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CHAPTER 3. AIR QUALITY OVERVIEW Air quality is important to human health, the vitality of the natural environment, and the quality of life in general. Poor air is of special concern for sensitive populations with potential health issues, such as asthmatics, people with other pulmonary health problems, children, and the elderly. From an environmental justice perspective, there is some evidence that certain ailments exacerbated by poor air quality have a higher incidence rate in minority and low-income populations than in the general population. Poor air quality can also degrade the natural environment by decreasing visibility and damaging animals, crops, vegetation, and buildings. Although quality of life is subjective, poor visibility, dust, odors, and the emotional impacts of exhaust smells have a negative impact on nearly everyone. In this chapter, we focus on air quality issues related to human activity, but natural sources of pollutants also can worsen an area's air quality problems. The important point is that the worse the general air quality in an area is due to whatever sources, the greater the harm that additional emissions are likely to bring about. Transportation projects can affect ground-level air quality (microscale or "hot-spot") due to increased concentrations of carbon monoxide caused by idling vehicles and congestion or to particulate matter caused by diesel engine emissions and stirred dust and dirt that become airborne due to disturbance by vehicles. Environmental justice assessment of micro-scale air quality impacts is a straightforward process of combining information about micro-scale effects and demographics for affected areas. While greenhouse gases and particulate emissions may affect regional air quality, their distribution is generally assumed to be uniform across large areas. The typical regional air quality assessment methods do not provide geographic distinctions. Therefore, environmental justice assessment of regional air quality is less informative than assessment of micro-scale issues unless experimental, resource-intensive methods are used. In cases where protected populations are very concerned about air quality, it may not be enough to assess the impact from transportation system changes. Because it is the cumulative exposure to all air pollutants that affect human health and quality of life, many environmental justice proponents have recommended evaluating the distribution of pollutants from all sources. This form of assessment can be time consuming and resource intensive due to the large amounts of monitoring equipment and data required to develop an understanding of cumulative ground-level concentrations. STATE OF THE PRACTICE The most common techniques being used to assess air quality are described in this section along with examples of successful environmental justice assessments. We discuss air quality 59

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regulation, regional air quality assessment, micro-scale air quality assessment, and mitigation strategies. Air quality has been regulated for many years, and transportation policies, programs, and projects must meet comprehensive federal and state standards. The current state of the practice is to identify both specific sites (i.e., hot spots) and regions (usually large metropolitan or multi- county areas) where these standards may be exceeded and to determine strategies for meeting the standards. Environmental justice assessments most often are performed when air quality standards are not met or would potentially not be met if a proposed project were built. The basic assumption is that, unless the standards are violated, there is no adverse effect to be evaluated for distributive effects to protected populations. Given this assumption, some argue that transportation air quality is not an important environmental justice issue because policies, projects, and programs cannot be implemented if they violate the standards. Many practitioners and community representatives do not accept this argument, however. Proponents of environmental justice argue that protected populations experience a disproportionate level of adverse health effects due to differing levels of exposure and differences in lifestyle, among other factors. There is also a considerable body of evidence indicating that protected population groups tend to live and work closer to sources of air pollution than does the general population (Bullard 1996; Bryant and Mohai 1992). It is beyond the scope of this guidebook to explore this argument fully or to propose alternative air quality standards that would be more protective of protected populations. Instead, the methods presented in this chapter are designed to be used independently of established air quality standards. In this way, practitioners can be responsive to air quality concerns raised by communities that argue they are experiencing adverse effects even when all air quality standards are being met. Air quality regulation Procedures for evaluating air quality primarily are guided by regional pollution control agencies, departments of health, and metropolitan planning organizations (MPOs). These agencies are responsible for monitoring air quality, which includes six common criteria pollutants: ozone (O3), particulate matter (PM), carbon monoxide (CO), nitrogen dioxide (NO2), and sulfur dioxide (SO2). A brief summary of the adverse effects of each pollutant is provided in Table 3-1. State and local agencies monitor air quality to determine if it complies with the National Ambient Air Quality Standards (NAAQS). As directed by the 1970 Clean Air Act, the U.S. Environmental Protection Agency (U.S. EPA) created the NAAQS to protect human health and the public welfare. Primary standards are designed to protect human health, whereas secondary standards protect public welfare. The current primary and secondary standards are provided in Table 3-2. When monitoring indicates that the concentration of one of the five criteria pollutants violates the NAAQS, the air quality status of the region may be changed from "attainment" to "non- attainment." If an area previously in the nonattainment category achieves attainment, it is 60

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Table 3-1. Effects of criteria pollutants Pollutant Description Ozone Ozone can irritate lung airways and cause wheezing, coughing, and pain when (O3) taking deep breaths. It also aggravates asthma and increases susceptibility to diseases such as pneumonia and bronchitis (U.S. EPA 2003a). Particulate matter Of all measured pollutants, PM may be the most detrimental to human health. (PM) PM has been linked to increased mortality rates (Lave and Seskin 1977). Children and seniors with respiratory problems such as asthma are at greatest risk (Schwartz and Dockery 1992). Asthma rates are higher in low-income populations and mortality rates are highest among African Americans (U.S. EPA 1996). Carbon monoxide Exposure reduces the amount of oxygen in the bloodstream (U.S. EPA 1995). (CO) People with heart disease are at greatest risk. Seniors are at risk. Heart disease rates are higher for most African American age groups compared to Caucasians (National Center for Health Statistics 1995). Nitrogen oxides (NOX) NOX reacts with sunlight to create ozone. NOX has been linked to acute respiratory problems (U.S. EPA 1996). Sulfur Dioxide dioxide Primarily emitted by diesel engines, SO2 is a serious irritant to asthmatics, and (SO2) contributes to particulate formation and to acid rain (U.S. EPA 1994a). Table 3-2. National ambient air quality standards Standard Standard Pollutant Statistic value* type Ozone (O3) 1-hour average 0.12 ppm (235 g/m3) Primary & secondary 3 8-hour average 0.08 ppm (157 g/m ) Primary & secondary 3 Particulate (PM10)** Annual arithmetic mean 50 g/m Primary & secondary 3 24-hour average 150 g/m Primary & secondary 3 Particulate (PM2.5)*** Annual arithmetic mean 15 g/m Primary & secondary 3 24-hour average 65 g/m Primary & secondary 3 Carbon monoxide (CO) 8-hour average 9 ppm (10 mg/m ) Primary 3 1-hour average 35 ppm (40 mg/m ) Primary 3 Nitrogen dioxide (NO2) Annual arithmetic mean 0.053 ppm (100 g/m ) Primary & secondary 3 Sulfur dioxide (SO2) Annual arithmetic mean 0.030 ppm (80 g/m ) Primary 3 24-hour average 0.14 ppm (365 g/m ) Primary 3 3-hour average 0.50 ppm (1300 g/m ) Secondary * Parenthetical value is an approximately equivalent concentration. ** Particles with aerodynamic diameters of 10 micrometers or less *** Particles with aerodynamic diameters of 2.5 micrometers or less Source: U.S. EPA 2003. 61

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designated as having "maintenance" status for that particular pollutant. For regions designated as nonattainment areas, state implementation plans (SIP) must be prepared by the responsible agencies. The SIP ensures that no transportation project or policy will result in an increase in regional emissions nor cause a pollutant violation (FHWA 2001). Transportation conformity refers to the coordination of the transportation planning and air quality planning processes. To achieve transportation conformity, Transportation Improvement Programs (TIPs) must be consistent with SIPs. Transportation conformity with the NAAQS only applies to O3, CO, PM, and NO2 non- attainment and maintenance areas. Note that an exceedance of a pollutant does not automatically constitute a violation. For example, CO must exceed the criteria two times in a year to be considered a violation. Nonattainment or maintenance status often results in rules stating that transportation projects must not cause an increase in a specified pollutant or that more stringent analysis procedures must be followed. State and local agencies then must enforce these rules and procedures (FHWA 2001). The models used to determine whether a transportation project or TIP would result in an air quality impact include EPA's MOBILE5 and the new MOBILE6. MOBILE6 was being phased into use nationwide at the time this document was created. These models are used to estimate emission factors for vehicles. Emission factors are the rate at which an average vehicle emits pollutants, usually expressed in grams/mile (moving vehicles) or grams/hour (idling vehicles). Emission factors determined by the MOBILE6 model often are stratified by speed and year. MPOs or state pollution control agencies usually determine the parameters used in the MOBILE6 model for application to a given location. These parameters can include vehicle age, mileage by vehicle type, inspection and maintenance programs, and specific fuel makeup characteristics. The MOBILE6 model output emission factors are incorporated into either or both microscale (hot-spot) and regional analyses. The microscale and regional analyses provide more meaningful results for use in quantifying project impacts. Regional air quality assessments Based on ISTEA and TEA-21 requirements, MPOs develop 20-year plans and 3 to 5-year TIPs. The TIP is a prioritized list of projects for which the MPO will seek FHWA or DOT approval. A regional air quality assessment is conducted to ensure that the TIP is in conformance with the SIP. This evaluation assesses the regional impacts that transportation investments will have on emissions in nonattainment or maintenance areas. Information required to perform a regional air quality assessment includes the following: Estimates of current and future population and employment; Estimates of current and future travel and congestion; Assumptions about current and future background pollutant concentrations; 62

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Transit operating policies and transit ridership and expected future changes in fares and level of service; and Effectiveness of SIP measures that have already been implemented. Regional air quality analyses incorporate travel demand information and emission factors to calculate total regional emissions. Depending on the attainment status for various pollutants and the population in the region, network-based travel demand models, local vehicle miles traveled (VMT) forecasts from the Highway Performance Monitoring System (HPMS), traffic speed and delay estimates, and/or local counts of all traffic in a region are used to evaluate regional air quality. The emission factors must be approved by the U.S. EPA. Currently, MOBILE6 is used to generate emission factors outside California, and the current version of EMFAC (short for emissions factor) is used within California. Regional travel demand models can project VMT and average speed on each roadway link of a road network. Multiplying the link VMT by the emission factor for a given link speed results in the total emissions for the link. The sum of emissions for all links gives a value for total regional emissions. Figure 3-1 provides an overview of the regional conformity assessment process (FHWA 2001). Base Year Highway { Base year HPMS Regional travel to model adjustment performance demand model factors by roadway monitoring system class (HPMS) Off-model post processing Modeled VMT HPMS-to-model HPMS VMT by roadway class VMT adjustment by roadway class Congested speeds HPMS-adjusted VMT by roadway class by roadway class Emissions factors Travel MOBILE computations by roadway class Regional emissions Future Year Future year Modeled VMT Base year Regional travel modeled VMT by growth rate by roadway modeled VMT by demand model roadway class class roadway class Congested speeds Future year Base year by roadway class HPMS-adjusted VMT HPMS-adjusted VMT by roadway class by roadway class Emission factors Emissions MOBILE by roadway class computations Regional emissions Figure 3-1. Regional conformity assessment process Source: FHWA 2001. 63

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Regional analyses focus on estimating emissions of transportation-related pollutants, which include CO, NO2, and volatile organic compounds (VOC). When VOCs interact with NO2 , heat, and sunlight, they form ground-level ozone (O3). Any increase in these pollutants is detrimental to the environment and, depending on the attainment status of the area, an increase could prevent a transportation project from moving forward. Micro-scale air quality assessment Motor vehicles are among the major contributors to criteria pollutant levels. They are the number one source of CO and NO2, the number two source of VOC, the number three source of PM, and the number four source of SO2. In total, highway vehicles and off-highway vehicles generate an estimated 77 percent of all CO emissions in the United States (U.S. EPA 1994b). Because CO is the most prevalent criteria pollutant, microscale analyses often screen for air quality violations by evaluating CO levels. Figure 3-2 provides an overview of the microscale air quality assessment process. This example is based on an approved process for meeting microscale transportation conformity regulations. This is just one example, however, and the process can vary from jurisdiction to jurisdiction. The most frequently used air dispersion models for localized analyses are CAL3QHC or one of the CALINE series models. The model results provide estimated carbon monoxide concentrations at discrete receptors near worst-case intersections. Analyses are performed at intersections because vehicles produce greater emissions when they are idling or traveling at slow speeds. The assumption is that if worst-case intersections do not exceed CO limits, there will be no exceedances for any of the criteria pollutants. The model incorporates the emission factors from the MOBILE6 model, along with intersection operating characteristics such as signal timing, traffic volume, and intersection geometry. Two scenarios must be evaluated to determine transportation conformity: If there are no projected exceedances or violations in the area affected by the project, the project's future effect is compared to the standard because the test is whether the project causes an exceedance of the standard. If there is a projected violation or exceedance in the area affected by the project, the project cannot worsen an existing violation, so a no-build/build comparison is required (FHWA 2001, Section F). For phased projects, it may be necessary to perform a microscale analysis for each significant project phase. This is done to ensure that interim phases do not cause NAAQS violations that might be eliminated once a project is fully implemented. The intent of the microscale analysis is to ensure that transportation system changes, in combination with existing or foreseeable future background concentrations, do not result in NAAQS violations. Although the results of these analyses generally are considered to be reasonably accurate, the highly localized nature of the assessment makes it difficult to directly relate any violation to disparate effects on protected populations. If an air quality impact were 64

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predicted to result from a planned project, the impact would be at discrete receptor locations, usually near a congested intersection. The discrete receptors used for the microscale assessments typically are on sidewalks or beside buildings very near to intersections. Project/intersection description Determine air quality/regulatory objectives Assemble all data pertaining to intersection-related traffic conditions Multiple intersection screening/ranking Individual intersection modeling Rank top 20 Assemble data on traffic, meteorology, by traffic volumes site characteristics, background Calculate LOS Model top 3 based for top 20 on traffic volumes Locate receptors Compute 1-hour peak- Rank by LOS traffic concentration using CAL3QHC LOS = A,B,C LOS = D,E,F Apply persistence factor and background No further analysis required unless in Model top 3 Compare results with top 3 based on based on LOS NAAQS traffic volumes Conformity determination Figure 3-2. Example of a local conformity assessment process Source: FHWA 2001. Mitigation measures Local air quality mitigation measures. If violations of local standards or the NAAQS are predicted to result from a proposed transportation project, mitigation measures would be required. Mitigation measures could include increasing intersection capacity by adding traffic lanes, optimizing signal timing for air quality purposes, or diverting traffic to other locations. It is possible that these mitigation measures could cause impacts themselves. Such impacts could include right-of-way acquisition for additional lanes or an increase in pedestrian conflict areas 65