Formation of hydroxyl radicals from photolysis of secondary organic aerosol material
Bibliographic record
Abstract
Abstract. This paper demonstrates that OH radicals are formed by photolysis of secondary organic aerosol (SOA) material formed by terpene ozonolysis. The SOA aerosol is collected on filters, dissolved in water containing a radical trap (benzoic acid), and then exposed to ultraviolet light in a photochemical reactor. The OH formation rates, which are similar for both α-pinene and limonene SOA, are measured from the formation rate of p-hydroxybenzoic acid as measured using offline HPLC analysis. To evaluate whether the OH is formed by photolysis of H2O2 or organic hydroperoxides (ROOH), the peroxide content of the SOA was measured using the horseradish peroxidase-dichlorofluorescein (HRP-DCF) assay, which was calibrated using H2O2. The OH formation rates from SOA are five times faster than from the photolysis of H2O2 solutions whose concentrations correspond to the peroxide content of the SOA solutions assuming that the HRP-DCF signal arises from H2O2 alone. The higher rates of OH formation from SOA are likely due to ROOH photolysis. This result is substantiated by photolysis experiments conducted with t-butyl hydroperoxide and cumene hydroperoxide which produce over three times more OH than photolysis of equivalent concentrations of H2O2. Relative to the peroxide level in the SOA, the quantum yield for OH generation from α-pinene SOA is 0.8 ± 0.4. This is the first demonstration of an efficient photolytic source of OH in SOA, one that may affect both cloudwater and aerosol chemistry.
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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) | 0.002 | 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".