IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v14y2022i17p11034-d906345.html
   My bibliography  Save this article

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

Author

Listed:
  • 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)

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.

Suggested Citation

  • Xiaoyan Dai & Chao Wei & Liguo Zhou & Ping Li, 2022. "Identification and Characterization of PM 2.5 Emission Sources in Shanghai during COVID-19 Pandemic in the Winter of 2020," Sustainability, MDPI, vol. 14(17), pages 1-15, September.
    • Handle: RePEc:gam:jsusta:v:14:y:2022:i:17:p:11034-:d:906345
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/14/17/11034/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2071-1050/14/17/11034/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Yaolin Lin & Jiale Zou & Wei Yang & Chun-Qing Li, 2018. "A Review of Recent Advances in Research on PM 2.5 in China," IJERPH, MDPI, vol. 15(3), pages 1-29, March.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Yanzhao Wang & Jianfei Cao, 2023. "Examining the Effects of Socioeconomic Development on Fine Particulate Matter (PM2.5) in China’s Cities Based on Spatial Autocorrelation Analysis and MGWR Model," IJERPH, MDPI, vol. 20(4), pages 1-23, February.
    2. Nan Jia & Yinshuai Li & Ruishan Chen & Hongbo Yang, 2023. "A Review of Global PM 2.5 Exposure Research Trends from 1992 to 2022," Sustainability, MDPI, vol. 15(13), pages 1-15, July.
    3. Wei Xue & Qingming Zhan & Qi Zhang & Zhonghua Wu, 2019. "Spatiotemporal Variations of Particulate and Gaseous Pollutants and Their Relations to Meteorological Parameters: The Case of Xiangyang, China," IJERPH, MDPI, vol. 17(1), pages 1-23, December.
    4. Hugo Wai Leung Mak & Daisy Chiu Yi Ng, 2021. "Spatial and Socio-Classification of Traffic Pollutant Emissions and Associated Mortality Rates in High-Density Hong Kong via Improved Data Analytic Approaches," IJERPH, MDPI, vol. 18(12), pages 1-27, June.
    5. Daoru Liu & Qinli Deng & Zeng Zhou & Yaolin Lin & Junwei Tao, 2018. "Variation Trends of Fine Particulate Matter Concentration in Wuhan City from 2013 to 2017," IJERPH, MDPI, vol. 15(7), pages 1-18, July.
    6. Aleksei S. Kholodov & Irina A. Tarasenko & Ekaterina A. Zinkova & Michele Teodoro & Anca Oana Docea & Daniela Calina & Aristidis Tsatsakis & Kirill S. Golokhvast, 2021. "The Study of Airborne Particulate Matter in Dalnegorsk Town," IJERPH, MDPI, vol. 18(17), pages 1-14, September.
    7. Timofey Leshukov & Konstantin Legoshchin & Olga Yakovenko & Sebastian Bach & Dmitriy Russakov & Daria Dimakova & Evgeniya Vdovina & Elizaveta Baranova & Kirill Avdeev & Elena Kolpina & Karina Oshchepk, 2022. "Fractional Composition and Toxicity Coal–Rock of PM 10 -PM 0.1 Dust near an Opencast Coal Mining Area and Coal-Fired Power Station," Sustainability, MDPI, vol. 14(24), pages 1-17, December.
    8. Zifeng Liang & Manli Zhang & Qingduo Mao & Bingxin Yu & Ben Ma, 2018. "Improvement of Eco-Efficiency in China: A Comparison of Mandatory and Hybrid Environmental Policy Instruments," IJERPH, MDPI, vol. 15(7), pages 1-20, July.
    9. Bowen He & Qun Guan, 2021. "A Risk and Decision Analysis Framework to Evaluate Future PM 2.5 Risk: A Case Study in Los Angeles-Long Beach Metro Area," IJERPH, MDPI, vol. 18(9), pages 1-23, May.
    10. Xingchuan Yang & Lei Jiang & Wenji Zhao & Qiulin Xiong & Wenhui Zhao & Xing Yan, 2018. "Comparison of Ground-Based PM 2.5 and PM 10 Concentrations in China, India, and the U.S," IJERPH, MDPI, vol. 15(7), pages 1-16, July.
    11. Dipak Kumar Mandal & Sharmistha Bose & Nirmalendu Biswas & Nirmal K. Manna & Erdem Cuce & Ali Cemal Benim, 2024. "Solar Chimney Power Plants for Sustainable Air Quality Management Integrating Photocatalysis and Particulate Filtration: A Comprehensive Review," Sustainability, MDPI, vol. 16(6), pages 1-31, March.
    12. Xiaowei Xu & Daxin Dong & Yilun Wang & Shiying Wang, 2019. "The Impacts of Different Air Pollutants on Domestic and Inbound Tourism in China," IJERPH, MDPI, vol. 16(24), pages 1-15, December.
    13. Sungwan Son & Aya Elkamhawy & Choon-Man Jang, 2022. "Active Soil Filter System for Indoor Air Purification in School Classrooms," IJERPH, MDPI, vol. 19(23), pages 1-16, November.
    14. Bo Li & Qingfeng Cao & Muhammad Mohiuddin, 2020. "Factors Influencing the Settlement Intentions of Chinese Migrants in Cities: An Analysis of Air Quality and Higher Income Opportunity as Predictors," IJERPH, MDPI, vol. 17(20), pages 1-18, October.
    15. Thomas M. T. Lei & Stanley C. W. Ng & Shirley W. I. Siu, 2023. "Application of ANN, XGBoost, and Other ML Methods to Forecast Air Quality in Macau," Sustainability, MDPI, vol. 15(6), pages 1-17, March.
    16. Ali Asghar Heidari & Mehdi Akhoondzadeh & Huiling Chen, 2022. "A Wavelet PM2.5 Prediction System Using Optimized Kernel Extreme Learning with Boruta-XGBoost Feature Selection," Mathematics, MDPI, vol. 10(19), pages 1-35, September.
    17. Ming Zeng & Jiang Du & Weike Zhang, 2019. "Spatial-Temporal Effects of PM 2.5 on Health Burden: Evidence from China," IJERPH, MDPI, vol. 16(23), pages 1-23, November.
    18. Hone-Jay Chu & Muhammad Zeeshan Ali, 2020. "Establishment of Regional Concentration–Duration–Frequency Relationships of Air Pollution: A Case Study for PM 2.5," IJERPH, MDPI, vol. 17(4), pages 1-13, February.
    19. Zhao, Chuanmin & Xie, Rui & Ma, Chunbo & Han, Feng, 2022. "Understanding the haze pollution effects of China's development zone program," Energy Economics, Elsevier, vol. 111(C).
    20. Le Yang & Jiahao Zhang & Yufeng Zhang, 2021. "Environmental Regulations and Corporate Green Innovation in China: The Role of City Leaders’ Promotion Pressure," IJERPH, MDPI, vol. 18(15), pages 1-21, July.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jsusta:v:14:y:2022:i:17:p:11034-:d:906345. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.