Multiphase Reactions between Organic Peroxides and Sulfur Dioxide in Internally Mixed Inorganic and Organic Particles: Key Roles of Particle Phase Separation and Acidity
Bibliographic record
Abstract
Organic peroxides (POs) are ubiquitous in the atmosphere and particularly reactive toward dissolved sulfur dioxide (SO 2 ), yet the reaction kinetics between POs and SO 2, especially in complex inorganic–organic mixed particles, remain poorly constrained. Here, we report the first investigation of the multiphase reactions between SO 2 and POs in monoterpene-derived secondary organic aerosol internally mixed with different inorganic salts (ammonium sulfate, ammonium bisulfate, or sodium nitrate). We find that when the particles are phase-separated, the PO-S(IV) reactivity is consistent with that measured in pure SOA and depends markedly on the water content in the organic shell. However, when the organic and inorganic phases are miscible, the PO-S(IV) reactivity varies substantially among different aerosol systems, mainly driven by their distinct acidities (not by ionic strength). The second-order PO-S(IV) rate constant decreases monotonically from 5 × 10 5 to 75 M –1 s –1 in the pH range of 0.1–5.6. Both proton catalysis and general acid catalysis contribute to S(IV) oxidation, with their corresponding third-order rate constants determined to be (6.4 ± 0.7) × 10 6 and (6.9 ± 4.6) × 10 4 M –2 s –1 at pH 2–6, respectively. The measured kinetics imply that the PO-S(IV) reaction in aerosol is an important sulfate formation pathway, with the reaction kinetics dominated by general acid catalysis at pH > 3 under typical continental atmospheric conditions.
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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".