Techno-economic assessment of low-carbon hydrogen export from Western Canada to Eastern Canada, the USA, the Asia-Pacific, and Europe
Bibliographic record
Abstract
The use of low-carbon hydrogen is being considered to help decarbonize several jurisdictions around the world. There may be opportunities for energy-exporting countries to supply energy-importing countries with a secure source of low-carbon hydrogen. The study objective is to assess the delivered cost of gaseous hydrogen export from Canada (a fossil-resource rich country) to the Asia-Pacific, Europe, and inland destinations in North America. There is a data gap on the feasibility of inter-continental export of hydrogen from an energy-producing jurisdiction to energy-consuming jurisdictions. This study is aimed at addressing this gap and includes an assessment of opportunities across the Pacific Ocean and the Atlantic Ocean, based on fundamental engineering-based models. Techno-economics were used to determine the delivered cost of hydrogen to these destinations. The modelling considers energy, material, and capacity-sizing requirements for a five-stage supply chain comprising hydrogen production with carbon capture and storage, hydrogen pipeline transportation, liquefaction, shipping, and regasification at the destinations. The results show that the delivered cost of hydrogen to inland destinations in North America is between CAD$4.81/kg and CAD$6.03/kg, to the Asia-Pacific from CAD$6.65/kg to CAD$6.99/kg, and at least CAD$8.14/kg for exports to Europe. Delivering hydrogen by blending in existing long-distance natural gas pipelines reduced the delivered cost to inland destinations by 17%. Exporting ammonia to the Asia-Pacific provides cost savings of 28% compared to shipping liquified hydrogen. The developed information may be helpful to policymakers in government and the industry in making informed decisions about international trade of low-carbon hydrogen in both energy-exporting and energy-importing jurisdictions, globally.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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".