Mapping the Spatial distribution of Soil heavy metals pollution by Principal Component Analysis and Cluster Analyses

Contamination of heavy metals in soil is a matter of great concern, which can be evaluated collectively by environmental and multivariate statistical analysis. In this study, concentration of heavy metals was measured in the topsoil samples of Sehwan Sharif, district Jamshoro. Three groups of elements were produced from statistical analysis using Hierarchical dendrogram, Pearson correlation and Principal Component Analysis (PCA). First group included As, Cd, Ni and Zn while second contained B, Mn, Cu and Fe and the third one comprised of Pb and Cr. Greater values of RSD and abnormal distribution of other statistical analysis confirmed the source of Cd, Ni, As, Cr, Pb and Zn due to human activities while Fe, B, Mn, and Cu are due to natural abundance. Subsequently, the calculated Pollution Index (PI) for Cd, Ni and Pb was 1.08, 1.11 and 1.02 respectively, which was>1. The spatial maps were generated by Inverse Distance Weighting (IDW) interpolation technique in the GIS software which showed the hotspots of metal concentrations due to distinct sources from the environment such as highest content of Zn (157.07 ppm) was present in city center indicating its contamination due to emission from traffic. Furthermore, Potential Ecological Risk was estimated quantitatively and Risk Index map was generated, and it was observed that Cd showed higher potential ecological risk among the studied elements. However, the overall cumulative risk index was 'considerable' according to the potential ecological risk grade in the reported study.