Impacts of Air Cleaners on Indoor Air Quality in Residences Impacted by Wood Smoke
Bibliographic record
Abstract
Residential wood combustion is an important source of ambient air pollution, accounting for over 25% of fine particulate matter (PM2.5) emissions in Canada. In addition to these ambient contributions, wood smoke pollutants can enter the indoor environment directly when loading or stoking stoves, resulting in a high potential for human exposure. A study of the effectiveness of air cleaners at reducing wood smoke-associated PM2.5 of indoor and outdoor origin was conducted in 31 homes during winter 2009-10. Day 1, the residents' wood burning appliance operated as usual with no air cleaner. Days 2 and 3, the wood burning appliance was not operational and the air cleaner was randomly chosen to operate in "filtration" or "placebo filtration" mode. When the air cleaner was operating, total indoor PM2.5 levels were significantly lower than on placebo filtration days (p = 0.0001) resulting in a median reduction of 52%. There was also a reduction in the median PM2.5 infiltration factor from 0.56 to 0.26 between these 2 days, suggesting the air cleaner was responsible for increased PM2.5 deposition on filtration days. Our findings suggest that the use of an air cleaner reduces exposure to indoor PM2.5 resulting from both indoor and ambient wood smoke sources.
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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 | 0.001 |
| 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) | 0.001 | 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".