PM pollution characteristics, drivers, and regional transport during different pollution levels in Linyi, China: An integrated PMF-ML-SHAP framework and transport models.

Journal: Journal of hazardous materials
Published Date: May 8, 2025

Abstract

Despite significant progress in air quality improvement, heavy fine particulate matter (PM) pollution events persist in China. The pollution characteristics of PM vary during different pollution levels, highlighting the necessity for a deeper understanding of its underlying driving factors and regional transport. This study systematically investigated the compositional characteristics, drivers, and regional transport of PM in Linyi by integrating multi-data fusion analysis, positive matrix factorization-machine learning-shapley additive explanation (PMF-ML-SHAP), and concentration weighted trajectory model. The results revealed that heterogeneous reactions dominated SO formation during polluted periods, while homogeneous reactions drove NO formation. In constructing the integrated PMF-ML-SHAP framework, RandomizedSearchCV and KFold techniques significantly enhanced CatBoost model performance. The contribution of local sources increased progressively from 85.6 % to 91.4 % with rising PM levels, with secondary nitrate formation emerging as the dominant driver of PM pollution. The influence share of biomass combustion was higher during clean (CP, 20.4 %) and slightly polluted periods (SPP, 17.3 %), while that of firework combustion was higher during heavily polluted periods (HPP, 25.9 %). Among meteorological factors, wind speed and ultraviolet radiation intensity played critical roles in PM dispersion and secondary aerosol formation. Regional transport analysis indicated that short-range and medium-range transport air masses primarily influenced CP and SPP, whereas local transport air masses dominated during moderately polluted periods (MPP, 54.4 %) and HPP (58.2 %). This study provides new insights into the drivers of PM pollution during different pollution levels, offering a scientific basis for targeted pollution control strategies in Linyi and similar industrial cities.

Authors

  • Sai Liu
    Department of Environmental and Safety Engineering, College of Chemistry and Chemical Engineering, China University of Petroleum (East China), Qingdao 266580, China.
  • Gang Wang
    National Clinical Research Center for Mental Disorders & Beijing Key Laboratory of Mental Disorders, Beijing Anding Hospital, Capital Medical University, Beijing, China.
  • Fanhua Kong
    Linyi Eco-Environment Monitoring Center of Shandong Province, Linyi 276000, China.
  • Na Zhao
    Department of Gynecology, Peking University First Hospital Ningxia Women and Children's Hospital, Yinchuan, Ningxia, China.
  • Wenkang Gao
    State Key Laboratory of Atmospheric Boundary Layer Physics and Atmospheric Chemistry (LAPC), Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029, China.
  • Hanyu Zhang
    Department of Environmental Science and Engineering, Beijing Technology and Business University, Beijing 100048, China.

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