Ecological Risk Assessment of Heavy Metal Contamination from Artisanal and Small-scale Mining: A Case Study of Mayo-Sinna, Ngoroje in Sardauna L.G.A, Taraba State, Nigeria

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Abstract

This study assessed the ecological risk of heavy metal contamination from artisanal and small-scale mining (ASM) activities in Mayo-Sinna, Nguroje (Sardauna L.G.A, Taraba State, Nigeria). Soil samples from mining and control sites were analyzed for cadmium (Cd), lead (Pb), cobalt (Co), copper (Cu), chromium (Cr), zinc (Zn), nickel (Ni), manganese (Mn), and iron (Fe) using atomic absorption spectrophotometry (AAS). Results revealed elevated Pb (0.1085 ppm) and Fe (1.4060 ppm) concentrations in mining sites exceeding World Health Organization (WHO) and Nigerian Standard for Drinking Water Quality (NSDWQ) guidelines, consistent with contamination patterns observed in other ASM regions. However, unexpected findings included lower Cu (-0.1964 ppm) and Zn (0.0789 ppm) levels in mining sites compared to control areas (1.5000 ppm and 2.7300 ppm, respectively), suggesting complex site-specific geochemical dynamics. Negative values for Cd, Co, and Cu indicated potential analytical interferences requiring methodological refinement. While Cr (0.0603 ppm) and Ni (0.0298 ppm) remained below regulatory thresholds, their presence warrants continued monitoring. The study highlights the need for improved mining practices and enhanced environmental monitoring protocols to mitigate heavy metal pollution in ASM communities. These findings contribute to the growing body of knowledge on mining-related environmental degradation in West Africa and underscore the importance of context-specific risk assessments for effective remediation strategies. 

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Article Details

How to Cite
Garkida, D. M., Oruenye, D. E., Mohammed, Y. A., & Leila, D. D. (2025). Ecological Risk Assessment of Heavy Metal Contamination from Artisanal and Small-scale Mining: A Case Study of Mayo-Sinna, Ngoroje in Sardauna L.G.A, Taraba State, Nigeria. Journal of Multidisciplinary Science: MIKAILALSYS, 3(2), 806-813. https://doi.org/10.58578/mikailalsys.v3i2.5644

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