Borah et al. (2025) Heat-stress reduction through targeted green infrastructure using computational urban climate twins

Identification

• Journal: Climatic Change
• Year: 2025
• Date: 2025-12-26
• Authors: Angana Borah, Sushobhan Sen, Udit Bhatia
• DOI: 10.1007/s10584-025-04091-3

Research Groups

• Department of Civil Engineering, Indian Institute of Technology Gandhinagar, India
• Department of Computer Science and Engineering, Indian Institute of Technology Gandhinagar, India

Short Summary

This study develops a high-resolution digital climate twin of a neighborhood in Ahmedabad, India, to evaluate the thermal co-benefits of small-footprint green infrastructure (GI) interventions, traditionally aimed at flood control. It demonstrates that strategically placed GI, particularly bioretention cells, can significantly reduce heat stress by lowering peak daytime air temperature by up to 2 °C and physiological equivalent temperature by 4–5 °C, while also providing flood mitigation.

Objective

• To evaluate the magnitude, timing (diurnal), and spatial footprint of air temperature and Physiological Equivalent Temperature (PET) reductions achievable with feasible deployments of green roofs (GR), permeable pavements (PP), and bioretention cells (BRC) in a dense Indian neighborhood.
• To assess the thermal performance of these stormwater-oriented GI types under realistic placement and coverage constraints.

Study Configuration

• Spatial Scale: A representative 0.8 km^2 neighborhood area in Ahmedabad, India, with simulations at 3 meter resolution.
• Temporal Scale: Model validation using data from 10 February 2024; scenario evaluation for thermal stress and GI interventions on 8 May 2024 (a typical hot pre-monsoon day). Simulations covered a 24-hour period, with main analysis focusing on daytime variations (08:00 to 19:00 IST).

Methodology and Data

• Models used: ENVI-met 5.6.1 for numerical simulations of surface-plant-air interactions.
• Data sources:
  • Meteorological observations: Hourly air temperature, relative humidity, wind speed/direction, and cloud cover from publicly available sources, private agencies, and the India Meteorological Department (IMD).
  • Geophysical attributes: Terrain elevation, soil properties, and local geological characteristics.
  • Land use characteristics: Land use and land cover (LULC) data from remote-sensing classifications and field observations, building footprints/heights/volumes from OpenStreetMap Buildings repository, and thermal/physical properties (albedo, emissivity, reflectance, heat capacity).
  • Field measurements: Hourly temperature and relative humidity measurements at 2 meters above ground at eight locations within the study area on 10 February 2024, using Testo 405i thermal anemometer and Testo 605i thermohygrometer.

Main Results

• Bioretention Cells (BRC): Covering 3% of the area, BRCs delivered the most substantial daytime cooling, reducing peak daytime air temperature by up to 2 °C and lowering Physiological Equivalent Temperature (PET) by 5–7 °C in some locations during the late afternoon. They also reduced peak runoff by approximately 24%.
• Permeable Pavements (PP): Occupying 6% of the domain, PPs showed localized air temperature reductions of up to 0.8 °C in the late afternoon, with PET improvements of 0.5–1.0 °C in high-coverage areas during mid-afternoon to early evening. They also contributed to stormwater runoff reduction.
• Green Roofs (GR): Covering 4.6% of the area, GRs provided modest cooling, with maximum air temperature reductions of about 0.6 °C during peak afternoon hours. PET differences were modest, with a few grid cells exceeding 4 °C in the late afternoon. They offered modest runoff reduction.
• Overall: None of the strategies significantly lowered nighttime temperatures. PET reductions (4–5 °C in select zones) provided more nuanced insights into perceived human comfort than air temperature alone, highlighting the importance of multifaceted metrics. Targeted, small-footprint GI retrofits are practical and effective for heat and flood mitigation in dense urban environments.

Contributions

• Developed and utilized a high-resolution computational urban climate twin to assess the microclimate impacts of targeted green infrastructure in a rapidly urbanizing tropical city.
• Quantified the specific magnitude, timing, and spatial footprint of air temperature and Physiological Equivalent Temperature (PET) reductions for green roofs, permeable pavements, and bioretention cells under realistic deployment constraints.
• Demonstrated that small-footprint, flood-oriented GI interventions can provide significant co-benefits for heat stress reduction, offering a dual-purpose solution for compound hazards.
• Emphasized the critical importance of evaluating PET in addition to air temperature for a comprehensive understanding of human thermal comfort, revealing that perceived comfort improvements can exceed air temperature changes.
• Provided a transferable framework and actionable guidance for sustainable urban adaptation and targeted GI planning in space-constrained, resource-limited regions globally.

Funding

• Ministry of Education’s AICOE Sustainable Cities (Phase 1) program
• DST Core Research Grant
• IIT Gandhinagar (for field data collection equipment)

Citation

@article{Borah2025Heatstress,
  author = {Borah, Angana and Sen, Sushobhan and Bhatia, Udit},
  title = {Heat-stress reduction through targeted green infrastructure using computational urban climate twins},
  journal = {Climatic Change},
  year = {2025},
  doi = {10.1007/s10584-025-04091-3},
  url = {https://doi.org/10.1007/s10584-025-04091-3}
}