Impact of trees on thermal comfort in adjacent park and neighborhood in hot-humid climate: A CFD study
Why this work is in the frame
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Bibliographic record
Abstract
We study the interactions between a park and a residential neighborhood in Singapore with high-fidelity microclimate simulations using Computational Fluid Dynamics (CFD). We reveal the broader spatial influence of trees, with cooling effects extending over distances of up to 100 m, though occasionally accompanied by unintended warming zones. Multifaceted effects of trees include the immediate, localized cooling effect in the planted zone, primarily driven by shading, and a variety of non-local effects influenced by air temperature, relative humidity, and wind speed. Results for this case study reveal that trees can significantly reduce values of the Universal Thermal Climate Index (UTCI), improving thermal comfort levels by up to 10 °C. However, trees can also cause non-local heating effects, increasing UTCI by up to 5 °C in unshaded areas within the park during peak conditions. UTCI reduction mainly comes from the shading effect, as the cooling effect of air temperature reduction is nearly offset by an increase in relative humidity. Wind sheltering caused by trees has a consistent minor negative impact of around +0.5 °C UTCI. We also study the interplay of trees with the presence of open space under lift-up buildings. We show that such nuanced understanding of microclimatic dynamics is essential to correctly plan mitigation strategies within hot-humid climates, emphasizing the importance and need of high-fidelity urban studies. These findings underscore the positive and negative impacts of vegetation on urban thermal comfort and highlight the need for advanced heat exposure indices to accurately assess the effectiveness of heat mitigation strategies.
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Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it