Geochemical data handling, using multivariate statistical methods for environmental monitoring and pollution studies

Abstract

Abstract This study utilized multivariate statistics such as hierarchical cluster and principal component analyses to monitor water and stream sediments pollution. Three Principal components loadings: PC1, PC2 and PC3 were generated from water samples data yielding eigen values of 20.563, 8.477, and 7.635 respectively. PC1 explained 28.56% of the total variance with high positive loadings for EC, turbidity, Br, Cl, SO 4 2 − , Ce, Dy, Er, Eu, La, Lu, Nd, Pr, Sm, Tb, Tm, Yb, Al, Ba, Bi, Co, Co, Cs, Mn, Th, Ti, U, V and Y. PC2 explained 11.77% of the total variance with high positive loadings for Hf and high negative factor loadings for Hg. PC3 explained 10.60% of the total variance and positively loaded for P, NO3, Cd, Ge, Ni, Pb, Sn, and Zn. PC1 is related to saline waters intrusion and geological nature of the aquifer. PC2 is controlled by high field strength element (HFSE) Hofnium (Hf) due to mineralization. PC3 contributed to pollution due to anthropogenic activities caused by chemical nitrogenous and phosphate fertilizer applications, to the soil and mineralogical constituents of the aquifer rock. Four principal components were identified in stream sediments and possessed eigen values of 12.29, 5.47, 3.19 and 2.10 respectively. PC1 explained 39.65% of the total variance and had significant positive loadings for Mo, Cu, Pb, Ni, Zn, Fe, U, Th, V, Ba, Ti, Sn, Nb, Be, Sc, Li, Zr, Rb and Hf. This suggest the occurrence of heavy mineral phases such as garnet, barite, zircon and monazite in mafic and ultramafic rocks and resistive heavy minerals. PC2 accounted for 17.65% of the total variance with moderate positive loadings for Mo, Cu, As and Ba, but with moderate negative loadings for Th, La and Ba. This component shows lithogeochemical input representative of weathering and mobility of sediments related mineralization. PC3 accounted for 10.29% of the total variance with positive high loadings for Mn, Bi and Y. PC3 may be related to anthropogenic activities such as agriculture, industry and urban life in the study area. PC4 accounted for 6.78% of the total variance with positive high loading for Ta. PC4 indicates the mineralization acquired by this component.