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Record W4392170493 · doi:10.1016/j.scs.2024.105302

Assessing impact of urban densification on outdoor microclimate and thermal comfort using ENVI-met simulations for Combined Spatial-Climatic Design (CSCD) approach

2024· article· en· W4392170493 on OpenAlex
Shreya Banerjee, Rachel Xin Yi Pek, Sin Kang Yik, Graces N Y Ching, Xiang Tian Ho, Yuliya Dzyuban, Peter J. Crank, Juan A. Acero, Winston Chow

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueSustainable Cities and Society · 2024
Typearticle
Languageen
FieldEnvironmental Science
TopicUrban Heat Island Mitigation
Canadian institutionsUniversity of Waterloo
FundersSingapore-MIT Alliance for Research and Technology CentreSingapore Management UniversityTechnische Universität MünchenNational Research Foundation SingaporeNational University of Singapore
KeywordsMicroclimateEnvironmental scienceContext (archaeology)NoonMeteorologyThermal comfortMean radiant temperatureUrban heat islandAtmospheric sciencesLatitudeSpatial variabilityGeographyClimate changeStatistics

Abstract

fetched live from OpenAlex

Future urban planning requires context-specific integration of spatial design and microclimate especially for tropical cities with extreme weather conditions. Thus, we propose a Combined Spatial-Climatic Design approach to assess impact of urban densification on annual outdoor thermal comfort performance employing ENVI-met simulations for Singapore. We first consider building bylaws and residential site guidelines to develop eight urban-density site options for a target population range. We further classify annual weather data into seven weather-types and use them as boundary conditions for the simulations. Comparing such fifty-six combined spatial-climatic simulation outputs by analyzing Outdoor Thermal Comfort Autonomy, we report the influence of site geometry is nominal on air temperatures but significant for mean radiant temperatures and physiological equivalent temperatures. Neighborhoods with taller (20% increase in mean height) buildings and narrower footprints exhibit better thermal performance compared to short and wider (12-58% decrease in mean width) buildings, due to less radiative heat gain during solar noon. For a high density tropical urban context, like Singapore with high sun angle and solar radiation, mutual shading and presence of wind enhances thermal comfort. Results provide useful and actionable recommendations on ideal building profile for heat responsive neighborhoods in low-latitude hot-humid cities similar to Singapore.

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.

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)0.000
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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.575
Threshold uncertainty score0.473

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
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 head0.032
GPT teacher head0.289
Teacher spread0.257 · 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