International Journal of
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Research Article Volume 9 Issue 2
Assessment of heavy metals (As, Ba, Co and Ni), pollution in rural drinking water sources, using correlation and principal component analysis in Western Sokoto Basin, Nigeria
Saadu Umar Wali, Abdulqadir Abubakar Usman, Peter Danladi, Hussaini Muhammad Usman, Salma Aliyu
Received: May 10, 2025 | Published: May 29, 2025
Citation: Wali SU, Usman AA, Danladi P, et al. Assessment of heavy metals (As, Ba, Co and Ni), pollution in rural drinking water sources, using correlation and principal component analysis in Western Sokoto Basin, Nigeria. Int J Hydro. 2025;9(2):60-72. DOI: 10.15406/ijh.2025.09.00404
Abstract
The study utilizes correlation and principal component analysis to examine heavy metal pollution (As, Ba, Co, and Ni) in 63 rural drinking water sources within the Western Sokoto Basin. The study employed both field and laboratory analyses. Results showed that physical parameters such as pH (ranging from 4.4 to 9.4) and temperature (32.8 to 39.8°C) indicate acidic conditions, with a mean pH of 4.98, which falls below WHO/NSDWQ limits and may enhance the solubility of heavy metals. Though electrical conductivity (EC) and total dissolved solids (TDS) are generally within acceptable ranges, some maximum values exceed permissible limits. Dissolved oxygen levels (0.01 to 26.8 mg/L) and Turbidity (0 to 96.3 NTU) suggest localized pollution, with turbidity levels exceeding the 5 NTU standard. Among the heavy metals analyzed, barium (54.10 mg/L) and copper (35.74 mg/L) surpass WHO guidelines, presenting health risks such as cardiovascular problems and gastrointestinal issues. Although arsenic and nickel levels are below the limits, the presence of arsenic, even in small amounts, raises concern due to its toxicity and association with agricultural pesticide use. Spatial analysis points to contamination sources, including agricultural runoff, waste disposal, and industrial emissions. The results underscore the importance of ongoing groundwater monitoring, especially in agricultural areas. Future studies should broaden sampling networks, perform longitudinal and cross-seasonal analyses, identify sources of contamination, and evaluate health risks. Policy suggestions include establishing water quality standards, encouraging sustainable agricultural practices, incorporating smart monitoring technologies like IoT and sensors for real-time data collection, and enhancing awareness programs.
Keywords: correlation analysis, principal component analysis, heavy metals, Sokoto Basin
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