Heat pumps and the path to net-zero: A comparative assessment of air-source heat pumps in Canada
Bibliographic record
Abstract
This study evaluates air-source heat pumps (ASHPs) as a low-carbon alternative to conventional residential heating in Nova Scotia, Quebec, Ontario, and British Columbia. Reducing greenhouse gas (GHG) emissions from residential heating is crucial for Canada's decarbonization goals. This study systematically compares ASHP feasibility across the four provinces with distinct energy grids, highlighting how regional differences in electricity generation impact operating costs and emissions reductions. It employs a techno-economic analysis using province-specific electricity rates, heating costs, and emissions factors. Data sources include government energy reports, utility tariffs, and emissions inventories, ensuring an accurate comparison of ASHP performance across the selected provinces. Findings indicate that ASHP viability varies by province. In British Columbia and Ontario, ASHPs provide cost savings except against natural gas and wood stoves, with Ontario benefiting from shorter payback periods due to higher electricity rates. In Quebec, low electricity costs make ASHPs economically favorable across all heating sources. Nova Scotia shows strong economic feasibility, though its coal-heavy grid limits environmental benefits. Across all provinces, ASHPs significantly reduce emissions compared to conventional heating. These findings highlight the need for financial incentives, grid decarbonization, and updated building codes to enhance ASHP adoption. Future research should assess long-term sustainability and ASHPs' role in achieving net-zero targets. • ASHP feasibility varies by province as grids shape costs and emissions. • A techno-economic model is applied using province-specific rates and emission factors. • In BC and Ontario, ASHPs cut costs except for natural gas and wood stoves. • ASHPs cut GHG emissions in every province versus conventional heating. • Adoption needs incentives, cleaner grids, and updated building codes.
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".