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Record W2951732912 · doi:10.1088/1748-9326/ab28ba

Passive survivability of buildings under changing urban climates across eight US cities

2019· article· en· W2951732912 on OpenAlexafffund
Amir Baniassadi, David J. Sailor, E. Scott Krayenhoff, Ashley M. Broadbent, Matei Georgescu

Bibliographic record

VenueEnvironmental Research Letters · 2019
Typearticle
Languageen
FieldEnvironmental Science
TopicClimate Change and Health Impacts
Canadian institutionsUniversity of Guelph
FundersNatural Sciences and Engineering Research Council of CanadaEnvironmental Protection AgencyNational Science Foundation
KeywordsOverheating (electricity)Environmental scienceThermal comfortMeteorologyClimate changeHeat waveAir conditioningClimatologyGeographyEngineering

Abstract

fetched live from OpenAlex

Abstract In the US, more than 80% of fatal cases of heat exposure are reported in urban areas. Notably, indoor exposure is implicated in nearly half of such cases, and lack of functioning air conditioning (AC) is the predominant cause of overheating. For residents with limited capacity to purchase, maintain, and operate an AC system, or during summertime power outages, the ability of buildings to maintain safe thermal conditions without mechanical cooling is the primary protective factor against heat. In this paper, we use whole-building energy simulations to compare indoor air temperature inside archetypical single-family residential buildings without AC at the start and middle of the century in eight US cities. We ran the models using hourly output from 10 year regional climate simulations that explicitly include heating from mid-century projections of urban development and climate change under a ‘business-as-usual’ emissions scenario. Moreover, to identify the impacts from evolving construction practices, we compare different versions of building energy standards. Our analysis shows that summertime overheat time may increase by up to 25% by the middle of century. Moreover, we find that, while newer building energy codes reduce thermal comfort under moderate outdoor weather, they perform better under extreme heat.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.187
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
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 science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0080.002

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 head0.052
GPT teacher head0.347
Teacher spread0.295 · 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; both teacher heads agree on what is shown here.

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

Citations55
Published2019
Admission routes2
Has abstractyes

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