Cost Analysis of the Blue Hydrogen Supply from Canada to Korea
Bibliographic record
Abstract
This study conducts a cost analysis of blue hydrogen supply from Canada to South Korea by modeling two distinct supply chain scenarios using Monte Carlo simulation.Scenario 1 involves importing liquefied natural gas (LNG) from Canada for domestic hydrogen production in South Korea, coupled with carbon capture and storage (CCS) integration.Scenario 2 involves producing blue hydrogen in Canada and importing it to Korea using various carrier options, such as liquefied hydrogen, ammonia, and liquid organic hydrogen carriers.Blue hydrogen, which is produced primarily through steam methane reforming, partial oxidation, and autothermal reforming, incorporates CCS to reduce carbon emissions.The economic analysis using Monte Carlo simulations in both scenarios shows that blue hydrogen stored in ammonia from Scenario 2 has the lowest supply cost at 7.33 $/kgH 2 , making it the most cost-effective option.Although Canada's current LNG supply to Korea is limited, future strategic energy planning supports the feasibility of this scenario.
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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 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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 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".