Carbon intensity threshold for Canadian oil sands industry using planetary boundaries: Is a sustainable carbon-negative industry possible?
Bibliographic record
Abstract
Previous studies on environmental performance of the oil sands industry in Canada conclude that its carbon footprint must be reduced. Yet, it remains unclear what threshold of carbon emissions intensity that the industry needs to meet to be within Canada's carbon share following Paris Climate Change Agreement. Here, for the first time, a top-down approach based on planetary boundary is used to identify the threshold of carbon emissions intensity that can keep Canadian oil sands industry within the planet's carrying capacities in absolute terms. The approach follows four steps in scaling down the global carbon budget into national level for Canada and industry level translated into emissions intensity threshold. The results reveal that under both 1.5 and 2 °C targets, the share of oil sands industry of Canada's carbon budget has been exhausted under most downscaling approaches: 10 % and 20 % annual reduction scenarios cannot help the industry to stay within their carbon budget under climate-relevant thresholds. Therefore, a carbon-negative industry is required where a reduction of 101.5–120 % of current emissions intensity is needed. Even in few cases where the industry is still within its cumulative carbon budget, an emission intensity reduction of 88–98 % is required. The results demonstrate the need for rapid transition that goes beyond zero-carbon to carbon-negative oil sands industry to be environmentally sustainable especially under the 1.5 °C target of the Paris Climate Change Agreement. This shows the need for new pathways in the sustainable energy industry such as hybrid renewable-oil sands operations and hydrogen from oil sands resources.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.000 | 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".