House construction CO<sub>2</sub> footprint quantification: a BIM approach
Bibliographic record
Abstract
Purpose This paper aims to establish a baseline for carbon dioxide (CO2) emissions quantification in the current residential construction process. Opportunities to reduce the environmental footprint of the homebuilding process are also identified. Design/methodology/approach CO2 emissions of various house construction stages are quantified and utilised in a 3D building information model. This allows rapid emission computations for various house sizes, designs and materials. An intelligent database calculates emissions for different house styles with different construction processes. Findings Two construction stages (basement walls foundation and framing) were identified as high CO2 emissions contributors. In addition, equipment operation on site, transportation to and from the site and heating for curing concrete were identified as the main sources of emissions during construction. Originality/value The paper addresses the limited attention given to CO2 emissions during the actual construction process. The introduction of building information modeling for quantifying emissions in the construction process is of significant value. This research is pertinent to the international homebuilding industry and homebuyers who all have a role in mitigating CO2 emissions.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".