PM2.5 pollution characteristics, drivers, and regional transport during different pollution levels in Linyi, China: An integrated PMF-ML-SHAP framework and transport models

IF 12.2 1区环境科学与生态学 Q1 ENGINEERING, ENVIRONMENTAL

Journal of Hazardous Materials Pub Date : 2025-05-08 DOI:10.1016/j.jhazmat.2025.138534

Sai Liu , Gang Wang , Fanhua Kong , Na Zhao , Wenkang Gao , Hanyu Zhang

{"title":"PM2.5 pollution characteristics, drivers, and regional transport during different pollution levels in Linyi, China: An integrated PMF-ML-SHAP framework and transport models","authors":"Sai Liu , Gang Wang , Fanhua Kong , Na Zhao , Wenkang Gao , Hanyu Zhang","doi":"10.1016/j.jhazmat.2025.138534","DOIUrl":null,"url":null,"abstract":"<div><div>Despite significant progress in air quality improvement, heavy fine particulate matter (PM2.5) pollution events persist in China. The pollution characteristics of PM2.5 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 PM2.5 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 SO42 − formation during polluted periods, while homogeneous reactions drove NO3− 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 PM2.5 levels, with secondary nitrate formation emerging as the dominant driver of PM2.5 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 PM2.5 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 PM2.5 pollution during different pollution levels, offering a scientific basis for targeted pollution control strategies in Linyi and similar industrial cities.</div></div>","PeriodicalId":361,"journal":{"name":"Journal of Hazardous Materials","volume":"494 ","pages":"Article 138534"},"PeriodicalIF":12.2000,"publicationDate":"2025-05-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Hazardous Materials","FirstCategoryId":"93","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0304389425014505","RegionNum":1,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ENGINEERING, ENVIRONMENTAL","Score":null,"Total":0}

引用次数: 0

Abstract

Despite significant progress in air quality improvement, heavy fine particulate matter (PM_2.5) pollution events persist in China. The pollution characteristics of PM_2.5 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_2.5 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 SO₄^2 − formation during polluted periods, while homogeneous reactions drove NO₃⁻ 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_2.5 levels, with secondary nitrate formation emerging as the dominant driver of PM_2.5 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_2.5 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_2.5 pollution during different pollution levels, offering a scientific basis for targeted pollution control strategies in Linyi and similar industrial cities.

Abstract Image

查看原文本刊更多论文

临沂市不同污染水平下PM2.5污染特征、驱动因素及区域运输：PMF-ML-SHAP框架与运输模型

尽管中国的空气质量改善取得了重大进展，但重细颗粒物（PM2.5）污染事件仍在持续。PM2.5在不同污染水平下的污染特征不同，凸显了深入了解其潜在驱动因素和区域运输的必要性。采用多数据融合分析、正矩阵分解-机器学习-shapley加性解释（PMF-ML-SHAP）和浓度加权轨迹模型，系统研究了临沂市PM2.5的成分特征、驱动因素和区域运输。结果表明，污染期间，非均相反应主导了SO42−的生成，而均相反应主导了NO3−的生成。在构建集成的PMF-ML-SHAP框架时，RandomizedSearchCV和KFold技术显著提高了CatBoost模型的性能。随着PM2.5浓度的升高，局地污染源的贡献从85.6%逐步增加到91.4%，次生硝酸盐形成逐渐成为PM2.5污染的主要驱动因素。生物质燃烧在清洁期（CP, 20.4%）和轻度污染期（SPP, 17.3%）的影响较大，而烟花燃烧在重度污染期（HPP, 25.9%）的影响较大。在气象因子中，风速和紫外线辐射强度对PM2.5的扩散和二次气溶胶的形成起关键作用。区域运输分析表明，近程和中程输送气团主要影响CP和SPP，而局地输送气团在中度污染期（MPP, 54.4%）和HPP期（58.2%）占主导地位。本研究对不同污染水平下PM2.5污染的驱动因素有了新的认识，为临沂及类似工业城市制定有针对性的污染控制策略提供了科学依据。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

求助全文

约1分钟内获得全文求助全文

来源期刊

Journal of Hazardous Materials 工程技术-工程：环境

CiteScore

25.40

自引率

5.90%

发文量

3059

审稿时长

58 days

期刊介绍： The Journal of Hazardous Materials serves as a global platform for promoting cutting-edge research in the field of Environmental Science and Engineering. Our publication features a wide range of articles, including full-length research papers, review articles, and perspectives, with the aim of enhancing our understanding of the dangers and risks associated with various materials concerning public health and the environment. It is important to note that the term "environmental contaminants" refers specifically to substances that pose hazardous effects through contamination, while excluding those that do not have such impacts on the environment or human health. Moreover, we emphasize the distinction between wastes and hazardous materials in order to provide further clarity on the scope of the journal. We have a keen interest in exploring specific compounds and microbial agents that have adverse effects on the environment.