Organic Peroxides and Sulfur Dioxide in Aerosol: Source of Particulate Sulfate
Bibliographic record
Abstract
Sulfur oxides (SO x ) are important atmospheric trace species in both gas and particulate phases, and sulfate is a major component of atmospheric aerosol. One potentially important source of particulate sulfate formation is the oxidation of dissolved SO 2 by organic peroxides, which comprises a major fraction of secondary organic aerosol (SOA). In this study, we investigated the reaction kinetics and mechanisms between SO 2 and condensed-phase peroxides. pH-dependent aqueous phase reaction rate constants between S(IV) and organic peroxide standards were measured. Highly oxygenated organic peroxides with O/C > 0.6 in α-pinene SOA react rapidly with S(IV) species in the aqueous phase. The reactions between organic peroxides and S(IV) yield both inorganic sulfate and organosulfates (OS), as observed by electrospray ionization ion mobility mass spectrometry. For the first time, 34 S-labeling experiments in this study revealed that dissolved SO 2 forms OS via direct reactions without forming inorganic sulfate as a reactive intermediate. Kinetics of OS formation was estimated semiquantitatively, and such reaction was found to account for 30–60% of sulfur reacted. The photochemical box model GAMMA was applied to assess the implications of the measured SO 2 consumption and OS formation rates. Our findings indicate that this novel pathway of SO 2 –peroxide reaction is important for sulfate formation in submicron aerosol.
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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".