Concerns of Pavement LCA Stakeholders in Canada and GHG Emissions Reduction from Ontario Roadways
Bibliographic record
Abstract
The integration of life cycle assessment (LCA) has become increasingly crucial in the Canadian pavement industry, primarily to address environmental concerns arising from construction, operation, and maintenance activities. In this research, at the first stage, an online, semi-structured survey was conducted to explore the current practices, methodologies, technical features, and tools adopted mainly by Canadian transportation agencies, industries and academic scholars. During the second stage, a comprehensive investigation was carried out to quantify environmental emissions from different structural conditions of asphalt pavements in Ontario. The study revealed that the manufacturing phase was the most significant contributor to environmental emissions, often exceeding 50%. In addition, incorporating reclaimed asphalt pavement (RAP) demonstrated significant greenhouse gas emission reductions, with the scenario analysis supporting facilitating RAP in pavement granular layers. Finally, this study sets a foundation for future research to develop sustainable practices to enhance resilience in asphalt pavement construction.
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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 | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.015 | 0.003 |
| Scholarly communication | 0.006 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.006 | 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".