Global S&T Development Trend Analysis Platform of Resources and Environment
DOI | 10.1088/1748-9326/ab7f0f |
Exploring sources of uncertainty in premature mortality estimates from fine particulate matter: the case of China | |
Giani, Paolo1; Anav, Alessandro2; De Marco, Alessandra2; Feng, Zhaozhong3; Crippa, Paola1 | |
2020-06-01 | |
发表期刊 | ENVIRONMENTAL RESEARCH LETTERS
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ISSN | 1748-9326 |
出版年 | 2020 |
卷号 | 15期号:6 |
文章类型 | Article |
语种 | 英语 |
国家 | USA; Italy; Peoples R China |
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 PM(2.5)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 PM(2.5)observations from more than 1600 monitoring stations with the output of a high-resolution (8 km) regional simulation, to accurately estimate PM(2.5)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, PM(2.5)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 PM(2.5)estimate should be also incorporated in health impact assessment studies. Although the overall mortality burden remains vast in China (similar to 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. |
英文关键词 | WRF-Chem health impact assessment particulate matter exposure China' s air quality uncertainty quantification Monte Carlo |
领域 | 气候变化 |
收录类别 | SCI-E |
WOS记录号 | WOS:000542486100001 |
WOS关键词 | CHEMISTRY-TRANSPORT MODELS ; AMBIENT AIR-POLLUTION ; GLOBAL BURDEN ; ANTHROPOGENIC EMISSIONS ; PM2.5 CONCENTRATIONS ; HUMAN HEALTH ; EXPOSURE ; IMPACTS ; DISEASE ; QUALITY |
WOS类目 | Environmental Sciences ; Meteorology & Atmospheric Sciences |
WOS研究方向 | Environmental Sciences & Ecology ; Meteorology & Atmospheric Sciences |
引用统计 | |
文献类型 | 期刊论文 |
条目标识符 | http://119.78.100.173/C666/handle/2XK7JSWQ/289339 |
专题 | 气候变化 |
作者单位 | 1.Univ Notre Dame, Dept Civil & Environm Engn & Earth Sci, Notre Dame, IN 46556 USA; 2.Natl Agcy New Technol Energy & Sustainable Econ D, Rome, Italy; 3.Univ Informat Sci & Technol, Sch Appl Meteorol, Nanjing 210044, Peoples R China |
推荐引用方式 GB/T 7714 | Giani, Paolo,Anav, Alessandro,De Marco, Alessandra,et al. Exploring sources of uncertainty in premature mortality estimates from fine particulate matter: the case of China[J]. ENVIRONMENTAL RESEARCH LETTERS,2020,15(6). |
APA | Giani, Paolo,Anav, Alessandro,De Marco, Alessandra,Feng, Zhaozhong,&Crippa, Paola.(2020).Exploring sources of uncertainty in premature mortality estimates from fine particulate matter: the case of China.ENVIRONMENTAL RESEARCH LETTERS,15(6). |
MLA | Giani, Paolo,et al."Exploring sources of uncertainty in premature mortality estimates from fine particulate matter: the case of China".ENVIRONMENTAL RESEARCH LETTERS 15.6(2020). |
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