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With the development of cities in cold regions, the demand for green spaces surpasses what formal areas like city parks can provide. This study employs an embodied cognition approach, based on the valence-arousal dimension model, to assess the emotional responses of residents in cold regions to informal green spaces (IGSs) from both subjective and objective perspectives. The findings reveal that IGSs positively influence the emotional valence and arousal of residents. The study also examines how different sample characteristics impact these emotional responses, confirming that IGSs in cold regions enhance residents’ emotional states both subjectively and objectively. The manner in which these characteristics influence residents’ emotional responses is investigated by comparing various IGSs with distinct characteristics. Key factors such as aspect ratio, size, vegetation layout, and maintenance significantly influence emotional valence, while vegetation type notably affects emotional arousal. This research underscores the importance of IGSs in cold regions for fostering “urban green space equity”. It provides theoretical guidance for designing these spaces, focusing on subjective perceptions and objective measurements for enhancing emotional well-being in cold urban environments. The methods and results of this study can provide a workable reference for future research and for urban planners tasked with designing green spaces.

Amid the burgeoning lunar economy, habitat establishment is vital for exploration. The investigation into lunar habitat morphology requires systematic organization. To systematically and comprehensively delve into lunar habitats morphological design, this study analyzes spatial elements and relationships through the profiling of lunar habitats. It comprehensively analyzes spatial elements and relationships, laying the groundwork for a dedicated performance evaluation system. It provides theoretical and technical references for lunar habitat forms in the early design phase. First, it summarizes four basic types of lunar habitat profiles. Second, it selects 23 factors influencing lunar habitat profile design, using the Delphi method to filter six major ones. Third, various simulation experiments assess each type’s performance under factors. Fourth, the TOPSIS method analyzes comprehensive performance. This study has developed a comprehensive performance evaluation system and an integrated experimental methodology for assessing the architectural profile morphology of lunar habitat structures. Employing the evaluation system, a comprehensive experimental analysis was conducted on four basic types in the current phase. This analysis yielded two design suggestions for profile elements and three optimization directions for profile design. The discussion offers insights for future evaluations, considering mission innovation and technological advancements.

In the midst of today’s energy crisis, carbon emissions from ice rinks in cold regions present a significant environmental challenge. The shape of an ice rink’s roof significantly influences these emissions. This study developed a methodology to quantify the carbon emissions of ice rinks and explained how their roof shapes impact emissions during the operational phase. Roof shapes were divided into the following three categories: flat, curved, and combined torsion shell. Carbon emission modeling was established and calibrated using the Ladybug + Honeybee platform, followed by regression analyses on the slope and curvature of each roof type. The findings indicate a robust correlation between the carbon emissions of an ice rink and the slope and curvature of its roof. Roof shape influences approximately 2% of carbon emissions during the operational phase of an ice rink. Among the various roof shapes, the curved dome roof demonstrates the most effective overall carbon savings, at a rate of 0.93% compared to the flat roof. Selecting an appropriate roof shape has significant carbon-saving potential for ice rinks. The findings of this study may serve as a valuable reference for the formulation of energy-saving design standards in cold regions.

Research has confirmed the positive impact of social interaction behaviors, including improved mental health, creativity, and stress reduction. Notably, a relationship exists between the spatial characteristics of university campuses and social interaction behaviors. The theories of supportive environment and ecological psychology were used to investigate the quantitative relationship between spatial features of informal spaces and social interactions at a university in a cold region to determine supportive features. Deep learning-based computer vision methods were employed to collect and analyze crowd behavior data, and multiple regression analysis was used to determine the relationship between the features and social interactions. The results indicate that functional features significantly influence social interactions, whereas physical features have a relatively minor impact on social interaction frequency. This finding confirms the efficacy of informal space design at cold-region universities in promoting social interaction behaviors. The deep learning method enables quantitative analysis of the effect of environmental features on social behaviors on cold-region university campuses, providing valuable design suggestions and insights for campuses in other regions and research related to social interaction behaviors.