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Nigerian Journal of Engineering Science and Technology Research

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HEAVY METAL CONTAMINATION AND RISK ASSESSMENT OF GROUNDWATER IN JALINGO VULNERABLE AREA, NIGERIA: A MULTI-METHOD APPROACH

Heavy metal contamination of groundwater in Jalingo, Nigeria, threatens public health and ecosystem services, driven by both natural geologic sources and intensive local anthropogenic activities. This study aimed to apply a multi-method approach to quantify heavy-metal levels, map spatial patterns, assess contamination and ecological risk, and predict pollution risk classes to inform management. Water was collected by purge-and-sample from vulnerable open wells, preserved with HNO3, and analysed by Atomic Absorption Spectroscopy for 11 metals (Pb, Hg, Cd, As, Cr, Ni, Mn, Zn, Cu, Co, Fe). Statistical and geospatial methods, which include Kernel Density Estimation (KDE), Pearson correlation, contour mapping (Surfer v28), Metal Index (MI), and Degree of Contamination (DoC) were combined with a Support Vector Machine (SVM) model to predict a Heavy Pollution Index Risk Factor (HPI-RF) using a 72/28 percent train-test split. Results show widespread exceedances of WHO limits for several metals (e.g., mean Pb ?1.21 mg/L vs. 0.01 mg/L guideline; Cu mean ?4.03 mg/L; As mean ?0.90 mg/L; Fe mean ?3.48 mg/L; Mn ?1.85 mg/L; Ni and Zn with localized maxima far above limits). KDE and maps revealed distinct contamination hotspots (As-NW, Pb-NE, Cu-east, Ni-south-central, Mn-central-SE, Hg-SE). Strong positive correlations among Pb, Cd, Cr, Hg, and Zn suggest a common source. SVM classified 25 sites into 12 high-risk, 2 medium-risk, and 11 low-risk locations, with an overall accuracy of 87.5%, but noted limitations due to class imbalance. The study concludes that groundwater in several zones is unsafe for consumption and requires urgent action. Targeted monitoring and remediation of hotspots, improved waste and industrial effluent management, infrastructure upgrades, routine surveillance, and expanded sampling to enhance predictive models and risk management.

Authors : Ngasoh, F.G., Ankidawa, B.A. and Burmamu B.R.

Category : Open Access     Volume (Issue) : 11(1)     Date Uploaded : 31st December 2025

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