Multiscale Modelling of Urban Heat and Population Health

This review examines multiscale modelling of urban heat and population health. The organizing question is how atmospheric, built-environment, mobility, physiological, and social scales should be connected. Ten related scholarly sources are synthesized through a decision-centered framework spanning problem definition, mechanism, measurement, evaluation, implementation, and governance. The review does not invent experiments, pooled estimates, or unreported quantitative results. It instead evaluates the strength and transferability of the available evidence, with particular attention to using area-average temperature as a proxy for personal exposure and health burden. The resulting framework links technical or empirical performance to explicit use conditions and identifies tests that should precede wider adoption in heat-resilient urban planning and public health.

1. Abulibdeh, A. (2021). Analysis of urban heat island characteristics and mitigation strategies for eight arid and semi-arid gulf region cities. Environmental Earth Sciences, 80(7), 259. https://doi.org/10.1007/s12665-021-09540-7 DOI
2. Antoniou, N., Montazeri, H., Blocken, B., & Neophytou, M. (2024). On the impact of climate change on urban microclimate, thermal comfort, and human health: Multiscale numerical simulations. Building and Environment, 260, 111690. https://doi.org/10.1016/j.buildenv.2024.111690 DOI
3. Chen, K., Boomsma, J., & Holmes, H. A. (2023). A multiscale analysis of heatwaves and urban heat islands in the western U.S. during the summer of 2021. Scientific Reports, 13(1), 9570. https://doi.org/10.1038/s41598-023-35621-7 DOI
4. Fu, J., Dupre, K., Tavares, S., King, D., & Banhalmi-Zakar, Z. (2022). Optimized greenery configuration to mitigate urban heat: A decade systematic review. Frontiers of Architectural Research, 11(3), 466-491. https://doi.org/10.1016/j.foar.2021.12.005 DOI
5. Ho, H., Knudby, A., & Huang, W. (2015). A Spatial Framework to Map Heat Health Risks at Multiple Scales. International Journal of Environmental Research and Public Health, 12(12), 16110-16123. https://doi.org/10.3390/ijerph121215046 DOI
6. Jenerette, G. D., Harlan, S. L., Buyantuev, A., Stefanov, W. L., Declet-Barreto, J., Ruddell, B. L., Myint, S. W., Kaplan, S., & Li, X. (2015). Micro-scale urban surface temperatures are related to land-cover features and residential heat related health impacts in Phoenix, AZ USA. Landscape Ecology, 31(4), 745-760. https://doi.org/10.1007/s10980-015-0284-3 DOI
7. Liu, C., Lu, S., Tian, J., Yin, L., Wang, L., & Zheng, W. (2024). Research Overview on Urban Heat Islands Driven by Computational Intelligence. Land, 13(12), 2176. https://doi.org/10.3390/land13122176 DOI
8. Sabrin, S., Karimi, M., & Nazari, R. (2020). Developing Vulnerability Index to Quantify Urban Heat Islands Effects Coupled with Air Pollution: A Case Study of Camden, NJ. ISPRS International Journal of Geo-Information, 9(6), 349. https://doi.org/10.3390/ijgi9060349 DOI
9. Zhong, Q., Li, Z., Zhu, J., & Yuan, C. (2025). Revealing multiscale and nonlinear effects of urban green spaces on heat islands in high-density cities: Insights from MSPA and machine learning. Sustainable Cities and Society, 120, 106173. https://doi.org/10.1016/j.scs.2025.106173 DOI
10. Zhou, D., Xiao, J., Bonafoni, S., Berger, C., Deilami, K., Zhou, Y., Frolking, S., Yao, R., Qiao, Z., & Sobrino, J. A. (2018). Satellite Remote Sensing of Surface Urban Heat Islands: Progress, Challenges, and Perspectives. Remote Sensing, 11(1), 48. https://doi.org/10.3390/rs11010048 DOI