Considerable interest has focused on the possible existence of an environmental Kuznets curve, whereby pollution first increases but later falls with increasing income. Empirical studies have concentrated on a wide spectrum of countries and run into inevitable problems of data comparability and quality. We avoid these problems by looking at seven types of air emissions across the 50 US states and find all seven pollutants decrease with increasing per capita income. We also find strong evidence of heteroscedasticity with respect to the income–emissions relationship: lower-income states display much greater variability in per capita emission levels than higher-income states. Additionally, we look at the best measured of these emissions, air toxics, for the period 1988–94. Using a simple sign test, we find support for the notion that an increase in income is associated with a decrease in per capita emissions. However, the change in emissions appears to be unrelated to the magnitude of the change in income. We do find, though, that the reduction in per capita emissions is increasing both in terms of the 1988 level of per capita emissions and income. Possible implications of these results for the development process are discussed.

During the 2000–2002 time period, between 36 and 56% of ozone monitors each year in the United States failed to meet the current ozone standard of 80 ppb for the fourth highest maximum 8-hr ozone concentration. We estimated the health benefits of attaining the ozone standard at these monitors using the U.S. Environmental Protection Agency’s Environmental Benefits Mapping and Analysis Program. We used health impact functions based on published epidemiologic studies, and valuation functions derived from the economics literature. The estimated health benefits for 2000 and 2001 are similar in magnitude, whereas the results for 2002 are roughly twice that of each of the prior 2 years. The simple average of health impacts across the 3 years includes reductions of 800 premature deaths, 4,500 hospital and emergency department admissions, 900,000 school absences, and > 1 million minor restricted activity days. The simple average of benefits (including premature mortality) across the 3 years is $5.7 billion [90% confidence interval (CI), 0.6–15.0] for the quadratic rollback simulation method and $4.9 billion (90% CI, 0.5–14.0) for the proportional rollback simulation method. Results are sensitive to the form of the standard and to assumptions about background ozone levels. If the form of the standard is based on the first highest maximum 8-hr concentration, impacts are increased by a factor of 2–3. Increasing the assumed hourly background from zero to 40 ppb reduced impacts by 30 and 60% for the proportional and quadratic attainment simulation methods, respectively.

Agricultural operations are the largest source of ammonia emissions in the United States and contribute to the formation of ammonium nitrate and ammonium sulfate, two prevalent forms of fine particulate matter. Researchers have found an association between fine particulate matter and a variety of adverse healths effects, including premature mortality, chronic bronchitis, hospital admissions, and asthma attacks. Management practices that reduce ammonia emissions may decrease adverse health effects, resulting in significant economic benefits. We estimated the impact of a variety of emission controls, including diet optimization, alum, and incorporation of manure into the land. The results suggest that relatively modest management policies can have a significant impact on fine particulate formation in the atmosphere. Because of the heterogeneous nature of particulate matter, a key question is the importance of particulate matter size and composition. To the extent that ammonium nitrate and ammonium sulfate contribute to adverse health effects, ammonia management may have significant health implications. Our results suggest that a 10% reduction in livestock ammonia emissions can lead to over $4 billion annually in particulate-related health benefits.

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As epidemiological work from around the world continues to tie PM2.5 to serious adverse health effects, including premature mortality, the U.S. Environmental Protection Agency (U.S. EPA) has developed a number of policies to reduce air pollution, including PM2.5. To assist in the benefit-cost analyses of these air pollution control policies, the U.S. EPA has developed the Environmental Benefits Mapping and Analysis Program (BenMAP). BenMAP is meant to (1) provide a flexible tool for systematically analyzing impacts of changes in environmental quality in a timely fashion, (2) ensure that stakeholders can understand the assumptions underlying the analysis, and (3) adequately address uncertainty and variability. BenMAP uses a "damage-function" approach to estimate the health benefits of a change in air quality. The major components of the damage-function approach are population estimates, population exposure, adverse health effects, and economic costs. To demonstrate BenMAP's ability to analyze PM2.5 pollution control policy scenarios, we assess two sample applications: (1) benefits of a national-level air quality control program, and (2) benefits of attaining two annual PM2.5 standards in California (annual average standards of 15 microg/m3 and 12 microg/m3). In the former, we estimate a scenario where control of PM2.5 emissions results in $100 billion of benefits annually. In the analysis of alternative standards, we estimate that attaining the more stringent standard (12 microg/m3) would result in approximately 2000 fewer premature deaths each year than the 15 microg/m3 achieves. BenMAP has a number of features to help clarify the analysis process. It allows the user to record in a configuration all of the choices made during an analysis. Configurations are especially useful for recreating already existing policy analyses. Also, BenMAP has a number of reporting options, including a set of mapping tools that allows users to visually inspect their inputs and results.