Concentrations and emissions of trichlorotrifluoroethane (CFC-113) from eastern china inferred from atmospheric observations
Bibliographic record
Abstract
Abstract Trichlorotrifluoroethane (C 2 Cl 3 F 3 , CFC-113) is a long-lived ozone-depleting substance (ODS) regulated under the Montreal Protocol and a potent greenhouse gas (GHG). Production and consumption of chlorofluorocarbons (CFCs) were phased out after 2007 in China, while unexpected increases in CCl 3 F (CFC-11) emissions from eastern China after 2012 were inferred from atmospheric observations. However, atmospheric concentrations and emissions of CFC-113 in China over the past few years are unclear. In this study, we conducted hourly observation of atmospheric CFC-113 concentrations in 2021 in eastern China, explored the potential CFC-113 emission sources using a dispersion model, and estimated the CFC-113 emissions using an interspecies correlation method. Results show that pollution events of CFC-113 were observed frequently, and the concentrations were higher than those of global background stations with similar latitudes. The dominant potential emission regions of CFC-113 were located in the eastern-central Yangtze River Delta region and Shandong province. The estimated mean CFC-113 emission from eastern China in 2021 was 0.88 ± 0.19 Gg/yr (5350 ± 1155 CO 2 -equivalent Gg/yr), which was higher than 0 Gg/yr (0 CO 2 -equivalent Gg/yr) in 2008−2021, as reported by bottom-up studies that considered CFC-113 to be phased out in China after 2007. Therefore, substantial CFC-113 emissions still existed in eastern China in 2021, which are of importance to protecting the ozone layer and mitigating the effects of climate change.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.012 | 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 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".