Influence of Building Height on Microclimate and Human Comfort: A Case Study from the New Administrative Capital
Bibliographic record
Abstract
This manuscript investigates the impact of urban development on microclimates worldwide, highlighting the critical role of pedestrian thermal comfort in human well-being and global climate.The built environment plays a significant role in moderating these effects, which are influenced by factors such as building heights and materials.To anticipate outdoor conditions, this research utilizes ENVI-met simulation to model various aspects of the microclimate, including wind patterns and solar radiation, which are crucial for human comfort.The manuscript emphasizes the importance of air motion, temperature, and humidity in determining thermal comfort and recommends radiant temperature adjustments in urban areas to mitigate adverse climate impacts.Focusing on the New Administrative Capital's neighborhood design, the research demonstrates how microclimatic enhancement through simulation techniques can inform city planning and shape urban design.The findings underscore the interconnectedness of human comfort, urban design, and microclimatic conditions, suggesting that modifying specific design elements can alter local climates.The study recommends that urban planners consider building heights and arrangements to optimize microclimatic conditions, enhancing human comfort while mitigating adverse climate impacts.This research presents evidence of how urban design influences microclimates and highlights the potential to enhance human comfort through informed design choices, providing practical recommendations for urban planners to incorporate into their designs.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".