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Temporal characteristics and spatial heterogeneity of air quality changes due to the COVID-19 lockdown in China

Previous studies have evaluated the impact of lockdown measures on air quality during the COVID-19 pandemic in China, but few have focused on the temporal characteristics and spatial heterogeneity of the impact across all 337 prefecture cities. In this study, we estimated the impact of the lockdown...

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Detalles Bibliográficos
Autores principales: Zeng, Jinghai, Wang, Can
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier B.V. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8825306/
https://www.ncbi.nlm.nih.gov/pubmed/35153377
http://dx.doi.org/10.1016/j.resconrec.2022.106223
Descripción
Sumario:Previous studies have evaluated the impact of lockdown measures on air quality during the COVID-19 pandemic in China, but few have focused on the temporal characteristics and spatial heterogeneity of the impact across all 337 prefecture cities. In this study, we estimated the impact of the lockdown measures on air quality in each of 337 cities using the Regression Discontinuity in Time method. There was a short-term influence from January 24th to March 31th in 2020. The 337 cities could be divided into six categories showing different response and resilience patterns to the epidemic. Fine particulate matter (PM(2.5)) in 89.5% of the cities was sensitive to the lockdown measures. The change of air pollutants showed high spatial heterogeneity. The provinces with a greater than 20% reduction in PM(2.5) and PM(10) and greater than 40% reduction in NO(2) during the impact period were mainly concentrated southeast of the “Hu Line”. Compared to the no-pandemic scenario, the national annual average concentration of PM(2.5), NO(2), PM(10), SO(2), and CO in 2020 were decreased by 6.3%, 10.6%, 7.4%, 9.0%, and 12.5%, respectively, while that of O(3) increased by 1.1%.This result indicates that 2020 can still be used as a baseline for setting and allocating air improvement targets for the next five years.