This study investigates the differences in outdoor thermal comfort in different spatial types over long-term observations during the transition season in a cold region. Using the Universal Thermal Climate Index (UTCI) as an evaluation index, subjective questionnaires and field surveys were conducted on thermal comfort in three different typical outdoor environments (sunlight, tree shade and building shade) in Dalian (Northeast China). The results demonstrated the following: (1) Air temperature and mean radiant temperature were the dominant meteorological factors affecting outdoor thermal comfort in Dalian. (2) The main thermal sensation recorded in the transition season was “slightly cool”. Over time, the human thermal sensation experienced a gradual transition from “hot” to “cold”. (3) Compared with direct sunlight, the average UTCI decreased by 6.6 and 3.5 °C for building shade and tree shade environments, and the neutral UTCI in Dalian was found to be 18.8 °C. Subjects were most sensitive to the thermal environment in building shade, then in tree shade and the least in sunlight. (4) When UTCI ≥ 21.9 °C, the thermal acceptability rate in building shade remained the highest; when 10.2 °C ≤ UTCI < 21.9 °C, it was highest in tree shade; and when the UTCI < 10.2 °C, it was highest in sunlight. This study verifies the UTCI applicability in the transition season in cold regions and analyzes the spatial differences in human thermal comfort. These differences play a positive role in developing optimization strategies for outdoor thermal environments, improving environmental satisfaction and facilitating pedestrian outdoor activities.

In the context of the escalating challenge of climate change, optimizing buildings’ energy performance has become a critical research area, yet studies specifically targeting library buildings are scarce. This study addresses this gap by investigating the impact of multi-objective optimization on energy efficiency and occupant comfort in educational library buildings under future climate scenarios. Utilizing the Non-Dominated Sorting Genetic Algorithm II (NSGA-II), this research optimizes a range of building parameters, including the cooling and heating setpoints, air change rates, shading device depths, window visible transmittance, and window gas types. The optimization aims to balance energy consumption and comfort, using simulations based on future weather data for the years 2020, 2050, and 2080. The results indicate that the optimized solutions can significantly reduce the heating energy by up to 95.34% and the cooling energy by up to 63.74% compared to the baseline models, while maintaining or improving the occupant comfort levels. This study highlights the necessity for dynamic, responsive architectural designs that can adapt to changing environmental conditions, ensuring both sustainability and occupant well-being. Furthermore, integrating these building-level optimizations into a City Information Model (CIM) framework can enhance urban planning and development, contributing to more resilient and energy-efficient cities. These findings underscore the importance of sustainable design practices in the context of climate change and the critical role of advanced optimization techniques in achieving energy-efficient, comfortable educational spaces.

By 2021, the urbanization rate of China had reached as high as 64.72%. At the same time, the efficiency-driven urban planning paradigm had shifted to that of an efficiency-and-fairness intent. Fairness refers to the publicness of public open spaces (POS) as an indicator of an inclusive and fair city. The authors are interested in the measure of POS. However, few studies evaluated POS by effective assessment frameworks and tools. Based on this critique, the authors propose to integrate a qualitative assessment tool—the Star Model, with that of a quantitative assessment tool—the Space Syntax, for assessing publicness and enhancing the understanding of POS (streets and squares). There are two conclusions: (1) The combined use of the quantitative and qualitative tools provides accuracy and enables a comprehensive understanding of public spaces, namely, the mechanism of publicness—of both bottom-up POS and top-down POS. On the one hand, bottom-up POS is an outcome of the spatial system enabled by a networked structure of space. On the other, the publicness of top-down POS can be largely twisted by the government and urban designers rather than the residents. (2) This research has introduced an improved combined tool for the benefits of both policymakers and planners.