End-of-life scenario-based assessment of building wood waste circulation through deconstruction: A case study in Canada
Bibliographic record
Abstract
• Deconstruction significantly reduces embodied carbon emissions by up to 8.36 tonnes CO₂-eq compared to traditional demolition. • Material reuse delivers the highest carbon savings among all end-of-life options. • Worker transport logistics emerge as a critical factor influencing deconstruction emissions. • Canada-specific evidence supports policies promoting mandatory deconstruction and reclaimed wood reuse. The circular economy plays a crucial role in reducing global carbon emissions, with end-of-life wood waste management offering significant environmental benefits. This study examines the potential for embodied carbon reduction through deconstruction practices, using a case study in Vancouver BC to provide Canada-specific insights. A life cycle assessment (LCA) approach was applied to evaluate embodied carbon emissions, considering system boundary stages C1–C4 and beyond-boundary impacts (stage D). Real-world data were collected from an on-site deconstruction project, and fourteen scenarios were developed to compare the environmental impacts of different wood waste circulation strategies. The results demonstrate that deconstruction significantly reduces embodied carbon emissions compared to traditional demolition, with reductions of up to 8.36 tonnes CO₂-eq (around 50 kg CO₂-eq/m 2 ). More advanced circulation strategies achieved the greatest carbon savings, with scenarios maximizing reuse (S61 and S62) emerging as the most effective. A key contribution of this study is the identification of worker transport as a non-negligible factor in deconstruction emissions, which is an area often overlooked in previous studies. This study also reinforces the waste management hierarchy, where reuse ranks higher than recycling and energy recovery due to its greater carbon reduction potential. However, despite regulatory advancements in Vancouver and other global cities, challenges remain in assessing material quality and establishing a robust reclaimed wood market. The findings provide empirical evidence for policies that promote and potentially mandate deconstruction over traditional demolition, advocating for enhanced reuse strategies to maximize environmental benefits.
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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 | 0.000 | 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 | 0.000 | 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".