Rates of Wintertime Atmospheric SO<sub>2</sub> Oxidation based on Aircraft Observations during Clear‐Sky Conditions over the Eastern United States
Bibliographic record
Abstract
Abstract Sulfur dioxide (SO2) is emitted in large quantities from coal‐burning power plants and leads to various harmful health and environmental effects. In this study, we use plume intercepts from the Wintertime INvestigation of Transport, Emission and Reactivity (WINTER) campaign to estimate the oxidation rates of SO2 under wintertime conditions and the factors that determine SO2 removal. Observations suggest that OH governs the rate SO2 oxidation in the eastern United States during winter. The range of mean oxidation rates during the day from power plants were 0.22–0.71%/hr, producing SO2 lifetimes of 13–43 days, if SO2 consumption is assumed to occur during 10.5 hr of daylight in cloudless conditions. Though most nighttime rate measurements were zero within uncertainty, there is some evidence of nighttime removal, which suggests alternate oxidation mechanisms. The fastest nighttime observed SO2 oxidation rate was 0.25±0.07%/hr, producing a combined day/night SO2 lifetime of 8.5–21 days. The upper limit of the oxidation rate (the mean+1σ of the fastest day and night observations) is 16.5%/day, corresponding to a lifetime of 6.1 days. The analysis also quantifies the primary emission of sulfate from power plants. The median mole percentage of SO4‐2 from observed plumes was 1.7% and the mean percentage sulfate was 2.8% for intercepts within 1 hr of transit to power plants. The largest value observed from close intercepts was over 7% sulfate, and the largest extrapolated value was 18%, based on intercepts further from their source and fastest observed oxidation rate.
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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) | 0.000 | 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".