A new method for assessment of sediment-associated contamination risks using multivariate statistical approach

Abstract

This paper presents the assimilation of heavy metal concentration data from sequential extraction method (SEM) with metal toxicity factors to develop and propose two new sediment quality indices modified hazard quotient (mHQ) and ecological contamination index (ECI), to predict the potential ecological risks associated with sediment contamination. Chemical speciation data of five heavy metals: cadmium (Cd), chromium (Cr), copper (Cu), nickel (Ni), and lead (Pb) from five coastal aquatic ecosystems of the Equatorial Atlantic Ocean were used in the assessment of the degree of heavy metal contamination. Evaluation based on ECI indicated that sediments of most aquatic ecosystems were considerably to highly contaminated. The results showed that the proposed indices are reliable, precise, and in good agreement with similar existing indices used for evaluating the severity of sediment-associated contamination by heavy metals. The principal component analysis (PCA) and factor analysis indicated that heavy metals in the benthic sediments were mostly from anthropogenic sources. • New indices – modified hazard quotient (mHQ) and ecological contamination index (ECI) - were developed for predicting sediment-associated risk adverse effects. • Newly proposed indices agree closely with the existing pollution indices. • Pollution indices reveal significant anthropogenic contamination by Cd and Pb. Method name: New ecological risk indices, Keywords: Fractionation, Heavy metals, Sediment pollution, Contamination indices, Principal component analysis