Historical trends in greenhouse gas emissions of the Alberta oil sands (1970–2010)
Bibliographic record
Abstract
There has been increased scrutiny of the Alberta oil sands due to their high carbon intensity (CI) relative to conventional crude oil. Relying entirely on public and peer-reviewed data sources, we examine historical trends in the CI of oil sands extraction, upgrading, and refining. Monthly data were collected and interpolated from 1970 to 2010 (inclusive) for each oil sands project. Results show a reduction in oil sands CI over time, with industry-average full-fuel cycle (well-to-wheels, WTW) CI declining from 165 gCO 2 e MJ −1 higher heating value (HHV) of reformulated gasoline (RFG) to 105 (−12, +9) gCO 2 e MJ −1 HHV RFG. 2010 averages by production pathways are 102 gCO 2 e MJ −1 for Mining and 111 gCO 2 e MJ −1 for in situ . The CI of mining-based projects has declined due to upgrader efficiency improvements and a shift away from coke to natural gas as a process fuel. In situ projects have benefitted from substantial reductions in fugitive emissions from bitumen batteries. Both mining and in situ projects have benefitted from improved refining efficiencies. However, despite these improvements, the CI of oil sands production (on a pathway-average basis) ranges from 12 to 24% higher than CI values from conventional oil production. Due to growing output, total emissions from the oil sands continue to increase despite improved efficiency: total upstream emissions were roughly 65 MtCO 2 e in 2010, or 9% of Canada's emissions.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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 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".