Whole Building Life Carbon Assessment of an Existing, Retrofit, and New Construction for a Toronto Detached Home Case Study
Bibliographic record
Abstract
This major research project was developed to better understand the whole building life cycle carbon analysis as a comparison between an existing baseline, a retrofit, and new construction of a detached case study home in Toronto. It investigates whether a deep energy retrofit, or new construction leads to lowest lifetime carbon emissions, accounting for both operational, simulated in DesignBuilder and Helioscope, and embodied carbon, calculated in OneClick LCA, over a lifetime of 60 years. A variety of energy saving strategies were applied consistent with leading practice such as air source heat pumps (ASHP), ASHP water heaters, low carbon high thermal resistance constructions, and photovoltaic renewable generation. Two scenarios for converting electricity to carbon emissions were used including marginal, resulting in high emissions, and baseload or average, resulting in low emissions. In all scenarios, both the retrofit and new build significantly reduced the emissions compared to the existing building. Depending on assumptions of carbon intensity of electricity, emissions factors (EFs), and details of specification, the carbon savings for the retrofit ranged from 76% to 98% and ranged from 88% to 97% for the new build. Thus, the retrofit’s carbon emissions are slightly less compared to the newbuild, supporting the time value of carbon ideology. Including renewable energy generation, none of the options resulted in a net-zero carbon status due to the case study urban site limitations. However, through other means of carbon offsetting such as purchasing carbon offsets and purchasing electricity from renewable energy source providers. Using different emission factors creates a large variation in the results and EFs with greater accuracy are required from the industry since the actual EF would be a combination of both baseload and marginal.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| 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 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".