Arsenic, selenium, cadmium and lead contamination in Garhwal Himalayan groundwater: an integrated geospatial, indexical and statistical framework for health risk evaluation and sustainable development.
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Contamination of drinking water sources by potentially toxic elements (PTEs) poses critical threats to human health via carcinogenic and non-carcinogenic pathways, yet comprehensive assessments targeting arsenic, selenium, cadmium and lead in Garhwal Himalayan groundwater systems have been absent. This study contributes to address this knowledge gap by evaluating As, Se, Cd and Pb concentrations in 88 groundwater samples from the Chamoli district of Uttarakhand, India, a tectonically active region where populations depend almost exclusively on groundwater for drinking purposes. It integrated pollution indexing, health risk assessment, spatial mapping and statistical analyses to comprehensively characterize contamination status, identify spatial patterns and apportion potential sources. The arithmetic mean of the elemental concentrations was in the sequence Cd (0.18 µg L⁻1) < Se (0.26 µg L⁻1) < As (3.66 µg L⁻1) < Pb (12.81 µg L⁻1). While Se and Cd concentrations fell within their permissible limits, As and Pb exceeded their regulatory thresholds in specific samples. The heavy metal pollution index ranged from 5.649 to 134.2 (mean = 27.875), with majority of water samples are suitable for drinking. Non-carcinogenic risk assessment revealed that hazard indices exceeded unity in 33 samples for children versus one sample for adults, hinting on age-specific vulnerabilities. Carcinogenic risk estimates for majority of samples exceeded the acceptable threshold of ≤ 1.0 × 10⁻⁶ for the ingestion pathway, however they remained within the acceptable limit for the dermal exposure pathway. Correlation analysis identified moderate positive association between Cd and Pb, suggesting common sources or co-mobility, while Se and Pb exhibited weak negative correlation, indicating independent origins. These findings establish critical baseline data for the Chamoli district, inform targeted remediation strategies and support sustainable groundwater management aligned with multiple SDG targets. To address its limitations, future studies should incorporate temporal monitoring, expand parameter coverage and employ advanced source apportionment techniques to strengthen contamination origin characterization.