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Changes of air quality and its associated health and economic burden in 31 provincial capital cities in China during COVID-19 pandemic.
Nie, Dongyang; Shen, Fuzhen; Wang, Junfeng; Ma, Xiaoyun; Li, Zhirao; Ge, Pengxiang; Ou, Yang; Jiang, Yuan; Chen, Meijuan; Chen, Mindong; Wang, Tijian; Ge, Xinlei.
  • Nie D; School of Atmospheric Sciences, Nanjing University, Nanjing 210023, China.
  • Shen F; Jiangsu Key Laboratory of Atmospheric Environment Monitoring and Pollution Control, Collaborative Innovation Center of Atmospheric Environment and Equipment Technology, School of Environmental Science and Engineering, Nanjing University of Information Science and Technology, Nanjing 210044, China.
  • Wang J; John A. Paulson School of Engineering and Applied Sciences, Harvard University, Cambridge, MA 02138, USA.
  • Ma X; Jiangsu Key Laboratory of Atmospheric Environment Monitoring and Pollution Control, Collaborative Innovation Center of Atmospheric Environment and Equipment Technology, School of Environmental Science and Engineering, Nanjing University of Information Science and Technology, Nanjing 210044, China.
  • Li Z; Jiangsu Key Laboratory of Atmospheric Environment Monitoring and Pollution Control, Collaborative Innovation Center of Atmospheric Environment and Equipment Technology, School of Environmental Science and Engineering, Nanjing University of Information Science and Technology, Nanjing 210044, China.
  • Ge P; Jiangsu Key Laboratory of Atmospheric Environment Monitoring and Pollution Control, Collaborative Innovation Center of Atmospheric Environment and Equipment Technology, School of Environmental Science and Engineering, Nanjing University of Information Science and Technology, Nanjing 210044, China.
  • Ou Y; Jiangsu Key Laboratory of Atmospheric Environment Monitoring and Pollution Control, Collaborative Innovation Center of Atmospheric Environment and Equipment Technology, School of Environmental Science and Engineering, Nanjing University of Information Science and Technology, Nanjing 210044, China.
  • Jiang Y; Jiangsu Key Laboratory of Atmospheric Environment Monitoring and Pollution Control, Collaborative Innovation Center of Atmospheric Environment and Equipment Technology, School of Environmental Science and Engineering, Nanjing University of Information Science and Technology, Nanjing 210044, China.
  • Chen M; Jiangsu Key Laboratory of Atmospheric Environment Monitoring and Pollution Control, Collaborative Innovation Center of Atmospheric Environment and Equipment Technology, School of Environmental Science and Engineering, Nanjing University of Information Science and Technology, Nanjing 210044, China.
  • Chen M; Jiangsu Key Laboratory of Atmospheric Environment Monitoring and Pollution Control, Collaborative Innovation Center of Atmospheric Environment and Equipment Technology, School of Environmental Science and Engineering, Nanjing University of Information Science and Technology, Nanjing 210044, China.
  • Wang T; School of Atmospheric Sciences, Nanjing University, Nanjing 210023, China.
  • Ge X; Jiangsu Key Laboratory of Atmospheric Environment Monitoring and Pollution Control, Collaborative Innovation Center of Atmospheric Environment and Equipment Technology, School of Environmental Science and Engineering, Nanjing University of Information Science and Technology, Nanjing 210044, China.
Atmos Res ; 249: 105328, 2021 Feb.
Article in English | MEDLINE | ID: covidwho-880403
ABSTRACT
With outbreak of the novel coronavirus disease (COVID-19), immediate prevention and control actions were imposed in China. Here, we conducted a timely investigation on the changes of air quality, associated health burden and economic loss during the COVID-19 pandemic (January 1 to May 2, 2020). We found an overall improvement of air quality by analyzing data from 31 provincial cities, due to varying degrees of NO2, PM2.5, PM10 and CO reductions outweighing the significant O3 increase. Such improvement corresponds to a total avoided premature mortality of 9410 (7273-11,144) in the 31 cities by comparing the health burdens between 2019 and 2020. NO2 reduction was the largest contributor (55%) to this health benefit, far exceeding PM2.5 (10.9%) and PM10 (23.9%). O3 instead was the only negative factor among six pollutants. The period with the largest daily avoided deaths was rather not the period with strict lockdown but that during February 25 to March 31, due to largest reduction of NO2 and smallest increase of O3. Southwest, Central and East China were regions with relatively high daily avoided deaths, while for some cities in Northeast China, the air pollution was even worse, therefore could cause more deaths than 2019. Correspondingly, the avoided health economic loss attributable to air quality improvement was 19.4 (15.0-23.0) billion. Its distribution was generally similar to results of health burden, except that due to regional differences in willingness to pay to reduce risks of premature deaths, East China became the region with largest daily avoided economic loss. Our results here quantitatively assess the effects of short-term control measures on changes of air quality as well as its associated health and economic burden, and such information is beneficial to future air pollution control.
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Full text: Available Collection: International databases Database: MEDLINE Type of study: Prognostic study Language: English Journal: Atmos Res Year: 2021 Document Type: Article Affiliation country: J.atmosres.2020.105328

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Full text: Available Collection: International databases Database: MEDLINE Type of study: Prognostic study Language: English Journal: Atmos Res Year: 2021 Document Type: Article Affiliation country: J.atmosres.2020.105328