, and recurring delay is lower (Schrank and Lomax 2001, Appendix B).

19

A good review of the literature is given by Small et al. (1999).

20

One review of studies revealed that the value of time for the journey to work averages about 50 percent of the before-tax wage rate; the range across different industrialized cities is from 20 to 100 percent (Small 1999, 147). Using a stated-preference survey approach, Calfee and Winston (1998) found a relatively low value (19 percent of the before-tax wage rate on average) for commuter willingness to pay for reductions in travel time under a range of different travel scenarios. Their explanation for this finding is that some of those with high values of travel time had opted for residential and workplace locations with short commutes or low levels of congestion, and thus were not represented in the sample.

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In an annual study by the Texas Transportation Institute (TTI), the costs of congestion are estimated for a sample of 68 urban areas, classified from small to very large in terms of their population size.21 Estimates include the costs of fuel and time wasted. It is estimated that in the sample of 68 urban areas, congestion resulted in 4.5 billion hours of delay and 6.8 billion gallons of wasted fuel in 1999, for a total cost of $78 billion (Schrank and Lomax 2001, 42–44).22 Delay represents by far the largest cost component, estimated at $69.2 billion in 1999. The TTI methodology has been criticized for overestimating congestion levels and costs by assuming an arbitrary cut-off point at which congestion begins.23 Nonetheless, the study does provide an order-of-magnitude estimate of the social costs of congestion.

Measurement of Congestion and Trend Analysis

Measurement of congestion has been a topic of interest to the transportation profession since the 1950s (Meyer 1994, 33). In more recent years, alternative approaches have been advanced to address the questions of whether and to what extent highway congestion is worsening. The majority of attention has been focused on urban highways, where population size and density create the conditions most conducive to high levels of congestion.

21

Data are provided for urbanized areas; only developed land with a density of greater than 1,000 persons per square mile is included in the boundary. Population sizes range from more than 3 million to less than 500,000. Data on urban-area travel volumes are taken from FHWA’s Highway Performance Monitoring System database, and supplemented by supporting information from various state and local agencies (Schrank and Lomax 2001, 4).

22

As shown in Appendix B (Schrank and Lomax 2001), delay costs are determined by applying a dollar value to the hours of delay in recurring and nonrecurring congestion for both passenger and commercial vehicles. Passenger vehicle occupant time is valued at $12.40 per person-hour with vehicle occupancy rates of 1.25 persons per vehicle. Commercial vehicle operating cost is valued at $2.85 per mile. Fuel costs are determined by applying statewide average fuel costs to vehicle-hours of recurring and nonrecurring delay at average peak-period congested speeds and associated average fuel economy, and multiplying the product by 250 working days.

23

The TTI approach assumes arbitrarily that congestion exists when average daily traffic per lane exceeds 15,000 vehicles on freeways and expressways and 5,500 vehicles on principal arterial streets. The percentage of daily travel in uncongested conditions varies by urban area, but the length of the peak travel period is held constant at 50 percent of the average daily VMT for all urban areas (Schrank and Lomax 2001, Appendix B).

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TABLE 2-2 Growth in Urban Miles, Lane Miles, and Vehicle-Miles Traveled

 

1980

1990

1999

Percent Change

1980–1990

1990–1999

1980–1999

Urban miles

624,000

744,644

846,059

19.3

13.6

35.6

Urban lane miles

1,395,245

1,670,496

1,911,303

19.7

14.4

36.9

Urban vehicle-miles traveled (in millions)

855,265

1,275,484

1,598,065

49.1

25.3

86.9

Note: An urban highway is defined as any road or street within the boundaries of an urban area, including or adjacent to a municipality or urban place, with a population of 5,000 or more (BTS 2001).

Source: BTS 2001, 7–8, 47.

A gross measure of congestion can be obtained by examining the gap between travel demand and highway capacity over time. For example, annual data collected by FHWA and reported by the Bureau of Transportation Statistics on urban road mileage and travel show that capacity increases have not kept pace with the growth in travel (see Table 2-2). Between 1980 and 1999, the most recent year for which data are available, VMT in urban areas grew nearly 2.5 times faster than additions to urban supply, measured either as highway miles or lane miles. The gap between highway demand and supply narrowed during the 1990s, mainly because of a slowing in the rate of growth of VMT. However, the shortfall may be larger because the data cannot distinguish between real additions to highway capacity and additions that result from reclassification of rural road and lane mileage to an urban designation.

Attempts to measure urban highway congestion directly have proven difficult. Very limited data are available nationally on levels of delay.24 One of the best-known measures was developed by TTI in the study just cited, but not all researchers agree that the index is valid, for the reasons previously discussed. Yet while these critiques

24

For example, FHWA has developed a measure of congestion on urban Interstate highways on the basis of traffic volume information and roadway capacity for sampled sections of highway. Unfortunately, numerous changes in the calculation of highway capacity preclude meaningful trend analysis.

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Suggested Citation:"Chapter 2 - Context of the CMAQ Program." Transportation Research Board. 2002. The Congestion Mitigation and Air Quality Improvement Program: Assessing 10 Years of Experience -- Special Report 264. Washington, DC: The National Academies Press. doi: 10.17226/10350.
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may call into question the validity of the TTI measures of absolute congestion levels and costs, the approach offers a consistent way of examining relative changes in congestion levels over time.

The most recent TTI report (Schrank and Lomax 2001) provides two indicators of congestion derived from estimates of travel delay due to the extra time spent in congested traffic.25 Both indicators compare travel times in peak periods with those in free-flow conditions; one index is based solely on recurring delay, and the other includes both recurring and nonrecurring delay.26 Many urban areas exhibit substantial levels of congestion as measured by one or both indicators.

The trend data show that between 1982 and 1999, 47 of the 68 urban areas studied suffered a growing time penalty from traffic volume increases and incidents. The relevant congestion index increased by 17 points during this period, resulting in a 3.5-minute or greater increase in a 20-minute commute trip during congested periods (Schrank and Lomax 2001, 14). Large urban areas experienced the heaviest time penalty, with up to 7 minutes being added to a congested-period trip (Schrank and Lomax 2001, 14). In another indicator of worsening congestion, the report indicates that, on average, the percentage of daily traffic in the congested periods (i.e., traffic moving at less than free-flow speeds) in all 68 urban areas grew from about 32 percent in

25

The methodology for estimating travel delay is explained in detail in Appendix B of Schrank and Lomax (2001). Travel delay is measured in two steps. First, recurring delay is measured by estimating travel speeds for each freeway and arterial link on the basis of placing each link in one of five travel speed categories—uncongested or one of four congested categories ranging from moderate to extreme—and weighting the links by the amount of VMT on each link to estimate vehicle delay. The travel speed for each link represents the average speed for both roadway directions during the peak period. The latter is estimated using a roadway congestion index—a measure of daily traffic volume per lane—that helps identify the length of time for which the areawide system may experience congestion. Second, incident delay is calculated by multiplying recurring hours of delay by a ratio of recurring to incident delay, using a different ratio for freeways and arterial streets.

26

To calculate the travel rate index (TRI), the ratio of freeway peak-period travel rates (measured in minutes per mile) to freeway free-flow travel rates, weighted by freeway peak-period VMT, is added to the same calculation applied to principal arterial streets, and the result is divided by the freeway plus arterial street peak-period VMT (Schrank and Lomax 2001, Appendix B). A TRI of 1.30, for example, indicates that the average peak-hour trip takes 30 percent longer than a trip in free-flow conditions. The travel time index involves the same comparisons as the TRI, with the addition of delay rates from incidents (Schrank and Lomax 2001, Appendix B).

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Suggested Citation:"Chapter 2 - Context of the CMAQ Program." Transportation Research Board. 2002. The Congestion Mitigation and Air Quality Improvement Program: Assessing 10 Years of Experience -- Special Report 264. Washington, DC: The National Academies Press. doi: 10.17226/10350.
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1982 to 45 percent in 1999, or from 5 to about 7 hours per day (Schrank and Lomax 2001, 17). Again, very large urban areas fared worse.

Congestion measures that focus on the driver and self-reported travel surveys instead of on facility-based measures, such as highway capacity and traffic volumes, paint a somewhat more favorable picture of congestion trends. For example, data from the Nationwide Personal Transportation Survey (NPTS) indicate that average commute trips by private vehicle were 3 miles longer in 1995 than in 1983 in metropolitan statistical areas (MSAs).27 However, average commute times were only 2.9 minutes longer in 1995 than in 1983, with average trip times being nearly 21 minutes in 1995 (see Figure 2-3). These results are not much different from the averages found in the TTI study when travel time changes between 1982 and 1999 were compared for 47 of the 68 urban areas in the TTI sample. However, the NPTS results show much smaller travel time increases for large MSAs—a 2-minute increase for MSAs with a population of more than 3 million versus a 7-minute increase for the same population size group in the TTI study. Changes in survey methodology and the problems associated with self-reported data may affect the validity of the NPTS results. However, those results may also reflect real behavioral changes in response to congestion—changes in residences, jobs, and job locations. Thus, the driver- and facility-based approaches to measuring congestion may simply measure different aspects of the congestion problem.

Congestion and Air Quality

Several of the most congested metropolitan areas are the most polluted. More specifically, of the 15 top-ranked urban areas on one or both of TTI’s congestion indices, 8 are rated as being in nonattainment for ozone, while 10 are rated as being in nonattainment for at least one of the criteria pollutants (see Table 2-3). Of course, air quality is determined by more than vehicle emissions; meteorology and topography play important roles, as previously discussed. To the

27

Except in the New England states, where MSAs consist of towns and cities, an MSA is defined as a county or group of contiguous counties that contains at least one city of 50,000 inhabitants or more, or “twin cities” with a combined population of at least 50,000. In addition, contiguous counties are included in MSAs if, according to certain criteria, they are socially and economically integrated with the central city (Hu and Young 1999, G-9).

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Suggested Citation:"Chapter 2 - Context of the CMAQ Program." Transportation Research Board. 2002. The Congestion Mitigation and Air Quality Improvement Program: Assessing 10 Years of Experience -- Special Report 264. Washington, DC: The National Academies Press. doi: 10.17226/10350.
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FIGURE 2-3 Private-vehicle trip lengths and travel times in MSAs, 1983, 1990, 1995. (Data are from the 1995 NPTS.)

extent that motor vehicle emissions contribute to poor air quality, however, congested travel plays a role.

Tailpipe emission rates and thus air quality are linked to congestion in a complex way. The distribution of vehicle speeds and accelerations28 in traffic varies by type of road facility and amount of traffic volume to produce potentially large variations in emission levels (TRB 1995, 99). Emission levels vary in a nonlinear manner with vehicle speed and acceleration. Generally speaking, at the very low

28

As vehicle speeds increase, higher loads are placed on engines, increasing emissions. Sharp accelerations contribute particularly to CO and VOC emissions by causing a vehicle to operate in a fuel-rich mode. The air/fuel ratio, controlled by the fuel injection system, or by a carburetor on older vehicles, is the most important variable affecting the efficiency of catalytic converters and thus the level of tailpipe emissions (TRB 1995, 42). Sharp accelerations that command fuel enrichment have little effect on NOx emissions, which are highest under fuel-lean conditions (TRB 1995, 42).

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Suggested Citation:"Chapter 2 - Context of the CMAQ Program." Transportation Research Board. 2002. The Congestion Mitigation and Air Quality Improvement Program: Assessing 10 Years of Experience -- Special Report 264. Washington, DC: The National Academies Press. doi: 10.17226/10350.
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TABLE 2-3 Air Quality Status of Congested Urban Areas

Urban Area

Population (thousands)

Rank on TTI Congestion Rating

Air Quality Status (Areas in Nonattainment)

TRI

TTI

Los Angeles, CA

12,600

1

1

Extreme ozone; serious CO; serious PM10

San Francisco–Oakland, CA

4,025

2

3

Ozone (unclassified)

Seattle-Everett, WA

1,995

3

2

 

Washington, DC–MD–VA

3,490

4

4

Serious ozone

Chicago, IL–Northwestern IN

8,085

5

7

Severe ozone

San Diego, CA

2,700

5

9

Serious ozone

Boston, MA

3,020

7

4

 

Portland–Vancouver, OR–WA

1,490

8

8

 

Atlanta, GA

2,860

9

10

Serious ozone

Las Vegas, NV

1,260

9

16

Serious CO

Denver, CO

1,860

11

11

Serious CO; moderate PM10

Houston, TX

3,130

12

11

Severe ozone

New York, NY–Northeastern NJ

16,430

13

16

Severe ozone; moderate CO

Miami–Hialeah, FL

2,100

13

14

 

Detroit, MI

4,020

15

13

 

Note: EPA classifications of nonattainment areas as of July 20, 2000. TRI = travel rate index; TTI = travel time index (see text for definitions); CO = carbon monoxide; PM10 = particulates between 2.5 and 10 micrometers and less than 2.5 micrometers in mean aerodynamic diameter. Population data are for urbanized areas; only developed land with a density of greater than 1,000 persons per square mile is included in the boundary.

Source: Schrank and Lomax (2001, Tables A1 and A2).

speeds characteristic of congested conditions, stop-and-start traffic, punctuated by vehicle accelerations and decelerations, contributes to high emission levels. Vehicle emissions are lowest in moderate speed ranges, at which vehicle speeds are more uniform and traffic is moving smoothly. At higher speeds, emission levels again rise, reflecting engine load from aerodynamic drag and high-speed accelerations from merging maneuvers on freeways, as well as lane-changing and passing behavior on both freeways and high-speed arterial roads (TRB 1995, 116).

These relationships are well illustrated in the most recent version of the model used by EPA to estimate vehicle emission rates—

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MOBILE6. Speed correction factors (SCFs) provide a way of adjusting vehicle emissions for the effects caused by differences in engine performance and driving behavior, including average speeds, aggressive driving (i.e., with sharp accelerations), and driving on different highway facilities (Brzezinski et al. 1999, 1).29 Results for several pollutants—hydrocarbons,30 CO, and NOx—are available for two major road types (freeways, and arterials and collectors); two different emission standards that are proxies for different vehicle model years;31 and average speeds, ranging from 2.5 mph (4 km/h) to 65 mph (104 km/h) for gasoline-fueled passenger vehicles and light trucks (Brzezinski et al. 1999, 8, 20).32

Graphing SCFs by average vehicle speed for normal-emitting, recent-model-year vehicles illustrates the patterns discussed previously. For VOCs, CO, and NOx, SCFs are highest at very low average vehicle speeds [i.e., below an average speed of about 15 to 20 mph (24 to 32 km/h) for freeways and of about 30 mph (48 km/h) for arterial and collector roads], indicating high vehicle emission rates (see Figures 2-4 and 2-5). For freeways, SCFs tend to flatten out between average speeds of 20 and 35 mph (32 and 56 km/h). At average speeds above 35 mph (56 km/h), SCFs for freeways start to rise again but do not regain the levels reached at average speeds

29

In MOBILE6, SCF is defined as the ratio of the predicted emissions at any average speed to the predicted emissions at 19.6 mph (31.4 km/h) for the same vehicle traveling either on freeways or on arterial and collector roads (Brzezinski et al. 1999, 20). To estimate emissions at a desired speed, predicted emissions at 19.6 mph are multiplied by the appropriate SCF.

30

Results are available for total hydrocarbons and for nonmethane hydrocarbons, denoted as VOCs in this report.

31

Results for Tier 0 emission standards, which applied to vehicle model years 1981 through 1993, include both normal- and high-emitting vehicles. Results for Tier 1 standards, which began with model year 1994 and are currently in effect, include only normal-emitting vehicles (NRC 2000, 24).

32

There are no freeway data for speeds below 13.1 mph (21 km/h) and no arterial/ collector data for speeds above 24.8 mph (39.7 km/h). Above 30 mph (48 km/h), the results for average speed and emission levels for freeways converge with those for arterial and collector roads (Brzezinski et al. 1999, 12–13). Below 7.1 mph (11.4 km/h), the effect of average speed on emissions is assumed to be the same for freeways and arterial/collector roads; between 7.1 and 13.1 mph, freeway emissions are calculated by linear interpolation (Brzezinski et al. 1999, 15). At idle, emissions are assumed to be the same as those that occur at an average speed of 2.5 mph (4 km/h) (Brzezinski et al. 1999, 2).

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Suggested Citation:"Chapter 2 - Context of the CMAQ Program." Transportation Research Board. 2002. The Congestion Mitigation and Air Quality Improvement Program: Assessing 10 Years of Experience -- Special Report 264. Washington, DC: The National Academies Press. doi: 10.17226/10350.
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FIGURE 2-4 Speed correction factors from MOBILE6 for freeways by average speed (mph) for Tier 1 normal-emitting gasoline-fueled passenger vehicles and light trucks. [Source: Brzezinski et al. (1999, 53).]

below 15 to 20 mph (24 to 32 km/h). For arterial and collector roads, SCFs decline more gradually as average speeds increase, up to nearly 30 mph (48 km/h), where they flatten out briefly. There are no separate data for arterials and collectors above average speeds of 30 mph (48 km/h). Emission rates of PM10 as a function of average speed are not as well established as rates for the other pollutants. Industry data suggest that diesel PM exhaust emissions follow the same trend as VOCs up to average speeds of about 50 mph (80 km/h); PM10 emission levels at higher speeds are not well understood (TRB 1995, 92).

In summary, the relationship between congestion and vehicle emissions is complex. The amount of emissions from vehicles traveling under congested conditions depends on the distribution of

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Suggested Citation:"Chapter 2 - Context of the CMAQ Program." Transportation Research Board. 2002. The Congestion Mitigation and Air Quality Improvement Program: Assessing 10 Years of Experience -- Special Report 264. Washington, DC: The National Academies Press. doi: 10.17226/10350.
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FIGURE 2-5 Speed correction factors from MOBILE6 for arterial and collector roadways by average speed (mph) for Tier 1 normal-emitting gasoline-fueled passenger vehicles and light trucks. [Source: Brzezinski et al. (1999, 54).]

vehicle operating speeds and accelerations, and the relations are nonlinear. For all pollutants, it appears that emission levels are highest at very low speeds, are moderate in the midspeed ranges, and rise again at high speeds. These patterns suggest that projects designed to relieve highly congested stop-and-start traffic will reduce emissions, at least in the short term. However, congestion relief projects must be selected carefully to ensure that traffic speeds do not become so high that emission levels again increase.

Contribution of CMAQ to Congestion Mitigation

CMAQ Projects and Congestion Relief

The CMAQ legislation and regulations clearly prohibit projects that expand highway capacity for single-occupant vehicle (SOV) travel

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(e.g., the addition of general-purpose lanes to an existing facility), even if they relieve congestion. However, as Table 2-4 shows, there are several CMAQ-eligible project categories that directly address congestion relief. Many of these projects fall under the category of traffic flow improvements and include traffic signalization projects, intersection improvements, and certain intelligent transportation systems measures (e.g., electronic toll collection systems). The primary objective of these projects from a congestion perspective is to improve traffic efficiency by alleviating recurring congestion. Other projects, such as construction of high-occupancy vehicle (HOV) lanes, carpool and vanpool programs, and demand management programs (such as employer trip reduction programs)—to the extent that they encourage higher vehicle occupancies—can also relieve recurring congestion and improve traffic flow. Traffic management centers and incident removal programs are CMAQ-eligible as well; these projects are focused primarily on nonrecurring congestion. Finally, although a

TABLE 2-4 Examples of CMAQ-Eligible Projects That Provide Congestion Relief and Their Effects

CMAQ-Eligible Project Type

Effects on Congestion

Type of Trip Affected

Traffic flow improvements

Direct

 

Traffic signalization

Recurring delays

All trips

Intersection improvements

Recurring delays

All trips

ITS measures

Recurring delays

All trips

Traffic management centers

Recurring delays

All trips

HOV lanes

Recurring delays

Work trips

Shared ride

Direct

 

Carpool and vanpool programs

Recurring delays

Work trips

Related parking programs

Recurring delays

Work trips

Demand management

Direct

 

Trip reduction measures

Recurring delays

Work trips

Flexible work hours

Recurring delays

Work trips

Traffic flow improvements

Direct

 

Traffic management centers

Nonrecurring delays

All trips

Incident management programs

Nonrecurring delays

All trips

Transit projects

Indirect, recurring delays

All trips

Bicycle and pedestrian projects

Indirect, recurring delays

All trips

Note: ITS = intelligent transportation systems; HOV = high-occupancy vehicle.

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×

less direct approach, transit, bicycle, and pedestrian projects may also help mitigate highway congestion to the extent that they encourage trips to shift from automobiles to other modes.

Many CMAQ-eligible congestion relief strategies are focused on work trips (see Table 2-4). Work trips are a major source of traffic volume during peak hours and have a higher valuation than other trip types in terms of travel time, but work trips account for only part of total trip taking. The 1995 NPTS revealed that trips to and from work represented about one-fifth of all person-trips using weighted NPTS data (Hu and Young 1999, 17). When trips made as part of a work trip (e.g., work to supermarket) were included, the number of work trips rose to approximately 30 percent, also using the weighted NPTS data.33 In addition, most CMAQ-eligible strategies represent an attempt to change traveler behavior through voluntary, nonmarket approaches. Price-based strategies, such as parking pricing and congestion pricing, have been found to provide stronger incentives for desired behavioral change (Apogee 1994, ii). Some market-based approaches, such as fare and fee subsidies for transit, carpools, and vanpools, are CMAQ-eligible to encourage greater use of alternative travel modes (FHWA 1999, 18). Other pricing strategies, such as congestion pricing, are not explicitly eligible; however, demand for these uses of CMAQ funds is small because such measures are frequently unpopular and have not been widely implemented.

Induced Traffic

In assessing the final outcome of projects aimed at relieving congestion, an important complication is the need to account for resulting changes in travel behavior. As travel times are improved on a facility, it is natural for travelers and potential travelers to adjust to the facility’s increased attractiveness. Such adjustments are likely to include shifts in the time of day of trips and may also include changes in route or mode. For example, in a city where several major arterials and a rail line serve an employment area, relieving bottlenecks on one arterial

33

The data represented all trips of less than 75 miles for all purposes and all days of the week.

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will probably divert some traffic from other arterials and may also cause some rail commuters to choose to drive instead. People who previously timed their trips inconveniently to avoid the worst congestion may now decide to travel closer to peak hours. And some new trips may be made just because it is more convenient to do so than before.

Over a long enough time period, changed conditions may also affect land use patterns and vehicle fleets in a way that generates new traffic. For example, building a new highway through a previously undeveloped area is well known to attract development to the area unless this is rigorously excluded by zoning. As a more subtle example, improved conditions on a commuter highway may cause some families to buy a second car for commuting purposes; doing so will probably then increase their nonwork trips, even on roads far removed from the improvement being analyzed.

Such shifts can also occur when a project attracts traffic away from a roadway by applying some incentive. For example, when a new rail line or carpool lane diverts peak-hour traffic from a particular expressway, new traffic is likely to shift to that expressway from some or all of the sources just mentioned. The same is true of telecommuting or other trip reduction policies.

Whatever the source of behavioral shifts, the story does not end with simply calculating the traffic from a first-round prediction of improved roadway conditions. The new traffic undoes some of the improvement that would otherwise take place; this in turn reduces the incentive for changing travel behavior. Only by simultaneously modeling travel behavior and congestion formation can the net result be predicted. The net change brought about by such simultaneous adjustments on the facility in question is called induced travel, induced traffic, or induced demand.34

It is common for evaluations conducted during project planning to account for some but not all sources of induced traffic. Conventional

34

Some analysts restrict the term “induced travel” to change resulting from movement along a short-run demand curve, and use the term “induced demand” to represent long-run changes resulting from a shift in that short-run demand curve (Lee et al. 2000, B-4). Although it is hazardous to use the terms “short” and “long” because the time spans for these shifts may overlap, “short-run” generally refers to changes that can be made without altering the capital stock, whereas “long-run” changes would result from alterations in the vehicle fleet or land use patterns.

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traffic models usually take account of route shifts, but may or may not consider changes in modes and times of travel. Newly generated trips often are not estimated. When the models used to analyze a project incorporate induced travel, they can account for the resulting loss of first-round benefits on the facility in question, as well as any additional gains or losses of benefits on other facilities.

Understanding induced travel is necessary for complete analysis of both the air quality and congestion relief objectives of CMAQ projects. For air quality analysis, it is especially critical to distinguish between shifts that do or do not generate new motor vehicle traffic, although shifts of traffic from other locations or times of day, even if they do not change total trips, VMT, or emissions, can also affect air quality. For congestion relief analysis, it is critical to know whether induced traffic occurs as a result of diversion from other congested facilities. If traffic diversion takes place, the analysis must consider the congestion benefits on those other roads.

Because of the conceptual complexity of the simultaneous determination of travel behavior and congestion, there is considerable confusion regarding the interpretation of induced traffic. Opinions range from its having negligible importance to its completely undermining any hoped-for congestion benefits.35 As noted below, the empirical evidence greatly narrows this range. In any case, it is useful to recognize that the existence of induced travel is simply an application of the basic economic principle of downward-sloping demand curves. When the first-round effects of any project reduce travel time on a facility, the cost of travel on that facility to users and potential users is reduced, resulting in more use.36 What makes the situation more complicated is the simultaneous adjustment of congestion, as

35

It is even theoretically possible for more than 100 percent of the first-round benefits to be eliminated by induced demand if the diversion comes from a transit system subject to increasing returns to scale, as in the “Downs-Thomson paradox” described by Arnott and Small (1994).

36

The amount of new travel demanded depends on the elasticity of demand, a measure of the responsiveness of the quantity demanded to changes in the price (i.e., the ratio of the percent change in the quantity demanded to the percent change in the price of the good) (Lee et al. 2000). If travel demand is elastic, traffic volumes will increase more than if travel demand is relatively inelastic. Each of the many mechanisms causing travel shifts may have a different demand elasticity.

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described above. Only by considering at the same time both the supply and demand mechanisms can the final outcome be predicted.

A large literature has been produced by those attempting to measure the size of induced travel effects.37 While there is ongoing debate over the details, the empirical evidence suggests that these effects are significant and need to be incorporated in any complete assessment of the results of congestion relief measures.

FUTURE PROGRAM DIRECTION

The context within which the CMAQ program operates has changed since the legislation was enacted in 1991 and is likely to continue to do so. This changing context has important implications for the future direction of the program.

Emerging Knowledge About Critical Pollutants

Knowledge about key pollutants and their health effects has changed considerably during the life of the CMAQ program. Since the program was enacted, CO has diminished in importance as a critical pollution problem in many metropolitan areas. Significant progress has also been made in the past decade toward attainment of the ozone standard, most notably in the South Coast Air Basin that includes the Los Angeles metropolitan area.38 However, NOx continues to be a problem for conformity determinations in the South Coast Air Basin and also in such metropolitan areas as Houston and Washington, D.C.

At the same time, as discussed earlier in this chapter, other pollutants, such as PM and air toxics, have become of increasing concern as knowledge about their adverse health effects has grown. This has

37

See TRB (1995, Chapter 4 and Appendix B) and Cervero and Hansen (2000) for critical reviews of the key literature. See also the February 1996 volume of Transportation (Coombe 1996), a special issue devoted to the topic of induced travel; Cohen (1998); Fulton et al. (2000); Barr (2000); papers from the 79th TRB Annual Meeting, including Noland and Cowart (2000) and Chu (2000); and the discussion of demand elasticities embedded in the VMT forecasts of the Highway Economic Requirements System model used by FHWA to estimate cost-beneficial highway investments (FHWA and FTA 2000, 7-12–1-13; Lee et al. 2000).

38

EPA shows a downward trend for all the criteria pollutants in the Los Angeles–Long Beach MSA from 1990 through 1999 (EPA 2001a, 205).

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certainly been the case for PM. In 1997 EPA issued new standards to regulate fine particles on the basis of epidemiological studies that found a close correlation between ambient particulate matter concentrations and increased mortality and illness from cardiac and pulmonary respiratory disease. A subsequent intensive research initiative established a more definitive causal relation between exposure levels and adverse health effects (HEI Perspective 2001).39 Much remains to be done, however, to understand the underlying mechanisms more precisely. Current research is focused on characterizing the chemical and physical nature of fine particle emissions and their transformation in the atmosphere, and the levels and chemical composition of exposure in the general population and in specific microenvironments (HEI 1999).40

Work is also under way to link atmospheric concentrations of fine particles to their sources, with particular emphasis on the contribution of exhaust from diesel vehicles.41 Although tailpipe emissions from highway vehicles represent a small share of directly emitted PM on a national basis, they account for a substantially higher proportion of longer-lived atmospheric concentrations of fine particles in urban areas, for example, up to 40 to 50 percent in the Denver and Los Angeles metropolitan areas, as previously noted. Heavy-duty diesel trucks and buses are the major source of PM emissions from highway vehicles (Figure 2-2). As the implementation schedule for the new EPA standards for PM2.5 and the nonattainment area designa-

39

A newly published study (Pope et al. 2002) has established that long-term exposure to combustion-related fine particulate air pollution is an important environmental risk factor for cardiopulmonary mortality and significant increases in lung cancer mortality. The associations between fine particulate air pollution and cardiopulmonary and lung cancer mortality are observed even after controlling for cigarette smoking, body mass index values, diet, occupational exposure, and regional and spatial differences.

40

EPA, state and local air pollution agencies, the Health Effects Institute, the U.S. Department of Energy, the Coordinating Research Council, the American Petroleum Institute, and vehicle and engine manufacturers are all currently sponsoring research in these areas.

41

The work is being conducted at several of the EPA-funded PM Centers and EPA-funded PM Supersites. The latter are charged with characterizing PM, supporting health effects and exposure research, and using state-of-the-art testing methods to conduct and evaluate comprehensive measurements of airborne gases and particles.

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tions are finalized, changes in the focus of the CMAQ program may be required to recognize this important pollutant source.

Air toxics are also regulated under the Clean Air Act, but have not been a focus of the CMAQ program. Nearly 200 pollutants have been identified as toxic air contaminants that derive from a broad range of sources.42 In 1998 California identified particulate emissions from diesel exhaust as a toxic air contaminant and potential carcinogen. The state has launched an aggressive program to develop appropriate control strategies for both new and existing diesel-fueled engines and vehicles.43 As the underlying science advances, the CMAQ program could also direct more attention to heavy-truck, bus, and freight projects focused on reducing diesel exhaust. In sum, to ensure that the CMAQ program remains effective and relevant in mitigating the future air quality impacts of transportation sources, adaptations to accommodate changing ambient air pollutant trends and the priorities that emerge from new research findings and the next generation of human exposure assessments must be considered.

Future Trends in Mobile Source Pollution

The primary factors that will affect future levels of highway vehicle emissions include the introduction of new emission control technologies in response to more stringent new-vehicle emission standards, use of cleaner-burning fuels, fleet turnover, and growth in VMT. The first three factors will tend to decrease the future benefits of many CMAQ-eligible TCMs, while growth in VMT will tend to increase future benefits. For example, once the latest round of light-duty vehicle emission standards (Tier 2) have been fully implemented in 2009, exhaust emission standards for CO, VOCs, and NOx will be

42

Primary emissions from motor vehicles and other combustion sources are highly complex mixtures containing many hundreds of organic and inorganic constituents of gaseous and solid material. Hazardous air pollutants in gaseous state include benzene, 1,3-butadiene, and formaldehyde; volatile and semivolatile organic compounds that are precursors to ozone; organic aerosols; and other hazardous secondary air pollutants, such as formaldehyde, acetaldehyde, and nitrated polycyclic aromatic hydrocarbons. Many organic compounds are emitted at elevated temperatures, forming ultra-fine and nuclei-range particles.

43

See the California Air Resources website (http://www.arb.ca.gov) for more information on California’s Diesel Risk Reduction Program.

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TABLE 2-5 Federal Exhaust Emission Standards for Light-Duty Vehicles

Model Year

Durability Requirement (miles)

CO (g/mi)

Total Hydrocarbons (g/mi)

NOx(g/mi)

Precontrola

 

84

10.6

4.1

1970–1971a

50,000

34 (59)

4.1 (61)

1972

50,000

39 (53)

3.4 (68)

1973

50,000

39 (53)

3.4 (68)

3.0 (27)

1975–1976

50,000

15 (82)

1.5 (86)

3.1 (24)

1977–1979

50,000

15 (82)

1.5 (86)

2.0 (51)

1980

50,000

7.0 (92)

0.41 (96)

2.0 (51)

1981–1993 Tier 0

50,000

3.4 (96)

0.41 (96)

1.0 (76)

1994–2003 Tier 1

50,000

3.4 (96)

0.41 (96)

(0.25)b (98)

0.4 (90)

 

100,000

4.2 (95)

0.31b (97)

0.6 (85)

2004–2009 Tier 2

100,000

4.2 (95)

0.09b (99)

0.07 (98)

Note: Percentage decreases from precontrol levels are in parentheses.

a Standards are adjusted to current test procedures.

b Emission standards were originally written for total hydrocarbons and later for nonmethane hydrocarbons or VOCs as denoted by this footnote.

Source: Adapted from NRC (2001b, 27).

95, 99, and 98 percent lower, respectively, than precontrol emission rates (see Table 2-5).44 The introduction of on-board diagnostic (OBD) technologies as a new approach to vehicle inspection and maintenance (I&M) represents a technological innovation for monitoring the performance of vehicle emission control equipment (NRC 2001b, 12).45 All light-duty vehicles built after 1996 are equipped with the OBDII system, and states are required by EPA to start phasing in OBD checks starting in 2002 (NRC 2001b, 97). OBDII has the potential to ensure that vehicles will continue to operate cleanly as

44

Current (Tier 1) vehicle exhaust emission standards are already 95, 97, and 85 percent lower, respectively, than precontrol emission rates (see Table 2-5).

45

Current OBD technology provides rapid verification of the operation of both exhaust and evaporative emission control components but does not measure emissions directly. It alerts motorists to potential problems by illuminating a malfunction indicator light and provides mechanics with diagnostic information about the source of the malfunction (NRC 2001b, 12).

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they age, and may encourage manufacturers to produce more durable emission control systems. Current experience is too limited, however, to know how OBD will function over the lifetime of a vehicle; perhaps more important, how drivers will heed the malfunction warnings, particularly when vehicles are no longer under warranty; and how effective OBD checks will be, especially as a substitute for more traditional I&M tailpipe testing (NRC 2001b, 12).

As noted earlier, in the coming decades, as cleaner vehicles become a larger share of the fleet and as OBD systems help reduce in-use emissions, the pollution reduction benefits of many TCMs will be lower than those derived during the past decade. For example, traffic flow improvements that are beneficial in reducing high levels of CO and VOCs in congested traffic may have less value. That having been said, the relatively slow turnover of the vehicle fleet—the average age of passenger vehicles in 1999 was 8.9 years—and the unknowns regarding the performance of OBD systems mean it will take some time before fleetwide emission levels are affected (Wards Communications 2000, 44).

During the next two decades, high emissions from gasoline-fueled vehicles will come primarily from two sources: (a) heavy engine loads resulting from certain types of driving and (b) high-emitting vehicles. Regarding the first of these, results from dynamic testing of exhaust emissions from properly functioning vehicles show that modern, low-mileage vehicles have low CO, VOC, and PM emission rates during the second phase of the test, which represents relatively nonaggressive driving and fully warmed-up vehicles.46 Emission rates are substantially higher for properly functioning vehicles starting cold47 and during intermittent high-engine-load conditions induced by hard

46

Running exhaust emissions from the second test phase include emissions from the tailpipe or through the crankcase after the vehicle is warmed up and in a stabilized mode. Exhaust emission rates are determined from dynamometer tests using the Federal Test Procedures (FTP). The FTP tests are used to certify new vehicles and to check compliance over time.

47

Cold-start exhaust emissions occur from the time the engine starts, after being off for 1 or more hours for a catalyst-equipped vehicle and 4 or more hours for a noncatalyst-equipped vehicle, until the coolant achieves its nominal operating temperature. Cold-start emissions are incremental emissions that are added to running exhaust emissions.

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accelerations and grades. One sharp acceleration may cause as much pollution as the entire remaining trip (Carlock 1993). High-emitting vehicles are the other major contributors to on-road vehicle emissions. The distributions of emission rates among in-use vehicles are highly skewed, such that a relatively small fraction of high emitters accounts for a disproportionate fraction of total emissions (NRC 2000, 77). This fraction is likely to increase during the next two decades as the Tier 2 emission standards are implemented and absorbed into the vehicle population. TCMs that are focused on these two pollutant sources (e.g., strategies to reduce vehicle cold starts, remote sensing to detect high-emitting vehicles) are likely to have big payoffs.48

Emission standards for heavy-duty diesel engines will also be tightened. Beginning with the 2004 model year, all heavy-duty vehicles will be required to meet an NOx level approximately 80 percent below the initial standard established in 1985 (see Table 2-6).49 PM emission standards will also be significantly tightened starting in model year 2007 (see Table 2-6). A related rule, reducing sulfur in diesel fuel and thereby enabling new diesel engines to run cleaner, is slated to take effect in 2006. As previously discussed, however, much remains to be done to reduce diesel emissions, especially particulates, and this could well become a more important focus area of the CMAQ program.

The impact of cleaner vehicles, however, both diesel- and gasoline-powered, may be retarded by growth in VMT. In the past, travel growth appears to have offset some of the projected gains from stricter vehicle emission standards (TRB 1995, 16).50 The question thus arises of whether metropolitan travel growth and related

48

Remote sensing refers to a method for measuring pollution levels in a vehicle’s exhaust while the vehicle is in use. If OBD systems are effective, they could also prevent vehicles from becoming high emitters.

49

The 2004 standard will be implemented in October 2002 for engine manufacturers, subject to a settlement agreement with EPA concerning the use of devices to defeat emission testing on earlier vehicles (Schimek 2001, 436).

50

For example, when the 1990 CAAA was passed, EPA estimated that gains in tailpipe emissions could be offset by 2002 for CO and VOCs and by 2004 for NOx. Thus, the act mandated measures designed to limit automobile trips in the most severely polluted areas and required strict monitoring of VMT growth in less severe nonattainment areas.

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TABLE 2-6 Federal Exhaust Emission Standards for Heavy-Duty Diesel Engines

Model Year

NOx

PM, Heavy Duty

PM, Urban Bus

1985

10.7

NA

NA

1988

10.7

0.60

0.60

1990

6.0 (44)

0.60

0.60

1991

5.0 (53)

0.25 (58)

0.25 (58)

1993

5.0 (53)

0.25 (58)

0.10 (83)

1994

5.0 (53)

0.10 (83)

0.07 (88)

1996

5.0 (53)

0.10 (83)

0.05 (92)

1998

4.0 (63)

0.10 (83)

0.05 (92)

2004 (2002)

2.0 (81)

0.10 (83)

0.05 (92)

2007–2010

0.2 (98)

0.01 (98)

0.01 (98)

Note: Standards are in grams per brake-horsepower hour; NA = not applicable. Percentage decreases from precontrol levels are in parentheses.

Source: Adapted from Schimek (2001, 437).

congestion are likely to worsen in the future. Arguing for a slowing in the rate of VMT growth are findings that travel effects due to the entrance of women into the workforce have largely been absorbed, that the ratio of vehicles to licensed drivers is 1 to 1 (Hu and Young 1999, 9), and that a growing proportion of the population of older motorists drive less.51 FHWA, for example, forecasts an average annual urban VMT growth rate of 2 percent for 1998 through 2017, a sharp decline from the 3.2 percent average annual rate of growth in urban travel between 1987 and 1997 (FHWA and FTA 2000, 2-10, 9-3). More flexible work policies and electronic advances that enable working at home or from a nearby telecommuting center may also limit work trips and peak-period travel, although there is some evidence that telecommuting can result in an increase in non-commute-related personal vehicle trips (Koenig et al. 1996). More essential, telecommuting may change the time of day and location of travel, with important

51

However, there is evidence that older drivers are driving more than in the past. For example, in 1995 older drivers took more trips and drove more than their corresponding cohorts in 1990 (Hu and Young 1999, 49).

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effects on emissions.52 The results of the NPTS, which show relatively constant average commuter trip times over a period of several years, suggest that in the longer run, households respond to increasing VMT and higher levels of congestion by moving farther away from metropolitan centers. As jobs follow people, commute times are kept relatively constant (TRB 1994, 114–115).

On the other hand, arguing for continuing growth in congestion for many metropolitan areas are projected increases in population and income—major determinants of travel in a region (Hansen et al. 1993, 6–29). Thus a definitive judgment about growth in VMT and congestion is simply not possible on the basis of the available data (Meyer 1994, 58). Both are likely to persist in many metropolitan areas, but some regions may see a slowing in the rate of travel growth, which in turn would decrease the benefits of traffic-related CMAQ strategies.

Advances in Analytic Methods for Estimating Strategy Effects

Estimating the pollution reduction potential of many CMAQ-eligible strategies may become easier in the future as new measurement tools become available and more appropriate models are developed. For example, although it may never be possible to measure changes in concentrations of important regional pollutants, such as ozone and PM, due to a particular project, methods for measuring changes in vehicle emissions at the tailpipe and human exposure levels are being developed. Remote sensing of vehicle exhaust emissions is already possible, as are remote readings of exhaust measurements (NRC 2001b, 103).53 A new generation of real-time instruments and sophisticated experimental designs has also been developed for characterization of human exposure to PM2.5 and gaseous pollutants in many micro environments, including a wide range of in-vehicle and

52

For example, travel at midday or in the afternoon under noncongested conditions and in locations removed from a central city may be less polluting than travel in the morning peak-period commute.

53

CO emissions can be measured reliably using remote sensing techniques. Less-certain results are available for VOCs and NOx, and measurement of PM is an important research priority. Attention to quality assurance and quality control is essential (NRC 2001b, 116–117).

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indoor atmospheres affected by the penetration of vehicle-related emissions (Monn 2001).54

New models are also under development that will be more appropriate for estimating the emission effects of many small-scale CMAQ projects. Future generations of mobile emission models will predict emissions as a function of vehicle operation, such as idle, steady-state cruise, and various levels of acceleration and deceleration. Two modal modeling approaches currently under development are the Comprehensive Modal Emissions Model (CMEM) (Barth et al. 2000) and the Mobile Emissions Assessment System for Urban and Regional Evaluation (MEASURE) (Guensler et al. 1998).55 USDOT, EPA, and the Department of Energy are sponsoring the development of a suite of integrated analytical and simulation models and supporting databases for transportation and air quality analysis (TMIP 1999). Known as the TRansportation ANnalysis and SIMulation System (TRANSIMS), the modeling system pairs data from a second-by-second traffic simulation model with a modal emission model (CMEM) to derive microscale-level emission estimates from changes in traffic signalization and other traffic operational changes; inputs are also provided for air quality modeling at appropriate temporal and geographic scales. The application of these new models should provide for more accurate microscale assessments of the travel-related effects (e.g., changes in traffic flows, speeds), emission effects, and possibly even air quality impacts of many CMAQ projects.

CONCLUSIONS AND IMPLICATIONS FOR PROGRAM EVALUATION

Transportation is one of the many sources of poor air quality in the United States. The primary goal of the CMAQ program is to reduce pollution from motor vehicles. Program funds are targeted to areas with the worst air quality (nonattainment and maintenance areas).

54

Other references on exposure assessment of air pollutants include Rodes et al. (1998), Long et al. (2000), Moosmuller et al. (2001), and Janssen et al. (1998).

55

The modal model under development at the University of California, Riverside, by Barth et al. is based on 300 vehicles tested under a variety of laboratory driving cycles. The modal approach under development at the Georgia Institute of Technology is a modal emissions model based on geographic information systems, using statistical analysis of historical laboratory and instrumented vehicle data.

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Ozone and its precursors and CO are the primary pollutants of concern, reflecting the critical pollution problems at the time the 1990 CAAA and the 1991 ISTEA were passed. Projects aimed at reducing PM10 emissions became explicitly eligible for CMAQ funding when TEA-21 reauthorized the program, but particulates are not reflected in the funding formula.

A region’s particular air quality problems and conformity requirements can influence how program funds are deployed. For example, nonattainment areas with significant air quality problems often look to CMAQ to help fund TCMs or other eligible projects for which credit can be taken toward meeting rate-of-progress requirements or SIP commitments. The type of local air quality problem may affect project choices as well. For example, areas having NOx problems may not undertake certain traffic flow improvements that would significantly increase vehicle speeds, even if such projects are CMAQ eligible, because those improvements can exacerbate ozone formation.

CMAQ program regulations require that states report annually, by the relevant affected pollutants, on the potential emission reductions of funded projects. No attempt is made to determine how these projects might affect pollutant concentrations, human exposure levels, or public health. Estimating emission reductions with any degree of certainty is often difficult because the available emissions models for making such projections, or their inputs, are not well suited to the purpose. The models were developed to assess regional emission effects, not to evaluate TCMs, whose impacts are modest and often focused on particular transportation corridors or subregions.

Congestion is a major problem in many large metropolitan areas. Congestion mitigation is another important goal of the CMAQ program; however, the legislation authorizing the CMAQ program prohibits spending on certain traditional congestion relief projects. For example, projects to provide new capacity for SOV travel, such as the addition of general-purpose lanes to an existing facility or a new highway at a new location, are ineligible even if those projects could help alleviate congestion. The reason for this is that such projects are viewed as not supporting the CMAQ program’s primary goal of reducing motor vehicle emissions because they encourage vehicular travel. Nor is it likely that many of these projects would meet con-

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formity requirements, another program requisite. Nevertheless, CMAQ funds can be used to support a wide range of other congestion relief strategies.

The context within which the program operates has changed since the program’s inception and will continue to do so. For example, as vehicles become cleaner, some TCMs may become less effective, while other strategies (e.g., vehicle scrappage programs) that target remaining air pollution sources (e.g., high-emitting vehicles) will become more valuable. Moreover, emerging knowledge about the health effects of various pollutants may require some redirection of CMAQ funds when the program is reauthorized. For example, as knowledge about the adverse health effects of particulates and air toxics has grown, projects that address the key transportation-related sources of these pollutants (e.g., heavy trucks and buses) may warrant greater attention. Fortunately, advances in measurement tools and models should make it easier to assess the pollution reduction potential of many CMAQ strategies and may even enable the analysis to be extended to an assessment of project effects on human exposure levels.

This chapter has provided information about the air quality and congestion context within which the CMAQ program operates to help the reader understand how the program has developed, provide perspective on the problems it attempts to address, and highlight some of the key changes that may affect its future direction. In the following chapter, an overview of program operations and spending trends to date is provided.

REFERENCE

Abbreviations

ALA American Lung Association

BTS Bureau of Transportation Statistics

EPA U.S. Environmental Protection Agency

FHWA Federal Highway Administration

FTA Federal Transit Administration

HEI Health Effects Institute

NCHRP National Cooperative Highway Research Program

NRC National Research Council

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TMIP Travel Model Improvement Program

TRB Transportation Research Board

ALA. 2000. Selected Key Studies on Particulate Matter and Health: 1997–2000. Washington, D.C., Sept. 12.

Apogee Research, Inc. 1994. Costs and Effectiveness of Transportation Control Measures (TCMs): A Review and Analysis of the Literature. Washington, D.C., Jan.

Arnott, R., and K. Small. 1994. The Economics of Traffic Congestion. American Scientist, Vol. 82, Sept.–Oct., pp. 446–455.

Barr, L. 2000. Testing for the Significance of Induced Highway Travel Demand in Metropolitan Areas. Volpe National Transportation Systems Center, U.S. Department of Transportation, Cambridge, Mass.

Barth, M., F. An, T. Younglove, G. Scora, C. Levine, M. Ross, and T. Wenzel. 2000. Development of a Comprehensive Modal Emissions Model, Final Report. NCHRP Project 25-11, National Academy Press, Washington, D.C.

Brzezinski, D. J., P. Enns, and C. J. Hart. 1999. Facility-Specific Speed Correction Factors, Draft. M6.SPD.002. EPA420-P-99-002, U.S. Environmental Protection Agency, Aug.

BTS. 2001. National Transportation Statistics 2000. BTS01-01. U.S. Department of Transportation, Washington, D.C., April.

Calfee, J., and C. Winston. 1998. The Value of Automobile Travel Time: Implications for Congestion Policy. Journal of Public Economics, Vol. 69, Issue 1, July, pp. 83–102.

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×

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×

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TRB Special Report 264 - Congestion Mitigation and Air Quality Improvement Program: Assessing 10 Years of Experience recommends that Congress retain the sole federal surface transportation program that funds projects to reduce pollution and traffic congestion in areas that must comply with national air quality standards.

The Congestion Mitigation and Air Quality Improvement (CMAQ) program was enacted as part of the surface transportation legislation authorized in 1991 to provide support for projects that would aid local efforts to meet the strict new federal deadlines imposed by the Clean Air Act Amendments (CAAA) of 1990. CMAQ was included in the reauthorization of surface transportation legislation in 1998 for another 6 years, and funding for this period was set at $8.1 billion. In the 1998 legislation, Congress also requested an evaluation of the effectiveness of the program and the cost-effectiveness of the projects funded by the program.

CMAQ funds are focused primarily on the transportation control measures (TCMs) contained in the 1990 CAAA (with the exception of vehicle scrappage programs, which have not been permitted). TCMs are strategies whose primary purpose is to lessen the pollutants emitted by motor vehicles by decreasing highway travel (for example, bicycle, pedestrian, and some transit projects) and to encourage more efficient facility use (for example, projects focused on ridesharing and on traffic flow improvements, such as signal timing). In addition, CMAQ funds may be used for projects that reduce vehicle emissions directly, such as through vehicle inspection and maintenance programs and purchase of alternative-fueled transit vehicles. In the spirit of the legislation that originally authorized the program, decisions about project selection are made at the local level, usually by or through the local metropolitan planning organization.

After reviewing the limited information available about these types of projects, the committee that evaluated the CMAQ program concluded that, when compared on the sole criterion of tons of emissions reduced per dollar spent, strategies aimed directly at emissions reductions—such as emissions and fuel standards for new vehicles, well-structured inspection and maintenance programs, and vehicle scrappage programs—are more cost-effective than the typical CMAQ TCMs, which tend to depend on changes in behavior. A few behaviorally based TCMs, however, such as pricing and regional ridesharing, compare favorably with vehicle- and fuel-based strategies. The committee recommended that the CMAQ program be continued, in part because it is a "funded" rather than an "unfunded" mandate. The committee also called for a focus of future projects on reductions in emissions with the largest public health consequences and for improved evaluation of project effectiveness.

Special Report 264 Summary

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