Mapping construction sector greenhouse gas emissions: a crucial step in sustainably meeting increasing housing demands
Bibliographic record
Abstract
Abstract This paper examines the tension between needing to build more infrastructure and housing and simultaneously reduce greenhouse gas emissions (GHG) to avoid the most catastrophic impacts of climate change. This study uses an Environmentally Extended Input-Output approach to conduct a high-resolution top-down analysis of Canada’s national construction GHG emissions. Our findings highlight that Canada’s current construction practices cannot accommodate the construction required to restore housing affordability by 2030 without substantial environmental consequences. On a consumption life cycle basis, the construction sector was responsible for approximately 90 Mt CO 2 e in 2018, equivalent to over 8% of Canada’s total GHG emissions, while delivering less than a third of Canada’s annual housing needs. Residential construction was responsible for the largest share (42%) of total construction emissions. Overall, 84% of emissions are from material manufacturing and 35% of construction emissions are imported, underscoring the need for a comprehensive regulatory framework addressing both domestic and imported emissions. Under current construction practices (i.e. current material use patterns and emissions intensities), meeting Canada’s 2030 housing affordability and climate commitments requires an 83% reduction in GHG emissions per construction product (i.e. per home) compared to the 40% economy-wide reduction promised in Canada’s international reduction commitments. Mitigating the GHG gap between emission caps and housing demand calls for changes in the ratio of housing to other infrastructure (e.g. fewer roads, less fossil fuel infrastructure), new construction approaches (e.g. increasing material efficiency) and/or disproportionally allocating climate budget to construction. The implications of our study extend beyond Canada, offering valuable insights for other growing countries with climate goals. The results emphasize the urgency in considering and establishing sectoral GHG budgets for construction and for transformative changes in the construction sector to meet national GHG emission reduction commitments.
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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 | 0.005 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".