Opinion: Stratospheric Ozone – Depletion, Recovery and New Challenges
Bibliographic record
Abstract
Abstract. We give a personal perspective on recent issues related to the depletion of stratospheric ozone and some newly emerging challenges. We first provide a brief review of historic work on understanding the ozone layer where we highlight some work from the late Paul Crutzen as a contribution to the special issue in his honour. We then review the status of ozone recovery from the effects of halogenated source gases and discuss the undoubted effectiveness of the Montreal Protocol and its challenges from renewed production of controlled substances and short-lived uncontrolled substances. We then discuss, in some detail, the recent observations of ozone depletion through injection of smoke particles from Australian fires in early 2020. Further unexpected perturbations to the ozone layer are occurring at the moment through injection of very large amounts of water vapour (and some sulphur dioxide) from the Hunga Tonga-Hunga Ha`apai volcano in January 2022. We conclude with some thoughts on the urgent need to ensure continuity in observations and on how to exploit ever more complex and expensive models. Overall, the stratospheric ozone layer continues to produce novel research challenges and reveal more processes that threaten this essential component of the Earth system.
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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 | 0.005 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.004 |
| Scholarly communication | 0.004 | 0.009 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.012 | 0.015 |
| Insufficient payload (model declined to judge) | 0.014 | 0.009 |
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".