Behavior of Isocyanic Acid and Other Nitrogen-Containing Volatile Organic Compounds in The Indoor Environment
Bibliographic record
Abstract
Isocyanic acid (HNCO) and other nitrogen-containing volatile chemicals (organic isocyanates, hydrogen cyanide, nitriles, amines, amides) were measured during the House Observation of Microbial and Environmental Chemistry (HOMEChem) campaign. The indoor HNCO mean mixing ratio was 0.14 ± 0.30 ppb (range 0.012-6.1 ppb), higher than outdoor levels (mean 0.026 ± 0.15 ppb). From the month-long study, cooking and chlorine bleach cleaning are identified as the most important human-related sources of these nitrogen-containing gases. Gas oven cooking emits more isocyanates than stovetop cooking. The emission ratios HNCO/CO (ppb/ppm) during stovetop and oven cooking (mean 0.090 and 0.30) are lower than previously reported values during biomass burning (between 0.76 and 4.6) and cigarette smoking (mean 2.7). Bleach cleaning led to an increase of the HNCO mixing ratio of a factor of 3.5 per liter of cleaning solution used; laboratory studies indicate that isocyanates arise via reaction of nitrogen-containing precursors, such as indoor dust. Partitioned in a temperature-dependent manner to indoor surface reservoirs, HNCO was present at the beginning of HOMEChem, arising from an unidentified source. HNCO levels are higher at the end of the campaign than the beginning, indicative of occupant activities such as cleaning and cooking; however the direct emissions of humans are relatively minor.
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 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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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".