Adaptive Built Environment Lab


Incorporating the effects of UHI in Building Energy Simulation

UHI has been developing as a major concern in urban areas, which, in addition to its negative impacts on human health, also increases building energy consumption in hot and warm climates. This project aims to quantify the relationship between UHI and building energy consumption (BEC) and develop a spatial regression model to predict UHI intensity based on the differences in surrounding urban morphology. The interactions between urban morphology, UHI, and BEC are being studied as two separate but interconnected relationships. First, the relationship between UHI and BEC will be evaluated to quantify the role of various internal and external factors pertinent to building design. With regard to the spatial variation of UHI, this research will develop a spatial regression model that will be used to extrapolate UHI intensity from airport weather data based on differences in urban design variables at the two locations. The development of this integrated UHI prediction model will solve a long-standing problem related to inaccurate BEC calculations in urban areas due to the lack of microclimatic data at the building location. 

Study 1.1 quantifies the dualistic relationship between UHI and building energy performance where UHI tends to increase the annual energy consumption of buildings located in hot climates and decrease it in cold climates. The figure above shows the impact of UHI on building energy consumption in 15 U.S. climate zones. 

This set of studies (1.2 - 1.4) examines the role of building internal variables in the UHI - BEC relationship by quantifying them into passive (eg., building envelope properties), active (eg., HVAC systems), and operational variables (eg., occupancy schedules). The table above shows the relative relevance of major building envelope properties in the relationship between UHI and energy consumption. 

Study 2 evaluates 8 temporal resolutions at which UHI can be applied to BES to determine the “Normalized UHI Indicators”. The figure above Performance comparison of Normalized UHI Indicators for Chicago, IL, Denver, CO, Los Angeles, CA, and Miami, FL .

Study 3 leverages the on-site meteorological data in addition to the urban landscape and geographical data to develop a spatial regression model capable of predicting the spatial variation of UHI intensity based on surrounding urban morphology. The figure above shows the Land surface temperatures in New Orleans, LA recorded on March 10, 2020.