Chemical Fate of Oils on Indoor Surfaces: Ozonolysis and Peroxidation
Bibliographic record
Abstract
Unsaturated triglycerides found in food and skin oils are reactive in ambient air. However, the chemical fate of such compounds has not been well characterized in genuine indoor environments. Here, we monitored the aging of oil coatings on glass surfaces over a range of environmental conditions, using mass spectrometry, nuclear magnetic resonance (NMR), and electron paramagnetic resonance (EPR) techniques. Upon room air exposure (up to 17 ppb ozone), the characteristic ozonolysis products, secondary ozonides, were observed on surfaces near the cooking area of a commercial kitchen, along with condensed-phase aldehydes. In an office setting, ozonolysis is also the dominant degradation pathway for oil films exposed to air. However, for indoor enclosed spaces such as drawers, the depleted air flow makes lipid autoxidation more favorable after an induction period of a few days. Forming hydroperoxides as the major primary products, this radical-mediated peroxidation behavior is accelerated by indoor direct sunlight, but the initiation step in dark settings is still unclear. These results are in accord with radical measurements, indicating that indoor photooxidation facilitates radical formation on surfaces. Overall, many intermediate and end products observed are reactive oxygen species (ROS) that may induce oxidative stress in human bodies. Given that these species can be widely found on both food and household surfaces, their toxicological properties are worth further attention.
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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".