Occupational Health and Toxicological Risk of Exposure to Toxic Elements (TEs) in Top Soil from Residentially Situated Automobile Workshops (AWs)
Bibliographic record
Abstract
Background: Undoubtedly the biggest single cause of pollution, automobile emissions have a variety of negative occupational and human health impacts. Chemicals, paints, primers, and other hazardous products are frequently used in auto workshops' operational procedures. Substances like petrol, diesel, solvents, lubricants, and grease can be unintentionally or purposely release/exposed to the terrestrial environment. Numerous rock oil products consist of organic compounds that are capable of causing significant risk to soil, organisms, and humans due to their high toxicity. Objectives: The study aims to assess the occupational and toxicological risk of exposure to toxic elements (TEs) in topsoil from residentially situated automobile workshops (AWs) in Abeokuta, Ogun State, Nigeria. Methods: 12 composite soil samples were strategically collected and transported to the laboratory. 1 g of the processed sample was digested using aqua regia, namely a mixture of nitric acid and hydrochloric acid, optimally in a molar ratio of 1:3, while toxic elements analyses were done using an atomic absorption spectrometer (AAS). Results: The result showed the presence of arsenic (As = 0.67 – 5.63 mg/kg), cadmium (Cd = 8.92 – 134 mg/kg), cobalt (Co = 6.21 – 71.22 mg/kg), nickel (Ni = 1.89 – 9.18 mg/kg), and lead (Pb = 32.6 – 211 mg/kg) in the soil. The concentrations of Cd and Pb in 66.7% and 58.3% of the sample are higher than the Canada soil guideline value (CSGV) (for Cd 22 and for Pb 140 mg/kg) respectively. Contamination factors (CF) indicate very high soil contamination from Cd and Pb, and the significant association between the TEs (Pb, Cd, Co, Ni and As) p < 0.01, suggests an emergence from an anthropogenic origin. Hazard index (HI) values for the TEs were < 1, except for Pb (27.8) in the children, indicating a significant non-cancer-related effect on exposure, while the total cancer risk (TCR) value was within the threshold limit. Conclusions: The investigated topsoil is polluted with Cd and Pb, and there is a non-cancer-related effect on children with prolonged exposure to Pb. Therefore, AWs should be cited away from residential homes, while remediation of the polluted soil should be considered.
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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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".