Multivariate statistical evaluation of dissolved trace elements and a water quality assessment in the middle reaches of Huaihe River, Anhui, China

A total of 211 water samples were collected from 53 key sampling points from 5-10th July 2013 at four different depths (0 m, 2 m, 4 m, 8 m) and at different sites in the Huaihe River, Anhui, China. These points monitored for 18 parameters (water temperature, pH, TN, TP, TOC, Cu, Pb, Zn, Ni, Co, Cr, Cd, Mn, B, Fe, Al, Mg, and Ba). The spatial variability, contamination sources and health risk of trace elements as well as the river Water quality were investigated. Our results were compared with national (CSEPA) and international (WHO, USEPA) drinking water guidelines, revealing that Zn, Cd and Pb were the dominant pollutants in the water body. Application of different multivariate statistical approaches, including correlation matrix and factor/principal component analysis (FA/PCA), to assess the origins of the elements in the Huaihe River, identified three source types that accounted for 79.31% of the total variance. Anthropogenic activities were considered to contribute Much of the Zn, Cd, Pb, Ni, Co, and Mn via industrial waste, coal combustion, and vehicle exhaust; Ba, B, Cr and Cu were controlled by mixed anthropogenic and natural sources, and Mg, Fe and Al had natural origins from weathered rocks and crustal materials. Cluster analysis (CA) was used to classify the 53 sample points into three groups of water pollution, high pollution, moderate pollution, and low pollution, reflecting influences from tributaries, power plants and vehicle exhaust, and agricultural activities, respectively. The results of the water quality index (WO) indicate that Water in the Huaihe River is heavily polluted by trace elements, so approximately 96% of the water in the Huaihe River is unsuitable for drinking. A health risk assessment using the hazard quotient and index (HQ/HI) recommended by the USEPA suggests that Co, Cd and Pb in the river could cause non-carcinogenic harm to human health. (C) 2017 Elsevier B.V. All rights reserved