Abstract
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.