OH Radical Oxidation of Organosulfates in the Atmospheric Aqueous Phase
Bibliographic record
Abstract
Organosulfates (OS, ROSO 3 – ), ubiquitous constituents of atmospheric particulate matter (PM), influence both the physicochemical and climatic properties of PM. Although the formation pathways of OS have been extensively researched, only a few studies have investigated the atmospheric fate of this class of compounds. Here, to better understand the reactivity and transformation of OS under cloudwater- and aerosol-relevant conditions, we investigate the hydroxyl radical (OH) oxidation bimolecular rate constants ( k OS+OH II ) and products of five atmospherically relevant OS as a function of pH and ionic strength: methyl sulfate (MeS), ethyl sulfate (EtS), propyl sulfate (PrS), hydroxyacetone sulfate (HaS) and phenyl sulfate (PhS). Our results show that OS are oxidized by OH with k OS+OH II between 10 8 – 10 9 M –1 s –1, which corresponds to atmospheric lifetimes of minutes in aqueous aerosol to days in cloudwater. We find that k OS+OH II increases with carbon chain length (MeS < EtS < PrS) and aromaticity (PrS < PhS), but does not depend on solution pH (2, 9). In addition, we find that whereas the OH reactivity of the aliphatic OS studied here decreases by ∼2× with increasing ionic strength (0–15 M), the reactivity of PhS decreases by ∼10×. The oxidation of EtS and PrS produced organic peroxides (ROOH) as first-generation oxidation products, which subsequently photolyzed; the oxidation of PhS resulted in hydroxylated aromatic products. These results highlight the need for inclusion of OS loss pathways in atmospheric models, and suggest caution in using ambient OS concentration measurements alone to estimate their production rates.
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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".