Evaluating circular economy strategies at the end-of-life stage of a mass timber building: pathways for sustainable construction
Bibliographic record
Abstract
The construction sector is widely recognized as a significant contributor to environmental degradation, with its impacts intersecting with multiple sustainable development goals related to resource consumption, climate action, sustainable cities and communities, as well as industry and infrastructure. Integration of circular economy (CE) strategies at the end-of-life (EoL) of the constructions can reduce resource use, waste generation, therefore the impacts of this sector on the environment. The application of CE principles is considered a progressive act that requires the adaptation of infrastructures, and a sudden circular approach cannot be achieved. This study focuses on improving the circularity of EoL of the construction and demolition wastes (CDW). To this end, the environmental impacts of current EoL practices in Quebec, Canada, on a case study of mass timber building are evaluated. Then, by analyzing the sensitivity of the results to the application of several circular strategies, an optimized short-term circular pathway for Quebec’s construction sector is proposed. This short-term pathway includes a 20% increase in current CDW recycling and a 20% rise in wood and steel reuse, which serves as an initial step towards achieving a CE in the construction sector in Quebec. Mid-term and long-term pathways followed these results involve higher recycling and reusing of materials, along with integrating the reduction and refusal approaches as other CE strategies. The long-term pathway also encourages focusing on reducing the use of glue in mass timber products and considering more sustainable options like dowel laminated timber (DLT) in mass timber constructions.
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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 | 0.005 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".