出版社：The International Institute for Science, Technology and Education (IISTE)
摘要：In this paper, multivariate statistical approaches based on principal component analysis (PCA) coupled with spatial assessment were employed to assess physicochemical parameters (turbidity, pH, electrical conductivity, total dissolved solids, total suspended solids, nitrates, nitrite, phosphate, ammonium, total hardness, total alkalinity, dissolved oxygen, BOD, Na, Cl, Ca, HCO 3 , SO 4 and F) and heavy metals (Cu, Cd, Fe, Mn, Pb, Hg and Zn) of more than fifty five (55) water samples from 20 mining and non-communities within the lower Pra basin. The correlation matrix, however, shows significant inter-metal relationships (p<0.05 and p<0.01). The Fe–Mn correlation is recognized as the weakest with a correlation coefficient r=0.422. Also, significant strong correlations (r>0.5) were found between Zn – Cd, Pb–Zn, Pb – Cd, Pb – Cu, Cu – Zn, Cu – Cd, Hg – Zn, Hg – Cd, Hg - Cu and two more toxic metals, Hg and Pb. From the results of the principal component analysis on surface water in the study, component model 1 is interpreted to be contaminated water with mercury. This is because Hg has the highest correlation value (0.985). Within the study area, illegal artisanal small scale miners (popularly referred to as galamsey) use mercury extensively in their activities. The mercury is a steady source of contamination of the surface water in the Lower Pra Basin area. The use of mercury in gold mining by the Artisanal Small Scale Miners constitutes a point source of contamination.
关键词：Multivariate statistical techniques; Principal component analysis; Lower Pra Basin; Heavy Metals
