Risk-based prioritization among air pollution control strategies in the Yangtze River Delta, China

Abstract

Background: The Yangtze River Delta (YRD) in China is a densely populated region with recent dramatic increases in energy consumption and atmospheric emissions. Objectives: We studied how different emission sectors influence population exposures and the corresponding health risks, to inform air pollution control strategy design. Methods: We applied the Community Multiscale Air Quality (CMAQ) Modeling System to model the marginal contribution to baseline concentrations from different sectors. We focused on nitrogen oxide (NOx) control while considering other pollutants that affect fine particulate matter [aerodynamic diameter ≤ 2.5 μm (PM2.5] and ozone concentrations. We developed concentration-response (C-R) functions for PM2.5 and ozone mortality for China to evaluate the anticipated health benefits. Results: In the YRD, health benefits per ton of emission reductions varied significantly across pollutants, with reductions of primary PM2.5 from the industry sector and mobile sources showing the greatest benefits of 0.1 fewer deaths per year per ton of emission reduction. Combining estimates of health benefits per ton with potential emission reductions, the greatest mortality reduction of 12,000 fewer deaths per year [95% confidence interval (CI), 1,200-24,000] was associated with controlling primary PM2.5 emissions from the industry sector and reducing sulfur dioxide (SO2) from the power sector, respectively. Benefits were lower for reducing NO xemissions given lower consequent reductions in the formation of secondary PM2.5 (compared with SO2) and increases in ozone concentrations that would result in the YRD. Conclusions: Although uncertainties related to C-R functions are significant, the estimated health benefits of emission reductions in the YRD are substantial, especially for sectors and pollutants with both higher health benefits per unit emission reductions and large potential for emission reductions.