Monitoring of Air Quality for Particulate Matter (PM<sub>2.5</sub>, PM<sub>10</sub>) and Heavy Metals Proximate to a Cement Factory in Ewekoro, Nigeria
Bibliographic record
Abstract
A cement factory nearby communities raise pollution concerns. This study assessed air pollution levels for respirable particulate matter (PM2.5 and PM10) and heavy metals (lead, chromium, nickel, cadmium, zinc and copper) adjacent to a cement factory in Ewekoro and neighbouring communities (Papalantoro, Lapeleko and Itori) in Ogun State, Nigeria. Respirable particulate matter (PM2.5 and PM10) and heavy metals were measured using an ARA N-FRM cassette sampler. Each location sampled was monitored for eight continuous hours daily for 12 days. The PM2.5, PM10 and heavy metals results were compared with different standards, including those of the World Health Organization (WHO), Nigeria’s National Environmental Standard and Regulation Enforcement Agency (NESREA) and Canadian Ambient Air Quality Standards (CAAQS). The PM levels fell within 11 - 19 μg/m3 of the air management level of CAAQS, which signifies continuous actions are needed to improve air quality in the areas monitored but below the NESREA standard. The mean Cd, Cr and Ni concentrations in the cement factory area and the impacted neighbourhoods are higher than the WHO/EU permissible limits, while Zn and Cu were below the WHO/EU permissible limit. A risk assessment hazard quotient (HQ) for Cr was above the WHO/EU safe level (=1) in adults and children throµgh ingestion, inhalation and dermal contact at all the monitoring sites. The HQ for Ni and Cd was higher than the safe level in the cement factory area and Papalantoro, while Zn was at safe levels.
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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 | 0.000 | 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".