Comment on egusphere-2023-6
Bibliographic record
Abstract
Abstract. Trifluoromethane (CHF3, HFC-23), one of the most potent greenhouse gases among HFCs, is mainly emitted to the atmosphere as a by-product in the production of the ozone depleting legacy refrigerant and chemical feedstock chlorodifluoromethane (CHClF2, HCFC-22). A recent study on global HFC-23 emissions (Stanley et al., 2020) showed significant discrepancies over 2014–2017 between the increase in the observation-derived (top-down) emissions and the 87 % emission reduction expected from capture and destruction processes of HFC-23 at HCFC-22 production facilities mandated by national phase-out plans (bottom-up). However, the actual sources of the increased emissions were not identified. Here, we estimate the regional top-down emissions of HFC-23 for East Asia based on in situ measurements at Gosan, South Korea, and show that the HFC-23 emissions from eastern China have increased from 5.0 ± 0.4 Gg yr-1 in 2008 to 9.5 ± 1.0 Gg yr-1 in 2019. The continuous rise was contrary to the large emissions reduction reported since 2015 under the Chinese hydrochlorofluorocarbons production phase-out management plan (HPPMP). The magnitude of the mismatch between top-down and bottom-up estimates for 2015–2019 in eastern China was ~23.7 ± 3.6 Gg, which accounts for 47 ± 11 % of the global mismatch. Given the location of HCFC-22 production plants in eastern China and the fraction of regional to global HCFC-22 production capacities, the HFC-23 emissions rise in eastern China is most likely associated with known HCFC-22 production facilities and thus, observed discrepancies between top-down and bottom-up emissions could be attributed to unsuccessful factory level HFC-23 abatement and inaccurate quantification of emission reductions.
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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 | 0.002 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.018 | 0.010 |
| Insufficient payload (model declined to judge) | 0.381 | 0.257 |
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".