GREENING THE UK BUILDING STOCK: Historic Trends and Low Carbon Futures 1970-2050
Bibliographic record
Abstract
Historic trends and future projections of energy use and carbon dioxide emissions associated with the United Kingdom building stock are analysed for the period 1970-2050. Energy use in housing is found to rise at a slightly slower rate than the increase in household numbers, which totalled some 25.5 million in 2000. It appears feasible to reduce carbon dioxide (CO2) emissions in the UK domestic building stock by more than 65% by 2050. But this would require a significant take-up of energy saving measures and the adoption of various low or zero carbon (LZC) energy technologies. Non-domestic buildings consisted of some 1.98 million premises in 2000. Anticipated changes in the UK Building Regulations will lead to reductions in energy use and carbon emissions of up to 17% and 12% respectively for 2010 standard buildings. Improvements in the non-domestic building stock and industrial processing could lead to a reduction of nearly 59% in CO2 emissions, via the adoption of LZC energy technologies. Thus, the potential for ‘greening' the UK building stock – making it environmentally benign - is large, but the measures needed to achieve this would present a significant challenge to the UK government, domestic householders, and industry in the broadest sense.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
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".