Multivariate canonical correlation techniques: An economic approach for evaluation of pollutants in soil and sediments of Bombay region, India

Abstract

Multivariate canonical correlation analysis has been carried out taking physical variables (mean, standard deviation, skewness, kurtosis) as predictors and chemical variables (Cd, Co, Cr, Cu, Fe, Mn, Ni, Pb, and Zn) as responses from the soils and sediments of Thane Creek and Ulhas River areas in Bombay, India. Soil samples provide the first canonical correlation to the presence of more clay fractions, which controls the concentration of trace elements such as Co, Fe, and Ni. In sediment samples, the first canonical correlation explains the role of mean particle size in controlling the concentration of Pb and Ni. The second correlation shows the role of clay minerals in controlling the concentration of the trace elements such as Fe and Zn. The plot of transformed scores of first canonical correlation for soil illustrate the high correlation between sets of variables as all points are grouped closely within an ellipsoidal field. The plot of transformed scores of first canonical correlation illustrate that there is a clear distinction between the type of sediments collected from Thane creek and the Ulhas river region.