Assessment of pollution levels, potential ecological risk and human health risk of heavy metals/metalloids in dust around fuel filling stations from the Kumasi Metropolis, Ghana
Bibliographic record
Abstract
The aim of this study was to evaluate the levels of selected heavy metals/metalloids in filling station dust from the Kumasi Metropolis, Ghana. A total of forty (40) dust samples were analysed for Fe, Ti, Zn, Zr, Mn, Sr, Ba, Cr, Pd, Ni, Cu, As and Mo using X-ray Fluorescence technique. Mean concentrations of Ba, As, Cr, Cu, Fe, Mn, Mo, Ni, Pb, Sr, Ti, Zn and Zr were 92.26, 6.20, 70.41, 50.18, 466.22, 163.68, 4.63, 44.05, 46.93, 106.69, 327.51, 280.32 and 182.05 mg/kg, respectively. The pollution index (PI) and geo-accumulation (Igeo) index values were in the order of Ba < Mn < Sr < Zr < Cu < Cr < Ni < Mo < As < Zn < Pb < Fe < Ti. The pollution load index had a mean of 2.20, signifying moderate pollution. Higher PI and Igeo value for Pb, Fe and Ti indicated high pollution. The PCA analysis identified anthropogenic inputs and natural origin as the main sources of pollution in filling station dust. The potential ecological risk index decreased as follows: As > Pb > Ni > Cu > Cr > Zn > Mn > Ba. The contribution of hazard quotient via ingestion for most of the heavy metals/metalloids were high with 11.83% for adults and 88.17% for children. For health risk assessment, non-carcinogenic values were below the threshold values, except hazard index via ingestion. The main exposure pathway for both children and adults was ingestion, followed by dermal contact and inhalation.
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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 | 0.000 | 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) | 0.001 | 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".