Source-specific probabilistic health risk judgement of soil heavy metals in a typical resource-based town in North China

Abstract

The process of rapid urbanization has led to an increase in energy consumption and pollution emissions, posing a significant threat to the environment, as well as human life and health. This is particularly evident in resource-based cities and towns where factors of production rely heavily on unsustainable development patterns. It is imperative to establish an emergency response mechanism for high-priority risks. In this study, risk indices were used to analyze the characteristics of soil HM pollution. The Monte Carlo Simulation (MCS) model and Human Health Risk Assessment (HHRA) model were used to assess the probabilistic health risks posed by HMs and were combined with the Positive Matrix Factorization (PMF) model to identify the major sources contributing to these risks. The soil contamination and ecological risks were assessed to be at minimal levels, with Cd and Hg identified as the predominant contaminants. Probabilistic HHRA indicated that health risks were higher for children than for adults. Specifically, HMs present unacceptable non-carcinogenic and carcinogenic risks with probabilities of 8.63% and 30.83% for children, respectively, while adults faced negligible non-carcinogenic risks and acceptable carcinogenic risks, both with a certainty of 100%. The PMF model identified five sources, including fuel combustion, agriculture, natural processes, transportation emissions, and processing and manufacturing. These sources were found to contribute insignificantly to non-carcinogenic risks for all populations but presented notable carcinogenic risks. Ni and Cr were identified as the leading elements contributing to health hazards, with transportation recognized as a priority anthropogenic source warranting regulatory attention. In this study, the assessment of pollution levels and health hazards mostly relied on HM concentrations, demonstrating a limited influence of toxicity. This research exemplifies the use of probabilistic risk assessment based on specific sources, which can offer new perspectives on the risk assessment of soil HMs in resource-dependent cities and towns as well as valuable insights into the development of risk prevention and control strategies.