Long-term assessment of groundwater contamination and associated health risks: A study of heavy metals in the Quaternary aquifer system in Great Hungarian Plain

This study investigates the spatiotemporal distribution and health risks of heavy metals in the Quaternary aquifer system Debrecen area, Hungary in the period between 2019 and 2024. A comprehensive methodology combining heavy metal pollution indices, multivariate statistics, uncertainty, and sensitivity analysis was employed. Heavy metal pollution (HPI) and ecological risk (ERI) indices were calculated based on arsenic (As), iron (Fe), and manganese (Mn). The results show an increase in both HPI and ERI values from 2019 to 2024, with higher pollution and ecological risk levels, driven by localized natural and anthropogenic activities. Building on these findings, the study evaluates the health risks associated with these heavy metals exposure through oral and dermal pathways for adults and children, using Hazard Quotients (HQ) and Hazard Indices (HI). Children demonstrated significantly higher non-carcinogenic risks compared to adults, with HI values exceeding the safety threshold (HI > 1) in 2024. Spatial analysis revealed expanding high-risk zones for both population groups, emphasizing an intensifying health threat over time. Monte Carlo simulation was employed to evaluate the HQ for individual metals and the cumulative HI. The results demonstrated consistently higher risk levels for children compared to adults across both periods. Arsenic emerged as the most significant concern, with HQ values for children frequently exceeding the safety threshold. Sobol sensitivity analysis revealed that exposure and physiological parameters are the dominant parameters influencing oral exposure risk, while dermal absorption parameters and skin area are critical for dermal exposure. • Spatiotemporal analysis shows rising heavy metal pollution from 2019 to 2024. • Health risk indices reveal children face higher risks than adults, exceeding thresholds. • Monte Carlo simulation indicated Arsenic as the most critical contaminant. • Sobol analysis identifies exposure and physiological factors as key risk drivers.