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Record W4412548704 · doi:10.1016/j.jobe.2025.113518

Decarbonization of residential houses in northern Climates: Traditional vs fully electrified approaches in Ontario Canada

2025· article· en· W4412548704 on OpenAlexafffundabout
Shafquat Rana, Joshua M. Pearce

Bibliographic record

VenueJournal of Building Engineering · 2025
Typearticle
Languageen
FieldEngineering
TopicBuilding Energy and Comfort Optimization
Canadian institutionsWestern University
FundersNatural Sciences and Engineering Research Council of CanadaWestern University
KeywordsEnvironmental scienceArchitectural engineeringGeographyEnvironmental protectionEngineering

Abstract

fetched live from OpenAlex

Greenhouse gas (GHG) emissions from burning fossil fuels are the primary source of climate destabilization. The energy sector is responsible for more than three quarters of GHG emissions and among this the largest share comes from the residential sector. Decarbonization of residential sector thus plays an important role in achieving energy and climate goals. Replacing the natural gas used in residential houses with clean energy will reduce emissions. Solar photovoltaics (PV) and heat pumps (HP) have already been proven technically viable solutions on their own. In addition, several studies have demonstrated that PV and HP integration for residential heating can immediately reduce GHG emissions substantially. There are no such case studies, however, available for Canada. This paper thus investigates case studies of three residential houses in London, Ontario, Canada. The first one being a conventional house with natural gas supply and grid electricity, with HP+grid electricity, and lastly PV+HP system. This fully electrical house is modelled to provide hourly total loads based on house consumption and compared with the actual traditional house. The result shows that GHG emission from a fully electrified house when the total consumption is supplied by grid electricity and rooftop PV electricity has a reduction of approximately 80% and 89%, respectively compared to a conventional house. This study also calculates the emission factor for rooftop PV electricity in London, Ontario, Canada is equal to 20.6 g CO 2 e/kWh and has 46% and 98.9% reduction compared to grid electricity and natural gas, respectively.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.709
Threshold uncertainty score0.957

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.013
GPT teacher head0.169
Teacher spread0.156 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
Domainnot available
GenreEmpirical

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".

Quick stats

Citations1
Published2025
Admission routes3
Has abstractyes

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