Risk sources quantitative identification of heavy metals in coal mining hinterland river sediments, Northern China

The accumulation of heavy metals (HMs) from coal resource exploitation and coal-related industries poses serious ecological and health risks in the hinterland river sediments of Shenfu coal field in Northern China. Using data from 59 samples, the geo-accumulation index and ecological health risks of HMs were assessed probabilistically using Monte Carlo Simulation. Two coupling models were constructed in this study, integrating both the Positive Matrix Factorization and ecological health risk models to identify the risk levels of pollution sources in the Kuye River. The risk of HMs during the wet season was explored due to the lower concentrations and a broader range of pollution sources compared to the dry season. The I_geo value of Hg was greater than 1 in 69% of the samples, suggesting moderately contaminated sediments. According to the source-oriented coupling models (PMF-RI/HRA), coal-mining sources contributed to the overall ecological risk by 48.79%, primarily due to Hg (98.50%). Industrial sources (51.48%) were the largest contributors to carcinogenic risk, with Ni corresponding to the target HM. This indicated that different HMs originating from distinct pollution sources were responsible for ecological or carcinogenic health risks. The probabilistic health risk evaluation results indicated that children faced higher risks than adults, with over 94.07% of carcinogenic risks exceeding thresholds. Traffic sources followed, contributing 34.41% to ecological and 41.09% to carcinogenic risks. The results highlight the priority sources and target HMs based on specific sources in the mixed 'mining-industrial-traffic' areas, providing valuable insights for environmental protection and the development of risk prevention strategies in a typical energy industry area.