Electricity savings and greenhouse gas emission reductions from global phase-down of hydrofluorocarbons
Bibliographic record
Abstract
Abstract. Hydrofluorocarbons (HFCs) are widely used as cooling agents in refrigeration and air conditioning, as solvents in industrial processes, as fire-extinguishing agents, for foam blowing, and as aerosol propellants. They have been used in large quantities as the primary substitutes for ozone-depleting substances regulated under the Montreal Protocol. However, many HFCs are potent greenhouse gases (GHGs) and as such subject to global phase-down under the Kigali Amendment (KA) to the Montreal Protocol. In this study, we develop a range of long-term scenarios for HFC emissions under varying degrees of stringency in climate policy and assess co-benefits in the form of electricity savings and associated reductions in GHG and air pollutant emissions. Due to technical opportunities to improve energy efficiency in cooling technologies, there exist potentials for significant electricity savings under a well-managed phase-down of HFCs. Our results reveal that the opportunity to simultaneously improve energy efficiency in stationary cooling technologies could bring additional climate benefits of about the same magnitude as that attributed to the HFCs phase-down. If technical energy efficiency improvements are fully implemented, the resulting electricity savings could exceed 20 % of future global electricity consumption, while the corresponding figure for economic energy efficiency improvements would be about 15 %. The combined effect of HFC phase-down, energy efficiency improvement of the stationary cooling technologies, and future changes in the electricity generation fuel mix would prevent between 411 and 631 Pg CO2 equivalent of GHG emissions between 2018 and 2100, thereby making a significant contribution towards keeping the global temperature rise below 2 ∘C. Reduced electricity consumption also means lower air pollution emissions in the power sector, estimated at about 5 %–10 % for sulfur dioxide (SO2), 8 %–16 % for nitrogen oxides (NOx), and 4 %–9 % for fine particulate matter (PM2.5) emissions compared with a pre-Kigali baseline.
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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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 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 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".