Life Cycle Analysis of Bitumen Transportation to Refineries by Rail and Pipeline
Bibliographic record
Abstract
Crude oil is currently transported primarily by pipelines and rail from extraction sites to refineries around the world. This research evaluates energy use and greenhouse gas (GHG) emissions for three scenarios (synthetic crude oil and dilbit with and without diluent return) in which 750 000 bpd of Alberta's bitumen is transported 3000 km to determine which method has a lower environmental impact. Each scenario has a pipeline and rail pathway, and the dilbit without diluent return scenario has an additional heated bitumen pathway, which does not require diluent. An Excel based bottom-up model is developed using engineering first-principles to calculate mass and energy balances for each process. Results show that pipeline transportation produced between 61% and 77% fewer GHG emissions than by rail. The GHG emissions decreased by 15% and 73% for rail and pipelines as the capacity increased from 100 000 to 800 000 bpd. A Monte Carlo simulation was performed to determine the uncertainty in the emissions and found that the uncertainty was larger for pipelines (up to ±73%) and smaller for rail (up to ±28%). The uncertainty ranges do not overlap, thus confirming that pipelines have lower GHG emissions, which is important information for policy makers conducting pipeline reviews.
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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 | 0.002 |
| Science and technology studies | 0.000 | 0.004 |
| 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 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".