Probabilistic Health Risk Assessment of Heavy Metals from a Typical Soil–Crop System Around a High-Altitude Industrial Park
The transfer of heavy metals (HMs) from industrial park soils to edible crops is strongly crop-specific; however, these differences have not been considered in probabilistic dietary health risk assessments. This study examined agricultural fields surrounding a high-altitude industrial park in southwestern China, where paired samples of surface soil, Chinese cabbage, and maize were collected and analyzed for Cd, Pb, Cr, Ni, Cu, Zn, Hg, and As. Spearman rank correlation and principal component analysis (PCA) were applied to identify elemental associations and probable sources; bioaccumulation factors (BAFs) were calculated to compare HM transfer and accumulation across the two crops; and Monte Carlo simulation was used to estimate probabilistic dietary health risks across age groups. The results showed that soil HMs in the study area displayed mixed-source characteristics, with marked enrichment of Pb, Cd, and Hg. After multiple comparison correction, only soil Ni showed a significant positive correlation with Ni in maize. Chinese cabbage had a relatively high accumulation capacity for Cd, whereas maize grains showed relatively limited transfer of most HMs, indicating pronounced crop-specific differences. Cd, Pb, Cr, Hg, and As concentrations in Chinese cabbage remained within permissible limits. For health risk, P95 hazard index (HI) values stayed below 1 across all age groups, indicating that non-carcinogenic risk was generally acceptable under the exposure scenarios evaluated; adults, however, carried higher estimated lifetime carcinogenic risk than other age groups. Sensitivity analysis revealed that As and Cd in Chinese cabbage were the dominant contributors to non-carcinogenic and carcinogenic risks, respectively, while the contribution of Cr to risk estimates was highly dependent on its speciation and toxicological parameter assumptions. By combining soil–crop monitoring, bioaccumulation analysis, and probabilistic risk assessment, this study characterizes crop-specific HM transfer patterns and identifies the principal drivers of health risk in industrially influenced agricultural systems, providing a scientific basis for risk-oriented monitoring, food safety management, and the long-term sustainable use of agricultural land in industrial–agricultural interface regions.