Cargando…

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...

Descripción completa

Detalles Bibliográficos
Autores principales: Zhao, Laijun, Wang, Yu, Zhang, Honghao, Qian, Ying, Yang, Pingle, Zhou, Lixin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer Netherlands 2022
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
_version_ 1784693279274565632
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
work_keys_str_mv AT zhaolaijun diversespillovereffectsofcovid19controlmeasuresonairqualityimprovementevidencefromtypicalchinesecities
AT wangyu diversespillovereffectsofcovid19controlmeasuresonairqualityimprovementevidencefromtypicalchinesecities
AT zhanghonghao diversespillovereffectsofcovid19controlmeasuresonairqualityimprovementevidencefromtypicalchinesecities
AT qianying diversespillovereffectsofcovid19controlmeasuresonairqualityimprovementevidencefromtypicalchinesecities
AT yangpingle diversespillovereffectsofcovid19controlmeasuresonairqualityimprovementevidencefromtypicalchinesecities
AT zhoulixin diversespillovereffectsofcovid19controlmeasuresonairqualityimprovementevidencefromtypicalchinesecities