A Multivariate Statistical Approach for Monitoring of Heavy Metals in Sediments: A Case Study from Wailpalli Watershed, Nalgonda District, Andhra Pradesh, India

摘要

The aim of the present study, focuses on investigation of heavy metal distribution in sediments of the Wailpalli watershed located in Nalgonda district of Andhra Pradesh, India, and to study different causes of enrichment by applying multivariate statistics on the studied elements, including correlation and factor analyses, and to identify possible sources of sediment bound heavy metals. Sediment samples were collected along the streams from a depth of 0-10 cm and were analyzed for Ba, Co, Cr, Cu, Ni, Pb, Rb, Sr, V, Zn and Zr by using Philips PW 2440 X-ray fluorescence spectrometer (XRF). The concentration ranges were Ba 128.5 to 929.4 mg/kg, Co 0.4 to 36.2 m g/kg, C r 15.8 to 107.8 mg/kg, Cu 1.6 to 43.1 mg/kg, Ni 0.2 to 69.8 mg/kg, Pb 2.3 to 14.1 mg/kg, Rb 8.0 to 446.2 mg/kg, Sr 73.0 to 360.6 mg/kg, V 7.9 to 240.8 mg/kg, Zn 24.5 to 130.1 mg/kg, and Zr 108.4 to 2668 mg/kg. Distribution maps metal concentrations in sediments were plotted by Golden Software's SURFER program. Using multivariate statistical analysis (correlation coefficients, factor analysis), the interrelationships among elements, and Enrichment Factor (EF) was calculated to differentiate the origin of metals between anthropogenic and geogenic sources. The results of median EF indicate no significant enrichment of the metals (Co, Cu, Ni, Pb, Rb, V and Zn) except for high Pb and Ni possibly indicating some point source input to the stream sediments. However, systematic and continuous monitoring of the study area for heavy metals is necessary as most of the area in Wailpalli watershed is under active irrigation and these elements may enter the food chain, and could be hazardous to human health.