Associate Professor Fudan University Shanghai, China (People's Republic)
Abstract: Urban Heat Islands (UHIs) have become a pressing concern for cities globally due to the conversion of natural landscapes into impervious surfaces and the increased utilization of artificial materials during urbanization, which retain heat and exacerbate the urban climate. In response to this issue, nature-based solutions (NbS) were formally proposed by the World Bank in 2008. This concept is grounded in the knowledge that healthy natural and managed ecosystems provide a diverse range of services that are essential to human well-being. One type of NbS, green infrastructure (GI), is considered a promising solution for mitigating UHIs. GI aims to incorporate green spaces and other natural features into the urban environment to provide cooling effects that are cost-effective, environmentally friendly, and politically acceptable. Our research proposes a new model, the Threshold Value of Efficiency (TVoE) of GI, which can use the smallest GI patch and optimal spatial structure to achieve the best cooling effect. The TVoE has been widely recognized and adopted by international scholars. Based on the findings from TVoE-based global studies, we speculate that the value of TVoE may vary with latitude. For example, the TVoE of green space in Beijing, Shanghai, and Hanoi is around 0.5 ha, 0.6 ha, and 1 ha, respectively. Building on these findings, we also propose an idealized urban thermal security pattern model (UTSP), which is a multi-grade hexagonal structure to mitigate UHI. Recently, UTSP has been employed in urban climate resilience planning. Moreover, we suggest shifting the research logic of UHI evaluation and mitigation from "patch" to "network." Our method, reverse thinking, aims to first build a heat network to identify the key nodes and corridors of such a network and subsequently block or break this network by NbS from the graph perspective. We believe NbS is a valuable tool for heat mitigation, and the TVoE, UTSP, and reverse thinking-driven model effectively combine urban ecological research with planning and practice, offering great value to UHI mitigation.
