A Data-Mining-Based Novel Approach to Analyze the Impact of the Characteristics of Urban Ventilation Corridors on Cooling Effect

Abstract

The appropriate design of urban ventilation corridors (VCs) can improve the urban thermal environment, thereby reducing urban energy consumption and promoting sustainable urban development. However, existing research lacks a comprehensive grasp of the characteristics of VCs from multiple dimensions and quantitative analysis of its cooling effect. We propose a novel approach based on data mining to comprehensively consider the morphological and environmental characteristics of VCs and explore the correlation between VC characteristics and the cooling effect. Selecting Nanjing as an example, a comprehensive index system was constructed, the cooling effect of the VC was investigated, and the optimal range of VC index with different underlying surface types was obtained. Results revealed that the cooling effect is closely related to the underlying surface, leading to a temperature difference of up to 5.4 °C. The VC cooling range can vary from 13 to 600 m. The recommended optimal parameter intervals for different VCs were determined. Finally, targeted strategies to alleviate the heat island effect were proposed for different underlying surface types. The study output contributes to the design of VCs, which is of great significance in alleviating the urban heat island effect and promoting sustainable development of cities.