Life cycle thinking evaluation of hydrogen-powered locomotives : a Canadian context
Bibliographic record
Abstract
The energy sector is one of the largest contributors to global greenhouse gas emissions, with the transportation sector alone accounting for approximately one-quarter of these emissions, primarily due to the reliance on fossil fuels. Therefore, clean energy solutions are essential for reducing GHG emissions, and hydrogen has emerged as a promising solution for decarbonizing the transportation sector. This research explores the use of hydrogen in the railway sector, which is recognized as one of the cleanest and most efficient modes of transportation. However, hydrogen can be produced through various pathways, and the potential environmental, economic, and social impacts of its use in locomotives may vary depending on the employed production methods. Consequently, a comprehensive evaluation is necessary to assess these impacts holistically. This thesis employs a life cycle thinking methodology to evaluate the three pillars of sustainability—environmental, economic, and social impacts—across five hydrogen production pathways, comparing these with conventional internal combustion engine locomotives. This life cycle analyzes all phases of the locomotive's life cycle, including the refurbishment with hydrogen technology components, operational use, and end-of-life impacts. Additionally, a multi-criteria decision-making analysis is conducted to compare the life cycle costs, life cycle emissions and potential social impacts of hydrogen-powered locomotives with those of diesel locomotives in seven Canadian regions. This research also presents the development of a multi-criteria decision-making tool designed to assist stakeholders in evaluating hydrogen-powered locomotives with a life cycle perspective. The findings reveal that significant efforts are needed to lower the market cost of hydrogen by around $5/kg to reduce greenhouse gas emissions when implementing hydrogen-powered locomotives. The environmental assessment revealed that the water electrolysis pathway significantly reduced life cycle emissions in British Columbia, Manitoba, Ontario, and Quebec, while steam methene reforming with carbon capture utilization and storage was most effective in Atlantic Canada and none of the hydrogen pathways considered in this analysis reduced emissions in Alberta and Saskatchewan. Additionally, diesel proved to be the least impacted pathway in the social assessment, largely due to its longstanding reliability. This work serves as a baseline for future applications of hydrogen technology in transportation worldwide.
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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 | 0.005 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".