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    MENG Fanchao, REN Guoyu, YAN Chao, DONG Guangtao, AO Xiangyu
    PROGRESS IN GEOGRAPHY. 2025, 44(12): 2526-2542. https://doi.org/10.18306/dlkxjz.2025.12.008

    Urban heat island (UHI) effect is an important factor affecting the spatiotemporal variations of energy consumption for building cooling and heating in urban areas. Understanding the impact of UHI effect on building energy consumption is crucial for urban energy conservation, carbon emission reduction, and high-quality development. This article reviewed the relevant literature on the impacts of UHI effect on building cooling and heating energy consumption. It described the basic framework for the assessment of UHI effect on building energy consumption, summarized problems with the current research, and suggested potential future research directions. The review of the research results and main findings both in China and internationally show that: 1) Generally, UHI effect increases building cooling energy consumption and reduces heating energy consumption in urban areas. Magnitude of the increase in cooling energy consumption and the decrease in heating energy consumption varies in different regions depending on their climate zones and urbanization stages. 2) There are significant spatial differences in the impacts of UHI effect on building cooling/heating energy consumption, with the strongest impacts in the central urban areas and the weakest in the suburban areas. 3) During extreme weather and climate events (for example, heat waves), the synergistic effect of the UHI and extreme events affects the occurrence time and level of peak energy consumption in urban buildings. There are still uncertainties in the study of the impacts of UHI effect on building cooling and heating energy consumption, as well as limitations in the studies of the effects of extreme weather and climate events, large-scale high spatiotemporal resolution assessment, and mechanisms of UHI effect on urban building energy consumption. Further investigations are needed in areas such as applying high spatiotemporal resolution data, innovating research methods, and incorporating extreme weather and climate impacts.