Assessment of Soil Contamination with Monocyclic Aromatic Hydrocarbons and Heavy Metals in Residential Areas Sited Close to Fuel Filling Stations in Ibadan Metropolis
Bibliographic record
Abstract
The study aimed to assess soil contamination with mono-cyclic aromatic hydrocarbons and heavy metals in residential areas situated close to (1-20m range) fuel filling stations in Ibadan metropolis, Nigeria. The study involved a laboratory based analysis of soil samples collected in the neighbourhood of five fuel filling stations systematically selected during the study. Two local government areas were randomly selected for the study, they were split into five natural clusters and soil samples were purposively collected from the neighbourhood of one fueling station per cluster. Topsoil (0 – 15cm deep) and subsoil (15 – 30cm deep) samples were collected at 5m, 10m, and 20m intervals away from the fuel filling stations. Samples were analyzed for benzene, toluene, ethyl-benzene, xylene, lead, and chromium using standard methods. Results were compared with Canadian and United Kingdom standards. Results were analyzed using descriptive statistics and were compared with the Canadian (monocyclic aromatic hydrocarbon) soil quality guideline limit for human health and the UK heavy metal guideline limit for soil in residential areas. Apart from xylene, the mean concentration of benzene, toluene, and ethyl-benzene were approximately 600 times higher than the Canadian limit both for topsoil and subsoil. Fortunately, mean concentrations of lead and chromium in all soil samples were insignificant compared with the UK limit. The study showed that there is contamination of the soil in the study area with some monocyclic aromatic hydrocarbons namely benzene, toluene, and ethyl-benzene while there are no potential threats with regards to heavy metal contamination.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 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 teacher head, 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".