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National Institute of Environmental Health Sciences

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Your Environment. Your Health.

Publication Detail

Title: The 17-y spatiotemporal trend of PM2.5 and its mortality burden in China.

Authors: Liang, Fengchao; Xiao, Qingyang; Huang, Keyong; Yang, Xueli; Liu, Fangchao; Li, Jianxin; Lu, Xiangfeng; Liu, Yang; Gu, Dongfeng

Published In Proc Natl Acad Sci U S A, (2020 10 13)

Abstract: Investigations on the chronic health effects of fine particulate matter (PM2.5) exposure in China are limited due to the lack of long-term exposure data. Using satellite-driven models to generate spatiotemporally resolved PM2.5 levels, we aimed to estimate high-resolution, long-term PM2.5 and associated mortality burden in China. The multiangle implementation of atmospheric correction (MAIAC) aerosol optical depth (AOD) at 1-km resolution was employed as a primary predictor to estimate PM2.5 concentrations. Imputation techniques were adopted to fill in the missing AOD retrievals and provide accurate long-term AOD aggregations. Monthly PM2.5 concentrations in China from 2000 to 2016 were estimated using machine-learning approaches and used to analyze spatiotemporal trends of adult mortality attributable to PM2.5 exposure. Mean coverage of AOD increased from 56 to 100% over the 17-y period, with the accuracy of long-term averages enhanced after gap filling. Machine-learning models performed well with a random cross-validation R 2 of 0.93 at the monthly level. For the time period outside the model training window, prediction R 2 values were estimated to be 0.67 and 0.80 at the monthly and annual levels. Across the adult population in China, long-term PM2.5 exposures accounted for a total number of 30.8 (95% confidence interval [CI]: 28.6, 33.2) million premature deaths over the 17-y period, with an annual burden ranging from 1.5 (95% CI: 1.3, 1.6) to 2.2 (95% CI: 2.1, 2.4) million. Our satellite-based techniques provide reliable long-term PM2.5 estimates at a high spatial resolution, enhancing the assessment of adverse health effects and disease burden in China.

PubMed ID: 32958653 Exiting the NIEHS site

MeSH Terms: Adult; Air Pollution/statistics & numerical data*; China; Environmental Exposure*/adverse effects; Environmental Exposure*/statistics & numerical data; Environmental Monitoring; Geographic Information Systems; Humans; Machine Learning; Models, Statistical; Mortality, Premature/trends*; Particulate Matter/analysis*; Spatio-Temporal Analysis

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