Energy Efficiency and Global Warming Potential in the Residential Sector: Comparative Evaluation of Canada and Saudi Arabia
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
In the Canadian building sector, residential housing has been identified as the largest contributor to greenhouse gas (GHG) emissions. Similarly, high-income countries, such as Saudi Arabia, are also excessively investing to meet their residential demands. Although developed countries are considered to have more sustainable development practices, factors such as occupancy per household and floor area of a single-family residence can contribute to greater energy consumption and GHG emissions per capita. To develop global sustainable strategies, there is a need to evaluate the global warming potential (GWP) on a household basis by considering different lifestyles and climatic conditions in different parts of the world. In this study, a methodical framework was developed to compare an average Canadian single-family detached house (CSDH) with an average Saudi Arabian villa (SAV) (with similar living standards) based on their energy consumption and associated GWP. Demographic and environmental data were collected from the literature and relevant organizations. To accommodate regional variations in construction practices and climatic conditions, two different types of houses in five different cities of both the countries were analyzed. The study found that the overall GWP of a SAV is approximately 25% higher than that of a CSDH because of the larger floor area. However, comparison on a per-person (occupant) basis revealed that the SAV produces 43% less GHG emissions than the CSDH. The results of this study will assist in formulating sustainable development policies in the residential sector and provides a rationale for both Canada and Saudi Arabia to adopt sustainable development strategies.
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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 | 0.000 | 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 it