Life Cycle Assessment for Sustainable Design of Precast Concrete Commercial Buildings in Canada
Bibliographic record
Abstract
2 Athena Sustainable Materials Institute Abstract: A life cycle assessment (LCA) was conducted on a typical five-storey commercial building with five variations of exterior wall system and two variations of climate and location. The goal of the LCA was to gain a better understanding of precast concrete's environmental performance in the context of whole buildings. LCA is an analytical tool to comprehensively quantify and interpret the energy and material flows to and from the environment over the life of a product, process, or service. The energy and material flows are the environmental emissions to air, land, and water, and the consumption of energy and material resources. This paper presents the cradle-to-grave LCA of precast concrete commercial buildings with precast structure and precast wall envelope, relative to alternative wall envelope systems. Because the LCA includes a public comparative assertion, the study was critically reviewed by an independent external committee of LCA experts to ensure the LCA is consistent with the requirements of international ISO standards on LCA. The results show that over the full life cycle, the buildings with precast concrete walls have less environmental impact than the buildings with masonry brick veneer walls and those with glass and aluminum curtain wall, all other factors being equal.
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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 | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".