Source-specific health risks apportionment of soil potential toxicity elements combining multiple receptor models with Monte Carlo simulation

Understanding the source-specific human health risk of soil potential toxicity elements (PTEs) for human is beneficial for pollution control and risk prevention. Multivariate statistics, absolute principal component score/multiple linear regression (APCS/MLR) model, positive matrix factorization (PMF) model, and GIS mapping were used to identify and apportion the sources of soil PTEs in typical mining and industrial area, southwestern China. Furthermore, source-specific health risks were apportioned by combining source apportionment with probabilistic health risk assessment based on Monte Carlo simulation which can define the probability that the risk exceed the guideline threshold value. The pollution factor and geo-accumulation index indicated that the soils were polluted by soil PTEs to different degrees. In particular, As and Cd were the primary pollutants. Mixed sources, agricultural activities, mining activities, and As-related smelting activities represented the potential sources of soil PTEs, with the contribution of 30.13%, 25.78%, 22.93%, and 21.16%, respectively. Source-specific probabilistic health risks indicated that As-related smelting activities contributed the most to non-carcinogenic risks (adults: 59.03%, children: 57.20%) and carcinogenic risks (adults: 81.82%; children 92.33%), despite the observation that it contributed the least to the accumulation of soil PTEs (21.16%). Non-carcinogenic and carcinogenic risk showed similar trend for children and adults. Therefore, Asrelated smelting activities were regarded as the priority source of soil PTEs, and corresponding prevention and control strategies should be implemented to protect human health.

Automated summary

Understanding the sources and risks of soil PTEs is important for pollution control and risk prevention. This study identified and apportioned the sources of soil PTEs in a mining and industrial area in southwestern China using statistical methods and models. It was found that smelting activities related to arsenic were the main source of pollution and posed the highest health risks.