Assessment of the Contamination Level of Polycyclic Aromatic Hydrocarbons in the Soil around Ekeatai River, Eket, Akwa Ibom State, Nigeria
Bibliographic record
Abstract
The presence of Polycyclic Aromatic Hydrocarbons (PAHs) in the environment has been a concern due to risk to human health and the ecosystem. This study was carried out to assess the contamination level of PAHs in the soil around Ekeatai watershed, Eket, Nigeria. Soil samples (0-30cm) were analyzed for the presence of the 16 US-EPA priority PAH and human health risk. The identification and quantification of the PAHs in the soil samples were carried out using the Aligent 7890B GC-FID. The results of the analysis revealed that amongst the 16 US-EPA priority PAHs, seven (7) were detected in the soil samples. The total concentration of PAHs detected in the study area were: fluorene (9.5870mg/kg), benzo(a)anthracene (1.2862mg/kg), pyrene (0.2782mg/kg), acenaphthene (0.1805mg/kg), anthracene (0.1545mg/kg), chrysene (0.1288mg/kg), and fluoranthene (0.0885mg/kg). PAH diagnostic ratio showed possible sources of PAHs to be pyrogenic, petrogenic and petroleum combustion. Benzo[a]anthracene and chrysene detected in the study area are known to be carcinogenic. The BaPTEQ for ΣPAH carcinogen ranged from 0.00013 - 0.13mg BaPTEQ/kg and the BaPTPE calculated in the study area was 0.13mg/kg. The values were lower than the human health-based soil quality guidelines for PAHs based on Incremental Lifetime Cancer Risk of the Canadian government.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".