Nonlinear relationships between air pollutant emissions and PM2.5-related health impacts in the Beijing-Tianjin-Hebei region

Bin Zhao; Shuxiao Wang; Dian Ding; Wenjing Wu; Xing Chang; Jiandong Wang; Jia Xing; Carey Jang; Joshua S Fu; Yun Zhu; Mei Zheng; Yu Gu

doi:10.1016/j.scitotenv.2019.01.169

Nonlinear relationships between air pollutant emissions and PM_2.5-related health impacts in the Beijing-Tianjin-Hebei region

Sci Total Environ. 2019 Apr 15:661:375-385. doi: 10.1016/j.scitotenv.2019.01.169. Epub 2019 Jan 16.

Authors

Bin Zhao¹, Shuxiao Wang², Dian Ding³, Wenjing Wu³, Xing Chang³, Jiandong Wang⁴, Jia Xing³, Carey Jang⁵, Joshua S Fu⁶, Yun Zhu⁷, Mei Zheng⁸, Yu Gu⁹

Affiliations

¹ School of Environment, and State Key Joint Laboratory of Environment Simulation and Pollution Control, Tsinghua University, Beijing 100084, China; Joint Institute for Regional Earth System Science and Engineering and Department of Atmospheric and Oceanic Sciences, University of California, Los Angeles, CA 90095, USA.
² School of Environment, and State Key Joint Laboratory of Environment Simulation and Pollution Control, Tsinghua University, Beijing 100084, China; State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, Beijing 100084, China. Electronic address: shxwang@tsinghua.edu.cn.
³ School of Environment, and State Key Joint Laboratory of Environment Simulation and Pollution Control, Tsinghua University, Beijing 100084, China; State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, Beijing 100084, China.
⁴ Multiphase Chemistry Department, Max Planck Institute for Chemistry, Mainz 55128, Germany.
⁵ U.S. Environmental Protection Agency, Research Triangle Park, NC 27711, USA.
⁶ Department of Civil and Environmental Engineering, University of Tennessee, Knoxville, TN 37996, United States.
⁷ School of Environmental Science and Engineering, South China University of Technology, Guangzhou 510006, China.
⁸ SKL-ESPC and BIC-ESAT, College of Environmental Sciences and Engineering, Peking University, Beijing 100871, China.
⁹ Joint Institute for Regional Earth System Science and Engineering and Department of Atmospheric and Oceanic Sciences, University of California, Los Angeles, CA 90095, USA; University of California, Los Angeles Institute for Technology Advancement, Suzhou Industrial Park (UCLA ITA - SIP), Suzhou, China.

Abstract

A direct and quantitative linkage of air pollution-related health effects to emissions from different sources is critically important for decision-making. While a number of studies have attributed the PM_2.5-related health impacts to emission sources, they have seldom examined the complicated nonlinear relationships between them. Here we investigate the nonlinear relationships between PM_2.5-related premature mortality in the Beijing-Tianjin-Hebei (BTH) region, one of the most polluted regions in the world, and emissions of different pollutants from multiple sectors and regions, through a combination of chemical transport model (CTM), extended response surface model (ERSM), and concentration-response functions (CRFs). The mortalities due to both long-term and short-term exposures to PM_2.5 are most sensitive to the emission reductions of primary PM_2.5, followed by NH₃, nonmethane volatile organic compounds and intermediate volatility organic compounds (NMVOC+IVOC). The sensitivities of long-term mortality to emissions of primary organic aerosol (POA), NMVOC+IVOC and SO₂ do not change much with reduction ratio, whereas the sensitivities to primary inorganic PM_2.5 (defined as all chemical components of primary PM_2.5 other than POA), NH₃ and NO_x increase significantly with the increase of reduction ratio. The emissions of primary PM_2.5, especially those from the residential and commercial sectors, contribute a larger fraction of mortality in winter (57-70%) than in other seasons (28-42%). When emissions of multiple pollutants or those from both local and regional emissions are controlled simultaneously, the overall sensitivity of long-term mortality is much larger than the arithmetic sum of the sensitivities to emissions of individual pollutants or from individual regions. This implies that a multi-pollutant, multi-sector and regional joint control strategy should be implemented to maximize the marginal health benefits. For NO_x emissions, we suggest a nationwide control strategy which significantly enhances the effectiveness for reducing mortality by avoiding possible side effects when only the emissions within the BTH region are reduced.

Keywords: CMAQ/2D-VBS; China; PM(2.5); extended response surface model (ERSM); premature mortality.

MeSH terms

Air Pollutants / adverse effects*
China / epidemiology
Environmental Exposure / adverse effects*
Humans
Mortality, Premature*
Nonlinear Dynamics
Particle Size
Particulate Matter / adverse effects*

Substances

Air Pollutants
Particulate Matter

Grants and funding

EPA999999/ImEPA/Intramural EPA/United States