Grill workers and air pollution health effects from charcoal combustion in Vientiane capital
Bibliographic record
Abstract
Introduction: Grilled street foods are popular in urban communities in Lao People's Democratic Republic (Lao PDR). Charcoal is the main fuel used for, posing a risk of elevated exposure to toxic pollutants. This study explored levels of cooking-related pollutants from grilled food business and workers’ health effects. Materials and methods: A quantitative approach using multiple techniques was conducted during March and April 2022 in Vientiane Capital, Lao PDR. Methods included pollutant emission estimation from charcoal-combusting grill shops/street-carts and Particulate Matter (PM2.5) measurement, and examined the exposure and health effects among grill workers. Multiple sampling techniques were applied to identify study samples. Respiratory symptoms were the health effect of interest among grill workers. Results: Estimated emission of pollutants was over 75 tons/year from grill shops. Average PM 2.5 level was 84.8 μg/m3 (21.6 - 254.8 μg/m3); which i above standard limits. A very high level of PM2.5 was found in grill markets. Most grill workers were female, worked 6-7 days/week, at least 8 h/day. Factors contributing to the presence of respiratory symptoms among grill workers were female gender, low income, indoor grilling, more years of grill-work, experience of intense smoke-cough, self-reliance on health and cigarette smoking. Conclusion: Grilling contributes to ambient air pollution, posing potential adverse environmental and public health impacts. Grill workers are likely to be exposed to high levels of all forms of air pollutants from street food grilling. Effective strategies are required to better protect grill workers from the effect of exposure to these harmful toxins and minimize the negative impacts on their health.
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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 | 0.000 | 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".