Based on an analysis comparing the 580 MW Altamont Pass wind farm in California and the 22 MW Sawtooth wind farm in Idaho with natural gas-fired generation, this article finds that wind energy provides significant and quantifiable human health, wildlife, and climate change benefits not normally considered by energy planners and utility operators. These benefits make wind energy far cheaper than natural gas.

How tangible are the costs of natural gas compared to the benefits of one of the fastest growing sources of electricity – wind energy – in the United States? To answer this question, this article calculates the benefits of wind energy derived from two locations: the 580 MW wind farm at Altamont Pass, CA, and the 22 MW wind farm in Sawtooth, ID. Both wind farms have environmental and economic benefits that should be considered when evaluating the comparative costs of natural gas and wind energy. Though there are uncertainties within the data collected, for the period 2012–2031, the turbines at Altamont Pass will likely avoid anywhere from $560 million to $4.38 billion in human health and climate related externalities, and the turbines at Sawtooth will likely avoid $18 million to $104 million of human health and climate-related externalities. Translating these negative externalities into a cost per kWh of electricity, we estimate that Altamont will avoid costs of 1.8–11.8 cents/kWh and Sawtooth will avoid costs of 1.5–8.2 cents/kWh.

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.

This report is the 16th in the series: The Annualized Social Cost of Motor-Vehicle Use in the United States, based on 1990-1991 Data. In this report, the authors explain how they model the contribution of motor vehicles and other emissions sources to ambient air pollution. They estimate the health, agriculture, or visibility effects of the difference between total air pollution, including motor-vehicle-related emissions, and air pollution with 10 percent of 100 percent of motor-vehicle-related emissions eliminated. To estimate the difference in pollution due to motor vehicle emissions, they use data on ambient air quality, a detailed emissions inventory, emissions correction factors, and a simple air-quality dispersion model.

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.

ISEE-332 Purpose: The U.S. Environmental Protection Agency (U.S. EPA) recently proposed regulations to reduce air pollution from diesel engines used in most kinds of construction, agricultural, and industrial equipment. This analysis reports the estimated health benefits of reductions in ambient particulate matter (PM) concentrations associated with those regulations based on the best available methods. Methods: Health impacts are estimated using EPA's environmental Benefits Mapping and Analysis Program (BenMAP), a customized geographic information system. Using outputs from the Regional Modeling System for Aerosols and Deposition (REMSAD), BenMAP calculates changes in air pollution metrics (e.g., daily averages) for input into health impact functions. BenMAP uses grid cell level population data, baseline health effect incidence rates, and changes in pollutant concentrations to estimate changes in health outcomes for each model grid cell. Economic values are then assigned to changes in health outcomes to generate monetized benefits. Using Monte Carlo methods, BenMAP also provides estimates of confidence intervals for health impacts and monetized benefits based on standard errors for effect estimates or other sources of uncertainty, such as meta-analyses of the epidemiological and economic literature. Results: The REMSAD modeling results suggest that when nonroad diesel engine emission reductions are fully realized in 2030, they will result in substantial, broad scale reductions in ambient fine particulate matter (population weighted reduction of over 0.5 μg/m3). This is associated with an estimated reduction in the incidence of premature mortality by 9,600, chronic bronchitis by 5,700, nonfatal myocardial infarctions by 16,000, and respiratory and cardiovascular hospital and emergency room admissions by 14,000. In addition, over 200,000 asthma exacerbations and millions of respiratory symptoms are predicted be avoided in 2030. The economic value of these health benefits is estimated at over $90 billion. Monetized benefits estimates are sensitive to choice of the effect estimate for premature mortality, valuation of mortality risk reductions, assumed lag/latency structure, and assumptions about the shape of the health impact function. However, under most reasonable assumptions, health benefits are substantial. Conclusions: This analysis estimated the health and welfare benefits of reductions in ambient concentrations of particulate matter resulting from reduced emissions of NOx, SO2, and diesel PM from nonroad diesel engines. The results suggests there will be significant health and welfare benefits arising from the regulation of emissions from nonroad engines in the U.S. and highlight the important role that pollution from the nonroad sector plays in the overall public health impacts of air pollution.

ISEE-532 Purpose: Recent EPA rules will substantially reduce air pollution in urban areas. However, benefits are sensitive to demographic characteristics of the population as well as estimates of potential population exposure. Using the new environmental Benefits Mapping and Analysis Program (BenMAP), we assess heterogeneity in potential urban health impacts associated with reductions in PM2.5 and ozone. Methods: BenMAP combines air pollution monitoring and modeling data, block level census data, and population projections to calculate a population’s exposure to ambient air pollution. Using these different types of data, BenMAP can estimate changes in population exposure for particular years and areas of interest. Given changes in population exposure, BenMAP calculates the associated distributions of changes in incidence and values of health effects using health impact and economic valuation functions derived from the epidemiological and economic literature. For each urban area of interest, we estimate the change in incidence of premature mortality and a broad range of chronic and acute health effects. Results: We will provide results for a wide range of urban areas in the U.S. and examine sensitivity of health impacts to population age composition, baseline health incidence rates, and geographic variability in concentration-response relationships, interpolation methods, and economic valuation functions. Initial results based on the effect estimate from the concentration-response function relating PM2.5 and all cause mortality from Pope et al. (2002) show variability in mortality impacts per microgram of PM2.5 reduced, ranging from 40 per million people in Atlanta to 79 per million people in Birmingham. This variability is primarily due to variation in baseline mortality rates and age composition across urban areas. When pollution reduction strategies result in spatially heterogeneous reductions in pollution concentrations, spatial resolution will affect impact estimates, especially in large urban areas with strong, correlated gradients in air pollution and population. We investigate this issue by estimating impacts using variable exposure grid sizes, ranging from 36 km2 to 1 km2. Conclusions: This analysis makes use of EPA’s new health impact and benefits analysis software, BenMAP, to analyze heterogeneity in the benefits of air pollution reductions across urban areas. Characterizing this heterogeneity is important for local and national policy analyses. For example, as control strategies are considered to attain PM health standards, it will be useful to understand the differences in benefits per microgram between nonattainment areas, to help identify where more costly control strategies would be justified based on health benefits.

Emissions from motor vehicles and related sources, such as petroleum refineries, have a variety of effects on human health. The effects can be as innocuous as itchy eyes, or as serious as chronic lung disease or heart failure. This chapter reviews recent studies of the health effects of air pollution related to use of motor vehicles in the U.S., and also attempts to quantify the impacts. Although the focus is on physical health effects, the authors also review how to combine the estimates of physical effects with their estimated monetary cost to produce an estimate of the total social cost of the health effects of motor vehicle pollution. An overview of motor vehicle emissions and exposure to motor-vehicle related air pollution is provided. The health effects of exposure to motor-vehicle-related air pollution are then discussed. The chapter concludes with a brief summary of the valuation of health effects and of 2 recent estimates of total social cost of the health effects of motor vehicle pollution.

The purpose of this paper is to show that the possibility cannot be ruled out that ozone is linked to mortality and chronic illness, effects which are costly and would considerable raise the costs of ozone pollution. Particulates are the most damaging pollutant and diesel vehicles cause mare damages per mile than do gasoline vehicles. The results of this paper suggest that emphasis should be placed on the regulation of particulates.

Motor vehicles have significantly larger health costs than previously reported. Particulates are the most damaging pollutant, while ozone and other pollutants have smaller effects. Diesel vehicles cause more damages per mile than do gasoline vehicles, because of greater particulate emissions. Very fine particles appear more dangerous than larger particles, and combustion particles appear more dangerous than road dust. The possibility cannot be ruled out that ozone is linked to mortality and chronic illness, effects which are costly and would considerably raise the costs of ozone pollution. These results suggest that emphasis should be placed on the regulation of particulates.

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.