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8 Benefits to Human Health and Agricultural Productivity of Reduced Air Pollution Yu Lei We have seen in prior chapters how the SO2 controls of the 11th Five-Year Plan (11th FYP) or a tax of 100 yuan per ton of carbon (27 yuan per ton of CO2) did reduce or would reduce emissions and concentrations of a variety of both primary and secondary air pollutants. Among the most powerful implications of either of these policies would be their very large effects on public health. To the extent that they affect concentrations of ground-level ozone, they would also impact the productivity of major grain crops. In this chapter, we estimate the health and agricultural benefits that would result from the improved air quality under the two policy options. We consider these topics in sequence, first addressing the centrally important health benefits and then turning to the crop benefits. 8.1 Health Benefits 8.1.1 Methodology and Data Framework of BenMAP We analyze health benefits under the base case and policy scenarios described in the previous chapters using the Benefit Mapping and Analysis Program (BenMAP). This is a tool developed by the U.S. Environmental Protection Agency (U.S. EPA) for estimating the health and associated economic impacts of changes in ambient air pollution levels (Hubbell, McCubbin, and Hallberg 2003). BenMAP was originally adapted for China by Xiaochuan Pan of Peking University, as part of the Integrated Environmental Strategies program sponsored by the U.S. EPA. Figure 8.1 illustrates the flow of calculations in BenMAP. The first step in evaluating the health impacts is estimating changes in population exposure to air pollution levels due to a given policy scenario compared to the base case. This is accomplished by combining a spatial projection of the population distribution with pollutant concentrations simulated by the air quality model. In 292 Chapter 8 the next step, BenMAP calculates the health effects, meaning the changes in various health endpoints such as the number of cases of premature mortality or outpatient hospital visits per year. These are estimated by applying concentration-response (C-R) functions from the epidemiological literature to the population exposure, along with the base incidences in the population of those health endpoints. (A C-R function, sometimes alternatively called an exposure-response function, relates a change in exposure to a pollutant with a change in the incidence of a health endpoint ; see U.S. EPA [2013] regarding the terminology. Base incidence refers to the baseline number of cases of the health endpoint in the population due to all causes, expressed in terms of cases per person per unit time—for example, the total deaths due to all causes per million people per year. The incidence of all-cause mortality, for instance, follows directly from total deaths due to all causes per million people per year.) The first two steps are represented by the following formula for pollutant x: Δ Δ HE f C Pop BI hx hx x h = × × ( ) (8.1) where ΔHEh denotes the change in the number of cases of health endpoint h; f is the C-R function and ΔCx denotes the change of concentration of air pollutant x; Pop represents the population exposed to the pollutant; and BIh represents the Figure 8.1 BenMAP flow diagram. Note: BenMAP has an additional component for monetizing health effects, a topic discussed in chapter 9. Benefits to Human Health and Agricultural Productivity of Reduced Air Pollution 293 baseline incidence of the health endpoint h. We thus require the four elements on the right-hand side of equation (8.1) to estimate the health effects of a policy. In our study, the changes in concentrations of air pollutants are provided by the output of the GEOS-Chem modeling described in chapter 7. Data on the population distribution and baseline incidence are drawn from official statistical sources, which are described later in this section. The C-R functions, critical factors in any estimation of health effects of pollution, will be discussed in section 8.1.2. Air Pollutants of Concern A large number of epidemiological studies have shown that particulate matter under 10 microns in aerodynamic diameter (PM10) leads to adverse health effects because it contains toxic and hazardous matter. (See Levy and Greco [2007] for a full summary of key findings in environmental epidemiology briefly introduced here.) PM2.5, the subset of PM10 made up of finer particles, is believed to pose higher health risks because the smaller size allows deeper penetration into...


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