Probabilistic multi-pathway human health risk assessment due to heavy metal(loid)s in a traditional gold mining area in Ecuador

Abstract

Mining operations are important causes of environmental pollution in developing countries where mining waste management is not adequate. Consequently, heavy metal(loid)s are easily released into the environment, being a potential risk to human health. This study carries out a Bayesian probabilistic human health risk assessment, related to multi-pathway exposure to heavy metal(loid)s in a gold mining area in Southern Ecuador. Concentrations of As, Cd, Cr, Cu, Ni, Pb, and Zn in tap water, surface water, and soil samples, were analyzed to assess the potential adverse human health effects based on the Hazard Index (HI) and Total cancer risk (TCR). Adults and children residents were surveyed to adjust their exposure parameters to the site-specific conditions. Exposure to heavy metal(loid)s resulted in unacceptable risk levels for human health in the two age groups, both carcinogenic (TCR > 1 × 10^-5) and non-carcinogenic (HI > 1) through ingestion of tap water and incidental ingestion of surface water. Sensitivity analysis showed that As concentration in waters and exposure frequency were the main contributors to risk outcome. Exposure to soil via accidental ingestion and dermal contact was below the safety limit, not posing a risk to human health. These findings can provide a baseline for the environmental management of the mining area and indicate the need for further research on As pollution in water and its implications on the health of the inhabitants of mining communities.

Keywords: Bayesian model; Mining pollution; Probabilistic assessment; Sensitivity analysis; Water quality.