Whole Building Life Cycle Assessment of New Multi-Unit Residential Buildings in Southern Ontario
Bibliographic record
Abstract
The built environment accounts for over one-third of global carbon emissions on an annual basis. Solutions for reducing carbon in the built environment typically focus on 'operational carbon' that is released during the day-to-day use of buildings. There is less understanding about how to reduce 'embodied carbon' that is released during the raw material manufacturing, transportation, construction and end of life phases of built assets. However, as operational carbon reduces, and the rate of new construction continues to increase, embodied carbon will grow to represent almost half of all emissions from new buildings. As a result, there is an urgent need to reduce embodied carbon to meet global climate change targets. This research paper begins with a literature review of embodied carbon in the built environment. This includes a review of the whole building life cycle assessment (WBLCA) methodology to calculate embodied carbon, assessment of outcomes from similar studies, consideration of key drivers of emissions and identification of potential reduction strategies. Based on this, a methodology and scope are defined for the WBLCA of 3 new multi-unit residential buildings located in southern Ontario. One Click LCA software is used to calculate the embodied carbon for each building. The baseline results ranged from 182 kg CO e/2 for the low-rise timber framed building up to 347 kg CO e/m fo2 the mid-rise concrete structure and 450 kg CO e/2 for the high-rise concrete structure. Cladding assemblies and floor finishes are identified as key drivers for embodied carbon in the timber frame, and horizontal structural slabs and foundations are the main contributors to emissions in the concrete structure. Six reduction strategies are identified to address the key contributors of embodied carbon in each building. Three of these measures are found to reduce the carbon footprint in the building by 10% or more. Replacement of the above grade concrete structure with timber frame and the use of low carbon concrete are found to be the most impactful reduction strategies. Combining several reduction strategies enables embodied carbon reductions of 20% or greater.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".