DUAL-MODAL RISK ASSESSMENT OF LEAD AND CADMIUM IN GROUNDWATER: BRIDGING DETERMINISTIC AND PROBABILISTIC FRAMEWORKS
DOI:
https://doi.org/10.33003/fjs-2025-0905-3683Keywords:
Exposure variability, Carcinogenic slope factor, Heavy metals, Monte Carlo simulationAbstract
Cadmium (Cd) and lead (Pb) are non-essential, highly toxic heavy metals with severe health implications. Cd, a Group One carcinogen, bioaccumulates in kidneys and liver, causing renal dysfunction, osteoporosis, and lung cancer even at low doses. Pb, a potent neurotoxin, disrupts cognitive development in children and elevates cardiovascular risks in adults, with no safe exposure threshold established. This study investigates the contamination of groundwater by Pb and Cd in ten samples from Unguwan Lumbaye, Nigeria, employing deterministic and probabilistic risk assessments to resolve conflicting risk prioritizations. The concentrations of Cd (0.040 – 0.070 ppm) and Pb (0.068 – 1.330 ppm) exceeded World Health Organization (WHO) limits by 17× and Pb by 65×, respectively. Deterministic methods identified Pb as the primary non-carcinogenic threat (HQ = 5.43 vs. Cd: HQ = 1.50), yet probabilistic Monte Carlo simulations (100,000 iterations) revealed universal carcinogenic risk for Cd (100% exceedance probability) compared to Pb (12.3%). This reversal stems from Cd’s extreme carcinogenic potency (slope factor = 6.1) and insensitivity to exposure variability, contrasting with Pb dependency on ingestion rates and body weights. Therefore, the Monte Carlo simulation played a key role in revealing risk reversal by highlighting cadmium's consistent carcinogenic threat across all exposure scenarios. Geochemical correlations, highlighted the complexity of metal mobility, whereas sensitivity analyses highlighted body weight and concentration as important risk factors. The study supports using probabilistic methods in regulation, emphasizing Pb hotspot remediation and agrochemical reforms to reduce Cd risks, while calling for adaptive measures to protect groundwater-reliant communities.
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