Twenty years of global stratospheric fluorine inventories from Atmospheric Chemistry Experiment Fourier Transform Spectrometer (ACE-FTS) measurements
Bibliographic record
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: HF, COF 2 , COClF, and 12 are source gases: SF 6 , PFC-14 (CF 4 ), CFC-11 (CCl 3 F), CFC-12 (CCl 2 F 2 ), CFC-113 (CClF 2 CCl 2 F), HCFC-22 (CHF 2 Cl), HCFC-141b (C 2 H 3 Cl 2 F), HCFC-142b (C 2 H 3 ClF 2 ), HFC-23 (CHF 3 ), HFC-32 (CH 2 F 2 ), HFC-125 (C 2 HF 5 ), and HFC-134a (C 2 H 2 F 4 ). As necessary, ACE-FTS data was supplemented with data from the TOMCAT 3-D chemical transport model and ground-based measurements from the National Oceanic and Atmospheric Administration (NOAA) & the Advanced Global Atmospheric Gases Experiment (AGAGE). The total fluorine (F tot ) 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 mid-latitudes (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 (CF 4 ), and increasingly in recent years HFCs. Above these altitudes HF increasingly dominates the F tot profile, reaching as much as 79% of F tot at 55 km. The 2004–2023 time series of the mean F tot inventories shows a global increase of 48.9 ± 0.7 ppt/year or 1.68 ± 0.02 %/year resulting in a mean F tot 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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 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".