Multivariate Analysis of Under Ground Water Pollution Sources in Agbabu Bitumen Belt

Abstract

Multivariate data analysis is used to analyse underground water samples from ten (10) different water sources in Agbabu bituminous belt of Nigeria. Principal component analysis (PCA) showed Component one (PC1) to be the most significant Component accounting for 54.09% of the pollution, with high loadings for Cd, Pb and Mn suggesting them to be the most significant pollutants for the study area. Mean concentrations of heavy metals indicated high pollutions with Cr, Cd and Mn to have highest concentrations and a relatively fairly concentrated Pb. Physicochemical properties were analysed for Alkalinity, dissolved oxygen, biochemical oxygen demand, and phosphates. Using Hierarchical clustering analysis (HCA), similarities in the pollution patterns of the various wells was observed, with Cluster one (CL1) showing similar clustering for wells highly polluted with Pb and Cd but low in Fe. Wells in cluster two (CL2) indicate wells highly polluted with Cd. Low polluted wells for Pb, Fe and Cd pollutants are found in Cluster three (CL3). All clusters agree with ANOVA and Pearson’s correlation result indicating variation among the various water sources. The cause of underground water pollution showed to be anthropogenic and geogenic in the study area and suggests the underlying bitumen deposit and its mining activity to be majorly responsible for the pollution.