Multiphase Oxidation of Sulfur Dioxide in Aerosol Particles: Implications for Sulfate Formation in Polluted Environments
Bibliographic record
Abstract
Abstract Atmospheric oxidation of sulfur dioxide (SO2) forms sulfate-containing aerosol particles that impact air quality, climate, and human and ecosystem health. It is well-known that in-cloud oxidation of SO2 frequently dominates over gas-phase oxidation on regional and global scales. Multiphase oxidation involving aerosol particles, fog, and cloud droplets has been generally thought to scale with liquid water content (LWC) so multiphase oxidation would be negligible for aerosol particles due to their low aerosol LWC. However, recent field evidence, particularly from East Asia, shows that fast sulfate formation prevails in cloud-free environments that are characterized by high aerosol loadings. By assuming that the kinetics of cloud water chemistry prevails for aerosol particles, most atmospheric models do not capture this phenomenon. Therefore, the field of aerosol SO2 multiphase chemistry has blossomed in the past decade, with many oxidation processes proposed to bridge the difference between modeled and observed sulfate mass loadings. This review summarizes recent advances in the fundamental understanding of the aerosol multiphase oxidation of SO2, with a focus on environmental conditions that affect the oxidation rate, experimental challenges, mechanisms and kinetics results for individual reaction pathways, and future research directions. Compared to dilute cloud water conditions, this paper highlights the differences that arise at the molecular level with the extremely high solute strengths present in aerosol particles.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".