Recent Trends in Stratospheric Chlorine From Very Short‐Lived Substances
Bibliographic record
Abstract
Abstract Very short‐lived substances (VSLS), including dichloromethane (CH 2 Cl 2 ), chloroform (CHCl 3 ), perchloroethylene (C 2 Cl 4 ), and 1,2‐dichloroethane (C 2 H 4 Cl 2 ), are a stratospheric chlorine source and therefore contribute to ozone depletion. We quantify stratospheric chlorine trends from these VSLS (VSLCl tot ) using a chemical transport model and atmospheric measurements, including novel high‐altitude aircraft data from the NASA VIRGAS (2015) and POSIDON (2016) missions. We estimate VSLCl tot increased from 69 (±14) parts per trillion (ppt) Cl in 2000 to 111 (±22) ppt Cl in 2017, with >80% delivered to the stratosphere through source gas injection, and the remainder from product gases. The modeled evolution of chlorine source gas injection agrees well with historical aircraft data, which corroborate reported surface CH 2 Cl 2 increases since the mid‐2000s. The relative contribution of VSLS to total stratospheric chlorine increased from ~2% in 2000 to ~3.4% in 2017, reflecting both VSLS growth and decreases in long‐lived halocarbons. We derive a mean VSLCl tot growth rate of 3.8 (±0.3) ppt Cl/year between 2004 and 2017, though year‐to‐year growth rates are variable and were small or negative in the period 2015–2017. Whether this is a transient effect, or longer‐term stabilization, requires monitoring. In the upper stratosphere, the modeled rate of HCl decline (2004–2017) is −5.2% per decade with VSLS included, in good agreement to ACE satellite data (−4.8% per decade), and 15% slower than a model simulation without VSLS. Thus, VSLS have offset a portion of stratospheric chlorine reductions since the mid‐2000s.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.022 | 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 teacher head, 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".