Exposure to indoor and outdoor air pollution in schools in Africa: Current status, knowledge gaps, and a call to action
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Chronic exposure to indoor and outdoor air pollution is linked to adverse human health impacts worldwide, and in children, these include increased respiratory symptoms, reduced cognitive and academic performance, and absences from school. African children are exposed to high levels of air pollution from aging diesel and gasoline second-hand vehicles, dusty roads, trash burning, and solid-fuel combustion for cooking. There is a need for more empirical evidence on the impact of air pollutants on schoolchildren in most countries of Africa. Therefore, we conducted a scoping review on schoolchildren's exposure to indoor and outdoor PM 2.5 (particulate matter with an aerodynamic diameter less than 2.5 μm and PM 10 (particulate matter with an aerodynamic diameter less than 10 μm) in Africa. Following PRISMA guidelines, our search strategy yielded 2975 records, of which eight peer-reviewed articles met our selection criteria and were considered in the final analysis. We also analyzed satellite data on PM 2.5 and PM 10 levels in five African regions from 1990 to 2019 and compared schoolchildren's exposure to PM 2.5 and PM 10 levels in Africa with available data from the rest of the world. The findings showed that schoolchildren in Africa are frequently exposed to PM 2.5 and PM 10 levels exceeding the recommended World Health Organization air quality guidelines. We conclude with a list of recommendations and strategies to reduce air pollution exposure in African schools. Education can help to produce citizens who are literate in environmental science and policy. Continuing air quality measurement in schools and more intervention studies are needed to protect schoolchildren's health and reduce exposure to air pollution in classrooms across Africa.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.001 |
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 it