Rethinking time-lagged emissions and abatement potential of fluorocarbons in the post-Kigali Amendment era
Bibliographic record
Abstract
The Montreal Protocol has been successful in safeguarding the ozone layer and curbing climate change. However, accurately estimating and reducing the time-lagged emissions of ozone-depleting substances or their substitutes, such as produced but not-yet-emitted fluorocarbon banks, remains a significant challenge. Here, we use a dynamic material flow analysis model to characterize the global stocks and flows of two fluorocarbon categories, hydrochlorofluorocarbons (HCFCs) and hydrofluorocarbons (HFCs), from 1986 to 2060. We assess emission pathways, time-lagged emission sizes, and potential abatement measures throughout different life cycle stages while focusing on the role of banked fluorocarbons in global and regional decarbonization efforts in the post-Kigali Amendment era. Although fluorocarbon releases are expected to decline, the cumulative global warming potential (GWP)-weighted emissions of HCFCs and HFCs are significant; these will be 6.4 (±1.2) and 14.8 (±2.5) gigatons CO2-equivalent, respectively, in 2022–2060 in our business-as-usual (BAU) scenario. Scenario analysis demonstrates that implementing currently available best environmental practices in developed economies can reduce cumulative GWP-weighted emissions by up to 45% compared with the BAU scenario. The cumulative global warming potential-weighted emissions of hydrochlorofluorocarbons and hydrofluorocarbons are significant, which will be 21.2 (±3.7) gigatons CO2-equivalent in 2022–2060 under a business-as-usual scenario.
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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 | 0.001 |
| 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".