Low-frequency contributions in the radiative efficiencies of HFC-236fa, HFC-245fa and HFC-43-10mee over the 225 - 298 K temperature range
Bibliographic record
Abstract
Hydrofluorocarbons (HFCs) are used as substitutes for ozone-depleting substances regulated under the Montreal Protocol. While having zero ozone depletion potential, HFCs strongly absorb infrared radiation, making them potent greenhouse gases. Vibrational modes associated with C--F stretching absorb strongly within the atmospheric window (750 --1250 cm-1), contributing substantially to radiative forcing. The low-frequency region (< 500 cm-1), which accounts for approximately 16% of the Earth’s thermal emission, has however remained largely unexplored mainly due to instrumental challenges. Here, we present the first experimental measurements of infrared (IR) absorption cross-sections in the 150--500~cm-1 range for HFC-236fa, HFC-245fa, and HFC-43-10mee - three industrially relevant compounds with high global warming potentials (GWPs). The spectra were recorded at the Rutherford Appleton Laboratory using a high-resolution Fourier-transform infrared (FTIR) spectrometer in the temperature range between 225 and 298 K at resolution of 0.25 cm-1. In addition, IR cross section spectra were simulated through quantum chemical (QC) calculations including a non-empirical treatment of anharmonic effects. From the experimental results, we derived radiative efficiencies (REs) in the low frequency region of 0.001, 0.005, and 0.003 Wm-2 ppbv-1 for HFC-236fa, HFC-245fa, and HFC-43-10mee, respectively, and revised global warming potentials over 20-, 100-, and 500-year time horizons. Comparison with values reported in the WMO Ozone Assessment Report 2022 reveals minor differences for HFC-245fa and HFC-43-10mee, whereas HFC-236fa shows a significant overestimation, corresponding to a discrepancy of approximately 700 units in the 100-year GWP. On the other hand, our theoretical predictions reproduced the experimental spectra with average deviations below 5%, confirming the reliability of the computational approach even in the low-frequency region. These findings highlight that small variations in the treatment of low-frequency absorptions can propagate into substantial contributions in climate metrics, particularly for long-lived compounds. Overall, this study provides a consistent experimental--theoretical framework for quantifying the radiative forcing of HFCs and reducing current uncertainties in the estimation of their climate-relevant parameters. The dataset comprises: (i) The corresponding raw transmission data of the HFCs measured by the spectrometer, for different sample pressures and temperatures. (ii) The derived experimental absorption cross-section data. The full details are in the associated paper to the data repository.
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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 | 0.000 |
| 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) | 0.002 | 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".