Formation and emission of hydrogen chloride in indoor air
Bibliographic record
Abstract
To improve our understanding of chlorine chemistry indoors, reactive chlorine species such as hydrogen chloride (HCl) must be analyzed using fast time-response measurement techniques. Although well studied outdoors, sources of HCl indoors are unknown. In this study, mixing ratios of gaseous HCl were measured at 0.5 Hz in the indoor environment using a cavity ring-down spectroscopy (CRDS) instrument. The CRDS measurement rate provides a major advance in observational capability compared to other established techniques. Measurements of HCl were performed during three types of household activities: (a) floor exposure to bleach, (b) chlorinated and nonchlorinated detergent use in household dishwashers, and (c) cooking events. Surface application of bleach resulted in a reproducible increase of 0.1 ppbv in the affected room. Emissions of HCl from automated dishwashers were observed only when chlorinated detergents were used, with additional HCl emitted during the drying cycle. Increased mixing ratios of HCl were also observed during meal preparation on an electric element stovetop. These observations of HCl derived from household activities indicate either direct emission or secondary production of HCl via chlorine atoms is possible. Calculations of photolysis rate constants of chlorine atom precursors provide evidence that photolysis may contribute to indoor HCl levels.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 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".