Projections of hydrofluorocarbon (HFC) emissions and the resulting global warming based on recent trends in observed abundances and current policies
Bibliographic record
Abstract
The emissions of hydrofluorocarbons (HFCs) have increased significantly in the past 2 decades, primarily as a result of the phaseout of ozone-depleting substances under the Montreal Protocol and the use of HFCs as their replacements. In 2015, large increases were projected in HFC use and emissions in this century in the absence of regulations, contributing up to 0.5 ∘ C to global surface warming by 2100. In 2019, the Kigali Amendment to the Montreal Protocol came into force with the goal of limiting the use of HFCs globally, and currently, regulations to limit the use of HFCs are in effect in several countries. Here, we analyze trends in HFC emissions inferred from observations of atmospheric abundances and compare them with previous projections. Total CO 2 eq. inferred HFC emissions continue to increase through 2019 (to about 0.8 GtCO2eq.yr-1) but are about 20 % lower than previously projected for 2017–2019, mainly because of the lower global emissions of HFC-143a. This indicates that HFCs are used much less in industrial and commercial refrigeration (ICR) applications than previously projected. This is supported by data reported by the developed countries and the lower reported consumption of HFC-143a in China. Because this time period preceded the beginning of the Kigali provisions, this reduction cannot be linked directly to the provisions of the Kigali Amendment. However, it could indicate that companies transitioned away from the HFC-143a with its high global warming potential (GWP) for ICR applications in anticipation of national or global mandates. There are two new HFC scenarios developed based (1) on current trends in HFC use and Kigali-independent (K-I) control policies currently existing in several countries and (2) current HFC trends and compliance with the Kigali Amendment (KA-2022). These current policies reduce projected emissions in 2050 from the previously calculated 4.0–5.3 GtCO2eq.yr-1 to 1.9–3.6 GtCO2eq.yr-1. The added provisions of the Kigali Amendment are projected to reduce the emissions further to 0.9–1.0 GtCO2eq.yr-1 in 2050. Without any controls, projections suggest a HFC contribution of 0.28–0.44 ∘ C to global surface warming by 2100, compared to a temperature contribution of 0.14–0.31 ∘ C that is projected considering the national K-I policies current in place. Warming from HFCs is additionally limited by the Kigali Amendment controls to a contribution of about 0.04 ∘ C by 2100.
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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 | 0.001 |
| 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 | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".