Aqueous-phase autoxidation in the atmosphere: fate and formation of organic peroxides
Bibliographic record
Abstract
Autoxidation is a widely recognized mechanism known to initiate the degradation of food and lipids and modify organic matter in the atmosphere. Given the low NOx concentration in aqueous media (e.g., cloud water and fog droplets), autoxidation can become vital to facilitate the formation of highly oxygenated molecules such as organic peroxides (ROOH and ROOR). Here, we have identified aqueous-phase autoxidation-initiated hydroperoxides in varying organic precursors, including a laboratory model compound and monoterpene oxidation products. Our results show that autoxidation-initiated ROOHs are suppressed at enhanced precursor and oxidant concentrations. Furthermore, we observed an exponential increase in the yield of ROOHs when UV light with longer wavelengths was used in the experiment, comparing UVA, UVB, and UVC. Water-soluble organic compounds represent a significant fraction of ambient cloud water component (up to 500 µM. Thus, aqueous-phase autoxidation can become an important oxidation pathway for water-soluble species and as such facilitate the formation of ROOHs, thereby adding to the climate and health burden of atmospheric particulate matter.
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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".