Assessment of Groundwater and Surface Soil using Multivariate Statistical Techniques and Contamination Indices: A Case Study of Gurugram Millennium City, Haryana, India

Abstract

Abstract Pollution of various environmental components, such as air, water, and soil, is caused by industrialization and urbanization in urban agglomerates. This study provides information about groundwater quality and the levels of heavy metals in the surface soils of Gurugram city. The groundwater and soil samples were analyzed for various chemical parameters. Heavy metals in groundwater and soil were measured using atomic absorption spectrophotometer (AAS). Groundwater samples show higher electrical conductivity (EC), bicarbonates (HCO3-), and chlorides (Cl-). Water quality index (WQI) indicates that groundwater is not suitable for drinking purposes. Most of the groundwater samples surpassed the prescribed limits for heavy metals. While in the case of soil, Cd, Ni and Cr were found above the average background value for soils. Contamination factors (CF) and Pollution load index (PLI) for various heavy metals in soil were found to vary from 0.006 to 20.9 and 0.64 to 1.93, respectively. The 70% of samples found with PLI >1, indicate deterioration of soil quality. Three soil samples have a high ecological risk index (ERI) with values of more than 600. Average value of geo-accumulation index (Igeo) varies in the order Cd>Pb>Cu>Zn>Ni> Cr>Fe with average value 3.43, 1.73, 0.86, 0.029, -.23, -1.2 and - 7.14, respectively. Principal component analysis (PCA), a multivariate statistical technique, shows that the first three principal components (PC) account for 84.99% of the variance in groundwater samples. In soil samples, the first two PCs account for 76.97% of the variance. Hierarchical cluster analysis (HCA) shows three clusters for groundwater samples and two clusters for soil samples. The study area shows higher pollution levels and needs an improved environmental management plan.