Carbon, Capture, Utilization and Storage CCUS: How to Commercialize a Business with No Revenue
Bibliographic record
Abstract
Abstract Canada has joined the growing list of countries committed to achieving net zero emissions by 2050. This will require a rapid transition to carbon-free energy systems over the next three decades, with Carbon Capture, Utilization, and Storage (CCUS) a core component of unlocking Canada's decarbonization objectives. It is estimated that Canada will need to capture upwards of 100 million metric tonnes of CO2e per year through CCUS to achieve net zero by 2050. However, Canadian CCUS projects currently face a plethora of commercial hurdles, ranging from capital intensive technology, long investment time horizons, lack of clarity of government incentives and policies, and disjointed carbon markets. Carbon pricing policies are one lever to drive industry adoption of CCUS, but a cohesive industry and government collaboration is required to establish the national infrastructure needed to scale and support the development of CCUS in Canada. The recent announcement of the Oil Sands Pathways to Net Zero comprises of six oilsands producers, representing 90 percent of oilsands production, and signals a willingness of industry to come together with government to tackle these issues and support the oil sands industry which is projected to add $3 trillion to GDP by 2050. The central pillar of their vision is the use shared transportation infrastructure and storage hubs. This model will require significant government support but what is the right model to secure Canada's future while de-risking public funding. Policy development is still required by government bodies to encourage the investment in, and the implementation of these multibillion-dollar, long term projects. The announcement of a Canadian federal investment tax incentive and enforcement of the incoming clean fuel standard may further drive organizations to incorporate CCUS into their decarbonization plans. To proceed, industry will require further clarification to determine the effects of policy decisions and potential government partnerships will have on the cost structure and commercial viability of CCUS projects. This paper will outline some of the current commercial barriers that industry faces with the adoption of CCUS. It will provide a roadmap on how to mobilize and partner to scale CCUS in Canada.
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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 | 0.001 |
| 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) | 0.000 | 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".