The three studies in this dissertation investigate the interdependent influence of various environmental features in Urban Green Space (UGS) on human thermal comfort at the microscale. This research pertains to microscale urban climatology. Urban climatology is an interdisciplinary field focused on advising urban construction to achieve the preferred urban climate. Microscale urban climatological studies have more application potential than those at meso- and local scales. Yet, current limitations in microscale urban climatological research hinder realizing this potential. Firstly, the costs of microscale studies are generally high. Secondly, it is difficult to apply the research results elsewhere. As a results, the high-cost microscale studies must be continuously repeated in various locations. The challenge of generalizing research results is a common limitation in urban climatology. Approaches have been proposed to alleviate this limitation in urban climatological studies at meso- and local scales. However, there is a lack of such attempts at the microscale. This research aims to propose an approach contributing to the generalization of research results in microscale urban climatological studies. This approach upgrades from the previous single-parameter approach to a multi-parameter approach. The multi-parameter approach views the UGS holistically by exploring the interdependent influence of various environmental features on human thermal comfort. The interdependent influence can enhance the comprehensiveness of results, improve the results generalization, and facilitate the knowledge transfer into specific guidelines for climate-adaptative UGS design and planning. To explore the interdependent influence, the multi-parameter approach utilizes the factorial experimental design. The microclimate model ENVI-met is used to simulate scenarios in the factorial experiments. The simulations are conducted on idealized and simplified scenarios to minimize the research costs. To control the research cost, the Latin Hypercube Sampling (LHS) design is adopted to sample a subset of scenarios from the factorial experiment for field measurement and simulation. For result applicability, this research evaluates UGS cooling effects using both climatic parameters and biometeorological index -- Physiological Equivalent Temperature (PET). PET values in this research are calculated using the RayMan model. This thesis comprises three independent studies on the interdependent influence of various environmental features of UGS on human thermal comfort. The following common conclusions can be drawn from these three studies. Firstly, different environmental features influence the cooling effects of UGS in an interdependent way. Specifically, the correlation between an environmental feature and the PCI effect depends on various environmental features. Secondly, the multi-parameter approach is significantly superior to the single-indicator approach in comprehensively and accurately capturing the interdependent influence. Additionally, these three studies provide specific and generalizable suggestions for the climate-adaptative UGS design and planning, demonstrating the capability of the multi-parameter approach to enhance the applicability and generalizability of findings in urban climatological studies. The characteristics of the multi-parameter approach include the following three aspects. At the practical level, it can provide specific guidelines for practical UGS design and planning; at the research level, it explores the interdependent influence of multiple environmental features on human thermal comfort; and at the philosophical level, it adopts the holistic view. This research is not only an attempt to enhance methodology and promote the application of research results, but also a manifestation of the philosophical paradigm shift in urban climatology.
