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Assessing the change of ambient air quality patterns in Jiangsu Province of China pre-to post-COVID-19.
Bhatti, Uzair Aslam; Zeeshan, Zeeshan; Nizamani, Mir Muhammad; Bazai, Sibghatullah; Yu, Zhaoyuan; Yuan, Linwang.
Afiliação
  • Bhatti UA; School of Geography, Nanjing Normal University, Nanjing, 210023, China; Key Laboratory of Virtual Geographic Environment, Ministry of Education, Nanjing Normal University, No. 1 Wenyuan Road, Nanjing, China.
  • Zeeshan Z; Kymeta Corporation, Redmond, WA, USA.
  • Nizamani MM; Key Laboratory of Tropical Biological Resources of Ministry of Education, School of Life and Pharmaceutical Sciences, Hainan University, Haikou, 570228, China.
  • Bazai S; School of Natural and Computational Sciences, Massey University, Auckland, 0632, New Zealand; Department of Computer Engineering, BUITEMS, Quetta 87300, Pakistan.
  • Yu Z; School of Geography, Nanjing Normal University, Nanjing, 210023, China; Key Laboratory of Virtual Geographic Environment, Ministry of Education, Nanjing Normal University, No. 1 Wenyuan Road, Nanjing, China.
  • Yuan L; School of Geography, Nanjing Normal University, Nanjing, 210023, China; Key Laboratory of Virtual Geographic Environment, Ministry of Education, Nanjing Normal University, No. 1 Wenyuan Road, Nanjing, China. Electronic address: 09142@njnu.edu.cn.
Chemosphere ; 288(Pt 2): 132569, 2022 Feb.
Article em En | MEDLINE | ID: mdl-34655644
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.
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Texto completo: 1 Base de dados: MEDLINE Assunto principal: Poluição do Ar / COVID-19 Limite: Humans País/Região como assunto: Asia Idioma: En Revista: Chemosphere Ano de publicação: 2022 Tipo de documento: Article País de afiliação: China

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Poluição do Ar / COVID-19 Limite: Humans País/Região como assunto: Asia Idioma: En Revista: Chemosphere Ano de publicação: 2022 Tipo de documento: Article País de afiliação: China