Cai et al. (2025) Multifaceted Analysis of Green Roof Characteristics in Modulating Urban Microclimate Patterns

Identification

• Journal: Lecture notes in civil engineering
• Year: 2025
• Date: 2025-12-10
• Authors: Qianwen Cai, Dongjin Cui, Yutong Chen
• DOI: 10.1007/978-981-95-2169-2_22

Research Groups

School of Architecture and Urban Planning, Shenzhen University, Shenzhen, China

Short Summary

This study utilized the ENVI-met simulation platform to systematically analyze how green roof characteristics (vegetation type, Leaf Area Index, substrate moisture) and environmental factors (meteorology, building height) modulate urban microclimate patterns, revealing that intensive green roofs and higher Leaf Area Index offer superior heat mitigation and thermal comfort benefits.

Objective

• To systematically examine the transboundary microclimate regulation mechanisms of green roofs, particularly through critical parameters like Leaf Area Index (LAI) and substrate moisture, and their interactions with environmental drivers such as meteorological forcing and building morphology.

Study Configuration

• Spatial Scale:
  • Simulation domain: 120 m × 120 m horizontally, 72 m vertically.
  • Grid resolution: 2 m × 2 m × 2 m (case studies); 2 m × 2 m × 1 m (validation).
  • Building size: 40 m × 40 m.
  • Pedestrian level: 1.5 m above ground.
  • Location: Shenzhen, China (22°4 N, 114°0 E).
• Temporal Scale:
  • Simulation duration: 30 hours (case studies), starting July 23, 2023, at 00:00.
  • Validation period: 8-hour diurnal cycle (09:00–17:00 LST) on July 23, 2023.
  • Model temporal resolution: 10 seconds.
  • Field measurement interval: 10 minutes.

Methodology and Data

• Models used: ENVI-met V5.5
• Data sources:
  • Field measurements: Air temperature (Ta), relative humidity (RH), and wind speed collected using a JT-IAQ-50 microclimate monitoring system at Kaili Garden, Shenzhen, on July 23, 2023.
  • Meteorological data: Hourly air temperature, relative humidity, wind speed, and wind direction from the Nanshan meteorological station.
  • Validation metrics: Coefficient of determination (R²), Root Mean Square Error (RMSE), and Mean Absolute Percentage Error (MAPE).

Main Results

• Vegetation Type: Intensive green roofs (trees) demonstrated the highest efficacy, providing a maximum cooling of 1 °C and humidification of 0.15% at the roof level, and improving Universal Thermal Climate Index (UTCI) by 5.63 °C at the roof level and 0.28 °C at the pedestrian level.
• Leaf Area Index (LAI): A higher LAI (3.5) resulted in the most pronounced cooling (0.76 °C) and humidifying (0.13%) benefits at the roof level, with benefits leveling off beyond a certain point.
• Substrate Moisture Content: Increased substrate moisture content (ζw = 0.8) significantly enhanced temperature and humidity differences during the day, leading to a maximum temperature difference of 0.74 °C and a minimum relative humidity difference of -2.91% (increased humidity) at the roof level.
• Meteorological Factors:
  • Wind Speed: Moderate wind speeds (around 2 m/s) supported green roof performance, with higher wind speeds leading to greater temperature and humidity differences at elevated heights (e.g., max ΔTa of 0.71 °C at 2 m/s).
  • Weather Conditions: Sunny days yielded the most significant microclimate benefits (e.g., ΔTa peaks at 0.71 °C, ΔUTCI at 5.81 °C on high-rise tops), while overcast days showed minimal impact.
• Building Height: Lower buildings (12 m) exhibited the highest temperature and humidity differences (e.g., max ΔTa of 0.91 °C, min ΔRH of -3.60%), with the cooling effect diminishing as building height increased.
• Diurnal Variation: Green roofs consistently improved microclimatic conditions during the day, with effects diminishing at night.
• Overall Influence: Meteorological factors had the most significant influence on green roof performance, followed by component parameters, with building height and layout having a smaller impact.

Contributions

• Delivers the first systematic examination of green roofs’ transboundary microclimate regulation mechanisms, specifically focusing on Leaf Area Index (LAI), substrate moisture, and wind-building interactions.
• Fills a critical knowledge gap in urban climate science regarding how green roof components interact with meteorological factors and building characteristics to regulate microclimates.

Funding

Open Fund of the Key Laboratory of Ecology and Energy Saving Study of Dense Habitat, Ministry of Education (20220104).

Citation

@article{Cai2025Multifaceted,
  author = {Cai, Qianwen and Cui, Dongjin and Chen, Yutong},
  title = {Multifaceted Analysis of Green Roof Characteristics in Modulating Urban Microclimate Patterns},
  journal = {Lecture notes in civil engineering},
  year = {2025},
  doi = {10.1007/978-981-95-2169-2_22},
  url = {https://doi.org/10.1007/978-981-95-2169-2_22}
}