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Long-term health impact of PM2.5 under whole-year COVID-19 lockdown in China.
Hao, Xin; Li, Jiandong; Wang, Huijun; Liao, Hong; Yin, Zhicong; Hu, Jianlin; Wei, Ying; Dang, Ruijun.
Afiliação
  • Hao X; Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters/Key Laboratory of Meteorological Disaster, Ministry of Education, Nanjing University for Information Science & Technology, Nanjing, 210044, China; Nansen-Zhu International Research Centre, Institute of Atmosph
  • Li J; Jiangsu Key Laboratory of Atmospheric Environment Monitoring and Pollution Control, Jiangsu Collaborative Innovation Center of Atmospheric Environment and Equipment Technology, School of Environmental Science and Engineering, Nanjing University of Information Science & Technology, Nanjing, 21004
  • Wang H; Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters/Key Laboratory of Meteorological Disaster, Ministry of Education, Nanjing University for Information Science & Technology, Nanjing, 210044, China; Nansen-Zhu International Research Centre, Institute of Atmosph
  • Liao H; Jiangsu Key Laboratory of Atmospheric Environment Monitoring and Pollution Control, Jiangsu Collaborative Innovation Center of Atmospheric Environment and Equipment Technology, School of Environmental Science and Engineering, Nanjing University of Information Science & Technology, Nanjing, 21004
  • Yin Z; Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters/Key Laboratory of Meteorological Disaster, Ministry of Education, Nanjing University for Information Science & Technology, Nanjing, 210044, China; Nansen-Zhu International Research Centre, Institute of Atmosph
  • Hu J; Jiangsu Key Laboratory of Atmospheric Environment Monitoring and Pollution Control, Jiangsu Collaborative Innovation Center of Atmospheric Environment and Equipment Technology, School of Environmental Science and Engineering, Nanjing University of Information Science & Technology, Nanjing, 21004
  • Wei Y; Institute of Urban Meteorology, China Meteorology Administration, Beijing, 100089, China.
  • Dang R; State Key Laboratory of Atmospheric Boundary Layer Physics and Atmospheric Chemistry (LAPC), Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing, 100029, China.
Environ Pollut ; 290: 118118, 2021 Dec 01.
Article em En | MEDLINE | ID: mdl-34523527
ABSTRACT
The health impact of changes in particulate matter with an aerodynamic diameter <2.5 µm (PM2.5) pollution associated with the COVID-19 lockdown has aroused great interest, but the estimation of the long-term health effects is difficult because of the lack of an annual mean air pollutant concentration under a whole-year lockdown scenario. We employed a time series decomposition method to predict the monthly PM2.5 concentrations in urban cities under permanent lockdown in 2020. The premature mortality attributable to long-term exposure to ambient PM2.5 was quantified by the risk factor model from the latest epidemiological studies. Under a whole-year lockdown scenario, annual mean PM2.5 concentrations in cites ranged from 5.4 to 68.0 µg m-3, and the national mean concentration was reduced by 32.2% compared to the 2015-2019 mean. The Global Exposure Mortality Model estimated that 837.3 (95% CI 699.8-968.4) thousand people in Chinese cities would die prematurely from illnesses attributable to long-term exposure to ambient PM2.5. Compared to 2015-2019 mean levels, 140.2 (95% CI 122.2-156.0) thousand premature deaths (14.4% of the annual mean deaths from 2015 to 2019) attributable to long-term exposure to PM2.5 were avoided. Because PM2.5 concentrations were still high under the whole-year lockdown scenario, the health benefit is limited, indicating that continuous emission-cutting efforts are required to reduce the health risks of air pollution. Since a similar scenario may be achieved through promotion of electric vehicles and the innovation of industrial technology in the future, the estimated long-term health impact under the whole year lockdown scenario can establish an emission-air quality-health impact linkage and provide guidance for future emission control strategies from a health protection perspective.
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Texto completo: 1 Base de dados: MEDLINE Assunto principal: Poluentes Atmosféricos / Poluição do Ar / COVID-19 Tipo de estudo: Prognostic_studies / Risk_factors_studies Limite: Humans País como assunto: Asia Idioma: En Ano de publicação: 2021 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Poluentes Atmosféricos / Poluição do Ar / COVID-19 Tipo de estudo: Prognostic_studies / Risk_factors_studies Limite: Humans País como assunto: Asia Idioma: En Ano de publicação: 2021 Tipo de documento: Article