Growth of climate change commitments from HFC banks and emissions
Bibliographic record
Abstract
Abstract. Chlorofluorocarbons (CFCs) are the primary cause of ozone depletion, and they also contribute to global climate change. With the global phaseout of CFCs and the coming phaseout of hydrochlorofluorocarbons (HCFCs), the substitute hydrofluorocarbons (HFCs) are increasingly used. While CFCs were originally used mainly in applications such as spray cans and were released within a year after production, concern about the ozone layer led to reductions in rapid-release applications, and the relative importance of slower-release applications grew. HFCs are now mainly used in refrigerators and air conditioners (AC) and are released over years to a decade after production. Their containment in such equipment represents banks, which are building up as production grows. A key finding of our work is that the increases of HFC banks represent a substantial unseen commitment to further radiative forcing of climate change also after production of the chemicals ceases. We show that earlier phaseouts of HFCs would provide greater benefits for climate protection than previously recognized, due to the avoided buildup of the banks. If, for example, HFC production were to be phased out in 2020 instead of 2050, not only could about 91–146 GtCO2-eq of cumulative emission be avoided from 2020 to 2050, but an additional bank of about 39–64 GtCO2-eq could also be avoided in 2050. Choices of later phaseout dates lead to larger commitments to climate change unless growing banks of HFCs from millions of dispersed locations are collected and destroyed.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.013 | 0.001 |
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".