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. 2022 Feb;288(Pt 2):132569.
doi: 10.1016/j.chemosphere.2021.132569. Epub 2021 Oct 14.

Assessing the change of ambient air quality patterns in Jiangsu Province of China pre-to post-COVID-19

Uzair Aslam Bhatti  1 , Zeeshan Zeeshan  2 , Mir Muhammad Nizamani  3 , Sibghatullah Bazai  4 , Zhaoyuan Yu  1 , Linwang Yuan  5
Affiliations

Assessing the change of ambient air quality patterns in Jiangsu Province of China pre-to post-COVID-19

Uzair Aslam Bhatti et al. Chemosphere. 2022 Feb.

Abstract

Following the outbreak of the novel coronavirus in early 2020, to effectively prevent the spread of the disease, major cities across China suspended work and production. While the rest of the world struggles to control COVID-19, China has managed to control the pandemic rapidly and effectively with strong lockdown policies. This study investigates the change in air pollution (focusing on the air quality index (AQI), six ambient air pollutants nitrogen dioxide (NO2), ozone (O3), sulphur dioxide (SO2), carbon monoxide (CO), particulate matter with aerodynamic diameters ≤10 μm (PM10) and ≤2.5 μm (PM2.5)) patterns for three periods: pre-COVID (from 1 January to May 30, 2019), active COVID (from 1 January to May 30, 2020) and post-COVID (from 1 January to May 30, 2021) in the Jiangsu province of China. Our findings reveal that the change in air pollution from pre-COVID to active COVID was greater than in previous years due to the government's lockdown policies. Post-COVID, air pollutant concentration is increasing. Mean change PM2.5 from pre-COVID to active COVID decreased by 18%; post-COVID it has only decreased by 2%. PM10 decreased by 19% from pre-COVID to active COVID, but post-COVID pollutant concentration has seen a 23% increase. Air pollutants show a positive correlation with COVID-19 cases among which PM2.5, PM10 and NO2 show a strong correlation during active COVID-19 cases. Metrological factors such as minimum temperature, average temperature and humidity show a positive correlation with COVID-19 cases while maximum temperature, wind speed and air pressure show no strong positive correlation. Although the COVID-19 pandemic had numerous negative effects on human health and the global economy, the reduction in air pollution and significant improvement in ambient air quality likely had substantial short-term health benefits; the government must implement policies to control post-COVID environmental issues.

Keywords: Air pollution; COVID-19; China; Particulate matter.

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Conflict of interest statement

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Figures

Image 1
Graphical abstract
Fig. 1
Fig. 1
Study area of Jiangsu with locations of monitoring stations in each city.
Fig. 2
Fig. 2
Daily change in air pollutants and AQI during COVID-19.
Fig. 3
Fig. 3
City-wise comparison of air pollutants and AQI (pre-COVID, active COVID, post-COVID).
Fig. 4
Fig. 4
Yearly change in the concentration of pollutants 2017–2021.
Fig. 5
Fig. 5
Correlation between AQI and air pollutants pre-COVID (2019), during active COVID (2020) and post-COVID (2021).
Fig. 6
Fig. 6
Change of air quality pattern of AQI and pollutants pre-COVID (2019), active COVID (2020) and post-COVID (2021).
See this image and copyright information in PMC

References

    1. Akhbarizadeh R., Dobaradaran S., Torkmahalleh M.A., Saeedi R., Aibaghi R., Ghasemi F.F. Suspended fine particulate matter (PM2. 5), microplastics (MPs), and polycyclic aromatic hydrocarbons (PAHs) in air: their possible relationships and health implications. Environ. Res. 2021;192:110339. - PubMed
    1. Ai J., Shi N., Shi Y., Xu K., Dai Q., Liu W., et al. vol. 149. Epidemiology & Infection; 2021. (Epidemiologic Characteristics and Influencing Factors of Cluster Infection of COVID-19 in Jiangsu Province). - PMC - PubMed
    1. Bai Y., Ni Y., Zeng Q. Impact of ambient air quality standards revision on the exposure-response of air pollution in Tianjin, China. Environ. Res. 2021;198:111269. - PubMed
    1. Baidu COVID-19 https://voice.baidu.com/act/newpneumonia/newpneumonia/?from=osari_aladin... accessed on 29th August 2021.
    1. Beig G., Korhale N., Rathod A., Maji S., Sahu S.K., Dole S., et al. On modelling growing menace of household emissions under COVID-19 in Indian metros. Environ. Pollut. 2021;272:115993. - PubMed