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Executive Summary THE MOBILE SOURCE EMISSIONS FACTOR (MOBILE) model is a computer model developed by the U.S. Environmental Protection Agency (EPA) for estimating emissions from on-road motor vehicles. MOBILE is used in air- quality planning and regulation for estimating emissions of carbon monox- ide (CO), volatile organic compounds (VOCs), and nitrogen oxides (NOx) and for predicting the effects of emissions-reduction programs.4 Because of its important role in air-quality management, the accuracy of MOBILE is critical. Possible consequences of inaccurately characterizing motor-vehi- cle emissions include the implementation of insufficient controls that en- danger the environment and public health or the implementation of inef- fective policies that impose excessive control costs. Billions of dollars per year in transportation funding are linked to air-quality attainment plans, which rely on estimates of mobile-source emissions. Transportation in- frastructure decisions are also affected by emissions estimates from MOBILE. iThe MOBILE model estimates emissions factors in grams per mile from informa- tion on the emissions characteristics of the vehicle fleet. Combining emissions factors with estimates of vehicle miles traveled produces emissions estimates. Particulate matter and air taxies (hazardous air pollutants) are estimated by the PARTS and MOBTOX models, respectively. Because these models are closely tied to MOBILE, they are discussed in the same context as MOBILE in this report. A new version of this model, MOBILES, is being developed and is expected to be re- leased in the summer of 2000. MOBILE6b is the version currently in use. 1

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2 MODE1/NG MOB!LE-SOURCE EMISSIONS There are numerous complexities involved in estimating and predicting mobile-source emissions from the on-road fleet. The fleet is made up of vehicles with a wide variety of emissions characteristics due to differences in condition, type, and age of vehicles; performance of the emissions-con- trol systems; and fuel composition. Emissions also are affected by local factors, such as meteorological conditions, traffic patterns, and travel ac- tivity. Developing predictions of future emissions requires projections for all of those characteristics. Finally, there is the issue of the spatial and temporal resolution required for the estimates. For example, estimating the effect of a regional emissions inspection and maintenance program would not require emissions estimates to be resolved at the level of detail needed for estimating the effect of an effort to coordinate traffic signals along a major corridor. Since its release more than 20 years ago, MOBILE has been used in- creasingly in regulatory applications. MOBILE is now the central tool used by environmental and transportation agencies to estimate on-road mobile-source emissions and to assess national, state, and local air-quality programs for controlling such emissions. The wide range of mobile-source emissions-control programs assessed with MOBILE varies from national vehicle emissions and fuel standards to local travel demand and conges- tion mitigation measures. This wide range of applications has placed greater demands on the model for accuracy and has opened it up to intense scrutiny. Questions have been raised about MOBILE's capability to evaluate reliably the im- pacts of air-quality-improvement initiatives, such as the vehicle-emissions inspection and maintenance programs and the use of oxygenates in win- tertime gasoline blends. Previous and current versions of the model have been criticized for their lack of adequate documentation on underlying methodologies and data. There has also been criticism by the U.S. General Accounting Office that EPA's policy on peer review had not been fully fol- lowed during the development of current and past versions of MOBILE. In response to a request from Congress, the National Research Council established the Committee to Review EPA's Mobile Source Emissions Fac- tor (MOBILE) Model in October 1998. The committee was charged to eval- uate MOBILE and to develop recommendations for improving the model. The fuB charge to the committee is given in Chapter 1. In carrying out its charge, the committee reviewed the structure and performance of the MOBILE model and considered ways to improve the model. The committee considered MOBILE in the context of its various applications, which include estimating on-road mobile-source emissions and predicting the efficacy of emissions-control strategies. In addition, the committee surveyed developments in other areas of mobile-source emis- sions modeling.

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EXECUTIVE SUMMARY 3 Although the necessary studies for a quantitative assessment of MOBILE's overall accuracy have not been conducted, some studies show that model estimates of emissions and effectiveness of control strategies are significantly different from those occurring in the real world. For ex- ample, studies relying on ambient observations and other field measure- ments indicate that MOBILE is substantially underestimating mobile- source VOC emissions. Such differences lead to questions about the level of accuracy needed for the intended applications of MOBILE. In response, additional testing of vehicles, rigorous evaluation of emissions estimates, model validation, and sensitivity analysis of the model are needed. These are resource-intensive efforts, but they are necessary for providing suffi- cient confidence in the emissions estimates from the model. The committee commends EPA for its response to a number of previous criticisms of the model as it continues to revise MOBILE. In particular, the documentation for MOBILES, EPA's new version of the model to be released in the near future, is greatly superior to that prepared for previ- ous versions of the model. EPA has attempted to "open up" the model de- velopment to users, stakeholders, and other interested parties by holding public workshops, providing detailed documentation, and asking for feed- back. That is a positive step by EPA. MOBILE's capabilities have ex- panded over time, and many improvements have been incorporated into MOBILES. MOBILE-SOURCE EMISSIONS MODELING RECOMMENDATIONS Development of a Toolkit of Models Finding Since its development in 1978, MOBILE has evolved from a tool for esti- mating regional emissions inventories to such uses as determining the conformity of transportation projects with requirements of State Imple- mentation Plans and assessing the emissions impacts of transportation- controT measures. The further the model's application deviates from its original purpose of estimating aggregate regional emissions, the more dif- ficult it becomes to verify the accuracy of its predictions and, as a result, the less appropriate it becomes for air-quaTity management. That finding is not a basis for the elimination of MOBILE. Instead, it indicates that an upgraded MOBILE model should be included with other emissions models in a toolkit devised to tackle the wide range of current applications. Such a modeling toolkit would provide flexibility for develop- ing mobile-source emissions estimates in response to the wide variety of emissions-control strategies.

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4 MODEl/NG MOB`1E-SOURCE EMISSIONS Recommendation Because no single mobile-source emissions mode] is appropriate for at! applications, the committee recommends development of a toolkit of models that includes the following: an aggregated regional emissior~s-factor modeling component (i.e., the updated MOBILE model) for estimating emissions using aggregate vehicle-activity data; a mesoscale emissions modeling component that integrates detailed transportation and emissions components to estimate regional and subre- gional (corridor) emissions through the coupling of vehicle operating condi- tions with appropriate emissions factors; and a microscale ir~stantan~eous emissions modeling component that uses instantaneous operating conditions of individual vehicles to estimate con- tinuous vehicle emissions and that can be used for a variety of applica- tions, including generating emissions factors for microscaTe traffic-simula- tion models, mesoscale emissions models, traffic data sets, and dispersion models. To allow for a nested progression of models, the models in the toolkit should be designed and maintained to be consistent, despite differences in the level of detail in inputs (e.g., variations in roadway network detail and meteorological variables) and outputs (e.g., variations in emissions inputs over space and time). Consistency requires that the different modeling components in the toolkit be based on a consistent data set to the maxi- mum extent possible. Consistency also requires that the models in the toolkit predict similar emissions for spatial scales that overlap. EPA will need to develop a procedure for approving new components of the toolkit for use by states and regions. Such a procedure will require development of guidance documentation describing the appropriate use of each component in the toolkit and technical documentation describing modeling methodologies and data sources. In addition, peer review and model validation must be part of the foundation for new model adoption. Validation efforts for all new modeling methods should be conducted with vehicles and test conditions not reflected in the data used to develop the model and undertaken at the scale (or scales) for which a model is de- signed. Model Evaluation Finding Mode! validation and evaluation have not been addressed adequately by EPA during MOBILE's development. MOBILE's predictions of the bene-

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EXECUTIVE SUMMARY 5 fits of air-quaTity programs (e.g., vehicle emissions inspection and mainte- nance, oxygenated fuels, and reformulated gasoline) are often taken as measurements of the benefits of these programs. Confidence in the model has been undermined when large discrepancies have been observed be- tween the model's predictions and field measurements. Proper testing and evaluation would improve the accuracy of mobile-source emissions model- ing in estimating emissions, estimating the effects of emissions on human health and the environment, and estimating the effectiveness of control strategies. Recommendation Enhanced model evaluation studies shoulc! begin immediately anal coa- tinue throughout the lor~g-term evolution and development of mobile-source emissions models. These studies should be done with oversight and guid- ance from a reviewing body such as the EPA Science Advisory Board that includes users and technical experts. They should be undertaken in tan- dem with the uncertainty studies suggested in the following recommenda- tion. Evaluation studies should be conducted to identify and reduce dispari- ties between model-predicted emissions and measured data on emissions and air quality. These studies should also focus on reducing the differ- ences between the model-predicted changes in emissions resulting from programs such as vehicle-emissions inspection and maintenance and the changes that actually occur. The evaluations should involve field observa- tions (e.g., ambient air measurements, tunnel studies, and remote sens- ing), air-quality modeling, and vehicle-emissions data (e.g., data from vehicle-emissions inspection and maintenance programs, roadside pullover inspections, and other direct on-board tailpipe emissions measurements). Emphasis should be placed on techniques that are considered to have the fewest and smallest uncertainties. Sensitivity and Uncerlainty Assessment Finding At present, the understanding and quantification of the uncertainties in MOBILE are inadequate. There are uncertainties in the data used to de- velop model algorithms, the statistical analysis of test data, and the model input parameters. A] of these lead to large uncertainties in model out- puts. Further, the committee is unaware of any specification of the level of

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6 MODELING MOB/LE-SOURCE EMISSIONS accuracy required from MOBILE to support specific decision-making pro- cesses, in contrast to the mode! performance guidelines for travel-demand and air-quality modeling. The level of required accuracy would be expected to differ depending upon the various types of decisions that are required. Uncertainty and sensitivity analyses of MOBILE should focus on improv- ing those elements that have the most impact on model results to help guide the development of testing programs and the next generation of models. Recommendation EPA, along with other agencies and industries, should conduct seasitiv- ity anal uncertainty analyses of the mobile-source emissions models in the toolkit, especially MOBILE, and explicitly assess the required accuracy for specific applications. These analyses should occur as a part of the ongoing process of model development and updating. Specifically, the analyses should: include a rigorous study of the model's sensitivity to all the input data to provide users with information on the most critical factors affect- ing model results; include a rigorous study of uncertainties and bias in all model compo- nents and in the data used to develop model parameters and relationships; explicitly define the levels of accuracy needed to fulfill EPA's regula- tory responsibilities; and be used to design future versions of MOBILE and other models in the toolkit. Long-Term Planning Finding EPA has not engaged adequately in long-term planning to coordinate future model-application needs with model developments. In general, the large transportation and emissions modeling efforts by EPA, the Califor- nia Air Resources Board, the U.S. Department of Transportation, and oth- ers are not sufficiently integrated to make the most effective use of data, techniques, and other resources. The result of this lack of coordination and cooperation is that comparable models from different agencies are in- consistent.

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EXECUTIVE SUMMARY Recommendation 7 EPA should promptly improve long-term planning to increase coordina- tion ire mobile-source emissions modeling. Within 1 year, EPA should coor- dinate with the California Air Resources Board, the U.S. Department of Transportation, and others to complete a tong-rar~ge plan that addresses improvements of or resew approaches to mobile-source emissions models. EPA should also arrange for a short policy study by an independent body to identify possible institutional barriers anal ways to enhance institutional coordination in model development. EPA should develop partnerships with other public and private organi- zations, in the United States and internationally, to improve planning and coordination of model development. This planning process should include the following: analysis of policy and modeling needs relevant to the control of ozone, hazardous air pollutants, and particulate matter (PM) and the develop- ment of off-road emissions regulations; analysis of modeling techniques that might be applicable to future versions of MOBILE and other mobile-source emissions models; assessment of present and future data needs and the feasibility of coordination of data-collection efforts; strategies and methods to improve the linkages among transporta- tion, mobile-source emissions, air-quality, and exposure models; better use of advances in supporting technologies (e.g., Geographical Information System (GIS) and other information systems); and development of methods for assessing model accuracy. Improving Characterization of Real-World Vehicle Emissions Finding A critical element in model accuracy is the accurate measurement of the emissions of current and new vehicles that are in use. Such measure- ments are especially important for developing emissions inventories for future years. EPA has projected substantial reductions in future deterio- ration rates of emissions-control equipment on the current fleet and has applied this trend to the emerging new generation of vehicles. Vehicles with accelerated mileage accumulation have been relied upon to some ex- tent for predicting lifetime performance of technologies, although there is

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MODELING MOB!LE-SOURCE EMISSIONS no assurance that vehicles with accelerated mileage accumulation accu- rately represent on-road vehicles deteriorating through normal aging and mileage accumulation. Emerging technologies, such as on-board diagnostic systems that detect emissions-control-system failures, offer the possibility of significant future emissions reductions. The committee is unaware of any studies conducted to assess the motorist response to illuminated malfunction indicator lights, although this response rate is one of the most important factors for deter- mining the effectiveness of on-board diagnostic systems in reducing emis- sions. It is also important to understand whether deterioration rates for emerging emissions-control technologies will be similar to those of in-use technologies or whether there are inherent differences that will result in vehicle emissions deteriorating at faster or slower rates. Recommendation EPA should develop a program to enable more accurate determir~ation of in-use emissions. This program should use more real-world approaches such as direct tailpipe-emissions monitoring systems and random roadside pullovers of vehicles (such as those done in California) to ensure accurate characterization of emissions. Estimation of deterioration rates should be based on age as well as mileage. This might be difficult to do because of the correlation between age and mileage in the vehicle data used for MO- BILE. The program should include the development of improved estimates for various parameters in the MOBILE model. The parameters in the inspec- tion and maintenance portions of the model, such as repair effectiveness, mechanic training, and deterioration of repaired vehicles are particularly important. A critical parameter in estimating the effectiveness of future inspection and maintenance programs is the fraction of motorists that get repairs in response to malfunction indicator lights of on-board diagnostic systems. The response rates must be established for areas with and with- out vehicle-emissions inspection and maintenance programs. This evalua- tion could be aided by use of a permanent on-board diagnostic memory system and simple data download techniques. Appropriate statistical approaches should be used to project how vehicle emissions will change as vehicles normally age. Further, techniques should be developed to better capture the effects of failures of future con- troT systems. This information will allow improved forecasting of the emis- sions for future model years with new emissions-control technologies.

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EXECUTIVE SUMMARY 9 RECOMMENDATIONS FOR IMPROVEMENTS TO MOB' LE The committee has developed a set of recommendations for the improve- ment of MOBILE as an air-quality planning tool. The most significant im- provements that can be made to MOBILE are the acquisition of data nec- essary to improve the accuracy of the model and validation and evaluation of the model. Emissions from Heavy-Duty Diesel Vehicles Finding NOX emissions from heavy-duty diesel vehicles are underestimated in the current MOBILE model, and both NOx and particulate matter (PM) emissions rates are highly uncertain. The proposed MOBILES emissions factors use engine certification data (in grams per brake horsepower hour) and conversion factors to estimate gram per mile emissions factors. For MOBILES to improve its accuracy, the model must better characterize real-worId emissions from this vehicle class. The model should be up- graded soon, because State Implementation Plans that depend on correct assessments of NOX control levels are now being developed and submitted. States are also developing plans to address problems with fine (less than 2.5 mm diameter) PM emissions, and emissions from heavy-duty diesel vehicles are expected to be a major target of those plans. Recommendation EPA should design arid undertake a large-scale testing program that wit! better assess real-worId emissions from heavy-duty diesel vehicles. The results should be incorporated into a subsequent revision of MOBILES. This testing program should include a broad range of engine technologies and ages and be based on driving cycles that accurately reflect real-worId driving patterns. Particulate Emissions Finding PARTS is inadequate for supporting the new PM ambient air-quality standards and regional haze regulations. Although the results of field

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7 O MODELING MOB![E-SOURCE EMISSIONS studies are conflicting, they indicate that PARTS does not provide an accu- rate current inventory of emissions. Other concerns with PARTS are its estimation of the effects of emissions-control equipment deterioration on PM emissions from heavy-duty diesel vehicles and emissions of fine PM. Given that EPA and the California Air Resources Board need to improve their modeling of PM emissions, early cooperation between the two agen- cies would produce a more unified approach and a stronger database. Recommendation EPA should promptly update PARTS with the best available data on PM emissions and incorporate it into a subsequent revision of MOBILES. PARTS should be substantially upgraded and evaluated against field stud- ies. These improvements should be carried out in collaboration with the larger model-development community. In particular, improvements in modeling PM emissions should be coordinated with the California Air Re- sources Board's efforts in modeling these emissions. Testing data are available that would greatly improve PARTS model predictions. However, EPA, with input from the technical community, should still assess data gaps and design and implement test programs to fill those data gaps. Of special concern should be the modeling of emissions of fine PM. High-Emilting Vehicles Finding Emissions from high-emitting vehicles are a large source of uncertainty, and EPA has been slow to characterize these high-emitting vehicles. There is a lack of data on the emissions, number, and activity of these ve- hicles as well as a lack of information characterizing the effects of vehicle age, model, and geographical region. These vehicles are thought to repre- sent a substantial fraction of mobile-source emissions and are the focus of some emissions-control programs, so they must be accurately character- ized. Random roadside pullover testing of exhaust emissions, such as those currently performed in California, appears to be one of the most promising means of identifying vehicles with high exhaust emissions. Re- mote sensing of exhaust emissions has shown some promise as well. However, neither of those techniques can be used to estimate emissions from vehicles with unusually high levels of evaporative emissions. VOCs can evaporate from a vehicle fuel system or result from liquid leaks. Im-

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EXECUTIVE SUMMARY 7 7 proved characterization of emissions from vehicles with high evaporative losses might be critical for resolving differences between MOBILE-esti- mated and observed emissions of VOCs. Recommendation EPA should begin a substantial research effort to characterize high ex- haust and evaporative emitting vehicles. These vehicles should be charac- terized in terms of number of vehicles, proportion of the on-road fleet, emissions rates, and travel-activity patterns. Effects of emissions-control programs, especially vehicle emissions inspection and maintenance pro- grams, on high-emitting vehicles must also be properly assessed and mod- eled. MOBILE currently assumes a uniform distribution of vehicles in a region. However, high-emitting vehicles represent a disproportionate frac- tion of the total vehicles in Tow-income areas. To model the effects of dif- ferences in spatial and temporal distribution of high-emitting vehicles, local planning agencies need to gather such distribution data and conduct separate runs of MOBILE for various subareas in their planning region. Frequency of Moclel Updates Finding Updating MOBILES to MOBILES has taken far too long. Information that invalidated assumptions in MOBILES about the deterioration of light-duty vehicles and the effectiveness of vehicle emissions inspection and maintenance programs, oxygenated fuel, and other control programs has been available for several years and has not been incorporated into the model. Thus, emissions inventories and control strategies being developed are based on out-of-date assumptions and inaccurate predictions, perhaps resulting in the selection and propagation of inefficient or ineffective con- trols. Recommendation EPA should be more timely (perhaps 1 to 2 years) in updating significant individual components of the model as important new information becomes available. Consolidated documentation written for end-users that explains how MOBILE works, how the components were updated, and how the new data sources are used should accompany model updates.

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72 MODEI`NG MOB/NE-SOURCE EMISSIONS Mobile-Source Toxic Emissions Finding Although EPA has developed a model for predicting mobile-source toxic emissions based on the MOBILES model, this model is not publicly avail- able. When this model is released, it probably will be the best available tool for assessing both mobile-source toxic emissions and the impacts on toxic emissions from control programs designed to reduce primary mobile- source pollutants. Recommendation EPA should incorporate estimates of mobile-source toxic emissions into MOBILE. The best available data should be used to update MOB TOX, which should be merged into MOBILE6. EPA should assess weaknesses in the mobile-source taxies databases, design and run test programs to fill data gaps, and incorporate new test data into a timely update of MOBILE6. OTHER RECOMMENDATIONS Off-Road Emissions Finding As emissions from on-road vehicles decrease due to tighter emissions standards, fuel-sulfur controls, and less deterioration of emissions-control devices, the emissions from off-road mobile sources will continue to in- crease in importance. That is particularly true for NOx and PM emissions. Although the committee's charge did not explicitly call for an evaluation of EPA's new model for off-road-emissions (NONROAD), the committee rec- ognizes the importance of accurately predicting off-road-emissions for eval- uation of human health and environmental impacts from mobile-source emissions. Primarily because of a lack of data, the current off-road-emis- sions model does not accurately estimate off-road emissions inventories or the effects of emissions controls on these sources. Recommendation Within 1 year of the release of MOBILE6, EPA should have a plan for compiling the needed data and using these data to update NONROAD.

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EXECUTIVE SUMMARY 7 3 The plan should include the population and activity data and real-world emissions factors for gasoline and diesel engines. TAKING THE NEXT STEPS The recommendations presented in this report will not be easy to ac- complish. Coordination of data collection, modeling, and evaluation efforts by EPA, the California Air Resources Board, the U.S. Department of Transportation, and others will need to be increased substantially. Signif- icant resources will be needed to improve mobile-source emissions model- ing. For example, the accuracy of MOBILE is limited by the availability of appropriate emissions testing, and the task of improving the emissions database is statistically complex and requires extensive resources. Expen- ditures of resources for testing, modeling, and evaluation are warranted, however, because the decisions that rely on the results of this model are of tremendous importance to human health, the environment, and the econ- omy. Failure to provide the required resources will likely result in a con- tinued loss of confidence in the accuracy of MOBILE and possibly result in inappropriate allocation of resources for mobile-source emissions controls. Recent reorganization of the EPA Office of Mobile Sources, the EPA of- fice responsible for MOBILE, into the Office of Transportation and Air Quality might have an impact on MOBILE's continued development. The reorganization should not impede rigorous development of MOBILE, which must be seen as an accurate reflection of mobile-source emissions.

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14 MODE! /NG MOB/! E-SOURCE EM/SS/ONS emissions (about 67,000 thousand tons), almost half of the NOX (about ~ 1,600 thousand tons), and 40/O of the VOCs (about 7,700 thousand tons) (see Figure ~ -1 ~ (EPA ~ 99Sb). The elimination of lead from gasoline has greatly reduced mobile-source emissions of this pollutant to just over 500 tons (1 3/O of total lead emissions) in 1997, compared with mobile-source lead emissions in 1970, which were over 180,000 tons (EPA 1998a). According to the EPA (199Sb), mobile-source exhaust is a less important source of PM-1 0 (those particles smaller than ~ O mm in diameter) and sulfur dioxide. Mobile-source contribution to fine particles (those smaller than 2.5 mm in diameter and referred to as PM-2.5) is an area of continuing study. One recent study reported higher than expected PM-2.5 emissions from light-duty vehicles (LDVs) at higher elevations (CadIe et al. 1998~. It should be noted that, for a given location, the fraction of emissions inventories contributed by mobile sources varies greatly. Human Health Concerns Total emissions from mobile sources contribute significantly to the detrimental health effects resulting from exposure to ambient ozone, CO, PM, and air toxics. Urban ozone has been one of the most persistent health concerns. The current 1-fur primary NMQS for ozone is 0.12 parts per million (ppm), which is the daily maximum not to be exceeded more than once per year on average. (This is averaged over three years, so the fourth highest 1-fur value over three years is the one that is used to compare with the standard.) Health effects associated with exposures above this standard are well documented and are summarized by Lippmann (1989~. They range from short-term consequences such as chest pain, decreased lung function, and increased susceptibility to respiratory infection to possible fong-term consequences such as premature lung aging and chronic respiratory illnesses. In ~ 997, approximately 48 million U.S. residents in 77 counties, primarily urban and suburban regions, lived in areas where the second highest daily maximum concentration exceeded 0.12 ppm (EPA ~ 998b). Due to concerns about prolonged exposures to lower levels of ozone, EPA adopted an 8-fur standard of 0.08 ppm, which would put a much greater area and population into nonattainment with the standard (Wolff ~ 996; Chameides et al. ~ 997~. Based on the period from ~ 993-1995, EPA estimated that 248 counties with a population of 83 million people would have violated the B-hr ozone standard (EPA ~ 997a). Prospects for the implementation of the new standards are uncertain because a U.S. Court of Appeals in May ~ 999 remanded them for further consideration by EPA. Attaining CO standards has been far more successful. There are two primary standards for CO, a 1-fur average of 35 ppm and an 8-fur average of 9 ppm. The health effects from exposures to concentrations exceeding these standards are also documented. CO enters the blood stream and links to hemoglobin, reducing the amount of oxygen the blood can carry and causing mental and physical impairment. In 1 997, approximately 9 million people in three urban counties lived in areas that exceeded these standards (EPA 199Sb). This number has been declining over time. Standards for PM and air taxies are currently changing due to increased knowledge about their health effects. Current regulations for ambient concentrations of PM focus on particles less than or equal to 10 mm. New regulations to control smaller particles (less than or equal to 2.5 mm), intended to address some preliminary findings that these particles have the greatest impact on human health (Dockery et al. 1993), were remanded for consideration back to EPA by a U.S. Court of Appeals in May ~ 999. Air toxics include a wide class of emissions and effects. Few of these substances have been studied to examine possible health effects. In ~ 99S, the California Air Resources Board (CARB) identified diesel PM as a toxic air contaminant.