Fischer-Tropsch Sustainable Aviation Fuel: An Assessment of Pioneer Plants and Canadian Supply
Bibliographic record
Abstract
Aviation aims to achieve net-zero emissions by 2050, and sustainable aviation fuel (SAF) produced from biomass via gasification and Fischer-Tropsch processes could make a large contribution to this goal. This thesis assesses (1) the production costs and GHG emissions of SAF from pioneer biomass gasification and Fischer-Tropsch projects and (2) the supply, costs, and GHG abatement potential of gasification and Fischer-Tropsch SAF from forest residues in Canada. Natural gas use in the conversion process of pioneer projects could lower SAF production costs by improving yields and reducing capital expenses but significantly lowers SAF GHG reduction benefits (from 91% to up to -17%) unless process emissions are captured and permanently stored. SAF from forest residues could meet up to 27% of Canada’s projected aviation fuel demand in 2050, requiring an investment of ~15.7 billion USD in SAF facilities, and could abate up to 47% of Canada’s projected emissions from aviation in 2050.
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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 | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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".