A Pre- to Post-COVID-19 Change of Air Quality Patterns in Anhui Province Using Path Analysis and Regression
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School of Information and Communication Engineering, Hainan University, Haikou 570228, China
State Key Laboratory of Millimeter Waves, Southeast University, Nanjing 211189, China
Department of Computer Engineering, Balochistan University of Information Technology, Engineering, and Management Sciences (BUITEMS), Quetta, Pakistan
Department of Information Technology, Balochistan University of Information Technology, Engineering, and Management Sciences (BUITEMS), Quetta, Pakistan
School of Geography, Nanjing Normal University, Nanjing, 210023, China
Key Laboratory of Tropical Biological Resources of Ministry of Education, School of Life and Pharmaceutical Sciences, Hainan University, Haikou, 570228, China
Submission date: 2021-10-26
Final revision date: 2022-03-23
Acceptance date: 2022-04-05
Online publication date: 2022-07-05
Publication date: 2022-09-01
Pol. J. Environ. Stud. 2022;31(5):4029–4042
During the epidemic period, primary emissions across the world were significantly reduced, while the response to secondary pollution such as ozone differed from region to region. To study the impact of the strict control measures of the new COVID-19 epidemic on the air quality of Anhui in early 2020, the air quality monitoring data of Anhui, from 2019 to 2021, specifically 1 January to 30 August, was examined to analyze the characteristics of the temporal and spatial distribution. Regression and path analysis were used to extract the relationship between the variable. PM10 and O3, on average, increased by 6%, and 2%, while PM2.5, SO2 decreased by 15% and 10% in the post-COVID-19 period. All air quality pollutants decreased during the active-COVID-19 period, with a maximum decrease of 21% observed in PM10, followed by 19% of PM2.5, and a minimum decrease of 2% observed in O3. Changes in air pollutants from 2017 to 2021 were also compared, and a decrease in all pollutants through 2020 was found. The air quality index (AQI) recorded a low decrease of 3% post-COVID-19, which shows that air quality will worsen in the future, but it decreased by 16% during the active-COVID-19 period. A path analysis model was developed to further understand the relationship between the AQI and air quality patterns. This path analysis shows a strong correlation between the AQI and PM10 and PM2.5, however, its correlation with other air pollutants is weak. Regression analysis shows a similar pattern of there being a strong relationship between AQI and PM10(r2 = 0.97) and PM2.5(r2 = 0.93). The government must implement policies to control the environmental issues which are causing poor air quality in post-COVID-19.