Source-oriented stochastic health risk assessment of toxic metals in soil via a hybrid model and Monte Carlo simulation

Toxic metal contamination in soils poses significant hazards to the environment and human health; thus, quantitative assessment of the sources and risks of metal contaminants are urgently needed. A hybrid model that integrates the positive matrix factorization (PMF) and random forest (RF) methods was proposed to quantify the sources of toxic metals in soils by combining diverse environmental variables (source proxies) in this study. In addition, a health risk assessment and Monte Carlo simulations were integrated to estimate the source-oriented stochastic health risk. The results suggested that, except for Ni, which exhibited moderate contamination, other toxic metals (As, Cd, Cr, Hg and Pb) presented slight contamination. Four sources (agricultural activities loaded heavily by As, atmospheric deposition loaded heavily by Hg and Pb, natural sources and mining activities loaded heavily by Cr and Ni, and industrial activities loaded heavily by Cd) were defined and explained 23.44 %, 26.65 %, 30.13 % and 19.78 % of the total variance in toxic metals, respectively. The principal route of exposure (i.e., ingestion), the population at highest risk (i.e., children), and the most hazard-inducing metals (i.e., As and Cr) were determined. Agricultural activities and the combination of natural sources and mining activities demonstrated certain degrees of noncarcinogenic risk to children, with exceedance ratios of 2.20 % and 2.56 %, respectively. Additionally, the combination of natural sources and mining activities demonstrated probabilities for significant carcinogenic risk to adults and children of 0.59 % and 3.76 %, respectively. To reduce the health risks of toxic metals in soils and to protect food and ecological safety, strict regulations should be established to control the discharge of waste from mining and agricultural activities.