Particulate Matter and Volatile Organic Compound Emissions Generated from a Domestic Air Fryer
Bibliographic record
Abstract
Air frying has become a popular cooking method for domestic cooking, but the level of released indoor air pollutants is poorly understood. In this work, we compared particle and gas phase emission factors (EF) and particle size distributions between cooking with a domestic air fryer and a pan for a variety of foods. The PM 10 EFs of air frying chicken wings and breast were higher than pan cooking by a factor of 2.1 and 5.4, respectively. On the other hand, a higher PM 10 emission factor from air frying can be achieved by increasing the amount of oil to levels similar to or above those from pan-frying for French fries and asparagus. We propose that higher temperature and greater turbulence lead to higher PM 10 EFs for cooking with the air fryer compared with the pan for the same mass of oil added. EFs of volatile organic compounds (VOCs) are also generally higher for cooking with the air fryer compared with the pan: 2.5 times higher for French fries and 4.8 times higher for chicken breast. Our study highlights the potential risk of higher indoor PM 10 levels associated with domestic air frying under certain cases and proposes possible mitigation measures.
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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 | 0.001 | 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".