Residential energy use and potential conservation through reduced laundering temperatures in the United States and Canada
Bibliographic record
Abstract
A residential energy-use model was developed to estimate energy budgets for household laundering practices in the United States and Canada. The thermal energy for heating water and mechanical energy for agitating clothes in conventional washing machines were calculated for representative households in the United States and Canada. Comparisons in energy consumption among hot-, warm-, and cold-water wash and rinse cycles, horizontal- and vertical-axis washing machines, and gas and electric water heaters, were calculated on a per-wash-load basis. Demographic data for current laundering practices in the United States and Canada were then incorporated to estimate household and national energy consumption on an annual basis for each country. On average, the thermal energy required to heat water using either gas or electric energy constitutes 80% to 85% of the total energy consumed per wash in conventional, vertical-axis (top-loading) washing machines. The balance of energy used is mechanical energy. Consequently, the potential energy savings per load in converting from hot-and-warm- to cold-wash temperatures can be significant. Annual potential energy and cost savings and reductions in carbon dioxide emissions are also estimated for each country, assuming full conversion to cold-wash water temperatures. This study provides useful information to consumers for conserving energy in the home, as well as to, manufacturers in the design of more energy-efficient laundry formulations and appliances.
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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 | 0.000 | 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 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".