Life Cycle Greenhouse Gas Emissions of Renewable Jet Fuels Produced in Canada
Bibliographic record
Abstract
Modern technology has enabled the transformation of renewable biomass and waste into renewable energy for the sectors of our society that use fossil fuels the most. This thesis contributes to knowledge on renewable jet fuels (RJF) and their potential greenhouse gas (GHG) emissions reduction benefits for the aviation sector from a Canadian context. The first part of this thesis quantifies the life cycle GHG emissions of ethanol produced using corn stover, an agricultural residue. Wide ranging results of 7.9 to 45 gCO2e MJ-1 were initially determined from two fuel life cycle assessment (LCA) tools that modelled corn stover ethanol. Harmonization of model parameters and assumptions in the two LCA tools led to similar estimates of 41 – 42 gCO2e MJ-1 although these values obscured substantial differences in GHG emissions at the individual contributor level, which can impact the fuel’s performance under different regulatory regimes. Next, the thesis conducted an LCA on RJF derived from corn stover or ethanol from corn stover. The LCA modelled Ontario and Québec RJF production using these regions’ corn production data. The study determined life cycle GHG emissions of 3.5 – 5.3 gCO2e MJ-1 for the Fischer-Tropsch jet fuel pathway while the ethanol-to-jet fuel pathway resulted in 28 – 36 gCO2e MJ-1 due to greater inputs in the ethanol production process. Québec benefitted from its low carbon intensity electricity but corn stover yields in Ontario were identified as advantageous. The last two parts of the thesis assessed the life cycle GHG emissions of RJF from canola, camelina, and carinata oilseeds. Respectively, GHG emissions from each oilseed-to-RJF are 16 – 58 gCO2e MJ-1, 53 – 72 gCO2e MJ-1, and 43 – 52 gCO2e MJ-1. Canola RJF values varied due to soil carbon effects from land use and land management changes. The range of results for camelina and carinata RJF are due to using input data from many sources and differences in modelling assumptions. A scenario maximizing camelina or carinata RJF production using Canadian marginal lands is estimated to reduce GHG emissions in aviation by up to 2 million tonnes of CO2e emissions per year 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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".