Report on the unexpected emissions of CFC-11. A report of the scientific assessment panel of the Montreal protocol on substances that deplete the ozone layer
Bibliographic record
Abstract
Global CFC-11 emissions were expected to decrease steadily after 2010 because of the full phaseout of production and consumption (see Figure ES.1, blue shading). Surprisingly, however, CFC-11 emissions began to increase in 2013 and were high from 2014 to 2018 (Figure ES.1, purple line). After the publication of this emission increase in 2018, emissions were substantially lower in 2019. A large fraction of the emission increase was attributed to Eastern China based on regional emission estimates. These regional emissions also declined substantially from 2017 to 2019. The increase in global CFC-11 emissions was not a result of increased bank releases. The amounts of CFC-11 in banks and the release rates from the banks remain highly uncertain (see Figure ES.1, blue shading). The increases in emissions observed to date are small enough not to have a major impact on CFC-11 atmospheric abundances, so they will not have a major impact on the expected stratospheric ozone recovery. However, the increases in banks and how they might augment future emissions have large uncertainties.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.011 | 0.004 |
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".