Profiles and monthly variations of selected volatile organic compounds in indoor air in Canadian homes: Results of Canadian national indoor air survey 2012–2013
Bibliographic record
Abstract
Volatile organic compounds (VOCs) are important pollutants in indoor air. A major survey campaign was carried out over a 24-month period in 2012 and 2013 to monitor 88 selected VOCs in 3524 Canadian residential homes as part of the Canadian Health Measures Survey (CHMS). Among the 88 VOCs six (limonene, decamethylcyclopentasiloxane, toluene, hexanal, nonanal and α-pinene) were present in the highest concentrations with a combined geometric mean value (63.22 μg/m 3 ) accounting for more than half (54%) of the sum of all 88 VOCs. The geometric means of the majority of the VOCs obtained from this study were not significantly different from the levels of VOCs that were measured in a previous CHMS data collection cycle between 2009 and 2011. This study also further confirmed higher concentrations of the majority of measured VOCs in apartments compared to houses; and of several tobacco-related VOCs (benzene, styrene, naphthalene, 2-butanone, 2-methyl-1,3-butadiene, 2-furancarboxaldehyde, 2,5-dimethylfuran, benzofuran and phenol) in smoking homes. Furthermore, concentrations of aromatic and aliphatic hydrocarbons were higher in winter and in the months of June and July. Oxygenated hydrocarbons such as aldehydes, alcohols and ketones, on the other hand, were found to be higher in warmer months and peaked in summer months. These results provide valuable information on the levels of selected VOCs of which many have been monitored for the first time in Canadian homes, and can be used to estimate population exposure.
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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 | 0.001 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".