Environmental monitoring and assessment of heavy metals in surface sediments at Coleroon River Estuary in Tamil Nadu, India

Abstract

The combined studies on grain size distribution, organic matter contents of sediments, sequential extraction and bulk concentration of heavy metals, statistical analysis, and ecological risk assessments were carried out to investigate the contamination sources and ecological risks of surface sediments at Coleroon River Estuary in Tamil Nadu, India. The sequential extraction of metals showed that a larger portion of the metals was associated with the residual phase and also in other fractions. The low concentrations of heavy metals were found in exchangeable and carbonate bounds (bioavailable phases). It revealed that sediments of Coleroon River Estuary were relatively unpolluted and were influenced mainly by natural sources. The observed order of bulk concentrations of heavy metals in the sediments was as follows: Fe > Mn > Zn > Cu > Pb > Cr > Ni > Co. Factor analyses represented that the enrichment of heavy metals was mostly resulted from lithogenic origins associated with anthropogenic sources. These sources were reconfirmed by cluster analysis. Risk assessment code (RAC) suggested that all metals were not harmful in monsoon season. However, Fe was in medium risk, and Mn and Cu were in low risk in summer. According to pollution load index (PLI) of sediments, all heavy metals were toxic. Cu might be related with adverse biological effects on the basis of sediment quality guidelines (SQG) in both seasons. These integrated approaches were very useful to identify the contamination sources and ecological risks of sediments in estuarine environment. It is expected that this research can give a useful information for the remediation of heavy metals in sediments.

A comprehensive risk assessment of metals in riverine surface sediments across the rural-urban interface of a rapidly developing watershed

“…Given the contrasting approaches utilized in various risk assessment indices, several discrepancies may arise between ecological risk predictions for a specific region. As a result, Venkatramanan et al (2015) proposed using several independent indices to avoid bias from a single risk index and provide a comprehensive ecological risk assessment.…”

Contamination assessment, source apportionment and health risk assessment of heavy metals in paddy soils of Jiulong River Basin, Southeast China

“…Multivariate statistical analyses have been widely used to trace the sources of heavy metals. [12][13][14][15][16] Principal component analysis (PCA) is a commonly used tool. Absolute principal component scoresmultiple linear regression (APCS-MLR) has been widely applied for quantitative analysis of pollution sources based on principal component analysis (PCA).…”

Water resources pollution associated with risks of heavy metals from Vatukoula Goldmine region, Fiji

“…Nickel had strong co-existence associations with Pb (r = 0.0.88, p < 0.01) and Mn (r = 0.90, p < 0.1), likely the idea of a similar source. Hydrated oxides of Mn might be related to other metals when Mn comprises potential sinks for Pb, Ni in the aquatic ecosystem, especially under oxidation circumstances (pH 6.42-7.83) (Venkatramanan et al, 2015). This is a basic physicochemical procedure of adsorption and co-precipitation conditions.…”