气候变化领域集成服务门户(CCPortal): Exploring sources of uncertainty in premature mortality estimates from fine particulate matter: The case of China

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DOI	10.1088/1748-9326/ab7f0f
	Exploring sources of uncertainty in premature mortality estimates from fine particulate matter: The case of China
	Giani P.; Anav A.; De Marco A.; Feng Z.; Crippa P.
发表日期	2020
ISSN	17489318
卷号	15 期号:6
英文摘要	Atmospheric pollution from fine particulate matter (PM2.5) is one of the major concerns in China because of its widespread and harmful impacts on human health. In recent years, multiple studies have sought to estimate the premature mortality burden from exposure to PM2.5 to inform policy decisions. However, different modeling choices have led to a wide array of results, with significant discrepancies both in the total mortality burden and in the confidence intervals. Here, we present a new comprehensive assessment of PM2.5-related mortality for China, which includes quantification of the main sources of variability, as well as of age and province-specific premature mortality trends during 2015-2018. Our approach integrates PM2.5 observations from more than 1600 monitoring stations with the output of a high-resolution (8 km) regional simulation, to accurately estimate PM2.5 fields along with their uncertainty, which is generally neglected. We discuss the sensitivity of mortality estimates to the choice of the exposure-response functions (ERFs), by comparing the widely used integrated exposure response functions (IERs) to the recently developed Global Exposure Mortality Models (GEMMs). By propagating the uncertainty in baseline mortalities, PM2.5 and ERFs under a Monte Carlo framework, we show that the 95% confidence intervals of mortality estimates are considerably wider than previously reported. We thus highlight the need for more epidemiological studies to constrain ERFs and we argue that uncertainty related to PM2.5 estimate should be also incorporated in health impact assessment studies. Although the overall mortality burden remains vast in China (∼1.6 million premature deaths, according to GEMMs), our results suggest that 200 000 premature deaths were avoided and 195 billion US dollars were saved in 2018 compared to 2015, bolstering the mounting evidence about the effectiveness of China's air quality policies. © 2020 The Author(s). Published by IOP Publishing Ltd.
英文关键词	China's air quality; health impact assessment; Monte Carlo; particulate matter exposure; uncertainty quantification; WRF-Chem
语种	英语
scopus关键词	Air quality; Particles (particulate matter); Atmospheric pollution; Comprehensive assessment; Epidemiological studies; Fine particulate matter; Fine particulate matter (PM2.5); Health impact assessment; Sources of uncertainty; Sources of variability; Uncertainty analysis; air quality; atmospheric pollution; estimation method; health impact; Monte Carlo analysis; mortality; particle size; particulate matter; pollution exposure; public health; uncertainty analysis; China
来源期刊	Environmental Research Letters
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/154001
作者单位	Department of Civil and Environmental Engineering and Earth Sciences, University of Notre Dame, Notre Dame, IN, United States; National Agency for New Technologies, Energy and Sustainable Economic Development (ENEA), Rome, Italy; School of Applied Meteorology, University of Information Science and Technology, Nanjing, 210044, China
推荐引用方式 GB/T 7714	Giani P.,Anav A.,De Marco A.,et al. Exploring sources of uncertainty in premature mortality estimates from fine particulate matter: The case of China[J],2020,15(6).
APA	Giani P.,Anav A.,De Marco A.,Feng Z.,&Crippa P..(2020).Exploring sources of uncertainty in premature mortality estimates from fine particulate matter: The case of China.Environmental Research Letters,15(6).
MLA	Giani P.,et al."Exploring sources of uncertainty in premature mortality estimates from fine particulate matter: The case of China".Environmental Research Letters 15.6(2020).