論文

Cities must improve their quality without an increase, or ideally with a decrease, in the amount of environmental load to become more sustainable. In order to monitor city's progress towards sustainable development goals, a Comprehensive Assessment System for Built Environment Efficiency (CASBEE) tool, named CASBEE-City has been developed. All cities in Japan are assessed from the following two aspects: environmental load (L) on the external environment and quality (Q), which represents the citizens' quality of life inside the city. Built environment efficiency (BEE = Q/L) is then calculated for the comprehensive assessment of each city. A high BEE value indicates that the city has excellent environmental efficiency. The assessment results are visually displayed on the map by using a geographic information system so that citizens, local government officers, and all other stakeholders can easily understand the actual status of their city in comparison with other cities in the country. This assessment and the visualization of the results are expected to support the realization of future sustainable cities.

Sharing successful practices with other stakeholders is important for achieving SDGs. In this study, with a deep-learning natural language processing model, bidirectional encoder representations from transformers (BERT), the authors aimed to build (1) a classifier that enables semantic mapping of practices and issues in the SDGs context, (2) a visualizing method of SDGs nexus based on co-occurrence of goals (3) a matchmaking process between local issues and initiatives that may embody solutions. A data frame was built using documents published by official organizations and multi-labels corresponding to SDGs. A pretrained Japanese BERT model was fine-tuned on a multi-label text classification task, while nested cross-validation was conducted to optimize the hyperparameters and estimate cross-validation accuracy. A system was then developed to visualize the co-occurrence of SDGs and to couple the stakeholders by evaluating embedded vectors of local challenges and solutions. The paper concludes with a discussion of four future perspectives to improve the natural language processing system. This intelligent information system is expected to help stakeholders take action to achieve the sustainable development goals.

Implementation of the Sustainable Development Goals (SDGs) requires localization and multi-stakeholder partnerships, and local governments have the best potential to act as intermediaries to facilitate partnerships. This study examines how local governments have facilitated partnerships for the SDGs, especially partnerships with private sectors. It focuses on how local governments conducted their intermediary roles from the perspective of sustainable transitions and analyzes Japanese cases. The results of our analysis provide the following suggestions for local governments to enhance their intermediary roles to facilitate partnerships for the SDGs. First, the SDGs should be recognized as a driver of sustainable transitions. Second, there needs a balance in terms of the level of the public sector's involvement in partnerships, so that local governments can maximize the benefits of informal networks in relation to SDG localization. Third, new intermediaries can be created by local governments. The findings of this study contribute to the growing body of literature on SDG localization and partnerships by identifying possible roles and suggestions that local governments can adopt as transition intermediaries.

The residential environment clearly affects health. For example, a previous study has established relationships between specific environmental factors and the health status of residents in detached houses. However, studies focused on apartment buildings are still insufficient. Therefore, in this study, a large nationwide questionnaire survey of residents of apartments was conducted. The residential environment was subjectively evaluated using a Japanese Comprehensive Assessment System for Built Environment Efficiency (CASBEE) tool: the CASBEE Health Checklist. The results showed that residents living in apartments who score higher on the checklist tend to have a lower prevalence of various diseases, indicating that residential environment may be an important determinant of health. Furthermore, the odds ratios for residents living in apartment buildings were lower for diabetes mellitus, hypertensive diseases, heart diseases, cerebrovascular diseases, chronic lower respiratory diseases, and inflammatory polyarthropathies compared with residents living in detached houses. These findings support the general link between the residential environment and residents' health and suggest that housing typology is an important factor.

In 2015, the 2030 Agenda for Sustainable Development Goals (SDGs) was adopted by all United Nations Member States. The indoor environment of residences affects the health of occupants regarding SDG 3 (Good Health and Well-being). Meanwhile, a vast amount of energy is used to supply power to houses worldwide, which emit sufficient volumes of CO2 and affect climate change regarding SDG 7 (Affordable and Clean Energy) and SDG 13 (Climate Action). A key step to delivering on these SDGs is improving the thermal insulation of houses and housing equipment performance to reduce energy consumption and protect the health of the occupants by improving the indoor environment. This study presents an evaluation method for quantifying the contribution of improving housing performance toward delivering the SDGs. The proposed approach is primarily based on the results of heat load simulations. Meanwhile, blood pressure is predicted as an indicator of health by using the interior environment obtained by the simulation. A case study was performed, and the results demonstrated the effectiveness of improving the housing performance of newly constructed houses compared to heating and retrofit. The proposed method is versatile and can be adjusted for application to alternative locations, house designs, and lifestyles.

There has been increasing interest in local-level implementation of the United Nations 2030 Agenda for Sustainable Development and its Sustainable Development Goals (SDGs). Despite the emergence of various initiatives undertaken by local governments, studies on the process of mainstreaming the 2030 Agenda within local contexts remain limited. This study is aimed at identifying possible approaches for supporting local governments in successfully mainstreaming the 2030 Agenda and the SDGs. We developed an analytical framework covering key components for local-level mainstreaming of the SDGs based on our review of recent policy guidelines for implementing the SDGs and the policy integration and coherence literature. Subsequently, we applied this framework within case studies of two designated municipalities under the Japanese government’s “SDGs Future Cities” initiative aimed at localizing the SDGs. The analysis demonstrated how local governments could develop and apply key components of the SDGs mainstreaming process. Our findings suggest that the following approaches can facilitate local governments’ efforts to mainstream the SDGs: first, municipalities can foster local ownership to address the challenges they face. Second, existing policy resources can be linked with formal procedures. Third, multi-stakeholder partnerships can be developed. Fourth, vertical communication channels can be established with international and national-level organizations. Overall, the article contributes to a growing literature on SDGs implementation at the local level by identifying key components required for their mainstreaming, introducing perspectives derived from Japanese case studies.

The thermal environment in offices affects the productivity of workers; thus, it is important to adjust the thermal environment appropriately with heating, ventilation, and air conditioning. However, there is an urgent need to reduce the amount of energy used in the building sector for cooling, which has been rising. Mixed-mode ventilation has attracted attention as a means of decreasing air conditioning power consumption and improving the satisfaction of office workers. In the present study, a measurement survey and a questionnaire survey were conducted during springtime to investigate air conditioning power consumption during mixed-mode ventilation and to elucidate the relationship between the use of mixed-mode ventilation and productivity. The power consumption on the mixed-mode ventilation floors was less than that on the mechanical ventilation floors in the measurement period when the average outdoor air temperature was 21 °C, with savings ranging from 3.1% to 70.6%, although it varied widely with the weather conditions. The relationship between the use of mixed-mode ventilation and productivity was analyzed using multilevel analysis (hierarchical linear model), a method that considers the data hierarchy. Mixed-mode ventilation improved the productivity of male participants by about 9.1%, suggesting that mixed-mode ventilation could both decrease air conditioning power consumption and improve productivity during springtime. However, the increase in productivity of female participants was about 0.5%, indicating that there may be differences depending on gender. The present study has practical implications for promoting mixed-mode ventilation as a means to reduce air conditioning power consumption in offices and improve productivity.