Environmental effects of stratospheric ozone depletion, UV radiation, and interactions with climate change: UNEP Environmental Effects Assessment Panel, Update 2021
Bibliographic record
Abstract
The Environmental Effects Assessment Panel of the Montreal Protocol under the United Nations Environment Programme evaluates effects on the environment and human health that arise from changes in the stratospheric ozone layer and concomitant variations in ultraviolet (UV) radiation at the Earth's surface. The current update is based on scientific advances that have accumulated since our last assessment (Photochem and Photobiol Sci 20(1):1-67, 2021). We also discuss how climate change affects stratospheric ozone depletion and ultraviolet radiation, and how stratospheric ozone depletion affects climate change. The resulting interlinking effects of stratospheric ozone depletion, UV radiation, and climate change are assessed in terms of air quality, carbon sinks, ecosystems, human health, and natural and synthetic materials. We further highlight potential impacts on the biosphere from extreme climate events that are occurring with increasing frequency as a consequence of climate change. These and other interactive effects are examined with respect to the benefits that the Montreal Protocol and its Amendments are providing to life on Earth by controlling the production of various substances that contribute to both stratospheric ozone depletion and climate change.
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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 | 0.009 | 0.010 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.005 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.004 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".