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Air pollution estimation under air stagnation—A case study of Beijing

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  • Ying Zhang
  • Song Xi Chen
  • Le Bao

Abstract

Air pollution continues to be a major environmental concern in China. The wind‐driven transmission poses difficulties in understanding the air pollution patterns at the local level. The main objective of this study is to offer a straightforward approach for investigating the temporal trends and meteorological effects on the air pollutant concentrations during the generation process without being confounded by the complex wind‐driven transmission effect. We focus on the hourly data of the three most common air pollutants: PM2.5, NO2$$ {}_2 $$, and CO under air stagnation in Beijing, China, during 2014–2017. We find that the local pollution levels under air stagnation in Beijing have decreased over the years; winter is the severest month of the year; Sunday is the clearest day of the week. Our model also interpolates the air pollutant concentrations at sites without monitoring stations and provides a map of air pollution concentrations under air stagnation. The results could be used to identify locations where air pollutants easily accumulate.

Suggested Citation

  • Ying Zhang & Song Xi Chen & Le Bao, 2023. "Air pollution estimation under air stagnation—A case study of Beijing," Environmetrics, John Wiley & Sons, Ltd., vol. 34(6), September.
    • Handle: RePEc:wly:envmet:v:34:y:2023:i:6:n:e2819
    DOI: 10.1002/env.2819
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    References listed on IDEAS

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    Cited by:

    1. Xin Wang & Xin Zhang, 2024. "Scanner: Simultaneously temporal trend and spatial cluster detection for spatial‐temporal data," Environmetrics, John Wiley & Sons, Ltd., vol. 35(5), August.

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