The Impact of Very-Short-Lived Chlorocarbons on Stratospheric Chlorine and Ozone Abundance During 2011-2022
Bibliographic record
Abstract
Stratospheric ozone is catalytically destroyed by chlorine released from ozone-depleting substances (ODS), e.g., chlorofluorocarbons, and halogenated very-short-lived substances (VSLS). In addition to chlorine contributions from continued emissions of Montreal Protocol-regulated long-lived ODSs (from existing banks, production, consumption, and feedstocks), recent research has highlighted concern over rapidly growing emissions of dichloromethane (CH2Cl2) - a chlorinated VSLS (Cl-VSLS). Large emissions come from Asia have developed because of fast economic growth. In this study, we have conducted model simulations with geographically resolved surface emissions of the two most abundant Cl-VSLS, CH2Cl2 and CHCl3, with the NASA GEOS Chemistry Climate Model (GEOSCCM). The simulations cover the 2011-2022 period to understand the transport pathway of Asian Cl-VSLS emissions to the stratosphere and to quantify the contribution of Asian emissions to the stratospheric chlorine budget w.r.t. the global estimate during the 2010s. With global emissions of about 1300 Gg/yr in 2020-2022, our results suggest Cl-VSLS adds about 120 ppt Cl to stratospheric chlorine. The Asian Summer Monsoon plays a dominant role in the troposphere-to-stratosphere transport of Cl-VSLS and is twice as efficient for delivering CH2Cl2 to the stratosphere than the tropics. About 200 ppt of VSLS-Cl gets into the stratosphere during summer 2022 within Asian Summer Monsoon Anticyclone. GEOSCCM simulation results suggest that the overall impact of Cl-VSLS on stratospheric ozone is < 2 DU (0.7%) globally. Interestingly, 2019 features an anomalously large ozone perturbation due to Cl-VSLS. While global ozone changes little, total column ozone decreases by 10 DU in the Antarctic but increases by 15 DU in the Arctic.
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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 | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".