Mapping Seasonal Variation in the Distribution and Concentration of Heavy Metals Using Water Quality Index and Geographic Information System Based Applications

  • Adu-Boahen K
  • Boateng I
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Abstract

Incessant monitoring of water is essential in terms of heavy metals and toxic substances as it provides detailed information on aquatic resources. Majority of lagoons receive freshwater from their catchment areas containing industrial and domestic waste. The paper analysed seasonal variations in the distribution and concentrations of Lead (Pb), Copper (Cu), Cadmium (Cd),and Manganese (Mn) in the Fosu lagoon in Ghana to ascertain the quality of the lagoon. Water was sampled from eighteen (18) different points on the lagoon and was analysed at the Water Research Institute (WRI) of the Center for Scientific and Industrial Research (CSIR) using Atomic Absorption Spectrometry (AAS) and the results were interpolated using kriging.The results obtained were compared with the World Health Organisation water quality index. Statistical analysis of heavy metal concentrations using Pearson’s two-tailed significance correlation showed positive correlations for both seasons; between Pb and Cu (0.297; sig. = 0.232, and 0.196; sig.= 0.436), and Cd and Mn (0.119; sig. = 0.643 and 0.191; sig. = 0.447) for the wet and dry seasons respectively. A paired sample t-test on concentrations also showed statistical differences between wet and dry seasons’concentrations for Pb (t = 1.324; sig. = 0.203), Cu (t = 2.759; sig. = 0.013),and Cd (t = 3.056; sig. = 0.007), and Mn (t = -4.014; sig. = 0.001). Pb and Cd showed higher concentrations above the World Health Organisation's permissible limits. Heavy metal concentrations of water samples analysed varied widely in terms of seasons and sampling points.

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Adu-Boahen, K., & Boateng, Isaac. (2021). Mapping Seasonal Variation in the Distribution and Concentration of Heavy Metals Using Water Quality Index and Geographic Information System Based Applications. Journal of Geographical Research, 4(2), 31–42. https://doi.org/10.30564/jgr.v4i2.3100

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