In the spring of 1985 an interagency consortium of federal land management agencies and the Environmental Protection Agency established the Interagency Monitoring of Protected Visual Environments (IMPROVE) network to assess visibility and aerosol monitoring for the purpose of tracking spatial and temporal trends of visibility and visibility‐impairing particles in rural areas. The program was initiated with 20 monitoring sites and was expanded to 165 sites between 2000 and 2003. This paper reports on fine aerosol data collected in the year 2001 at 143 sites. The major fine (dp < 2.5 μm) particle aerosol species, sulfates, nitrates, organics, light‐absorbing carbon, and wind‐blown dust, and coarse gravimetric mass are monitored, and at some sites, light scattering and/or extinction are measured. Sulfates, carbon, and crustal material are responsible for most of the fine mass at the majority of locations throughout the United States, while at sites in southern California and the midwestern United States, nitrates can contribute significantly. In the eastern United States, sulfates contribute between 50 and 60% of the fine mass. Sulfate concentrations tend to be highest in the summer months while organic concentrations can be high in the spring, summer, or fall seasons, depending upon fire‐related emissions. However, at the two urban sites, Phoenix, Arizona, and Puget Sound, Washington, organics peak during the winter months. Nitrate concentrations also tend to be highest during the winter months. During the spring months in many areas of the western United States, fine soil can contribute as much as 40% of fine mass. The temporal changes in soil concentration that occur simultaneously over much of the western United States including the Rocky Mountain region suggest a large source region, possibly long‐range transport of Asian dust.

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The chemical mass balance (CMB) receptor model was applied to the chemically speciated diurnal particulate matter samples acquired at nine locations in California's South Coast Air Basin (SOCAB) during the summer and fall of 1987 as part of the Southern California Air Quality Study (SCAQS). Source profiles applicable to the Los Angeles area were used to apportion PM,, and PM,, (particles with aerodynamic diameters < 2.5 and 10 pm, respectively) to primary paved road dust, primary construction dust, primary motor vehicle exhaust, primary marine aerosol, secondary ammonium

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e d m a n * Smog c h e c k data o n 307 of these vehicles.Of these, 126 (41%) showed deliberate tampering, and another 77 (25%) had defective or ~nissi~lg equiptnent that tnay not have been the result of tampering (for ex-I n response to continuing pollution prob-lected 91,679 records with valid H C and ample, missing air pump belts). Overall, 282 lems, in 1990 Congress passed the Clean CO tneasurements (8). T h e etnission distri-(92%) failed the inspection even though all Air A c t Amendments, many parts of which bution is highly skewed; the half of the fleet had valid registrations. Thus, less than 8% deal with motor vehicles. Motor vehicles are with the lowest emissio~ls contributed less of the vehicles identified as gross polluters the ~r i m a r v source of urban carbon tnonox-than 10% of the C O and HC. while a few bv remote sensine nassed a n immediate " L ide (CO) and are an important source of the high-emission vehicles dominated the rdadside test. W h e n r a~l d o~n pullover studhvdrocarbons I H C ) and oxides of nitrogen mean values. I n this instance. 7% of the ies were carried out bv the California BLI--(NO,) that are responsible for the fortnation of photochemical stnog and ground-level ozone (1). Cost estimates for itnplenlenting the act's mobile source provisions range up to $1 2 billion annuallv 12). Thus it is im-,~, portant to analyze the scientific basis for these legislative programs (1 ).For any region violating air quality standards, a State Itnolenle~ltation Plan (SIP) , , must be submitted to and approved by the U.S. Environmental Protection Agency (EPA). In approving the SIP, EPA grants credit for each portion of the plan, including new vehicle emission standards, new fuels, vehicle scrappage, and inspection and maintenance (IM) programs, o n the basis of predictions from a spreadsheet computer tnodel 13). This EPA model treats all cars of ~, a given tnodel year as having the same odometer reading, the same annual mileage accutnulation, and an equal likelihood of emission control systetn probletns. T h e model has had little success in predicting urban on-road vehicle etnissions (4), and the use of unverified computer models as the sole guide for public policy decisions is controversial (5). Calvert et al. (6) criticized the tnodel and recommended in-use vehicles accounted for 50% of'the on-road C O emissions, and 10% of the vehicles accou~lted for 50% of the on-road HC etnissions. These vehicles we call gross polluters. About 5% of the vehicles were gross polluters for both HC and CO (9).It is often assumed that gross poll~tters are sitnply old vehicles. In fact, all model vears of vehicles we have measured o n the road include some proportion of gross polluters, as shown in Fig. l. W e found that the highest emitting 20% of the newest cars were worse polluters than the lowest emitting 40% of vehicles from any tnodel year, even those from model years before the advent of catalytic converters (1970 and earlier). These data are typical of CO and H C results across the United States an...