Residential energy efficiency programs, retrofit choices and greenhouse gas emissions savings: a decade of energy efficiency improvements in Waterloo Region, Canada
Bibliographic record
Abstract
Since 1999, the Residential Energy Efficiency Project, through Green Communities Canada, has been a delivery agent for EnerGuide for Houses and ecoENERGY programs in the Waterloo Region. This research analyzed 10,208 initial and 2,383 final evaluations made by the Residential Energy Efficiency Project between May 1999 and February 2009 to understand what energy efficiency improvements homeowners have made over time. Because of changes to federal and provincial programs, the data are analyzed under four main periods: the EnerGuide program with no financial incentives (1999 to 2003), the EnerGuide program with financial incentives based on performance (2003 to April 2006), no official program (April 2006 to April 2007), and the ecoENERGY program with financial incentives by measure (April 2007 to February 2009). Participating households were divided into cohorts associated with each of these periods. For each of these cohorts, the impact of retrofit changes was assessed as the amount of energy and greenhouse gas emissions saved. It was also assessed whether homeowners treated the ‘house as a system’, that is, whether they made multiple energy efficiency changes (e.g., increasing insulation in the ceiling, foundation or main walls, upgrading windows and doors, air sealing, improving heating, ventilation, air conditioning, or domestic water heating systems) or focused on a single change associated with large energy savings, such as changing their furnace. The findings show that recommended and achieved energy and greenhouse gas emissions savings differed across cohorts, and that achieved savings were generally less than recommended. The final cohort of homeowners who achieved major energy savings was twice as likely (25%) to take the single action of replacing the furnace as during earlier periods. Changes to furnaces were associated with higher levels of energy savings, but overall, 85% of the homes which achieved the highest levels of savings made multiple changes, thereby adopting the ‘house as a system’ approach to energy efficiency improvements. Finally, homeowners were less likely to make improvements to the building envelope, and these improvements were generally less extensive than the identified technical potential for improvement. Copyright © 2011 John Wiley & Sons, Ltd.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.006 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".