Cost estimation of the use of low-carbon fuels in prospective scenarios for air transport
Why this work is in the frame
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Bibliographic record
Abstract
View Video Presentation: https://doi.org/10.2514/6.2023-2328.vid Using low-carbon energies is a major lever to reduce the CO2 emissions of aviation. Some low-carbon energy carriers consist in fuels that are drop-in and require few modifications to current aircraft, like biofuels and electrofuels. Hydrogen is another low-carbon fuel that would be relevant in the long term only since it requires significant aircraft modifications (non-drop-in fuel). In both cases, several production pathways exist with radically different impacts in terms of cost of production and life-cycle CO2 emissions. Literature is already exhaustive on prospective decarbonization scenarios for aviation and low-carbon fuel production cost estimates. In this paper, an open-source simulation framework named CAST is enhanced by a module that links low-carbon fuels production cost to their respective consumption in given scenarios. Hence, the cost of a custom decarbonization scenario is evaluated. Results show that the cost of the integration of low-carbon fuels in this scenario would represent around 40 % of airlines revenues in 2050, while the energy demand growth would necessitate important capital investments, regularly increasing to 130 Bn e in 2050. A sensitivity analysis shows that these cost estimates are subject to large uncertainties.
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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 | 0.001 |
| 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) | 0.000 | 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 it