Atmospheric impacts of chlorinated very short-lived substances over the recent past – Part 2: Impacts on ozone
Bibliographic record
Abstract
Abstract. Depletion of the stratospheric ozone layer remains an ongoing environmental issue, with increasing stratospheric chlorine from very short-lived substances (VSLS) recently emerging as a potential but uncertain threat to its future recovery. Here the impact of chlorinated VSLS (Cl-VSLS) on past ozone is quantified, for the first time, using the UM–UKCA (Unified Model–United Kingdom Chemistry and Aerosol) chemistry-climate model. Model simulations nudged to reanalysis fields show that in the second decade of the 21st century Cl-VSLS reduced total column ozone by, on average, ∼ 2–3 DU (Dobson unit) in the springtime high latitudes and by ∼0.5 DU in the annual mean in the tropics. The largest ozone reductions were simulated in the Arctic in the springs of 2011 and 2020. During the recent cold Arctic winter of 2019/20 Cl-VSLS resulted in local ozone reductions of up to ∼7 % in the lower stratosphere and of ∼7 DU in total column ozone by the end of March. Despite nearly doubling of Cl-VSLS contribution to stratospheric chlorine over the early 21st century, the inclusion of Cl-VSLS in the nudged simulations does not substantially modify the magnitude of the simulated recent ozone trends and, thus, does not help to explain the persistent negative ozone trends that have been observed in the extra-polar lower stratosphere. The free-running simulations, on the other hand, suggest Cl-VSLS-induced amplification of the negative tropical lower-stratospheric ozone trend by ∼20 %, suggesting a potential role of the dynamical feedback from Cl-VSLS-induced chemical ozone loss. Finally, we calculate the ozone depletion potential of dichloromethane, the most abundant Cl-VSLS, at 0.0107. Our results illustrate a so-far modest but nonetheless non-negligible role of Cl-VSLS in contributing to the stratospheric ozone budget over the recent past that if continues could offset some of the gains achieved by the Montreal Protocol.
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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 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".