Preliminary hazard assessment of air pollution levels in Nizwa, Rusayl and Sur in Oman
Bibliographic record
Abstract
The World Health Organization (WHO) recognises air pollution as a serious public health concern in many developing countries due to the influx of energy-intensive industries with limited planning and exposure mitigation strategies. Due to industrial expansion and release of associated air pollutants in Oman, the US Environmental Protection Agency human health risk assessment (HHRA) model was used to determine the non-carcinogenic hazard associated with exposure to industrial emissions. Across the three industrial cities (Nizwa, Sur and Rusayl), the study found ambient average concentrations (μg/m 3 ) of 1 h carbon monoxide (CO) (606–1974), nitrogen dioxide (NO 2 ) (7.7–43.9) and sulfur dioxide (SO 2 ) (4.8–9.0) and 24 h PM 2.5 (7.3–7.8) and PM 10 (38.7–51.5) to be significantly lower than both the Ministry of Environment and Climatic Affairs (MECA) and WHO limits. The HHRA analysis showed that exposure to the air pollutants produced low non-carcinogenic adverse health effects, as the hazard quotient (HQ) was found to be <1 among the population. However, there was an increase in HQ for WHO reference exposure level (REL) values compared with that of MECA; this is due to the relaxed/high REL limits of the latter. Future epidemiological studies involving long-term air pollution exposure assessment and health data may improve the reliability of the current HHRA estimates.
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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 | 0.001 | 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 | 0.000 | 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".