Receptor model-based source apportionment and ecological risk of metals in sediments of an urban river in Bangladesh

Abstract Metal accumulation (As, Cd, Cr, Cu, Fe, Hg, Mn, Ni, Pb, and Zn) in Korotoa River sediment was studied in order to determine the metal content, distribution, sources, and their possible ecological impacts on the riverine ecosystem. Our study found significant spatial patterns of toxic metal concentration and principal coordinate analysis (PCoA) accounted for 45.2% of spatial variation from upstream to downstream. Metal contents were compared to sediment quality standards and found all studied metal concentrations exceeded the Threshold Effect Level (TEL) whereas Cr and Ni surpassed probable effect levels. All metal concentrations were higher than Average Shale Value (ASV) except Mn and Hg. The positive matrix factorization (PMF) and absolute principal component score-multiple linear regression models (APCS-MLR) were applied to identify promising sources of metals in sediment samples. Both models identified three potential sources i.e. natural source, traffic emission, and industrial pollution, which accounted for 50.32%, 20.16%, and 29.51% in PMF model whereas 43.56%, 29.42%, and 27.02% in APCS-MLR model, respectively. Based on ecological risk assessment, pollution load index (7.74), potential ecological risk (1078.45), Nemerow pollution index (5.50), and multiple probable effect concentrations quality (7.73) showed very high contamination of toxic metal in sediment samples.