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Assessment of health benefit of PM2.5 reduction during COVID-19 lockdown in China and separating contributions from anthropogenic emissions and meteorology.
Bai, Heming; Gao, Wenkang; Zhang, Yuanpeng; Wang, Li.
  • Bai H; Research Center for Intelligent Information Technology, Nantong University, Nantong 226019, China; Nantong Research Institute for Advanced Communication Technologies, Nantong 226019, China.
  • Gao W; State Key Laboratory of Atmospheric Boundary Layer Physics and Atmospheric Chemistry, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029, China.
  • Zhang Y; Research Center for Intelligent Information Technology, Nantong University, Nantong 226019, China; Department of Medical Informatics, Medical School, Nantong University, Nantong 226019, China.
  • Wang L; Research Center for Intelligent Information Technology, Nantong University, Nantong 226019, China; Nantong Research Institute for Advanced Communication Technologies, Nantong 226019, China; Department of Medical Informatics, Medical School, Nantong University, Nantong 226019, China. Electronic addre
J Environ Sci (China) ; 115: 422-431, 2022 May.
Article in English | MEDLINE | ID: covidwho-1046320
ABSTRACT
The national lockdown policies have drastically disrupted socioeconomic activities during the COVID-19 pandemic in China, which provides a unique opportunity to investigate the air quality response to such anthropogenic disruptions. And it is meaningful to evaluate the potential health impacts of air quality changes during the lockdown, especially for PM2.5 with adverse health effects. In this study, by using PM2.5 observations from 1388 monitoring stations nationwide in China, we examine the PM2.5 variations between the COVID-19 lockdown (February and March in 2020) and the same period in 2015-2019, and find that the national average of PM2.5 decreases by 18 µg/m3, and mean PM2.5 for most sites (about 75%) decrease by 30%-60%. The anthropogenic and meteorological contributions to these PM2.5 variations are also determined by using a stepwise multiple linear regression (MLR) model combined with the Kolmogorov-Zurbenko filter. Our results show that the change of anthropogenic emissions is a leading contributor to those widespread PM2.5 reductions, and meteorological conditions have the negative influence on PM2.5 reductions for some regions, such as Beijing-Tianjin-Hebei (BTH). Additionally, the avoided premature death due to PM2.5 reduction is estimated as a predicted number based on a log-linear concentration-response function. The total avoided premature death is 9952 in China, with dominant contribution (94%) from anthropogenic emission changes. For BTH, Yangtze River Delta, Pearl River Delta and Hubei regions, the reductions of PM2.5 are 24.1, 24.3, 13.5 and 29.5 µg/m3, with the avoided premature deaths of 1066, 1963, 454 and 583, respectively.
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Full text: Available Collection: International databases Database: MEDLINE Main subject: Air Pollutants / Air Pollution / COVID-19 Type of study: Experimental Studies / Observational study / Prognostic study Limits: Humans Country/Region as subject: Asia Language: English Journal: J Environ Sci (China) Journal subject: Environmental Health Year: 2022 Document Type: Article Affiliation country: J.jes.2021.01.022

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Full text: Available Collection: International databases Database: MEDLINE Main subject: Air Pollutants / Air Pollution / COVID-19 Type of study: Experimental Studies / Observational study / Prognostic study Limits: Humans Country/Region as subject: Asia Language: English Journal: J Environ Sci (China) Journal subject: Environmental Health Year: 2022 Document Type: Article Affiliation country: J.jes.2021.01.022