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 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 5 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, but we cannot rule out a contribution from secondary processes as well. This result is substantiated by photolysis experiments conducted with t-butyl hydroperoxide and cumene hydroperoxide which produce over 3 times more OH than photolysis of equivalent concentrations of H2O2. Relative to the peroxide level in the SOA and assuming that the peroxides drive most of the ultraviolet absorption, 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 cloud water and aerosol chemistry.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.007 | 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 teacher head, 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".