Global emissions of fluorinated greenhouse gases until 2050: technical mitigation potentials and cost
Bibliographic record
Abstract
The anthropogenic fluorinated (F-gases) greenhouse gas emissions have increased significantly in recent years and are estimated to rise further in response to increased demand for cooling services and the phase out of ozonedepleting substances (ODS) under the Montreal Protocol. F-gases (HFCs, PFCs and SF6) are potent greenhouse gases, with a global warming effect up to 22,800 times greater than carbon dioxide (CO2). This study presents estimates of current and future global emissions of F-gases, their technical mitigation potential and associated costs for the period 2005 to 2050. The analysis uses the GAINS model framework to estimate emissions, mitigation potentials and costs for all major sources of anthropogenic F-gases for 162 countries/regions, which are aggregated to produce global estimates. For each region, 18 emission source sectors with mitigation potentials and costs were identified. Global F-gas emissions are estimated at 0.7 Gt CO2eq in 2005 with an expected increase to about 3.6 Gt CO2eq in 2050. There are extensive opportunities to reduce emissions by over 95 percent primarily through replacement with existing low GWP substances. The initial results indicate that at least half of the mitigation potential is attainable at a cost of less than 20C per t CO2eq, while almost 90 percent reduction is attainable at less than 100C per t CO2eq. Currently, several policy proposals have been presented to amend the Montreal Protocol to substantially curb global HFC use. We analyze the technical potentials and costs associated with the HFC mitigation required under the different proposed Montreal Protocol amendments.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.002 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".