The estimated schedule and mitigation potential for hydrofluorocarbons phase-down in China
Bibliographic record
Abstract
As the major producer and consumer of hydrofluorocarbons (HFCs), China is obligated to phase-down HFCs to mitigate global warming if China ratifies the Kigali Amendment (KA) to the Montreal Protocol. Based on historical HFCs consumption in each sector, here we estimated historical HFCs emissions with a bottom-up method, and projected the consumption baseline and schedule for HFCs phase-down in China under the KA and the corresponding potential for emission reduction. Results showed that China's HFCs consumption and emissions in 2017 were 164,000 t (311 Mt CO2-eq) and 108 Mt CO2-eq, respectively. HFCs consumption baseline was projected to be (724 ± 18) Mt CO2-eq in 2024, and China should take measures to phase-down HFCs by 2029, at the latest, to meet the requirements of the KA. HFCs consumption in 2050 under KA would reach the level of 2012–2013. Cumulative reduced consumption was estimated at 10.8 (10.1–11.6) Gt CO2-eq, and cumulative reduced emissions were estimated at 5.38 (4.90–5.64) Gt CO2-eq by 2050.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".