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Record W7139923821 · doi:10.71892/11143/1467

Role of urban trees in mitigating pedestrian heat exposure across diverse climates

2025· other· en· W7139923821 on OpenAlexaboutno aff
Clément Nevers

Bibliographic record

VenueUSherbrooke-PROD · 2025
Typeother
Languageen
Field
Topic
Canadian institutionsnot available
Fundersnot available
KeywordsMesoscale meteorologyMicroclimateUrban heat islandUrban climateAdvectionPopulationClimate changeClimate modelVegetation (pathology)Albedo (alchemy)

Abstract

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Cities now host more than half of the world population and account for nearly three-quarters of global energy use. Their compact geometry, extensive use of impermeable low-albedo materials, and limited vegetation amplify urban heat and intensify the urban heat-island effect. In parallel, climate change is increasing the frequency and severity of heat waves, compounding risks to human health. Urban vegetation, especially trees, is often advanced as a prominent nature-based solution. Through shading and evapotranspiration, trees can lower surface and air temperatures and reduce radiative loads, while offering co-benefits. Yet these cooling effects are not uniform and can be offset by potential drawbacks, including ventilation obstruction, higher humidity, and reduced nocturnal radiative cooling. The net impact on thermal comfort depends strongly on background climate, tree form, canopy density, and surrounding urban morphology. Current knowledge remains fragmented, with most studies limited to single sites or simplified models that cannot capture the mechanistic interactions of vegetation within complex urban contexts. This thesis addresses this gap by developing a nested modeling framework coupling mesoscale meteorology with microscale simulations, enabling explicit quantification of the complex interactions between tree physiological responses, radiative exchanges, and advection effects under varying climatic conditions. The open-source solver urbanMicroclimateFoam is employed to resolve urban phenomena that govern tree-atmosphere interactions at neighborhood scale. Three representative urban contexts are studied: Montreal, Canada (continental), Singapore (tropical hot-humid), and Oujda, Morocco (arid hot-dry). Within each, multiple vegetation configurations are examined, including street trees or parks. Thermal comfort is assessed using the Universal Thermal Climate Index (UTCI), from which generalized assessment tools are developed. A cooling efficiency (CE) metric quantifies reductions in heat exposure relative to baseline conditions, while clustering identifies recurring spatiotemporal patterns to support targeted planning interventions. Results reveal that tree cooling varies strongly with climate and generates both local benefits and non-local trade-offs. In continental climate, trees reduce thermal stress by up to 8 °C UTCI locally (CE of -50%) but obstruct ventilation corridors, causing non-local heating up to +3 °C UTCI (CE of +25%). In tropical climate, high background humidity limits the comfort benefits of transpiration, yet shading still provides local reductions up to 8 °C UTCI (−40% CE), but non-local heating reaches up to +6 °C UTCI (+35% CE). In arid climate, transpiration is particularly effective when water is sufficient, achieving only positive impact of −50% CE locally and −15% non-locally. However, drought trees lead to non-local heating up to +15% CE. Across all cases, tree arrangement and canopy density are essential to control local cooling and non-local heating effects. Additional simulations apply the three climatic conditions to a common idealized geometry, isolating how background climate alone governs tree cooling effect and spatial extent. The work concludes that trees remain a key adaptation strategy, but their effectiveness is context-specific and requires climate-sensitive design guidelines. Future perspectives include extending analyses to long-term climate scenarios, integrating complementary heat mitigation strategies, enriching guidance for city dwellers and planners, and assessing socio-economic and ecological co-benefits.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.464
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.013
GPT teacher head0.267
Teacher spread0.255 · 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 designNot applicable
Domainnot available
GenreOther

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

Citations1
Published2025
Admission routes1
Has abstractyes

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