Life Cycle Greenhouse\nGas Emissions of Current Oil\nSands Technologies: Surface Mining and <i>In Situ</i> Applications
Bibliographic record
Abstract
Life cycle greenhouse gas (GHG) emissions associated\nwith two major\nrecovery and extraction processes currently utilized in Alberta’s\noil sands, surface mining and <i>in situ,</i> are quantified.\nProcess modules are developed and integrated into a life cycle model-GHOST <b>(G</b>reen<b>H</b>ouse gas emissions of current <b>O</b>il <b>S</b>ands <b>T</b>echnologies) developed in prior\nwork. Recovery and extraction of bitumen through surface mining and <i>in situ</i> processes result in 3–9 and 9–16 g\nCO<sub>2</sub>eq/MJ bitumen, respectively; upgrading emissions are\nan additional 6–17 g CO<sub>2</sub>eq/MJ synthetic crude oil\n(SCO) (all results are on a HHV basis). Although a high degree of\nvariability exists in well-to-wheel emissions due to differences in\ntechnologies employed, operating conditions, and product characteristics,\nthe surface mining dilbit and the <i>in situ</i> SCO pathways\nhave the lowest and highest emissions, 88 and 120 g CO<sub>2</sub>eq/MJ reformulated gasoline. Through the use of improved data obtained\nfrom operating oil sands projects, we present ranges of emissions\nthat overlap with emissions in literature for conventional crude oil.\nAn increased focus is recommended in policy discussions on understanding\ninterproject variability of emissions of both oil sands and conventional\ncrudes, as this has not been adequately represented in previous studies.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.004 | 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".