Life cycle thinking-based analysis of diesel and electric-powered buses for Canadian transit systems
Bibliographic record
Abstract
Increasing greenhouse gas emissions from the conventional fleet of diesel buses has made Canadian transit agencies explore low-emission alternative fuels. Despite electric buses showing great potential to reduce emissions during their operational phase, the transformation from diesel buses to electric buses would require in-depth analysis pertaining to their economic and social implications. Published literature highlights the importance of developing a comprehensive framework that considers multiple decision parameters over a life cycle perspective for analyzing different fuel options to replace the existing fleet of diesel buses. This paper assesses the triple-bottom-line sustainability of diesel and electric buses in different regions of Canada. Moreover, a framework is proposed to incorporate multiple decision criteria (life cycle environmental, economic, and social impacts) over different perspectives to make the best decisions for transitioning the diesel bus fleet. The results showed that the environmental performance of electric buses highly depended on the electricity grid mix. Despite diesel buses having a low cost of production compared to electric buses, most provinces showed a low life cycle operational cost for electric buses. Electric buses’ life cycle social impacts are high during their production stage, whereas diesel buses have the highest social impacts during their operational phase. Overall, electric buses have a high sustainability performance in all provinces and territories in Canada except Nunavut. The proposed framework and findings can aid policymakers and planners in implementing electric buses for public transit systems in Canada and beyond.
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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 | 0.003 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".