ArticleScientific reports2026
Source identification and probabilistic health risk systematic assessment of soil metals and metalloids pollution in a typical coal-industrial city in Weibei, China.
Article in Scientific reports, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
Systematic assessment of the ecological and human health risks induced by soil metals and metalloids (MMs) from various sources is critical for pollution control and risk prevention. This study takes Hancheng, a typical coal-industrial city in Weibei, China, as an example and employs the geological accumulation index, potential ecological risk assessment, positive matrix factorization (PMF), and Monte Carlo probabilistic health risk assessment to comprehensively quantify and evaluate regional risks. The results show that among the eight soil metals and metalloids, only the average Cr concentration does not exceed the background value of Shaanxi Province, with all elements influenced by anthropogenic activities. Cd and Hg are identified as the most polluting elements, exhibiting pronounced accumulation and ecological risks. The PMF receptor model reveals four sources: mixed transportation and specific industry sources (28.6%), coal-fired sources (31.2%), natural sources (29.1%), and industrial emissions (11.1%), with human-induced sources collectively contributing 70.9%. The geological background of the study area and coal industrial activities exert a synergistic enhancing effect on soil MMs pollution. By integrating the Monte Carlo method with the PMF model, the source-contribution-based probabilistic health risk assessment indicates that children face higher health risks than adults, and the combined effect of multiple MMs significantly increases health risks compared to individual elements. Transportation-related and industrial sources are major contributors to human health risks, with As, Ni, and Cd prioritized as pollutants due to their elevated concentrations. These findings offer a scientific basis for targeted pollution prevention and prioritized management in coal-industrial cities, supporting efforts to mitigate regional ecological and health risks.
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