This comprehensive review critically examines current methodologies and optimization strategies for designing indoor thermal environments in educational buildings amid the challenges of global climate change and energy demands. The paper evaluates existing research methods, such as numerical simulations, data-driven models, and field measurements, revealing significant limitations in addressing the complex and dynamic nature of educational environments. It highlights the overemphasis on energy efficiency while neglecting user comfort and individual differences, such as students’ physiological and psychological needs. The review underscores the necessity of integrating human-centered design strategies, climate adaptability, and interdisciplinary approaches to improve building performance and enhance student well-being. Future research should focus on developing multimodal data fusion frameworks, applying AI-based optimization, and incorporating emerging technologies like BIM and IoT for dynamic management. By advocating for more adaptable and sustainable thermal environment strategies, this study provides a foundation for advancing educational building design in response to climate change and energy crises.

Securing thermal comfort while minimizing energy consumption in educational buildings is vital for achieving sustainable development goals. Drawing on the Environmental, Social, and Governance (ESG) framework, this systematic review synthesizes findings from 84 peer-reviewed studies published over the past decade, with a focus on how thermal comfort and energy use are assessed in educational contexts. The review identifies three primary research themes: climate resilience, multidimensional human-centric design, and energy decarbonization. However, it also reveals that existing studies have placed disproportionate emphasis on the environmental dimension, with insufficient exploration of issues related to social equity and governance structures. To address this gap, this study introduces an ESG-driven theoretical framework encompassing seven dimensions: thermal environment stability, multimodal thermal comfort assessment integration, sustainable energy use, heterogeneous thermal demand equality, passive–active design synergy, participatory thermal data governance, and educational thermal well-being inclusivity. By fostering interdisciplinary convergence and emphasizing inclusive stakeholder engagement, the proposed framework provides a resilient and adaptive foundation for enhancing indoor environmental quality in educational buildings while advancing equitable climate and energy strategies.

Urban walking spaces are shaped by both relatively stable visual–spatial features and dynamic contextual exposures, yet the independent emotional effects of these exposures remain unclear. This study develops a causal screening framework to examine the adjusted effects of high pedestrian flow and high background wind speed on pedestrian emotion. Using 9552 participant-location observations collected along a 1.0 km walking route in Changsha, China, pedestrian emotion was expressed as a baseline-referenced emotional response (BRER). Propensity-score trimming established treatment-specific overlap before applying partially linear regression, double machine learning, and causal forest estimation. High flow showed a stable negative adjusted effect with broader empirical support and some heterogeneity, whereas high wind also showed a negative estimate but was treated as exploratory because of limited independent exposure support. Overall, dynamic social and meteorological exposures may retain adjusted effects on pedestrian emotion beyond the observed visual–spatial environment, with stronger evidence for pedestrian flow. Urban walking-space design should therefore strengthen its capacity to buffer transient social and meteorological pressures.