Exploring the Role of Airtightness for Achieving Carbon Neutrality in Canadian Residential Buildings: A Streamlined Life Cycle Assessment
Bibliographic record
Abstract
This study delves into the relationship between airtightness levels and the entire life cycle carbon emissions of buildings across diverse Canadian climates. With the 2020 update of the National Energy Code of Canada for Buildings, whole-building airtightness testing was introduced as an option, prompting discussions on its mandatory nature. Using a net zero target, our assessment unfolds in two phases. Initially, we employ three-dimension (3D) modeling in Revit to replicate a typical Canadian detached house’s architectural features and material compositions. Subsequently, the model was imported into One Click life cycle assessment (LCA) to set parameters such as lifetime, gross interior area, and annual electricity consumption. Our analysis is bifurcated into assessing climatic conditions in Edmonton, Toronto, and Vancouver, alongside examining code-specified airtightness levels. We compared annual energy loss per unit area at varying airtightness levels accounting for the general deterioration of airtightness in new buildings during the pre-service phase to pinpoint the optimal airtightness value (ACH50) during the design stage. The subsequent phase evaluated increased carbon emissions from material replacement to meet this optimal airtightness condition and passive energy savings. Findings underscore that designing airtightness to an ACH50 value of 1.0 is the most energy-efficient. Comparative analysis reveals that achieving carbon neutrality solely through increased envelope airtightness and passive energy savings, is viable in Edmonton (18.4 years) owing to regional energy source disparities. In contrast, Toronto and Vancouver necessitate active energy-saving devices to attain carbon neutrality over the design lifetime.
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".