Massive timber building vs. conventional masonry building. A comparative life cycle assessment of an Italian case study
Bibliographic record
Abstract
Abstract This work aims to investigate the environmental friendliness of building materials, and in particular the benefit of using biogenic products as replacement of conventional materials. The sustainability of wood as a construction material is a complex issue since the environmental impacts are strongly related to forest management, service life and, finally, to end-of-life scenarios and waste treatment processes. In this study, a Life Cycle Assessment (LCA) comparison was carried out between a semi-detached house out of cross-laminated timber (CLT) and a conventional building with similar geometric characteristics and equal thermal performance (U-value), out of light-clay bricks with a reinforced concrete structure. Particularly, the environmental impacts from raw materials supply, transportation and product processing (cradle to gate) were investigated and the Recipe mid-point method was adopted for the impact assessment to compare the environmental burdens of the two equivalent buildings. The positive environmental values resulted in the massive timber building are mainly connected to the replacement of the reinforced concrete mass used in the structure. The outcome, in terms of global warming potential, show that the use of wood as a building material instead of conventional materials results in a reduction of greenhouse gas emissions of roughly 25%. This material replacement, if extended on a large scale, could give a valid contribution on achieving the community goals of reducing emissions from the construction sector.
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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 | 0.001 | 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 | 0.003 |
| Scholarly communication | 0.000 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 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".