Transforming Built and Urban Microclimates: Advancing Resilience Science for Vulnerable Populations in a Decarbonized and Electrified Canada
Summary
As extreme weather grows more frequent and intense, Canadian communities need faster, smarter ways to adapt. This project brings together experts in engineering, AI, climate science, psychology, and Indigenous housing to reimagine how cities prepare for and withstand climate shocks—while cutting emissions and advancing equity.
The research spans five key areas: high-resolution data collection on heat and health impacts, predictive tools using AI and quantum computing, real-world testing of green retrofits and wildfire prevention, knowledge mobilization through AI-based learning tools, and policy recommendations to strengthen codes and climate resilience guidelines.
The project closes major data and policy gaps, especially for seniors and Indigenous communities. It supports retrofits, permafrost assessments, and climate-smart housing, while influencing national strategies through partnerships with NRC, ECCC, and NRCan. By fusing deep science with scalable applications, it sets the foundation for electrified, low-carbon, climate-ready communities across Canada.
Key details
| Principal investigator | Liangzhu Leon Wang, Concordia University |
| Co-principal investigators | Ted Strathopoulos, Concordia University Biao Li, Concordia University Carly Ziter, Concordia University Honghao Fu, Concordia University Hua Ge, Concordia University Jinqiu Yang, Concordia University Marius Paraschivoiu, Concordia University Muthu Packirisamy, Concordia University Nathalie Phillips, Concordia University |
| Areas of Research | Modelling and Design Technologies, Monitoring Technologies, Control, Systems, and Access Technologies, Construction-related Technologies, Building and Building Envelope Technologies, Infrastructure/Utility Technologies, Equity and Accessibility to Renewable Energy or Renewable Energy Technologies, Public Policy and Governance of Energy or Energy-related Technologies, Knowledge Mobilization of Decarbonization and Electrification Processes |
| Non-academic partners | Earthrise Building Services Inc, SFTec Inc, Origin Geomechanics Inc, Geotherma Solutions Inc, Rowan Williams Davies & Irwin Inc, NRC, Environment and Climate Change Canada, Institute national de la recherce scientifique, NRCan, TU Bergakademie Freiberg, IEA EBC Annex 97/IEA CITIES Task 5, Alzheimer Society of Canada, Frauhofer Institute for Building Physics, Lawrence Berkeley Laboratory |
Publications:
S. Rayegan et al., “Development of a 3D ray tracing-based direct solar shading model for urban building energy simulation,” Renewable Energy, vol. 256, p. 123883, Jan. 2026, doi: 10.1016/j.renene.2025.123883.
A. Marey, J. Zou, S. Goubran, L. L. Wang, and A. Gaur, “Urban morphology impacts on urban microclimate using artificial intelligence – a review,” City and Environment Interactions, vol. 28, p. 100221, Dec. 2025, doi: 10.1016/j.cacint.2025.100221.
T. Chen et al., “Machine learning as CFD surrogate models for rapid prediction of building-related physical fields: A review of methods and state-of-the-art,” Building and Environment, vol. 285, p. 113667, Nov. 2025, doi: 10.1016/j.buildenv.2025.113667.
X. Hu et al., “Effects of different activation functions on multilayer perceptron performance for predicting indoor airflow fields,” Building and Environment, vol. 285, p. 113680, Nov. 2025, doi: 10.1016/j.buildenv.2025.113680.
L. Li, A. Kross, C. D. Ziter, and U. Eicker, “Analyzing spatial patterns of urban green infrastructure for urban cooling and social equity,” Urban Forestry & Urban Greening, vol. 112, p. 128983, Oct. 2025, doi: 10.1016/j.ufug.2025.128983.
A. Marey, L. L. Wang, A. Gaur, H. Lu, S. Leroyer, and S. Belair, “Urban climate simulation for extreme heat events – A comparison between WRF and GEM,” Urban Climate, vol. 63, p. 102570, Sept. 2025, doi: 10.1016/j.uclim.2025.102570.
R. Li, J. Niu, Y. Zhao, L. (Leon) Wang, X. Shi, and N. Gao, “Wind tunnel experiments on the aerodynamic effects of a single potted tree: Hot-wire anemometry and PIV measurements,” Urban Climate, vol. 62, p. 102520, Aug. 2025, doi: 10.1016/j.uclim.2025.102520.
D. Qi, L. L. Wang, M. Heidarinejad, and M. Hamdy, “Adapting building performance simulation for climate resilience: accounting for urban microclimates and future climates,” Journal of Building Performance Simulation, pp. 1–7, Aug. 2025, doi: 10.1080/19401493.2025.2540927.
F. Baba et al., “Field assessment of thermal conditions in naturally ventilated classrooms during spring: microclimate and passive cooling impacts in cold climate,” Smart and Sustainable Built Environment, pp. 1–25, Aug. 2025, doi: 10.1108/SASBE-03-2025-0142.
A. Marey, L. L. Wang, and S. Goubran, “Developing accurate land cover projection to accelerate the realization of SDG 11 in urbanized cities: a comparative study,” Clean Techn Environ Policy, Aug. 2025, doi: 10.1007/s10098-025-03297-4.
J. Zou, L. Wang, S. Yang, M. Lacasse, and L. (Leon) Wang, “Predicting long-term urban overheating and their Mitigations from nature based solutions using Machine learning and field measurements,” Energy and Buildings, vol. 338, p. 115720, July 2025, doi: 10.1016/j.enbuild.2025.115720.
R. Zmeureanu, H. Dou, H. Ge, L. Wang, and Z. Xie, “Thermal time constant estimation of unoccupied school buildings from field measurements over summer,” Journal of Building Engineering, vol. 104, p. 112311, June 2025, doi: 10.1016/j.jobe.2025.112311.
R. Li, Y. Zhao, L. (Leon) Wang, J. Niu, X. Shi, and N. Gao, “Fast fluid dynamics simulations of the drag effect of trees on airflow distributions,” Building and Environment, vol. 278, p. 113039, June 2025, doi: 10.1016/j.buildenv.2025.113039.
N. Luo et al., “A data schema for exchanging information between urban building energy models and urban microclimate models in coupled simulations,” Journal of Building Performance Simulation, vol. 18, no. 3, pp. 333–350, May 2025, doi: 10.1080/19401493.2022.2142295.
D. Al-Assaad et al., “Resilient passive cooling strategies during heat waves: A quantitative assessment in different climates,” Building and Environment, vol. 274, p. 112698, Apr. 2025, doi: 10.1016/j.buildenv.2025.112698.
S. Qin et al., “Modeling multivariable high-resolution 3D urban microclimate using localized Fourier neural operator,” Building and Environment, vol. 273, p. 112668, Apr. 2025, doi: 10.1016/j.buildenv.2025.112668.
Accepted publications in national and international conferences:
L. L. Wang, “The Rise of Quantum Computing -- Take a BITE for Built Environment and Micro Climate Research,” Sept. 2025.
L. L. Wang, “Influence of Upstream Fetch for Environmental Wind Engineering,” Aug. 2025.
L. L. Wang, “ISO Wall Factor Refinement for Wind-Driven Rain on Buildings: CFD-based Machine Learning Models,” Aug. 2025.
L. L. Wang, “Process in Assessing Wind Loads on Roof-mounted Solar Panels: Research and Standards,” Aug. 2025.
L. L. Wang, “Wind Turbulence in the Built Environment via CPU and GPU Based LES,” Aug. 2025.
L. L. Wang, “A Comprehensive Experimental Study through Building-Integrated Wind Turbines,” July 2025.
L. L. Wang, “Optimization of Airflow Mixing based on Taguchi, ANOVA and GRA Methods,” July 2025.
L. L. Wang, “A Hybrid Approach for Urban Microclimate Modeling for Environmental and Structural Applications,” July 2025.
L. L. Wang, “Multi-objective Optimization of Airflow Mixing in various Distribution Systems with Taguchi-based Grey Relational Analysis: Application in a Classroom,” June 2025.
S. Qin, D. Geng, J. Vogel, A. Afshari, and L. (Leon) Wang, “Deep Learning for Urban Microclimate Downscaling: From Coarse WRF Data to Building-Resolved PALM Simulations,” May 2025. doi: 10.5194/icuc12-568.
J. Zou, L. Wang, S. Yang, M. Lacasse, and L. Wang, “Evaluating the Impacts of Natural Based Soluations on Long-term Urban Overheating through Machine Learning and Field Measurements,” May 2025. doi: 10.5194/icuc12-310.
A. Marey et al., “Spatiotemporal Urban Morphology Prediction: A Conditional Diffusion Model Approach,” May 2025. doi: 10.5194/icuc12-506.
S. Rayegan, L. (Leon) Wang, and R. G. Zmeureanu, “Urban-scale modeling of building energy self-sufficiency using rooftop photovoltaics,” May 2025. doi: 10.5194/icuc12-186.
L. L. Wang, “Validation of Turbulence Inflow Generation Methods for Wind Loads Prediction on a Generic Tall Building via LES,” May 2025.
Iris Guan: Canadian Young Leaders for Climate Resilience Program, Standards Council of Canada, October 6, 2025.
Theodore Stathopoulos: Research Impact Award, Concordia University, May 28, 2025.
Sohail Akhtar: Best paper presentation award, 23th Global Joint Seminar on GeoEnvironmental Engineering (GEE 2025), May 22-23, 2025.
Liangzhu Leon Wang: Provost's Circle of Distinction, Concordia University, April 22, 2025.
Liangzhu Leon Wang: ASHRAE Fellow, American Society of Heating, Refrigerating and Air-Conditioning Engineers, February 9, 2025.
Related graduate programs
Related master's programs
- Biology (MSc)
- Building Engineering (MASc)
- Civil Engineering (MASc)
- Computer Science (MCompSc)
- Industrial Engineering (MASc)
- Information Systems Security (MASc)
- Mechanical Engineering (MASc)
- Nanoscience and Nanotechnology (MASc)
- Psychology (MA)
- Quality Systems Engineering (MASc)
- Software Engineering (MASc)
