Formation pathways of aldehydes from heated cooking oils
Bibliographic record
Abstract
Cooking emissions account for a major fraction of urban volatile organic compounds and organic aerosol. Aldehyde species, in particular, are important exposure hazards in indoor residential and occupational environments, and precursors to particulate matter and ozone formation in outdoor air. Formation pathways of aldehydes from oils that lead to their emissions are not well understood. In this work, we investigate the underlying mechanisms involved in the formation of aldehydes from heated cooking oil emissions, through studying how antioxidants and oil composition modulate oxidation chemistry. Our results demonstrate that gaseous emissions are driven by radical-mediated autoxidation reactions in cooking oil, and the composition of cooking oils strongly influences the reaction mechanisms. Antioxidants have a dual effect on aldehyde emissions depending on the rates of radical propagation reactions. We propose a mechanistic framework that can be used to understand and predict cooking emissions under different cooking conditions. Our results highlight the need to understand the rates and mechanisms of autoxidation and other reactions in cooking oils in order to accurately predict the gas- and particle-phase emissions from food cooking in urban atmospheres.
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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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".