National assessment of transit electrification in Canada: infrastructure costs, energy demand, and greenhouse gas reduction potential
Bibliographic record
Abstract
Battery electric buses (BEBs) offer a scalable solution for decarbonizing public transit; however, comprehensive national-level assessments remain limited. This study presents the first bottom-up evaluation of BEB adoption across Canada, using open-source data from 102 transit providers. We quantify fleet requirements, infrastructure needs, electricity demand, and the cost-effectiveness of greenhouse gas (GHG) reductions under a fully electrified bus transit system. Our analysis indicates a required 17% increase in fleet size and an additional 1.255 TWh of electricity annually, representing just 0.20% of Canada's total generation. GHG emissions would decline by over 92% to approximately 130,000 tonnes annually, with the social cost of carbon falling by a similar margin (92.68%). These findings demonstrate that nationwide BEB deployment is technically feasible, economically manageable, and environmentally impactful. This study offers reproducible, open-source-based, critical evidence to guide energy planning, policy decisions, and investments in a sustainable, zero-emission transit future.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.001 | 0.000 |
| 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".