Pollution status, ecological risk, and source apportionment of trace metals in shelf surface sediments off the southeast coast of India

Abstract

Trace metal accumulation in marine sediments is a significant environmental concern due to their prolonged residence times, toxicity, and potential ecological impacts. This study investigated the distribution, pollution status, ecological risk, and source apportionment of trace metals in shelf surface sediments off the southeast coast of India. A set of 35 surface sediments was analysed for sediment texture, organic matter (OM), and concentrations of Fe, Cr, Co, Zn, Ni, Pb, Cd, Cu, Ba, V, and Mn. The sediments were predominantly muddy sand to slightly muddy sand in texture, and OM ranged from 1.05% to 2.65%. The minimum and maximum concentrations of Fe: 1.38–6.33 wt%, Cr (7.24-169.95 ppm), Co (2.79–29.64 ppm), Zn (2.85–44.89 ppm), Ni (13.17–53.74 ppm), Pb (12.20-38.25 ppm), Cd (0.22–4.10 ppm), Cu (22.04–80.48 ppm), Ba (18.71-567.15 ppm), V (15.87-121.39 ppm), and Mn (75.24-1239.49 ppm). Average concentrations of Pb, Cu, and Cd were higher than the upper continental crust (UCC) values. Various contamination indices (Contamination factor, degree of contamination, modified degree of contamination, and geoaccumulation index) indicate substantial Cd contamination, moderate Pb contamination, and no Cu contamination. Ecological risk indices further revealed that Cd posed an extremely high ecological risk, whereas Pb and Cu posed a moderate risk, and the remaining metals showed negligible risk. The Pollution Load Index (PLI) is < 1, indicating a baseline level of pollution. Pearson’s correlation revealed that fine-grained sediments primarily control metal concentrations, whereas OM exerted a secondary influence. However, three potential sources: lithogenic (54%), mixed lithogenic-anthropogenic (25%), and maritime-related activities (21%) were identified using principal component analysis with absolute principal component scores (PCA-APCS). The PCA findings are broadly consistent with Pearson’s correlation and Q-mode cluster analyses.