Sustainable architectural education is offered in colleges and universities all over the world. Studies have emphasized the importance of sustainable architectural education in introductory courses of architecture major programs, but methods and strategies for teaching sustainable architecture at lower levels are scarce. This study focuses on the design-to-physical-construction process and creates a teaching framework that incorporates the concept of sustainable development from the perspectives of sustainable economy, environment and society. Based on the teaching method of learning through the design-to-physical-construction process and referring to the grounded theory, a case study on a bamboo construction project was conducted to explore approaches and strategies of sustainable architectural education in introductory courses. Results reveal that five systems, including the system of sustainable development, consist of a framework that illustrated the teaching effects. Based on the framework, we discovered five factors that should be considered in incorporating the concept of sustainable development into architectural design teaching, including the necessity of conducting sustainable architectural education in introductory courses. This study helps explore the potential role sustainability plays in incorporating interdisciplinary knowledge, connecting specialized knowledge across different program levels, and motivating student learning. It also provides a reference for the practice of sustainable architectural education.

Rural arts events (triennials/festivals) are mainly aimed at local and regional revitalization. This exhibition-driven tourism (unlike traditional festivals, conferences, and exhibitions) has existed for more than 20 years in Japan. The curators of exhibition-driven tourism hope that these events can promote the economy and stop population decline as a result of the aging population. Therefore, this paper attempts to evaluate the effects of urban and rural arts event tourism in local and neighborhood areas in Niigata, Japan from the perspective of SDG 8.9. The Echigo-Tsumari Art Triennial and Water and Land Niigata Art Festival were chosen as case studies. Panel data (1997–2019) concerning tourists, income, and population in Niigata were evaluated using multiple empirical methods with descriptive correlation statistics (simple linear regression (SLR) and one-way ANOVA) and spatial analysis (Moran’s I). Through multiple-method analysis, the positive impacts of urban and rural arts event tourism in local and neighborhood areas in relation to Sustainable Development Goal 8.9 were evaluated. The findings presented herein have meaningful implications for tourism academia and the industry in general.

After the severe industrial pollution from World War II, the Setouchi Sea areas and its islands (the Triennale hosting areas) experienced severe economic and population shrinkage. The target of SDG 8.9 is to promote “direct tourism GDP” and “tourism-related jobs” by devising and implementing policies (e.g., some Triennale and Biennale) for sustainable tourism. Triennale-driven tourism is an essential component of sustainable tourism and city revitalization, lasting almost 20 years in Japan. The current paper attempts an empirical analysis into the positive impacts of exhibition-driven sustainable tourism for SDG 8.9 in these rural islands (from pollution to green and low-carbon islands revitalization). The panel data of “pollution load of living environment items” by cities in Japan and “tourists, income, and population” from 14 areas in Kagawa were monitored using multiple methods, such as descriptive and inferential statistics (the one-way ANOVA test and Simple Linear Regression (SLR)). It is a new attempt to devise and implement policies and theories for a sustainable tourism-related industry and its SDGs. Therefore, the present findings offer meaningful implications in academia and industry, not only in Setouchi Sea areas but also for similar areas in and out of Japan.

Model-free reinforcement learning (RL) techniques are currently drawing attention in the control of heating, ventilation, and air-conditioning (HVAC) systems due to their minor pre-conditions and fast online optimization. The simultaneous optimal control of multiple HVAC appliances is a high-dimensional optimization problem, which single-agent RL schemes can barely handle. Hence, it is necessary to investigate how to address high-dimensional control problems with multiple agents. To realize this, different multi-agent reinforcement learning (MARL) mechanisms are available. This study intends to compare and evaluate three MARL mechanisms: Division, Multiplication, and Interaction. For comparison, quantitative simulations are conducted based on a virtual environment established using measured data of a real condenser water system. The system operation simulation results indicate that (1) Multiplication is not effective for high-dimensional RL-based control problems in HVAC systems due to its low learning speed and high training cost; (2) the performance of Division is close to that of the Interaction mechanism during the initial stage, while Division’s neglect of agent mutual inference limits its performance upper bound; (3) compared to the other two, Interaction is more suitable for multi-equipment HVAC control problems given its performance in both short-term (10% annual energy conservation compared to baseline) and long-term scenarios (over 11% energy conservation).

This study evaluates the carbon emission reduction potential of industrialized construction technologies—specifically robotic 3D printing and prefabrication—in lower-star hotels in Hangzhou, China, from 2018 to 2023. A multidimensional ternary spatiotemporal model is developed to quantify the interactions among temporal, spatial, and hotel classification dimensions, enabling a systematic comparison between conventional construction (CC) and prefabricated construction (PC). The results show that prefabricated construction consistently reduces embodied carbon emissions across hotel categories, with the most significant reduction observed in 2-star and 3-star hotels, where carbon emissions can be reduced by approximately 20–35% compared to conventional methods. The findings further indicate that carbon reduction effectiveness varies by hotel classification and spatial distribution, with lower-star hotels benefiting more from standardized modular construction, while high-star hotels exhibit relatively lower reduction efficiency due to structural complexity. Spatiotemporal analysis also reveals heterogeneous decoupling patterns across districts, suggesting that carbon–economic relationships are strongly influenced by regional development conditions and construction intensity. This study advances the integration of carbon accounting and construction technology assessment by providing a quantitative and scalable framework for evaluating embodied carbon reduction in the hospitality sector. The findings offer robust evidence to support targeted low-carbon construction strategies and contribute to carbon–economic decoupling pathways in resource-constrained urban environments, aligning with the scope of carbon balance and management.

Under the influence of China’s rapid urbanization, traditional villages and intangible cultural heritage (ICH), as an organically coupled cultural ecosystem, are faced with severe spatial imbalance. Quantitative analysis and mechanism interpretation of their spatial relationship are crucial for the integrated conservation and collaborative development of cultural heritage. This study takes Zhejiang Province as the research scope, integrates GIS spatial analysis, bivariate spatial autocorrelation, spatial mismatch index, and optimal parameter geographic detector (OPGD) to systematically reveal the spatial distribution characteristics, spatial associations, spatial mismatch patterns, and driving mechanisms of traditional villages and ICH. The results show that: (1) In terms of spatial distribution, traditional villages are highly concentrated in the hilly and mountainous southwest, with a hierarchical pattern featured by “two main cores and two secondary cores”, while ICH is abundant in the flat and coastal northeast and southeast, presenting a multi–center equilibrium pattern. (2) In terms of spatial relationships, there exists a weak but statistically significant negative correlation, which is embodied in typical clusters: “high–low” clusters mainly in the southwest and “low–high” clusters in the northeast and southeast, corresponding to negative spatial mismatch zones dominated by traditional villages and positive spatial mismatch zones dominated by ICH, respectively. (3) As for driving mechanisms, the spatial mismatch pattern is influenced by the tripartite interaction of “natural geographical constraints, socioeconomic drivers, and cultural policy adjustments,” with resident population, GDP, and public budget expenditure as the core driving factors. This study offers scientific recommendations for the conservation and governance of traditional villages and ICH in Zhejiang Province, while providing methodological guidance for cultural heritage preservation in comparable regions.