Identification of the Contamination Sources by PCBs Using Multivariate Analyses: The Case Study of the Annaba Bay (Algeria) Basin

Molecules. 2023 Sep 28;28(19):6841. doi: 10.3390/molecules28196841.

Abstract

Persistent Organic Pollutants (POPs), particularly the indicator polychlorinated biphenyls (PCBs), were first quantified in water and sediments of two wadis, Boujemaâ and Seybouse, as well as in the effluents from a fertilizer and phytosanitary production industrial plant (Fertial). Since these contaminated discharges end in Annaba Bay (Algeria) in the Mediterranean Sea, with a significant level of contamination, all the potential sources should be identified. In this work, this task is conducted by a multivariate analysis. Liquid-liquid extraction and gas chromatography/mass spectrometry (GC-MS) methods were applied to quantify seven PCB congeners, usually taken as indicators of contamination. The sum of the PCB concentrations in the sediments ranged from 1 to 6.4 μg/kg dw (dry weight) and up to 0.027 μg/L in waters. Principal component analysis (PCA) and hierarchical cluster analysis (HCA) were used for the multivariate analysis, indicating that the main sources of PCB emissions in the bay are urban/domestic and agricultural/industrial. The outfalls that mostly contribute to the pollution of the gulf are the Boujemaâ wadi, followed by the Seybouse wadi, and finally by the Fertial cluster and more precisely the annex basin of the plant. Although referring to a specific site of local importance, the work aims to present a procedure and a methodological analysis that can be potentially applicable to further case studies all over the world.

Keywords: PCA/HCA; PCB contamination sources; POPs; multivariate analysis; urban waste; wastewater.

MeSH terms

  • Algeria
  • Bays
  • Environmental Monitoring
  • Geologic Sediments / chemistry
  • Polychlorinated Biphenyls* / analysis
  • Water Pollutants, Chemical* / chemistry

Substances

  • Polychlorinated Biphenyls
  • Water Pollutants, Chemical

Grants and funding

This research was funded by King Saud University grant number RSP2023R404.