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Just one more storey? The embodied greenhouse gas impacts of adding height, slab thickness, building code and design tranches

2025· article· en· W4417451598 on OpenAlexafffund
Avery Hoffer, Evan C. Bentz, Shoshanna Saxe

Bibliographic record

VenueResources Conservation and Recycling · 2025
Typearticle
Languageen
FieldEnvironmental Science
TopicEnvironmental Impact and Sustainability
Canadian institutionsUniversity of Toronto
FundersNatural Sciences and Engineering Research Council of CanadaCanada Research ChairsUniversity of TorontoCement Association of Canada
KeywordsEmbodied cognitionGreenhouse gasGlobeSlabResource (disambiguation)SkepticismSustainable designEmbodied energy

Abstract

fetched live from OpenAlex

Societies across the globe are simultaneously trying to build much more housing while drastically reducing greenhouse gas emissions. This is precipitating debates about the nature of sustainable housing. ‘Conventional wisdom’ holds that taller buildings are worse for the environment coinciding with longstanding skepticism of height, yet the research and data is often anecdotal or incomplete and contradictory. This paper contributes to the discussion by examining how building height affects embodied emissions for new 5-to-20 storey reinforced concrete residential buildings. We find that while height contributes to embodied emissions, its impact is smaller than slab thickness and design tranches within the studied storey range, which offer more effective opportunities to improve resource productivity, reduce material intensity and associated embodied emissions, without reducing building function. Our findings encourage a shift beyond height-based restrictions, urging designers and policy makers to focus on design decisions to conserve resources, lower emissions, and support circular-economy objectives

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.080
Threshold uncertainty score0.450

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.027
GPT teacher head0.268
Teacher spread0.241 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2025
Admission routes2
Has abstractyes

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