Sui Shaobo, Wang Mingshi, Wang Mingya, Ma Wanqi, Yang Shili, Zhang Fan, Jia Luhao, Liu Tong
College of Resource and Environment, Henan Polytechnic University, Jiaozuo 454003, China.
iScience. 2025 Apr 23;28(5):112524. doi: 10.1016/j.isci.2025.112524. eCollection 2025 May 16.
Despite strict government controls on pollutant discharges, heavy metal (HM) levels in China's surface waters remain elevated above background values. Accurate source identification of HM pollution is essential for effective environmental management and public health protection. This study collected and analyzed water samples from the southwestern North China Plain to assess HM contamination levels, sources, and health risks, employing the absolute principal component score-multiple linear regression (APCS-MLR) model for robust source apportionment and quantification of pollution source contributions. Surface water HMs remained at "clean" levels but exceeded background values by 1-50 times. Source apportionment identified three primary sources: livestock/poultry (48.3%) > industrial (31.6%) > hybrid sources (20.1%), demonstrating a transition from point to non-point source (NPS) dominance. Monte Carlo simulation revealed serious carcinogenic risks for 1.1% of children and 19.5% of adults. These findings highlight evolving HM pollution patterns in China's agricultural regions, offering important implications for developing nations.
尽管政府对污染物排放实施了严格管控，但中国地表水的重金属（HM）含量仍高于背景值。准确识别HM污染来源对于有效的环境管理和公众健康保护至关重要。本研究采集并分析了华北平原西南部的水样，以评估HM污染水平、来源及健康风险，采用绝对主成分得分-多元线性回归（APCS-MLR）模型进行稳健的污染源解析及污染来源贡献量的量化。地表水HM含量处于“清洁”水平，但超出背景值1至50倍。源解析确定了三个主要来源：畜禽（48.3%）＞工业（31.6%）＞混合源（20.1%），表明污染源已从点源为主转变为非点源为主。蒙特卡洛模拟显示，1.1%的儿童和19.5%的成年人面临严重致癌风险。这些发现凸显了中国农业地区HM污染模式的演变，对发展中国家具有重要启示意义。
