Linkages between ozone depleting substances, tropospheric oxidation and aerosols
Bibliographic record
Abstract
Abstract. Coupling between the stratosphere and the troposphere allows changes in stratospheric ozone abundances to affect tropospheric chemistry. Large-scale effects from such changes on chemically produced tropospheric aerosols have not been systematically examined in past studies. We use a composition-climate model to investigate potential past and future impacts of changes in stratospheric Ozone Depleting Substances (ODS) on tropospheric oxidants and sulfate aerosols. In most experiments, we find significant responses in tropospheric photolysis and oxidants, with small but significant effects on methane radiative forcing. The response of sulfate aerosols is sizeable when examining the effect of increasing future nitrous oxide (N2O) emissions. We also find that without the regulation of chlorofluorocarbons (CFCs) through the Montreal Protocol, sulfate aerosols could have increased by 2050 by a comparable amount to the decreases predicted due to relatively stringent sulfur emissions controls. The historical radiative forcing of CFCs through their indirect effects on methane (−22.6 mW m−2) and sulfate aerosols (−3.0 mW m−2) discussed here is non-negligible when compared to known historical CFC forcing. Our results stress the importance of accounting for stratosphere-troposphere, gas-aerosol and composition-climate interactions when investigating the effects of changing emissions on atmospheric composition and climate.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".