Baia et al. (2026) LUCIDiT: A Lean Urban Comfort Intelligent Digital Twin for Quick Mean Radiant Temperature Assessment

⚠️ Warning: This summary was generated from the abstract only, as the full text was not available.

Identification

• Journal: Atmosphere
• Year: 2026
• Date: 2026-03-17
• Authors: Michele Baia, Giacomo Pierucci, Carla Balocco
• DOI: 10.3390/atmos17030305

Research Groups

Not specified in the provided text.

Short Summary

The study introduces LUCIDiT, a physically based digital twin framework designed for rapid Mean Radiant Temperature (MRT) assessment in complex urban environments, significantly reducing computational costs while maintaining physical accuracy.

Objective

• To develop a computationally efficient modeling framework for evaluating outdoor thermal comfort and testing urban climate adaptation strategies.

Study Configuration

• Spatial Scale: Urban pilot site in Florence, Italy.
• Temporal Scale: Not specified (utilizes recursive time-series filtering for thermal inertia).

Methodology and Data

• Models used: LUCIDiT (integrating simplified mutual radiative heat exchange and recursive time-series filtering), Urban Multi-scale Environmental Predictor (UMEP) for validation.
• Data sources: Drone-acquired thermographic data.

Main Results

• Computational processing times were reduced by orders of magnitude compared to traditional high-resolution physical models.
• Validation showed high reliability and coherence with both drone-acquired thermographic data and the UMEP model.
• Simulation of mitigation scenarios indicates that replacing impervious surfaces with irrigated greenery and arboreal canopies can reduce radiant loads by up to 20 °C.

Contributions

• Provides a robust and scalable operational digital twin that enables the rapid testing of urban mitigation scenarios and evidence-based climate adaptation planning without the prohibitive computational costs of standard physical models.

Funding

Not specified in the provided text.

Citation

@article{Baia2026LUCIDiT,
  author = {Baia, Michele and Pierucci, Giacomo and Balocco, Carla},
  title = {LUCIDiT: A Lean Urban Comfort Intelligent Digital Twin for Quick Mean Radiant Temperature Assessment},
  journal = {Atmosphere},
  year = {2026},
  doi = {10.3390/atmos17030305},
  url = {https://doi.org/10.3390/atmos17030305}
}