Evaluation of Polycyclic Aromatic Hydrocarbons Contamination in Fresh And Dried Sardinella Madarensis (Flat Sardine Fish) From the Sombriero River, Niger Delta, Nigeria
The Niger Delta is a region that has been significantly impacted by oil exploration and other anthropogenic activities, that have resulted in severe environmental pollution. Fish serves as a primary source of protein in the local diet; hence, assessing contamination levels in fish species commonly consumed is crucial for public health safety. This study evaluates the contamination levels of polycyclic aromatic hydrocarbons (PAHs) in composite samples of fresh and dried (traditionaly smoked) Sardinella madarensis fish collected from the Sombreiro River in Nigeria’s Niger Delta. A total of 30 fish samples (15 fresh and 15 dried) were randomly collected from different vendors in locations along the riverbank and analysed as composites to provide an average contamination profile. PAHs were measured using gas chromatography-mass spectrometry (GC-MS), and the coefficient of variation (CV%) was used to evaluate the variability of contaminant concentrations. The results revealed significantly higher concentrations of 13 PAHs in dried fish, suggesting the influence of traditional smoking. Notably, the concentration of benzo(a)pyrene (BaP), a class I carcinogen, in dried fish (51.08 µg/kg), significantly exceeds the EU’s maximum limit of 2 µg/kg for BaP in smoked foods. High concentrations of benzo(b)fluoranthene both fresh and dried fish samples, were also noted, suggesting its environmental prevalence. These findings revealed the associated health risks of fish consumption in the region, emphasizing the urgent need for continuous monitoring and improved processing methods to safeguard public health.
Authors
- Oteiva Mokie Frank
- Jude Onoriode Otedo
- Abigail Okezi Isoje
- Enebi Estella Jasper
Institutions
- Western Delta University (NG)
- Rivers State University (NG)
Publication Details
- Journal
- ChemClass Journal
- Published
- 2025-05-25
- DOI
- https://doi.org/10.33003/chemclass-2025-0901/152
- Primary Topic
- Computational Drug Discovery Methods
- Type
- article
- Field-Weighted Citation Impact
- 0.00