Whole building life cycle assessment for residential buildings : a design improvement framework
Bibliographic record
Abstract
The environmental impacts of building stock have received significant attention in recent years, as buildings consume more than 40% of the world’s energy and release one third of total greenhouse gas emissions. In the past, most efforts were focused on mitigating environmental impacts during the operational stage of buildings, while the environmental performance of the other life cycle stages received limited attention. In an attempt to address this limitation, whole-building life cycle assessment (WBLCA) has become a trend in order to ensure the best environmental performance of a building in holistic terms. However, research studies usually face challenges to systematically evaluating WBLCA performance at the design stage due to the complexity of assessments at the building level. On the other hand, there are very few studies that consider environmental and economic impacts simultaneously at the building level. Furthermore, the current WBLCA studies usually end after the LCA results are calculated and interpreted. There is no study that provides a building design improvement method based on the final LCA results. The main goal of this research is to develop a design improvement framework based on the proposed WBLCA method to evaluate and improve the environmental and economic performance at the building level. The Environmental Product Declaration (EPD) methods were adopted at the building level to ensure the WBLCA is comprehensive and reliable. Building Information Modelling (BIM) and life cycle cost (LCC) were used to ensure the building assemblies are accurate, and to provide dynamic material updates with associated costs for the design improvement framework. The fuzzy-based multiple criteria decision making (MCDM) approach was used to compare the comprehensive building-level LCA results, and select the most suitable building design by considering all the environmental and economic impacts at different life cycle stages. The deliverables of this research will aid in decision making for sustainable urban planning and environmental performances in the building sector. The developed design improvement framework will assist building designers in efficiently improving the WBLCA performance by highlighting the most critical life cycle stages and building assemblies while considering the economic performance. The BIM-based WBLCA approach will contribute to the development of a digital platform that can also support designers through dynamic WBLCA results in the design revision stages.
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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 | 0.006 | 0.004 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| 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".