Life cycle assessment and life cycle costing of container-based single-family housing in Canada: A case study
Bibliographic record
Abstract
This research presents an early-design analysis of single-family housing located in Calgary, Canada; and combines energy analysis, life cycle assessment (LCA), and life-cycle costing (LCC), to investigate the life cycle impacts associated with repurposing upcycled containers into modular housing. The study considers four case studies; container and lightwood designed to code specifications, both serving as base models and two improved models of container and lightwood, designed by incorporating energy efficiency measures and passive solar design standards. The life cycle assessment results for the code cases clearly show that majority of the life cycle environmental impacts (95%) occur at the use and operation phase, followed by the pre-use contributing 4%, and less than 1% at the end of life. For the improved cases, results show similar findings as the use and operation phase contributes approximately 85% impact, however, a higher pre-use impact of 12% is reported. Over the 50 years lifespan, the comparative life cycle impacts show only 3% difference when comparing container to lightwood cases. Sensitivity analysis show that utilizing Scenario 100:0 (container code-cut-of-method) in housing can result in a substantial amount of avoided impact about 46 (t CO2 eq) and (538 GJ) 149,444 kWh energy savings as compared to Scenario 0:100 (improved container – end of life recycling). Approximately 10% life cycle cost reduction is realized with the improved cases compared to code cases. This study proves the potentials for repurposing container for long-term usage as a building system, thereby meeting affordable housing needs with less environmental impacts.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| 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".