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Diverse spillover effects of COVID-19 control measures on air quality improvement: evidence from typical Chinese cities
The COVID-19 prevention and control measures are taken by China’s government, especially traffic restrictions and production suspension, had spillover effects on air quality improvement. These effects differed among cities, but these differences have not been adequately studied. To provide more know...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer Netherlands
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9035376/ https://www.ncbi.nlm.nih.gov/pubmed/35493768 http://dx.doi.org/10.1007/s10668-022-02353-z |
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author | Zhao, Laijun Wang, Yu Zhang, Honghao Qian, Ying Yang, Pingle Zhou, Lixin |
author_facet | Zhao, Laijun Wang, Yu Zhang, Honghao Qian, Ying Yang, Pingle Zhou, Lixin |
author_sort | Zhao, Laijun |
collection | PubMed |
description | The COVID-19 prevention and control measures are taken by China’s government, especially traffic restrictions and production suspension, had spillover effects on air quality improvement. These effects differed among cities, but these differences have not been adequately studied. To provide more knowledge, we studied the air quality index (AQI) and five air pollutants (PM(2.5), PM(10), SO(2), NO(2), and O(3)) before and after the COVID-19 outbreak in Shanghai, Wuhan, and Tangshan. The pollution data from two types of monitoring stations (traffic and non-traffic stations) were separately compared and evaluated. We used monitoring data from the traffic stations to study the emission reduction caused by traffic restrictions. Based on monitoring data from the non-traffic stations, we established a difference-in-difference model to study the emission reduction caused by production suspension. The COVID-19 control measures reduced AQI and the concentrations of all pollutants except O(3) (which increased greatly), but the magnitude of the changes differed among the three cities. The control measures improved air quality most in Wuhan, followed by Shanghai and then Tangshan. We investigated the reasons for these differences and found that differences in the characteristics of these three types of cities could explain these differences in spillover effects. Understanding these differences could provide some guidance and support for formulating differentiated air pollution control measures in different cities. For example, whole-process emission reduction technology should be adopted in cities with the concentrated distribution of continuous process enterprises, whereas vehicles that use cleaner energy and public transport should be vigorously promoted in cities with high traffic development level. |
format | Online Article Text |
id | pubmed-9035376 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Springer Netherlands |
record_format | MEDLINE/PubMed |
spelling | pubmed-90353762022-04-25 Diverse spillover effects of COVID-19 control measures on air quality improvement: evidence from typical Chinese cities Zhao, Laijun Wang, Yu Zhang, Honghao Qian, Ying Yang, Pingle Zhou, Lixin Environ Dev Sustain Article The COVID-19 prevention and control measures are taken by China’s government, especially traffic restrictions and production suspension, had spillover effects on air quality improvement. These effects differed among cities, but these differences have not been adequately studied. To provide more knowledge, we studied the air quality index (AQI) and five air pollutants (PM(2.5), PM(10), SO(2), NO(2), and O(3)) before and after the COVID-19 outbreak in Shanghai, Wuhan, and Tangshan. The pollution data from two types of monitoring stations (traffic and non-traffic stations) were separately compared and evaluated. We used monitoring data from the traffic stations to study the emission reduction caused by traffic restrictions. Based on monitoring data from the non-traffic stations, we established a difference-in-difference model to study the emission reduction caused by production suspension. The COVID-19 control measures reduced AQI and the concentrations of all pollutants except O(3) (which increased greatly), but the magnitude of the changes differed among the three cities. The control measures improved air quality most in Wuhan, followed by Shanghai and then Tangshan. We investigated the reasons for these differences and found that differences in the characteristics of these three types of cities could explain these differences in spillover effects. Understanding these differences could provide some guidance and support for formulating differentiated air pollution control measures in different cities. For example, whole-process emission reduction technology should be adopted in cities with the concentrated distribution of continuous process enterprises, whereas vehicles that use cleaner energy and public transport should be vigorously promoted in cities with high traffic development level. Springer Netherlands 2022-04-25 2023 /pmc/articles/PMC9035376/ /pubmed/35493768 http://dx.doi.org/10.1007/s10668-022-02353-z Text en © The Author(s), under exclusive licence to Springer Nature B.V. 2022 This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic. |
spellingShingle | Article Zhao, Laijun Wang, Yu Zhang, Honghao Qian, Ying Yang, Pingle Zhou, Lixin Diverse spillover effects of COVID-19 control measures on air quality improvement: evidence from typical Chinese cities |
title | Diverse spillover effects of COVID-19 control measures on air quality improvement: evidence from typical Chinese cities |
title_full | Diverse spillover effects of COVID-19 control measures on air quality improvement: evidence from typical Chinese cities |
title_fullStr | Diverse spillover effects of COVID-19 control measures on air quality improvement: evidence from typical Chinese cities |
title_full_unstemmed | Diverse spillover effects of COVID-19 control measures on air quality improvement: evidence from typical Chinese cities |
title_short | Diverse spillover effects of COVID-19 control measures on air quality improvement: evidence from typical Chinese cities |
title_sort | diverse spillover effects of covid-19 control measures on air quality improvement: evidence from typical chinese cities |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9035376/ https://www.ncbi.nlm.nih.gov/pubmed/35493768 http://dx.doi.org/10.1007/s10668-022-02353-z |
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