Toxicological Risk Evaluation of Polycyclic Aromatic Hydrocarbons in Soils from a Petroleum Spillage Site at Kokori in the Niger Delta Region of Nigeria
Bibliographic record
Abstract
Polycyclic aromatic hydrocarbons (PAHs) are widespread environmental contaminants that are produced by the incomplete combustion of organic sources and are widely found in soils. This present research was carried out to evaluate the concentrations and toxicological risk assessment of the United States Environmental Protection Agency's sixteen priority polycyclic aromatic hydrocarbons (16 priority PAHs) in soils from the vicinity of an oil spillage site in Delta State of Nigeria. The level of pollution and potential toxicological health hazards of the PAHs were assessed in surface soil samples using soxhlet extraction of and Gas Chromatography-Mass Spectrometry (GC-MS). Thirteen out of the sixteen USEPA priority PAHs were detected in the soil sample. The concentrations of PAHs in the petroleum-contaminated soils in this investigation ranged from 0.01181 ppm to 1.16054 ppm, with the total estimated concentration of the 16 priority PAHs being 5.6713 ppm. Furthermore, the distribution of the PAHs in the study area was predominated by LMW PAHs (62%) over HMW PAHs (38%). Additionally, the total toxicity equivalency quotients TEQ (B[a]Peq) result of the carcinogenic potency of the USEPA priority PAHs was calculated as 0.08689 ppm (8.689%) and was discovered to be within the Canadian TEQ (B[a]Peq) threshold of 0.6 ppm. This suggests that the soil in the study area is safe based on the Canadian TEQ (B[a]Peq) standard and does not constitute a carcinogenic risk. However, the long-term bioaccumulation of these low quantities of PAHs in human has been found to constitute a potential health concern due to bioaccumulation in living systems.
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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 | 0.000 |
| 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".