Assessment of heavy metal contamination by multivariate statistical methods from the sediment of Ulhas river estuary, Maharashtra, India

Abstract

Ulhas River estuary is one of the most significant estuarine systems situated western coast of India. This estuary has been polluted by several point and nonpoint source and therefore, the multivariate statistical methods were used to determine sediments parameter concentrations, their distributions, and their relationship. In the present study, sediment samples were collected from five different stations and analyzed eight heavy metals' concentrations with seven other parameters. The multivariate statistical methods (PCA, nMDS, and ANOSIM) were used to determine sediments parameter concentrations, their distributions, and their relationship. The PCA results showed that the concentrations of N%, H%, S%, C/N, C/H, EC, and OC% were significant contributors to PC1 (36%) while the heavy metals such as Cu, Pb, Cd, Ni, Si, and Hg concentration were major contributor to PC2 (20%). Both PCs are indicated anthropogenic pollutant deposition towards the mouth of the estuary. Other results of nMDS showed a high degree of similarities within the stations such as 2, 3, and 4. Moreover, analysis of similarities (ANOSIM) results also support them at a significant level of 0.01% with a global R-value (0.6). The observed level of heavy metals contamination in the sediment samples was in the order of Cr >Pb >Cu > Ni >Zn > Hg >Si>Cd. Industrial discharges within the catchment area may be the potential source of sediment pollution and warrants immediate targeted actions to protect this vital ecosystem and its biodiversity.