数字农科院2.0

Environmental hazard and human health risk attributed to surface water pollution in China: City-level assessment and socioeconomic driver identification

文献类型： 外文期刊

作者： 关杨;强烨;厉斌;肖旸;张南南;秦昌波;师荣光

关键词： Surface water pollution;Conventional pollutant;Potentially toxic element;Composite environmental hazard;Human health risk;Socioeconomic driver

期刊名称： JOURNAL OF HAZARDOUS MATERIALS

ISSN： 0304-3894

年卷期： 2026 年

页码：

收录情况： SCIE（2025版） ; ; EI（2025版）

摘要： Surface water pollution could threaten water security and public health, hindering progress toward the Sustainable Development Goals. Using China—a country facing challenges in surface water quality—as a case study, this work integrates the most recent monitoring data (2021–2024) with localized exposure parameters to assess city-level environmental hazards and health risks associated with surface water pollution, and further identifies their potential socioeconomic drivers. The assessment of composite environmental hazards, covering 21 key pollutants, shows that cities in eastern and northern China—particularly those in the North China Plain and the northern Yangtze River Delta—experienced more severe environmental hazards, with nutrient pollutants (conventional indicators) emerging as the dominant contributors. The health risk assessment, which includes 11 potentially toxic elements and other hazardous substances, indicates that arsenic contamination in surface waters may pose widespread and substantial health risks. Environmental hazards and health risks exhibit marked spatial heterogeneity across cities. Driver identification using machine learning and Shapley Additive exPlanations (SHAP) reveals that overall socioeconomic development has exerted a significant influence on these composite hazards and risks. On the contrary, most indicators representing water-related resources and ecological conditions generally act as constraining factors. Regional divisions function as a significant confounding factor for the machine learning-based driver identification results.

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