Optimizing building spatial morphology to alleviate human thermal stress

Abstract

Achieving urban cooling from a sustainable perspective requires strategic planning of building area (S) and height (H). However, there is a lack of human thermal stress assessment and it is not clear how to optimize the layout of building spatial morphology to alleviate human thermal stress. We simulated the Universal Thermal Climate Index (UTCI), characterizing high spatial resolution human comfort, by machine learning, and analyzed the relationship between building spatial morphology and UTCI to determine the feasible layout of building spatial morphology. Our findings indicated that the study area experienced poor human thermal comfort, with residents facing high thermal stress (average UTCI of 36 °C). Zoning analysis revealed that an increase in S resulted in a simultaneous rise in UTCI, while an increase in H leaded to a trend of UTCI that initially rose and then declined. An increase in S-rating had a more pronounced impact on elevating UTCI (0.29 °C on average) compared to an increase in H-rating (0.11 °C on average). To maintain UTCI within the UTCI threshold that characterized ideal human comfort, a trade-off relationship between S and H should be maintained, which was further influenced by the stationary and plunge intervals in their relationship curve. The findings have the potential to provide valuable insights for policymakers and stakeholders, aiding them in making informed decisions in urban planning to alleviate human thermal stress.