Hydroxyl radical reactivity at the air-ice interface
Bibliographic record
Abstract
Abstract. Hydroxyl radicals are important oxidants in the atmosphere and in natural waters. They are also expected to be important in snow and ice, but their reactivity has not been widely studied in frozen aqueous solution. We have developed a spectroscopic probe to monitor the formation and reactions of hydroxyl radicals in situ. Hydroxyl radicals are produced in aqueous solution via the photolysis of nitrite, nitrate, and hydrogen peroxide, and react rapidly with benzene to form phenol. Similar phenol formation rates were observed in aqueous solution and bulk ice. However, no reaction was observed at air-ice interfaces, or when bulk ice samples were crushed prior to photolysis to increase their surface area. We also monitored the heterogeneous reaction between benzene present at air-water and air-ice interfaces with gas-phase OH produced from HONO photolysis. Rapid phenol formation was observed on water surfaces, but no reaction was observed at the surface of ice. Under the same conditions, we observed rapid loss of the polycyclic aromatic hydrocarbon (PAH) anthracene at air-water interfaces, but no loss was observed at air-ice interfaces. Our results suggest that the reactivity of hydroxyl radicals toward aromatic organics is similar in bulk ice samples and in aqueous solution, but is significantly suppressed in the quasi-liquid layer (QLL) that exists at air-ice interfaces.
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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".