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.
Background: Future climate change may cause air quality degradation via climate-induced changes in meteorology, atmospheric chemistry, and emissions into the air. Few studies have explicitly modeled the potential relationships between climate change, air quality, and human health, and fewer still have investigated the sensitivity of estimates to the underlying modeling choices.Objectives: Our goal was to assess the sensitivity of estimated ozone-related human health impacts of climate change to key modeling choices.Methods: Our analysis included seven modeling systems in which a climate change model is linked to an air quality model, five population projections, and multiple concentration–response functions. Using the U.S. Environmental Protection Agency’s (EPA’s) Environmental Benefits Mapping and Analysis Program (BenMAP), we estimated future ozone (O3)-related health effects in the United States attributable to simulated climate change between the years 2000 and approximately 2050, given each combination of modeling choices. Health effects and concentration–response functions were chosen to match those used in the U.S. EPA’s 2008 Regulatory Impact Analysis of the National Ambient Air Quality Standards for O3.Results: Different combinations of methodological choices produced a range of estimates of national O3-related mortality from roughly 600 deaths avoided as a result of climate change to 2,500 deaths attributable to climate change (although the large majority produced increases in mortality). The choice of the climate change and the air quality model reflected the greatest source of uncertainty, with the other modeling choices having lesser but still substantial effects.Conclusions: Our results highlight the need to use an ensemble approach, instead of relying on any one set of modeling choices, to assess the potential risks associated with O3-related human health effects resulting from climate change.
As part of its assessment of the health risks associated with exposure to particulate matter (PM), the U.S. Environmental Protection Agency analyzed the risks associated with current levels, and the risk reductions that might be achieved by attainment of alternative PM standards, in two locations in the United States, Philadelphia, and Los Angeles. The concentration-response function describing the relation between a health endpoint and ambient PM concentrations is an important component, and a source of substantial uncertainty, in such risk analyses. In the absence of location-specific estimates, the concentration-response functions necessary for risk assessments in Philadelphia and Los Angeles must be inferred from the available information in other locations. Although the functional form of the concentration-response relations is assumed to be the same everywhere, the value of the PM coefficient in that function may vary from one location to another. Under this model, a distribution describes the probability that the PM coefficient in a randomly selected location will lie in any range of interest. An empirical Bayes estimation technique was used to improve the estimation of location-specific concentration-response functions relating mortality to short-term exposure to particles of aerodynamic diameter less than or equal to 2.5 microm (PM-2.5), for which functions have previously been estimated in several locations. The empirical Bayes-adjusted parameter values and their SEs were used to derive an estimate of the distribution of PM-2.5 coefficients for mortality associated with short-term exposures. From this distribution, distributions of relative risks corresponding to different specified changes in PM-2.5 concentrations could be derived.
Under Executive Order 12898, the U.S. Environmental Protection Agency (EPA) must perform environmental justice (EJ) reviews of its rules and regulations. EJ analyses address the hypothesis that environmental disamenities are experienced disproportionately by poor and/or minority subgroups. Such analyses typically use communities as the unit of analysis. While community-based approaches make sense when considering where polluting sources locate, they are less appropriate for national air quality rules affecting many sources and pollutants that can travel thousands of miles. We compare exposures and health risks of EJ-identified individuals rather than communities to analyze EPA’s Heavy Duty Diesel (HDD) rule as an example national air quality rule. Air pollutant exposures are estimated within grid cells by air quality models; all individuals in the same grid cell are assigned the same exposure. Using an inequality index, we find that inequality within racial/ethnic subgroups far outweighs inequality between them. We find, moreover, that the HDD rule leaves between-subgroup inequality essentially unchanged. Changes in health risks depend also on subgroups’ baseline incidence rates, which differ across subgroups. Thus, health risk reductions may not follow the same pattern as reductions in exposure. These results are likely representative of other national air quality rules as well.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.