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

Authors:
Prof. Udosen E D, PhD
Prof. Udosen E D, PhD
University of Uyo, Nigeria
Professor
Environmental / Inorganic Chemistry
Ikot Ekpene, Akwa Ibom | Nigeria
Omowunmi H Fred-Ahmadu
Omowunmi H Fred-Ahmadu
Covenant University
Faculty
Environmental Chemistry
Ota, Ogun | Nigeria

MethodsX 2018 30;5:268-276. Epub 2018 Mar 30.

Industrial and Environmental Chemistry Unit, Department of Pure and Applied Chemistry, Ladoke Akintola University of Technology, Ogbomoso, Nigeria.

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 (HQ) 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 (HQ) 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.

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Source
http://dx.doi.org/10.1016/j.mex.2018.03.005DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6053633PMC
March 2018
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1 Citation

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