Emissions of the powerful greenhouse gas HFC-23 suggest significant under-reporting since the implementation of the Kigali Amendment
Bibliographic record
Abstract
HFC-23 (trifluoromethane) is a potent greenhouse gas, believed to be emitted to the atmosphere primarily as a by-product during the production of the refrigerant and feedstock HCFC-22 (chlorodifluoromethane). Due to the high global warming potential of HFC-23 (GWP100 ~ 14,700), the Kigali Amendment to the Montreal Protocol requires countries to limit their emissions of HFC-23 as much as possible and report these emissions to the United Nations Environment Programme. Global reported emissions have been in the range 2-3 Gg yr-1 since 2019 and reflect the near-total destruction of emissions from HCFC-22 production reported by the countries with major HCFC-22 manufacturers, such as China and India. However, atmospheric observations show that, whilst emissions fell from their maximum in 2019 of 17.3 ± 0.8 Gg yr-1 to 14.0 ± 0.9 Gg yr-1 in 2023, they remain many times higher than reported. In addition, regional inverse modelling was performed based on measurements from the AGAGE site at Gosan, South Korea, using three different Bayesian inverse models (FLEXINVERT+, InTEM and RHIME) to estimate emissions from eastern China. These inversions use the same observational data, but different transport models, baselines, priors and uncertainties. Results are compared to better quantify regional emissions and their uncertainties. The results suggest that emissions from eastern China are four to six times higher than reported for the whole of China. In addition, we examine the emission of HFC-23 as a by-product during the production of other hydrofluorocarbons and fluorochemicals. In-atmosphere HFC-23 production (from the breakdown of certain hydrofluoroolefins used as replacements for HFCs) is also investigated further using a 3D chemical transport model incorporating photolysis and ozonolysis reactions. Our results indicate that, based on currently available information, these potential alternative sources contribute less than 2.0 Gg yr-1 to global emissions. This suggests that HFC-23 emissions from HCFC-22 production have been consistently under-reported since the implementation of the Kigali Amendment. It therefore appears likely that abatement of HFC-23 emissions has not occurred to the extent reported in this period. Improved monitoring and verification of HFC-23 emissions from industrial sources is essential to the continued success and efficacy of the Kigali Amendment.
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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 | 0.002 |
| 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 | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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".