Impact of Tree Leaf Area Density on Cooling and Ventilation of an Urban Neighborhood
Bibliographic record
Abstract
Abstract The impact of trees during heat waves can be diverse, as their interaction with their surroundings depends on several parameters that modify shading, ventilation potential and transpiration rate. A multiscale coupled model is presented that allows the detailed analysis of the local impact of vegetation as a mitigation measure for urban heat islands. A case study is performed on an urban neighborhood in Zurich, Switzerland, with an aim to improve the understanding of physical processes in urban microclimate subjected to a heat wave. A parametric study presents the impact of varying the leaf area density (LAD) of the existing trees in the neighborhood. Comparisons of surface temperatures and rate of transpiration with available measured data show a good agreement. The results show that urban trees can reduce heat storage during the day due to shadowing, especially when they are in groups. The reduction in air temperature due to transpiration largely depends on LAD, wind-flow patterns and urban morphology. The results also indicate locations with an increase in air temperature due to the presence of trees.
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How this classification was reachedexpand
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 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".