Identification and Characterization of PM 2.5 Emission Sources in Shanghai during COVID-19 Pandemic in the Winter of 2020

Xiaoyan Dai, Chao Wei (), Liguo Zhou () and Ping Li
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Xiaoyan Dai: Department of Environmental Science and Engineering, Fudan University, Shanghai 200438, China
Chao Wei: College of Surveying and Geo-Informatics, Tongji University, Shanghai 200092, China
Liguo Zhou: Department of Environmental Science and Engineering, Fudan University, Shanghai 200438, China
Ping Li: College of Biological and Environmental Sciences, Zhejiang Wanli University, Ningbo 315000, China

Sustainability, 2022, vol. 14, issue 17, 1-15

Abstract: The novel coronavirus (COVID-19) epidemic broke out in Wuhan at the end of 2019 and spread around the whole of China in 2020. In order to reduce the spread of COVID-19, transportation and industrial activities in different regions were limited to varying degrees. This study uses bivariate concentration polar plots, integrated with k-means clustering and temporal variation analyses for PM 2.5 time series data, to understand the PM 2.5 source characteristics in Shanghai during the COVID-19 pandemic in the winter of 2020. Our findings show that 34.33% of the PM 2.5 particles arise from external sources while 65.67% are from local sources. The results of source apportionment combined with land use, wind speed, and direction data are further used to locate the most likely directions of different source categories and geographic origins of PM 2.5 . During the lockdown period in 2020, traffic and industrial activity were still primary local sources of PM 2.5 emissions in Shanghai. The growth of motor vehicle ownership, limited public transport, and a large volume of freight transport in Shanghai result in a higher level of PM 2.5 concentrations on weekends than in midweeks. On the other hand, the regional-scale transport of air pollutants from the Yangtze River Delta, the Central Plains, the inland area of northern China, and coastal cities in the north and south of Shanghai aggravates PM 2.5 pollution in Shanghai under unfavorable meteorological conditions. The methods and results presented here lay a basis for further study on the complicated effects of meteorological and anthropogenic factors on PM 2.5 pollution and on the development of detailed and urgent strategies for the improvement of air quality.

Keywords: PM 2.5; source apportionment; bivariate polar plot; cluster analysis; COVID-19 (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2022
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