Mechanisms of urban blue-green infrastructure on winter microclimate using artificial neural network

Abstract

In response to climate change, urban blue-green infrastructure (UBGI) improves the microclimate of the built environment. In previous research, UBGI (consisting of water and greenery) is found to be a cold source in the summer, alleviating urban thermal stress. However, studies on the heating effect of UBGI in the winter are limited. This effect can improve environmental temperature, which is beneficial to human thermal comfort in the cold season. Therefore, this study conducted the objective and subjective evaluation of the winter microclimate of UBGI through field measurement and questionnaire in China’s cold regions. The coupling mechanisms of UBGI on winter microclimate were quantified by using the artificial neural network (ANN), and the thermal demand characteristic of UBGI users was established. The study results showed that the heating effect of water and greenery was most significant at a distance of 4 m from the water in the winter. Neural network-predicted models are established to discuss coupling mechanisms in depth. The new microclimate influence (MI) model of coupling mechanisms was proposed based on the ANN. In addition, when the air temperature was 9.07–14.75℃, the UBGI not only satisfied the thermal comfort demand but also had a greater comfort level than general urban underlying surfaces did. The universal thermal climate index (UTCI) evaluation based on the coupling mechanisms for UBGI users was obtained. This study offers scientific guidance and reference for the planning and redevelopment of UBGI.