A recent slowdown in the decline of CFC-11 concentrations in the upper troposphere
Bibliographic record
Abstract
Since 2004, the Atmospheric Chemistry Experiment – Fourier Transform Spectrometer (ACE-FTS) instrument has been measuring concentrations of chlorofluorocarbons (CFCs) in the stratosphere and upper troposphere and is currently the only satellite instrument that measures vertically resolved profiles of CFC‑11. Since CFCs are major ozone depleting substances, monitoring their atmospheric abundances is critical for understanding ozone layer recovery. Recent studies based solely on surface-level measurements have shown strong evidence for new CFC‑11 production, leading to an increase in CFC‑11 emissions over the past decade. In this study, the TOMCAT/SLIMCAT 3-D chemical transport model is used in order to bridge the altitude/geolocation gap between ACE-FTS measurements in the UTLS and surface level measurements. Trends in two different time periods over the ACE-FTS mission, 2004-2012 and 2013-2018, are examined to determine if the recent change in surface level CFC-11 trends is influencing UTLS concentrations. The ACE-FTS measurements show that, below ~10 km, the rate of decrease of global CFC-11 concentrations was slower during 2013-2018 (-1.2 pptv/year) than during 2004-2012 (‑2.0 pptv/year). Similar trends are observed in the model data for the same spatial/temporal regions.
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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 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".