Leveraging hourly emission factors of electric grids to evaluate the operational performance of Canadian buildings
Bibliographic record
Abstract
Abstract Building electrification is seen as an essential means towards decarbonization, yet greenhouse gas emissions (GHG) due to building electricity use vary significantly depending on grid energy generation mixes. While total energy usage is still a primary concern, the timing of energy use becomes increasingly critical in terms of flexibility, energy costs and GHG emissions. This paper investigates how hourly average and marginal emission factors of different electric grids could impact the assessment of building GHG emissions. The proposed case study targets medium-office buildings located in two Canadian provinces (Québec, Ontario), equipped with a dual energy heating system and leveraging fuel switching during electric grid peak events to increase flexibility. Results show that calculations using average and marginal factors could lead to 44-106% differences, while in Ontario, fuel switching leads to an increase in GHG emissions using average factors but a decrease using marginal factors. These results laid the foundations for a broader discussion on appropriate metrics to assess building performance to properly drive building decarbonization strategies or policy.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 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 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".