Chapter 6. Assessing the Environmental Benefits of Using Glass Powder as a Supplementary Cementitious Material in a Context of Open-loop Recycling
Bibliographic record
Abstract
Although it is an abundant recyclable resource, mixed colour waste glass does not meet quality standards to be recycled and is often landfilled in Quebec (Canada). Glass powder (GP) has been shown to have pozzolanic properties; it therefore has potential application in the concrete industry as an alternative supplementary cementitious material. The construction of a concrete pedestrian bridge provides an opportunity to compare the potential environmental impacts of three different types of concrete: conventional concrete and two mixtures of ultra-high-performance concrete (UHPC), conventional UHPC (Conv-UHPC) and UHPC incorporating GP as a partial replacement for Portland cement (Glass-UHPC). Such a comparison was conducted using the Life Cycle Assessment methodology. The results highlight the environmental benefits of using UHPCs rather than conventional concrete in every impact category. As an example, building the bridge using Conv-UHPC and Glass-UHPC resulted in a 42% and 53% decrease in greenhouse gas emissions compared with that of conventional concrete, respectively. The same results were also observed when comparing the two UHPCs. Indeed, the incorporation of GP led to a decrease of 3–20% in all environmental categories of the final results, in comparison to those of the Conv-UHPC. However, these conclusions depend on the effective life span of the concrete (120 years for the UHPCs and 50 years for the conventional concrete).
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".