Life cycle GHG emissions assessment of vanadium recovery from spent catalysts from bitumen upgraders
Bibliographic record
Abstract
Bitumen from oil sands is a key source of fossil fuels. Bitumen is upgraded to produce synthetic crude oil, which is subsequently refined. The amount of vanadium in bitumen upgrading spent catalyst is substantial. Vanadium plays a vital role in steel production, chemical processes, and energy storage through its use in batteries, making it a valuable commodity worldwide. Recovering this metal from bitumen can be a profitable activity that could help contribute to global demand. Besides the economics of the process, the environmental impact should be addressed. However, details on the greenhouse gas (GHG) emissions generated during the process are not available. Therefore, we conducted a life cycle assessment of recovering vanadium from spent catalyst generated during bitumen upgrading. We developed a data-intensive model to estimate the GHG emissions from each life cycle stage of vanadium recovery from bitumen upgraders. The estimated life cycle GHG emissions are 11.8 kg CO 2 eq/kg V 2 O 5 . Of the total GHG emissions, 69 % are indirect and 31 % are direct emissions. If we consider the displacement of co-produced metals like molybdenum and alumina, the life cycle GHG emissions of the production system would drop to 0.63 kg CO 2 eq/kg V 2 O 5 . Sensitivity and uncertainty analyses show that the emission factor of electricity production, the specific energy consumption in the electric arc furnace, and the salt-to-spent catalyst ratio are the parameters with the most significant impact on the GHG emissions. Coupling a vanadium recovery plant with a bitumen upgrader is worthy of consideration because of the potential environmental benefits of the process.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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 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".