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Long-term health impact of PM(2.5) under whole-year COVID-19 lockdown in China()
The health impact of changes in particulate matter with an aerodynamic diameter <2.5 μm (PM(2.5)) 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 concent...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier Ltd.
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8419199/ https://www.ncbi.nlm.nih.gov/pubmed/34523527 http://dx.doi.org/10.1016/j.envpol.2021.118118 |
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author | Hao, Xin Li, Jiandong Wang, Huijun Liao, Hong Yin, Zhicong Hu, Jianlin Wei, Ying Dang, Ruijun |
author_facet | Hao, Xin Li, Jiandong Wang, Huijun Liao, Hong Yin, Zhicong Hu, Jianlin Wei, Ying Dang, Ruijun |
author_sort | Hao, Xin |
collection | PubMed |
description | The health impact of changes in particulate matter with an aerodynamic diameter <2.5 μm (PM(2.5)) 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 PM(2.5) concentrations in urban cities under permanent lockdown in 2020. The premature mortality attributable to long-term exposure to ambient PM(2.5) was quantified by the risk factor model from the latest epidemiological studies. Under a whole-year lockdown scenario, annual mean PM(2.5) 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 PM(2.5). 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 PM(2.5) were avoided. Because PM(2.5) 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. |
format | Online Article Text |
id | pubmed-8419199 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Elsevier Ltd. |
record_format | MEDLINE/PubMed |
spelling | pubmed-84191992021-09-07 Long-term health impact of PM(2.5) under whole-year COVID-19 lockdown in China() Hao, Xin Li, Jiandong Wang, Huijun Liao, Hong Yin, Zhicong Hu, Jianlin Wei, Ying Dang, Ruijun Environ Pollut Article The health impact of changes in particulate matter with an aerodynamic diameter <2.5 μm (PM(2.5)) 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 PM(2.5) concentrations in urban cities under permanent lockdown in 2020. The premature mortality attributable to long-term exposure to ambient PM(2.5) was quantified by the risk factor model from the latest epidemiological studies. Under a whole-year lockdown scenario, annual mean PM(2.5) 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 PM(2.5). 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 PM(2.5) were avoided. Because PM(2.5) 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. Elsevier Ltd. 2021-12-01 2021-09-06 /pmc/articles/PMC8419199/ /pubmed/34523527 http://dx.doi.org/10.1016/j.envpol.2021.118118 Text en © 2021 Elsevier Ltd. All rights reserved. Since January 2020 Elsevier has created a COVID-19 resource centre with free information in English and Mandarin on the novel coronavirus COVID-19. The COVID-19 resource centre is hosted on Elsevier Connect, the company's public news and information website. Elsevier hereby grants permission to make all its COVID-19-related research that is available on the COVID-19 resource centre - including this research content - immediately available in PubMed Central and other publicly funded repositories, such as the WHO COVID database with rights for unrestricted research re-use and analyses in any form or by any means with acknowledgement of the original source. These permissions are granted for free by Elsevier for as long as the COVID-19 resource centre remains active. |
spellingShingle | Article Hao, Xin Li, Jiandong Wang, Huijun Liao, Hong Yin, Zhicong Hu, Jianlin Wei, Ying Dang, Ruijun Long-term health impact of PM(2.5) under whole-year COVID-19 lockdown in China() |
title | Long-term health impact of PM(2.5) under whole-year COVID-19 lockdown in China() |
title_full | Long-term health impact of PM(2.5) under whole-year COVID-19 lockdown in China() |
title_fullStr | Long-term health impact of PM(2.5) under whole-year COVID-19 lockdown in China() |
title_full_unstemmed | Long-term health impact of PM(2.5) under whole-year COVID-19 lockdown in China() |
title_short | Long-term health impact of PM(2.5) under whole-year COVID-19 lockdown in China() |
title_sort | long-term health impact of pm(2.5) under whole-year covid-19 lockdown in china() |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8419199/ https://www.ncbi.nlm.nih.gov/pubmed/34523527 http://dx.doi.org/10.1016/j.envpol.2021.118118 |
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