Assessing the Effects of Stove Use Patterns and Kitchen Chimneys on Indoor Air Quality during a Multiyear Cookstove Randomized Control Trial in Rural India
Bibliographic record
Abstract
We conducted indoor air quality (IAQ) measurements during a multiyear cookstove randomized control trial in two rural areas in northern and southern India. A total of 1205 days of kitchen PM2.5 were measured in control and intervention households during six ∼3 month long measurement periods across two study locations. Stoves used included traditional solid fuel (TSF), improved biomass, and liquefied petroleum gas (LPG) models. Intent-to-treat analysis indicates that the intervention reduced average 24 h PM2.5 and black carbon in only one of the two follow-up measurement periods in both areas, suggesting mixed effectiveness. Average PM2.5 levels were ∼50% lower in households with LPG (for exclusive LPG use: >75% lower) than in those without LPG. PM2.5 was 66% lower in households making exclusive use of an improved chimney stove versus a traditional chimney stove and TSF-exclusive kitchens with a built-in chimney had ∼60% lower PM2.5 than those without a chimney, indicating that kitchen ventilation can be as important as the stove technology in improving IAQ. Diurnal trends in real-time PM2.5 indicate that kitchen chimneys were especially effective at reducing peak concentrations, which leads to decreases in daily PM2.5 in these households. Our data demonstrate a clear hierarchy of IAQ improvement in real world, “stove-stacking” households, driven by different stove technologies and kitchen characteristics.
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.
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 | 0.001 | 0.003 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".