Search Results (117)

The accelerating global demand for renewable heating, cooling and electricity, driven by climate change and rising living standards, presents both a challenge and an opportunity for sustainable energy transitions. This paper introduces the Initial-Aid Cashback (IAC) model, an innovative business model designed to finance renewable energy solutions, with a focus on space cooling, by leveraging citizen participation and collaborative financing mechanisms. The model incentivizes private investors through discounted energy prices, while system operators benefit from reduced upfront capital requirements and minimised financial risk. Through two case studies, an office building in Romania (small-scale case) and the application of the REGEN-BY-2 technology in a mixed housing–office area (large-scale case), the paper demonstrates the model’s potential to accelerate the adoption of renewable cooling technologies, enhance profitability for operators, and provide attractive returns for investors. The findings highlight the model’s adaptability to diverse stakeholder needs, its scalability, and its role in fostering the clean energy transition (CET). However, challenges such as the need for a minimum number of investors, legal complexities, and trust-building among stakeholders are identified as critical barriers to implementation. The paper concludes that the IAC model offers a promising pathway to integrate citizens and small investors into the CET, while emphasising the importance of supportive policies, clear governance structures, and practical testing to ensure its success. Full article

Urban Digital Twins (UDTs) represent a recent application of Digital Twins (DTs), with the objective of replicating cities and providing a framework for urban planning. The utilization of UDTs provides a structured approach for the modeling and analysis of urban environments, incorporating a range of geospatial data presented in both two-dimensional (2D) and three-dimensional (3D) formats. This article details the process of processing, modeling, and integrating urban geospatial data into a Digital Twin. Two integrations for end-user platforms were demonstrated using a Geographic Information System (GIS) and an Unreal Engine (UE5) game platform. GIS-based dashboard systems provide professionals with the tools necessary to monitor, analyze, and create scenarios, thereby promoting collaboration between authorities and citizens. Game engines have the potential to play a pivotal role in the development of future UDTs by facilitating the creation of immersive experiences that aid users in comprehending their environment and promoting citizen engagement. Full article

Modern police work requires a high degree of versatility, shifting between sedentary tasks and intense physical demands. While bicycle patrols are recognized as a tool for enhancing community policing, few empirical studies have examined the specific nature and frequency of the tasks performed by bicycle patrol officers. This study aims to compare the professional tasks of bicycle and car patrol officers in the city of Saguenay, Québec, over a three-year period. A retrospective analysis of 539 computer-aided dispatch (PCAD) entries was conducted for eight male officers (six on bicycles, two in police cars) during the summer months of 2021 to 2023. We analyzed task frequency, duration, priority, and risk level using descriptive statistics. Results showed that while both patrol types performed similar core tasks, such as citizen assistance, enforcement of municipal regulations, and responses to suspicious individuals, bicycle patrols were associated with significantly longer total PCAD-recorded intervention times (49 ± 47 min vs. 33 ± 29 min). Moreover, the distribution of call types suggests a slightly higher proportion of interventions occurring in public spaces or involving direct citizen contact, although this does not constitute a measure of increased proximity. No significant differences were observed in terms of priority or risk. Because the PCAD system does not systematically record on-scene time, the longer durations observed for bicycle patrols cannot be interpreted as qualitative advantages. Instead, the study reveals operational similarities alongside noteworthy differences between patrol types. As one of the first Canadian CAD-based analyses of bicycle patrol tasks, this research underscores the need for future studies capable of isolating on-scene time and examining the qualitative dimensions of police–citizen interactions. Full article

Urban public space is a crucial constituent of livable city construction. A pleasant and comfortable public space is not simply spacious, bright, and accessible but also subjectively preferred by citizens who use it. Efforts to understand how citizens experience and perceive therein thus matters and would significantly aid urban design and well-being improvement. This research constructs a perception lexicon for 129 sites of public street space, a significant type of public space, in Shanghai and identifies how citizens comment on these sites through sentiment analysis based on social platform texts. A Chinese natural language processing (NLP) tool is applied to sort out the extent of citizens’ feelings on the urban street environment through a 0–1 scoring system. Six types of built environment elements and five categories of urban public spaces are identified. Pleasantly perceived sites primarily locate in the urban center and sporadically distribute in the outskirts and are normally “high-density” and “multi-function” in nature. Among the five categories of urban public spaces, sites that are commercially dynamic with culture, arts, and historical elements or that have gourmet food and good walkability generally receive the higher sentiment scores, but scores of ancient town commercial streets (many are antique streets), once popular and contributing much to tourism economy, are not satisfactory. The NLP-based text analysis also quantifies the intensity of emotional perceptions toward the six types of built environment elements and their associations with the general perception. This study not only offers insights for designers and policy makers in public space optimization but also showcases a scalable, data-driven approach for integrating public emotional and experiential dimensions into urban livability assessments. Full article

Background: Mobility limitation is a pivotal but under-documented dimension of disability in Saudi Arabia. Leveraging the 2017 National Disability Survey, this cross-sectional study provides a population-wide profile of mobility-related physical difficulty. Objectives: Five research aims were pursued: (1) estimate national prevalence and severity by sex; (2) map regional differentials; (3) examine educational and marital correlates; (4) characterize cause, duration, and familial context among those with multiple limitations; and (5) describe patterns of assistive-aid and social-service use. Methods: Publicly available aggregate data covering 20,408,362 Saudi citizens were cleaned and analyzed across 14 mobility indicators and three baseline files. Prevalence ratios and χ² tests assessed associations. Results: Overall, 1,445,723 Saudis (7.1%) reported at least one functional difficulty; 833,136 (4.1%) had mobility difficulty, of whom 305,867 (36.7%) had mobility-only impairment. Severity was chiefly mild (35% of cases), with moderate (16%) and severe (7%) forms forming a descending pyramid. Prevalence varied more than threefold across the thirteen regions, peaking in Aseer (9.4%) and bottoming in Najran (2.9%). Mobility difficulty clustered among adults with no schooling (36.1%) and widowed status (18.5%), with sharper female disadvantage in both domains (p < 0.001). Among those with additional limitations, chronic disease dominated etiology (56.3%), and 90.1% had lived with disability for ≥25 years; women were overrepresented in the longest-duration band. Aid utilization was led by crutches (47.7%), personal assistance (25.3%), and wheelchairs (22.6%), while 83.8% accessed Ministry rehabilitation services, yet fewer than 4% used home or daycare support. Conclusions: These findings highlight sizeable, regionally concentrated, and gender-patterned mobility burdens, underscoring the need for education-sensitive prevention, chronic-care management, investment in advanced assistive technology, and distributed community services to achieve Vision 2030 inclusion goals. Full article

Cantabrian mixed forests, located in areas of Spain, Portugal, and France, serve as an essential biogeographic transition region, noted for its extraordinary plant diversity and ecological intricacy. To aid conservation and research initiatives, a uniform checklist of vascular plants was created, incorporating information from citizen science platforms, scientific databases, herbarium records, and local floras. The outcome is a carefully selected collection of more than 8000 taxa, with over 76% recognized as native, highlighting the area’s importance as a reservoir of biodiversity and a climate refuge. Taxonomic discrepancies were resolved via expert verification and adherence to international naming standards, establishing a dependable basis for ecological research. The checklist demonstrates notable variations in organisms, ecological approaches, and evolutionary lineages, influenced by geographical diversity, climate variations, and past land use patterns. Importantly, the study emphasizes the drawbacks of unchecked biodiversity data and shows the benefits of expert-driven synthesis for addressing gaps and biases in species documentation. The floristic information presented here can act as a basis for transboundary conservation planning, ongoing biodiversity tracking, and the development of adaptive management approaches in response to climate change and ecological decline. This initiative represents an important move towards safeguarding the distinct natural heritage of this distinctive biogeographic region. Full article

This study examines the constrained social acceptance of small-scale geothermal energy in a rural sub-Saharan region, a critically understudied area, characterised by high energy poverty, heavy dependence on biomass, and suitable for geothermal energy exploration. Small-scale geothermal energy may offer an additional option for decentralised power supply through mini grids. The study investigates public awareness and knowledge level of geothermal energy technologies among the residents of Eka Awoke, Ikwo, Ebonyi State, Nigeria, to assess the potential of the deliberative process to enhance the social acceptance of geothermal energy technologies and the development of an improved participatory framework to aid the discussion. Citizen jury and survey methods, combining qualitative and quantitative research techniques, were employed. This study presents the first in-depth analysis of the social acceptance of small-scale geothermal energy for electricity supply in a rural African context. Pre-deliberative assessments revealed that 36% of the jurors had limited knowledge and expressed environmental concerns. The post-deliberative assessment revealed that over 80% of jurors reported improved understanding and views. The study demonstrates that citizen jury, when combined with surveyed results can serve as a powerful and scalable tool for advancing social acceptance of geothermal energy. These findings provide a solid foundation for policymakers, stakeholders, and energy providers to design more effective communication engagement strategies for sustainable energy transition in the community. Full article

The United States national identity is changing as the non-religious population is growing and fewer Americans follow traditional Christian faiths. When Alexis De Tocqueville visited the United States, he found that the national government gained legitimacy and support from the popular national religion. This faith was nominally Christian but lacked any meaningful theological content. The national creed was a simple monotheism that was supported through the public’s integration of a Cartesian methodology. This national religion was critical in providing the foundation for American economic growth and identity. Today, fewer Americans identify as Christians than at any point in its history, and more citizens have no religious preference or creed. The dominant religious culture is changing, and to understand the United States future, it is important to identify the political preferences of the non-religious population. This paper looks at the most recent Cooperative Election Survey and assesses the non-religious population’s political participation and its aggregate support for U.S. military aid to Ukraine. The data show that the non-religious population is less politically active and more opposed to miliary aid to Kyiv. United States is becoming more secular. The division between the traditional religious and the growing secular populations is generating a cultural conflict—one that has a fundamental consequence for the American national identity. Full article

Web accessibility is essential for e-government in the Philippines to ensure that all citizens, including those with disabilities, can access important information and services. This study evaluates government web accessibility using the Web Content Accessibility Guidelines 2.0 from the World Wide Web Consortium and web presence based on the Government Website Template Design guidelines. A combination of automated testing tools and visual inspections was used for the assessment. Results showed significant discrepancies between web presence and web accessibility. Web presence compliance ranged from 28% to 82.67%, averaging 53.43%. Web accessibility scored higher, with compliance rates ranging from 62.32% to 97.1% and an average of 82.5%. This indicates that while many government agencies have focused on accessibility, there is a need to improve their digital services and visibility. A well-structured and user-friendly website is vital. However, without expanded online services, mobile accessibility, and transactional features, the full potential of digital governance remains untapped. Future studies are directed to aid government agencies with adopting accessible design principles, conducting regular audits, collaborating with disability advocacy groups, and integrating assistive technologies to foster a more inclusive and efficient digital government ecosystem. Full article

Corruption in public procurement remains a challenge to good governance, especially in developing nations. Blockchain technology has been espoused as a new paradigm for achieving sustainable public procurement practices for effective service delivery and, by extension, promoting sustainable development. Given the potential of blockchain technology, its implementation has been slow in developing countries. Additionally, there is an inadequate decision support framework to prioritize corruption-prone stages of the public procurement cycle for strategic blockchain integration at the most critical corruption-prone stages of the public procurement cycle given the scarce resources available in developing countries. Therefore, we employed a matured theory that is the principal-agent theory to identify key agency problems related to public procurement in developing countries. An interview with 25 experts and a thorough review of Ghana’s Auditor General produced seven public procurement cycle stages. Further, a survey was designed for experts and stakeholders to prioritize the identified procurement stages under the agency problems through the Analytic Hierarchy Process (AHP). Our results revealed that tender evaluation was the most critical stage susceptible to corruption, followed by contract management and procurement planning in the public procurement stages. Additionally, for the relative importance of the criteria, information asymmetry was ranked first, followed by moral hazard, and then adverse selection. This study offers a targeted framework for blockchain deployment in public procurement from an African country perspective. The outcome of this study provides insights for policymakers and procurement practitioners to know the most critical stages of public procurement stages and leverage blockchain technology given the scarcity of resources in developing countries to aid sustainable public procurement. The proposed blockchain framework can enhance service delivery, citizens’ trust, and international donor confidence in partnership and funding for public procurement projects in developing countries. Full article

Municipal solid waste management (MSWM) is an advantageous subject for implementing circular economy (CE) strategies. In this context, the waste generation and waste collection steps of MSWM in the third largest Greek city (Patras), in western Greece, were evaluated according to the proposed CE indicators. Public opinion and knowledge on CE in MSWM were also evaluated in a small sample of citizens from the Municipality of Patras (207 individuals) through a questionnaire survey. Results showed that (a) the CE performance indicators objectively assessed circularity in MSWM; (b) Patras fared better than Greece and EU in some indicators [waste generation (kg per capita × year), food waste generation (kg per capita × year)] and worse in others [food waste composting (% w/w), WEEE recycling (kg per capita × year)]; (c) citizens have not adopted CE practices in their waste management; and (d) there is a clear reluctance to change practices in older individuals. Based on these results, some recommendations for improvement were made. These results may aid in delineating existing conditions in MSWM in large eastern Mediterranean cities and contribute to the transition toward a reduction in waste disposal and an increase in material reuse. Full article

Satellite data have emerged as a widely used tool for global research. In particular, satellite data aid in overcoming long-term observational challenges caused by seasonal effects, facilitating comprehensive monitoring of large regions and simplifying infrastructure maintenance. However, in Korea, the application of satellite SAR (Synthetic Aperture Radar) data within the construction sector remains relatively limited. This study used satellite SAR data to analyze the effects of infrastructure (underground roads and subway systems) currently under construction in Korea on the surrounding ground surface, in order to identify risk zones. This study explored methods for continuously monitoring extensive areas over long distances and selecting potential risk zones. The results indicated substantial ground displacements at specific locations and seasonal changes. Furthermore, past and current satellite SAR data were overlapped to facilitate a time-series analysis. The results confirmed that satellite SAR can improve the monitoring of construction projects in Korea and provide valuable information that can contribute to enhancing maintenance efforts, including near-future ground displacement data. The results are expected to help citizens maintain a safe and sustainable life in urban areas. Full article

Traffic crashes have become one of the key public health issues, triggering significant apprehension among citizens and urban authorities. However, prior studies have often been limited by their inability to fully capture the dynamic and complex nature of spatiotemporal instability in urban traffic crashes, typically focusing on static or purely spatial effects. Addressing this gap, our study employs a novel methodological framework that integrates an Integrated Nested Laplace Approximation (INLA)-based Stochastic Partial Differential Equation (SPDE) model with spatially adaptive graph structures, which enables the effective handling of vast and intricate geospatial data while accounting for spatiotemporal instability. This approach represents a significant advancement over conventional models, which often fail to account for the fluid interplay between time-varying weather conditions, geographical attributes, and crash severity. We applied this methodology to analyze traffic crashes across three major U.S. cities—New York, Los Angeles, and Houston—using comprehensive crash data from 2016 to 2019. Our findings reveal city-specific disparities in the factors influencing severe traffic crashes, which are defined as incidents resulting in at least one person sustaining serious injury or death. Despite some universal trends, such as the risk-enhancing effect of cold weather and pedestrian crossings, we find marked differences across cities in relation to factors like temperature, precipitation, and the presence of certain traffic facilities. Additionally, the adjustment observed in the spatiotemporal standard deviations, with values such as 0.85 for New York and 0.471 for Los Angeles, underscores the varying levels of annual temporal instability across cities, indicating that the fluctuation in crash severity factors over time differs markedly among cities. These results underscore the limitations of traditional modeling approaches, demonstrating the superiority of our spatiotemporal method in capturing the heterogeneity of urban traffic crashes. This work has important policy implications, suggesting a need for tailored, location-specific strategies to improve traffic safety, thereby aiding authorities in better resource allocation and strategic planning. Full article

(1) Background: Public transport has a vital role to play in creating sustainable, accessible societies. Accessible and inclusive, door-to-door public transport systems with low barriers to use benefit everyone, increasing the mobility of citizens and improving independence. As the industry strives towards multi-modal and Mobility as a Service (MaaS) concepts, there is a need to delve deep into the needs and perceptions of transport user’s door-to-door journeys to find ways to improve. Accordingly, in order to increase the sustainability of MaaS, improving accessibility and understanding service user perceptions are of utmost importance. However, there is a scarcity of research within national transport services to determine unmet user needs to increase the accessibility and autonomy of door-to-door journeys. This research aims to investigate if it is possible to improve the door-to-door journey experience for public transport travellers, increasing the accessibility and the perception of autonomy via technology, and by doing so, providing a more sustainable alternative to road transport. It focuses on understanding service users of Ireland’s National Rail service, Irish Rail, to create key improvements in interactive systems. (2) Methods: The study applies a user-centred mixed-methods methodology using surveys (N = 316) and co-design workshops (four workshops N = 15). The research collected deep insights into the mindsets and needs of service users, showing the potential to improve this door-to-the-door customer journey. Key improvements for interactive systems were outlined. Experience maps were designed, leading to a Conceptual Design for a travel assistant to aid the service user throughout the door-to-door journey. (3) Results: Travellers’ autonomy and the sense of freedom they experience can be improved, mainly if their needs across the complete door-to-door customer journey are supported. Highlighted areas for action include information, accessibility, personal security, ticketing, comfort, facilities, and anxiety. (4) Conclusions: This research reiterates the need for national transport and MaaS providers to prioritise service users’ perspectives when developing sustainable services. Co-designing is recommended as a means of achieving this. Full article

Machine learning approaches for pattern recognition are increasingly popular. However, the underlying algorithms are often not open source, may require substantial data for model training, and are not geared toward specific tasks. We used open-source software to build a green toad breeding call detection algorithm that will aid in field data analysis. We provide instructions on how to reproduce our approach for other animal sounds and research questions. Our approach using 34 green toad call sequences and 166 audio files without green toad sounds had an accuracy of 0.99 when split into training (70%) and testing (30%) datasets. The final algorithm was applied to amphibian sounds newly collected by citizen scientists. Our function used three categories: “Green toad(s) detected”, “No green toad(s) detected”, and “Double check”. Ninety percent of files containing green toad calls were classified as “Green toad(s) detected”, and the remaining 10% as “Double check”. Eighty-nine percent of files not containing green toad calls were classified as “No green toad(s) detected”, and the remaining 11% as “Double check”. Hence, none of the files were classified in the wrong category. We conclude that it is feasible for researchers to build their own efficient pattern recognition algorithm. Full article