This research examines the process through which the European Union (EU) constructed legitimacy for the Corporate Sustainability Reporting Directive (CSRD) in the process of transition from the Non-Financial Reporting Directive (NFRD). Employing institutional work theory, the paper discusses the four strategies – advocacy, defining, constructing normative networks, and theorizing – that were used to justify and embed the CSRD. Drawing on EU policy documents from 2019 to 2024, the study illustrates how these strategies generated different forms of legitimacy: cognitive, normative, pragmatic, input, and throughput, and points out three coordination mechanisms – temporal sequencing, legitimacy spillover, and pre-emptive legitimation – that structure legitimation across institutional domains. The findings contribute to institutional work theory by showing how legitimacy is built actively during the design phase of sustainability regulation in complex supranational governance settings.

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This study aims to investigate the primary determinants of household willingness-to-pay (WTP) for improved piped water services in Jakarta, a megacity facing a paradox of high network coverage but low public adoption. Based on social capital theory, this study empirically tested the relative power of two competing explanations, namely conventional economic constraints versus institutional trust. Data were collected from 1,388 households through a survey method and analyzed using a logistic regression model. The results showed that although household income was identified as a significant factor (Odds Ratio = 1.2820), institutional trust in the service provider was the most powerful predictor of WTP (Odds Ratio = 1.5031). This was supported by qualitative evidence showing that public perception distinguishes between an acceptable water product and an unreliable delivery service. In conclusion, the primary barrier to adopting improved piped water services is not a lack of financial capacity, but a profound deficit of public confidence grounded in a history of institutional failure. This reframes the policy problem, demanding a strategic pivot from purely technical solutions towards socio-technical strategies that prioritize building trust through tangible service improvements.

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Digital twins of trees have significant applications in urban landscape re-creation, growth simulation, and biomass assessment. Accurate whorl detection—identifying points where multiple branches originate from the trunk—is crucial for precise 3D tree modeling. However, existing methods face limitations in detection accuracy and predominantly rely on 2D projection approaches that result in information loss. This paper describes a new 3D whorl detection method that directly uses point cloud data through toroidal (doughnut-shaped) sectioning around the trunk. The method was evaluated using the TreeNet3D dataset on two species: small-leaved olive (25 trees) and fir (25 trees). Unlike conventional 2D projection methods, this approach preserves 3D spatial information, enabling detection even in dense foliage. The toroidal sectioning technique can be adapted to various tree species by adjusting radius parameters. This research contributes to advancing whorl detection accuracy and establishes a foundation for applications in tree age estimation, timber value assessment, and high-precision 3D tree modeling.

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The CO2 emissions by Japanese prefecture before fiscal year 1990 for each sector, such as manufacturing, residential households/businesses, and transportation (passenger/freight), were estimated to contribute to the deliberation of medium- to long-term local policies towards Carbon Neutral by 2050, which is a statutory goal in Japan. Referring to previous studies, the modified Weaver method to typify emission characteristics was used based on the estimation results for each prefecture. From fiscal year 1980 to 1990, the trend of the manufacturing sector’s emission composition ratio standing out had continued in 45 prefectures. However, the number of prefectures that showed a type where only the manufacturing sector stood out decreased from 15 in 1980 to 9 in 1990. Throughout the 1980s, similar to the national trend, the number of prefectures where the emission composition ratio of the manufacturing and residential households/businesses sector stood out increased, and by 1990, the number of prefectures where the emission composition ratio of any sector did not stand out became the most common.

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This study investigated the spatial distribution, temporal variations, and relationships between fog occurrence and air pollution across Japan. Fog exhibited clear seasonal and geographical characteristics and was broadly classified into two types: advection fog occurring during the warm season and radiation fog occurring during the cold season. In large cities, the number of fog days, which ranged from approximately 20 to 80 days per year in the 1950s–1960s, decreased to fewer than 10 days per year after 1975. This decline was strongly associated with urban warming of approximately 2–3 °C and reductions in air pollutant concentrations. In Nagoya, a temporary increase in fog days coincided with an increase in SPM concentration, suggesting that aerosols may play an important role in fog formation. In contrast, although a long-term decrease in the number of fog days was observed in small and medium-sized cities, no significant change was detected in the frequency of radiation fog, indicating that the effects of urban warming and surface drying were more limited than in large cities. However, in Toyooka, where more than 100 fog days occurred annually, a clear relationship was observed between the decrease in fog days and reductions in SPM concentration. These results suggest that the long-term decrease in fog occurrence in Japan is driven by multiple factors that vary depending on city size and geographic conditions, with urban warming and reductions in air pollution playing major contributing roles.

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This study examined the spatial characteristics of the urban and suburban thermal environments in Nagano City, an inland basin city in central Japan, using multisite fixed-point meteorological observations conducted during the summer of 2015. The results revealed that daytime air temperature differences among land-use types were relatively modest, whereas WBGT exhibited pronounced spatial contrasts. Low-rise residential areas consistently recorded higher WBGT values owing to greater solar exposure and larger sky view factors, whereas shading from dense buildings in the urban core reduced the radiation load and lowered daytime WBGT. During nighttime, WBGT hotspots were concentrated in the urban core, reflecting enhanced heat storage and suppressed radiative cooling, whereas contrasts in suburban areas largely disappeared. Component analysis indicated that globe temperature was the dominant driver of WBGT variations, particularly during the daytime, and statistical analysis demonstrated a significant correlation between WBGT and the sky view factor. These findings highlight the critical role of radiative environments in shaping urban thermal stress. Thus, urban design strategies that reduce sky exposure and enhance shading can effectively mitigate heat-related health risks in cities with large diurnal temperature variations.

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The rapid growth of small domestic appliances containing lithium-ion batteries (LiBs) has heightened environmental and safety risks, especially when they are improperly disposed of. To address this issue, we developed an artificial intelligence (AI) system based on a vision–language model (VLM) to identify items that may contain LiBs, with a particular emphasis on the point of disposal. Because the YOLO11x model showed a drawback in terms of recall, despite its strong performance in other metrics, the VLM-based approach was adopted for its adaptability and integration into practical applications. A web application was then implemented to make the AI system easily accessible. Users register securely, upload or capture images, and receive detection results with a detailed output of the process. Each detection generates a QR code, enabling future integration with collection box systems and potential incentive schemes. The interface was designed to be intuitive, guide users in a step-by-step manner, and prevent operational errors. This combination of robust detection and user-friendly design may provide a pathway toward improved LiB sorting, potentially contributing to safer waste management.

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