Toward resolving the mysterious budget discrepancy of ozone-depleting CCl <sub>4</sub> : An analysis of top-down emissions from China
Bibliographic record
Abstract
Abstract. Emissive production and use of carbon tetrachloride (CCl4), one of the first-generation ozone-depleting substances, have been banned by the Montreal Protocol with the 2010 phase-out for developing countries, but production and consumption for non-dispersive use as a chemical feedstock and as process agent are still allowed. Here, we present evidence that significant unreported emissions of CCl4 still persist, based on the high frequency and magnitude of CCl4 pollution events observed in the 8-year real time atmospheric measurement record at Gosan station, a regional background monitoring site in East Asia. From this we estimate top-down emissions of CCl4 amounting to 23.6 ± 7.1 Gg yr−1 from 2011 to 2015 for China, in contrast to the 4.3–5.2 Gg yr−1 reported as the most up-to-date post-2010 Chinese bottom-up emissions. The missing emissions (~ 19 Gg yr−1) for China are highly significant, contributing about 54 % of global CCl4 emissions. We show that 89 ± 6 % of the CCl4 enhancements observed at Gosan can be accounted for by fugitive emissions of CCl4 occurring at the factory level during the production of CH3Cl, CH2Cl2, CHCl3 and C2Cl4 (PCE) and feedstock and solvent use in chemical manufacturing industries. Thus, it is crucial to implement technical improvements and better regulation strategies to reduce the evaporative losses of CCl4 occurring at the factory and/or process level.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".