Twenty Years of Global Stratospheric Fluorine Inventories From Atmospheric Chemistry Experiment Fourier Transform Spectrometer (ACE‐FTS) Measurements
Bibliographic record
Abstract
Abstract We present fluorine inventories calculated for twenty years (2004–2023) and five latitude bands (82°–60°N, 60°–30°N, 30°N–30°S, 30°–60°S, and 60°–82°S) at altitudes from the surface up to 55 km. The inventories were calculated using the Atmospheric Chemistry Experiment Fourier transform spectrometer (ACE‐FTS) version 5.2 retrievals of the volume mixing ratios (VMRs) of 15 fluorine‐containing species. Of these 15 species, 3 are product gases: , , , and 12 are source gases: , PFC‐14 (), CFC‐11 (), CFC‐12 (), CFC‐113 (), HCFC‐22 (), HCFC‐141b (), HCFC‐142b (), HFC‐23 (), HFC‐32 (), HFC‐125 (), and HFC‐134a (). As necessary, ACE‐FTS data were supplemented with data from the TOMCAT 3‐D chemical transport model and ground‐based measurements from the National Oceanic and Atmospheric Administration (NOAA) and the Advanced Global Atmospheric Gases Experiment (AGAGE). The total fluorine () profiles are dominated by source gas contributions in the troposphere and lower stratosphere up to 35 km in the tropics (30°N–30°S), 30 km in midlatitudes (60°–30°N/30°–60°S) and 24 km near the poles (82°–60°N/60°–82°S). In this atmospheric region, the primary contributions come from CFCs, HCFCs, carbon tetrafluoride (), and increasingly in recent years HFCs. Above these altitudes increasingly dominates the profile reaching as much as 79% of at 55 km. The 2004–2023 time series of the mean inventories shows a global increase of 48.9 0.7 ppt/year or 1.68 0.02%/year resulting in a mean approaching 3.5 ppb in 2023.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".