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<p>The intensity and frequency of severe fine particulate matter (PM<sub>2.5</sub>) pollution events in Shanghai have reduced following strict emission controls. However, an unexpected resurgence of PM<sub>2.5</sub> occurred during 2023–2024 winter (peak 162.7 μg m<sup>−3</sup>, highest since 2018–2019), yet its characteristics and underlying drivers remain unclear. Using observations, the Community Multiscale Air Quality (CMAQ) model, and machine learning (eXtreme Gradient Boosting [XGBOOST], SHapley Additive exPlanations [SHAP]), this study revealed that nitrate (NO<sub>3</sub><sup>−</sup>) dominated PM<sub>2.5</sub> composition (33%) and three of four pollution events, primarily from local emissions (16.8%) and adjacent transport (39.4%), with volatile organic compounds (VOCs), relative humidity, and ammonia (NH<sub>3</sub>) as key factors. Sensitivity analyses demonstrated NH<sub>3</sub> reductions effectively reduced NO<sub>3</sub><sup>−</sup> and PM<sub>2.5</sub> in Shanghai, while VOCs controls showed greater efficacy for PM<sub>2.5</sub> at low reduction levels, though regional effectiveness varied. These findings highlight the importance of VOCs and NH<sub>3</sub> reductions to mitigate NO<sub>3</sub><sup>−</sup> and PM<sub>2.5</sub> pollution in Shanghai and eastern China.</p>

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Nitrate-driven extreme winter PM2.5 pollution in Shanghai, China

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2025年10月1日

查看全文
  • Guochao Chen,
  • Yiheng Wang,
  • Chenliang Tao,
  • Zhaolei Zhang,
  • Min Zhou,
  • Rusha Yan,
  • Dan Dan Huang,
  • Hongli Wang,
  • Hongliang Zhang

摘要

The intensity and frequency of severe fine particulate matter (PM2.5) pollution events in Shanghai have reduced following strict emission controls. However, an unexpected resurgence of PM2.5 occurred during 2023–2024 winter (peak 162.7 μg m−3, highest since 2018–2019), yet its characteristics and underlying drivers remain unclear. Using observations, the Community Multiscale Air Quality (CMAQ) model, and machine learning (eXtreme Gradient Boosting [XGBOOST], SHapley Additive exPlanations [SHAP]), this study revealed that nitrate (NO3−) dominated PM2.5 composition (33%) and three of four pollution events, primarily from local emissions (16.8%) and adjacent transport (39.4%), with volatile organic compounds (VOCs), relative humidity, and ammonia (NH3) as key factors. Sensitivity analyses demonstrated NH3 reductions effectively reduced NO3− and PM2.5 in Shanghai, while VOCs controls showed greater efficacy for PM2.5 at low reduction levels, though regional effectiveness varied. These findings highlight the importance of VOCs and NH3 reductions to mitigate NO3− and PM2.5 pollution in Shanghai and eastern China.