Exploring Conditions for Ultrafine Particle Formation from Oxidation of Cigarette Smoke in Indoor Environments
Bibliographic record
Abstract
Cigarette smoke is an important source of particles and gases in the indoor environment. In this work, aging of side-stream cigarette smoke was studied in an environmental chamber via exposure to ozone (O 3 ), hydroxyl radicals (OH) and indoor fluorescent lights. Aerosol mass concentrations increased by 13–18% upon exposure to 15 ppb O 3 and by 8–42% upon exposure to 0.45 ppt OH. Ultrafine particle (UFP) formation was observed during all ozone experiments, regardless of the primary smoke aerosol concentration (185–1950 μg m –3 ). During OH oxidation, however, UFP formed only when the primary particle concentration was relatively low (<130 μg m –3 ) and the OH concentration was high (∼1.1 × 10 7 molecules cm –3 ). Online aerosol composition measurements show that oxygen- and nitrogen- containing species were formed during oxidation. Gas phase oxidation of NO to NO 2 occurred during fluorescent light exposure, but neither primary particle growth nor UFP formation were observed. Overall, exposure of cigarette smoke to ozone will likely lead to UFP formation in indoor environments. On the other hand, UPF formation via OH oxidation will only occur when OH concentrations are high (∼10 7 molecules cm –3 ), and is therefore less likely to have an impact on indoor aerosol associated with cigarette smoke.
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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".