Life Cycle Assessment for Concrete and Asphalt Pavement at the Network Scale
Bibliographic record
Abstract
In 2001 the Québec Ministry of Transportation (MTQ), Canada, has adopted a policy subdividing the existing pavement network into dedicated concrete and asphalt networks. Pavement designs for 16 Functional Class were compared for asphalt and concrete for a 50 years analysis period using a Life Cycle Cost Analysis (LCCA). In addition to LCCA, a multiple criteria analysis was performed to account for input factors not amenable to quantification in monetary terms. The 2010 policy was updated for cost and traffic demand. Environment issues were also addressed through a life cycle assessment (LCA) performed on 32 pavements designs. This paper presents the application of conventional LCA methodology to roads, salient inventory data and main comparative results with respect to midpoint and endpoint environmental impacts. Results are clearly in favour of asphalt pavements for three out of four endpoint impact, namely human health, climate change and ecosystem quality, whereas impacts on resource consumption is favorable to concrete pavement.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".