Toward resolving the budget discrepancy of ozone-depleting carbon tetrachloride (CCl <sub>4</sub> ): an analysis of top-down emissions from China
Bibliographic record
Abstract
Carbon tetrachloride (CCl 4 ) is a first-generation ozone-depleting substance, and its emissive use and production were globally banned by the Montreal Protocol with a 2010 phase-out; however, production and consumption for non-dispersive use as a chemical feedstock and as a process agent are still allowed. This study uses the high frequency and magnitude of CCl 4 pollution events from an 8-year real-time atmospheric measurement record obtained at Gosan station (a regional background monitoring site in East Asia) to present evidence of significant unreported emissions of CCl 4 . Top-down emissions of CCl 4 amounting to 23.6±7.1 Gg yr −1 from 2011 to 2015 are estimated for China, in contrast to the most recently reported, post-2010, Chinese bottom-up emissions of 4.3–5.2 Gg yr −1 . The missing emissions (∼19 Gg yr −1 ) for China contribute to approximately 54 % of global CCl 4 emissions. It is also shown that 89 % ±6 % of CCl 4 enhancements observed at Gosan are related to CCl 4 emissions from the production of CH 3 Cl, CH 2 Cl 2 , CHCl 3 and C 2 Cl 4 and its usage as a feedstock and process agent in chemical manufacturing industries. Specific sources and processes are identified using statistical methods, and it is considered highly unlikely that CCl 4 is emitted by dispersive uses such as old landfills, contaminated soils and solvent usage. It is thus crucial to implement technical improvements and better regulation strategies to reduce evaporative losses of CCl 4 occurring at the factory and/or process levels.
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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 | 0.000 |
| 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 | 0.001 | 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".