Search Results (22,013)

The emergence of advanced mobility systems, including Demand Responsive Transport (DRT), shared mobility, and Mobility as a Service (MaaS), has required a reassessment of the evaluation indicators for public transportation systems. Existing studies often address only limited aspects and lack a comprehensive, structured classification, while the unique impacts of advanced systems remain insufficiently captured. Moreover, little attention has been given to which indicators are suitable for simulation despite their growing role in transport planning. To fill these gaps, this study develops a structured classification of quantitative evaluation indicators from the existing literature, serving as a foundation for assessing advanced mobility systems. It highlights system-specific characteristics, identifies relevant indicators, and examines their correspondence with conventional ones. Furthermore, it explores the applicability of these indicators in simulation environments, offering guidance for selecting representative indicators in simulation setup, operational monitoring, and impact assessment. Finally, it highlights the potential of quantitative indicators to approximate qualitative ones, suggesting directions for future research in simulation-based evaluation. By integrating environmental, economic, and societal dimensions, this study contributes to a sustainability-oriented framework for evaluating advanced mobility systems, providing insights for both academic research and practical mobility planning. Full article

The conceptual design phase in architecture establishes the foundation for subsequent design decisions and influences up to 80% of a building’s lifecycle environmental impact. While Building Information Modeling (BIM) demonstrates transformative potential for sustainable design, its application during conceptual design remains constrained by perceived technical complexity and limited support for abstract thinking. This research examines how BIM tools can facilitate conceptual design through diagrammatic reasoning, thereby bridging technical capabilities with creative exploration. A mixed-methods approach was employed to develop and validate a Diagrammatic BIM (D-BIM) framework. It integrates diagrammatic reasoning, parametric modeling, and performance evaluation within BIM environments. The framework defines three core relationships—dissection, articulation, and actualization—which enable transitions from abstract concepts to detailed architectural forms in Revit’s modeling environments. Using Richard Meier’s architectural language as a structured test case, a 14-week quasi-experimental study with 19 third-year architecture students assessed the framework’s effectiveness through pre- and post-surveys, observations, and artifact analysis. Statistical analysis revealed significant improvements (p < 0.05) with moderate to large effect sizes across all measures, including systematic design thinking, diagram utilization, and academic self-efficacy. Students demonstrated enhanced design iteration, abstraction-to-realization transitions, and performance-informed decision-making through quantitative and qualitative assessments during early design stages. However, the study’s limitations include a small, single-institution sample, the absence of a control group, a focus on a single architectural language, and the exploratory integration of environmental analysis tools. Findings indicate that the framework repositions BIM as a cognitive design environment that supports creative ideation while integrating structured design logic and performance analysis. The study advances Education for Sustainable Development (ESD) by embedding critical, systems-based, and problem-solving competencies, demonstrating BIM’s role in sustainability-focused early design. This research provides preliminary evidence that conceptual design and BIM are compatible when supported with diagrammatic reasoning, offering a foundation for integrating competency-based digital pedagogy that bridges creative and technical dimensions of architectural design. Full article

Global urbanization has led to massive generation of high-water-content waste slurry, creating serious environmental challenges. Conventional treatment methods are costly and unsustainable, while cement-based foamed lightweight soils typically exhibit low strength and limited CO₂ sequestration. To address this issue, this study proposes a novel stabilization pathway by integrating a MgO–mineral powder–carbide slag composite binder with CO₂ foaming–carbonation. The approach enables simultaneous slurry lightweighting, strength enhancement, and CO₂ fixation. A series of laboratory tests were conducted to evaluate flowability, density, compressive strength, and deformation characteristics of the carbonated lightweight stabilized slurry. Microstructural analyses, including SEM and XRD, were used to reveal the formation of carbonate phases and pore structures. The results showed that MgO content strongly promoted carbonation, leading to denser microstructures and higher strength, while mineral powder and carbide slag optimized workability and pore stability. Orthogonal testing indicated that a mix with 25% mineral powder, 12.5% MgO, and 7.5% carbide slag achieved the best performance, with unconfined compressive strength up to 0.48 MPa after carbonation. Compared with conventional cement- or GGBS-based foamed lightweight soils, the proposed system exhibits superior strength development, improved pore stability, and enhanced CO₂ sequestration potential. These findings demonstrate the feasibility of recycling high-water-content waste slurry into value-added construction materials while contributing to carbon reduction targets. This study not only provides a sustainable solution for waste slurry management but also offers new insights into the integration of CO₂ mineralization into geotechnical engineering practice. Full article

Fujian Tulou, a UNESCO World Heritage Site, is highly vulnerable to environmental and anthropogenic stresses, with its earthen walls prone to surface cracking that threatens both structural stability and cultural value. Traditional manual inspection is inefficient, subjective, and may disturb fragile surfaces, highlighting the need for non-destructive and automated solutions. This study proposes a dual-path framework that integrates lightweight crack detection with independent physical simulation. On the detection side, an improved YOLOv12 model is developed to achieve lightweight and accurate recognition of multiple crack types under complex wall textures. On the simulation side, a two-layer RFPA^3D model was employed to parameterize loading conditions and material thickness, reproducing the four-stage crack evolution process, and aligning well with field observations. Quantitative validation across paired samples demonstrates improved consistency in morphology, geometry, and topology compared with baseline models. Overall, the framework offers an effective and interpretable solution for standardized crack documentation and mechanistic interpretation, providing practical benefits for the preventive conservation and sustainable management of Fujian Tulou. Full article

Wood is a renewable, carbon-sequestering, and structurally versatile material that has supported human civilization for millennia and continues to play a central role in advancing sustainable development. Although its low density, high specific strength, and esthetic appeal make it highly attractive, its intrinsic flammability presents significant challenges for safety-critical uses. This review offers a comprehensive analysis that uniquely integrates three key domains, covering advanced processing technologies, flame-retardant functionalization strategies, and multifunctional applications. Clear connections are drawn between processing approaches such as delignification, densification, and nanocellulose extraction and their substantial influence on improving flame-retardant performance. The review systematically explores how these engineered wood substrates enable more effective fire-resistant systems, including eco-friendly impregnation methods, surface engineering techniques, and bio-based hybrid systems. It further illustrates how combining processing and functionalization strategies allows for multifunctional applications in architecture, transportation, electronics, and energy devices where safety, durability, and sustainability are essential. Future research directions are identified with a focus on creating scalable, cost-effective, and environmentally compatible wood-based materials, positioning engineered wood as a next-generation high-performance material that successfully balances structural functionality, fire safety, and multifunctionality. Full article

In increasingly turbulent environments, organizations must go beyond generic robustness and develop Requisite Resilience, the capacity to align internal variety with environmental variety to sustain core functions during crises. This study situates Requisite Resilience within organizational theory and strategic management, assessing how major theories of the firm contribute to its development. The analysis groups these perspectives into foundational/diagnostic theories, which clarify environmental, structural and institutional constraints and correspond to passive resilience frameworks, and enabling/capability-building theories, which emphasize managerial agency, resource orchestration and adaptive learning, corresponding to active resilience frameworks. Findings indicate that while foundational perspectives offer essential diagnostics, they are insufficient on their own to foster Requisite Resilience. A composite configuration provides the strongest fit: co-evolutionary views offer an integrative backbone, dynamic capabilities and organizational learning enhance sensing, seizing and acting, and resource dependence theory informs the design of permeable boundaries. Full article

This study addresses the growing need for intelligent monitoring in aquaponic systems by developing a predictive system based on artificial intelligence and environmental sensing. The goal is to improve fish welfare through the early detection of adverse water conditions. The system integrates low-cost digital sensors to continuously measure key physicochemical variables—pH, dissolved oxygen, and temperature—using these as inputs for real-time classification of fish health status. Four supervised machine learning models were evaluated: linear discriminant analysis (LDA), support vector machines (SVMs), neural networks (NNs), and random forest (RF). A dataset of 1823 instances was collected over eight months from a red tilapia aquaponic setup. The random forest model yielded the highest classification accuracy (99%), followed by NN (98%) and SVM (97%). LDA achieved 82% accuracy. Performance was validated using 5-fold cross-validation and label permutation tests to confirm model robustness. These results demonstrate that sensor-based predictive models can reliably detect early signs of fish stress or mortality, supporting the implementation of intelligent environmental monitoring and automation strategies in sustainable aquaponic production. Full article

The exponential increase in environmental pollutants due to industrialization, urbanization, and agricultural intensification has underscored the urgent need for sensitive, selective, and real-time monitoring technologies. Among emerging analytical tools, organic fluorescent sensors have demonstrated exceptional potential for detecting a wide range of pollutants in water, air, and soil, with a limit of detection (LOD) in the pM–µM range. This review critically examines recent advances in organic fluorescent sensors, focusing on their photophysical properties, molecular structures, sensing mechanisms, and environmental applications. Key categories of organic sensors, including small molecules, polymeric materials, and nanoparticle-based systems, are discussed, highlighting their advantages, such as biocompatibility, tunability, and cost-effectiveness. Comparative insights into inorganic fluorescent sensors, including quantum dots, are also provided, emphasizing their superior photostability and wide operating range (in some cases from pg/mL up to mg/mL) but limited biodegradability and higher toxicity. The integration of nanomaterials and microfluidic systems is presented as a promising route for developing portable, on-site sensing platforms. Finally, the review outlines current challenges and future perspectives, suggesting that fluorescent sensors, particularly organic ones, represent a crucial strategy toward sustainable environmental monitoring and pollutant management. Full article

All over the world, the problem of ensuring the safety of pedestrians, who are the most vulnerable road users, is becoming more acute due to urbanization and the growth of micromobility. In 2013, according to WHO data, more than 270 thousand pedestrians were dying each year worldwide (accounting for 22% of all traffic accidents). Currently, experts report that around 1.3 million people die every year globally from road crashes. The roads in developing countries are particularly hazardous, according to experts, because the increase in the number of vehicles far exceeds the development of road infrastructure and safety systems. Since the risk of hitting a pedestrian depends on many factors that can have different natures, and the severity of the consequences can be determined by a set of other factors, the risk of an accident can only be reduced by influencing all these factors in a comprehensive manner. The novelty of our approach is to create an intelligent system that will gradually accumulate all the best practices into a single complex aimed at reducing the risk of an accident with pedestrians and the severity of the consequences if an accident does occur. The distinction lies in offering an integrated system where each module addresses a particular task, so by mitigating risks at every stage, one achieves a synergistic outcome. From the analysis of existing and applied developments, it is known that many specialists mainly solve a narrowly focused problem aimed at ensuring the one subsystems sustainability in the “vehicle-infrastructure-driver-pedestrian” system. Some of these ideas are given as practical examples. The relevance of the designated problem increases with the emergence of autonomous vehicles and smart cities, the sustainability of which depends on the sustainable interaction between all road users. As experience shows, only the implementation of comprehensive solutions allows us to solve strategic problems, including improving road safety. Here, by complex solutions we mean solutions that combine technical issues, as well as environmental, social, and managerial aspects. To account for different kinds of effects, indicator systems are developed and composite indices are computed to choose the most rational solution. The novelty of our approach consists in combining within a unified DSS algorithms for assessing the efficiency of the proposed solution with respect to technological soundness, environmental sustainability, economic viability, social acceptability, as well as administrative rationality and computation of interrelated effects resulting from implementing any given project. In our opinion, the proposed system will lead to a synergistic effect due to the integrated application of various developments, which will ensure increased sustainability and safety of the transport system of smart cities. Our paper proposes a conceptual approach to addressing pedestrian safety, and the examples provided illustrate how the same model or algorithm can lead to positive changes from different perspectives. Full article

University campuses in rapidly urbanizing regions face increasing pressure to balance infrastructure development with environmental sustainability, yet their carbon storage potential remains largely unexplored in sub-Saharan Africa. This study assessed land use changes, carbon storage dynamics, and economic valuation across three Ghanaian universities, University of Ghana (UG), Kwame Nkrumah University of Science and Technology (KNUST), and University of Cape Coast (UCC), from 2017 to 2023, and evaluated five future scenarios using the InVEST carbon model. Land use analysis employed ESRI 10 m annual land cover data, while carbon storage was estimated using regionally appropriate carbon pool values, and economic valuation applied Ghana’s social cost of carbon ($0.970/tCO₂). Historical analysis revealed substantial carbon losses: UG declined by 17.1% (19,695 Mg C), KNUST by 29.5% (20,063 Mg C), and UCC by 7.9% (3292 Mg C), due to tree cover conversion to built areas. Scenario modeling demonstrated that infrastructure-focused development would cause additional losses of 4211–6891 Mg C, while extensive tree expansion could increase storage by 1686–5227 Mg C. Economic analysis showed tree expansion generating positive net present values ($1612–$5070), while infrastructure development imposed costs (−$4028 to −$6684). These findings provide quantitative evidence for sustainable campus planning prioritizing carbon conservation in tropical institutional landscapes. Full article

As cattle are criticized for contributing to environmental problems by emitting pollutants, it is expected that environmental regulations on livestock will be strengthened. This will lead to an increase in the costs and benefits associated with these regulations. This paper develops a model that clearly shows the effects of environmental regulations on the production costs for cattle-breeding farmers and the changes in social welfare, as well as environmental benefits. The benefits associated with the regulation are measured by evaluating reductions in both greenhouse gas (GHG) and ammonia emissions. These benefits are then compared to the reduction in social welfare. According to the analysis, the reduction in social welfare, in terms of consumer and producer surplus, outweighs the environmental benefits. These results suggest that, in designing environmental regulations, policy measures are needed to alleviate producers’ economic burdens and minimize reductions in social welfare through byproduct utilization and technical support. Furthermore, this study contributes to laying the institutional foundation for the sustainable development of the livestock industry and the reduction in management costs associated with manure treatment. Full article

The green macroalgae Ulva Linnaeus, 1753, also known as sea lettuce, is one of the most ecologically and economically significant algal genera. Its representatives occur in marine, brackish, and freshwater environments worldwide and show high adaptability, rapid growth, and marked biochemical diversity. These traits support their ecological roles in nutrient cycling, primary productivity, and habitat provision, and they also explain their growing relevance to the blue bioeconomy. This review summarizes current knowledge of Ulva biodiversity, taxonomy, and physiology, and evaluates applications in food, feed, bioremediation, biofuel, pharmaceuticals, and biomaterials. Particular attention is given to molecular approaches that resolve taxonomic difficulties and to biochemical profiles that determine nutritional value and industrial potential. This review also considers risks and limitations. Ulva species can act as hyperaccumulators of heavy metals, microplastics, and organic pollutants, which creates safety concerns for food and feed uses and highlights the necessity of strict monitoring and quality control. Technical and economic barriers restrict large-scale use in energy and material production. By presenting both opportunities and constraints, this review stresses the dual role of Ulva as a promising bioresource and a potential ecological risk. Future research must integrate molecular genetics, physiology, and applied studies to support sustainable utilization and ensure safe contributions of Ulva to biodiversity assessment, environmental management, and bioeconomic development. Full article

To explore the coupling between agricultural farming models and surface water environmental in central China’s irrigation districts, this study focuses on the Four Lakes Basin within Jianghan Plain, a key grain-producing and ecological protection area. Integrating remote sensing images, statistical yearbooks, and on-site monitoring data, the study analyzed the phased characteristics of the basin’s agricultural pattern transformation, the changes in non-point source nitrogen and phosphorus loads, and the responses of water quality in main canals and Honghu Lake to agricultural adjustments during the period 2010~2023. The results showed that the basin underwent a significant transformation in agricultural patterns from 2016 to 2023: the area of rice-crayfish increased by 14%, while the areas of dryland crops and freshwater aquaculture decreased by 11% and 4%, respectively. Correspondingly, the non-point source nitrogen and phosphorus loads in the Four Lakes Basin decreased by 11~13%, and the nitrogen and phosphorus concentrations in main canals decreased slightly by approximately 2 mg/L and 0.04 mg/L, respectively; however, the water quality of Honghu Lake continued to deteriorate, with nitrogen and phosphorus concentrations increasing by approximately 0.46 mg/L and 0.06 mg/L, respectively. This indicated that the adjustment of agricultural farming models was beneficial to improving the water quality of main canals, but it did not bring about a substantial improvement in the sustainable development of Honghu Lake. This may be related to various factors that undermine the sustainability of the lake’s aquatic ecological environment, such as climate change, natural disasters, internal nutrient release from sediments, and the decline in water environment carrying capacity. Therefore, to advance sustainability in this basin and similar irrigation districts, future efforts should continue optimizing agricultural models to reduce nitrogen/phosphorus inputs, while further mitigating internal nutrient release and climate disaster risks, restoring aquatic vegetation, and enhancing water environment carrying capacity. Full article

Sustainable development goals were laid out by the United Nations in 2015 as a means to address the profound issues present in the world by 2030. Nations have been encouraged to make amendments to their policies and frameworks by adding the SDGs to promote sustainability. In this era, where nations look for sustainable solutions, 3D printing has emerged as a revolutionary technology that has the potential to aid in accomplishing the SDGs. Advancements and developments in technology have boosted manufacturing efficiency and provide the pathway to achieving the set targets of multiple SDGs. Thus, this article looked into the potential contribution of 3D printing towards Sustainable Development Goal 13—Climate Action. A comprehensive literature review was performed using the PRISMA framework to understand the latest advancements in 3D printing and how 3D printing has been used to achieve the SDG targets. Moreover, an exploration of the impact of 3D printing on SDG 13 was performed. The potential impact topics explored include the reduction in GHG emissions using sustainable AM, decentralized manufacturing, resilient infrastructure to climatic hazards, the circular economy and product lifecycle extension. Qualitative analysis was conducted by looking into the effects of the SDGs on both the environmental and socio-technical aspects. Challenges in the implementation of AM within different economic sectors and its potential solutions are discussed in this article. The literature review and qualitative analysis pointed to a strong correlation between SDG 13 and 3D printing, paving the way for a sustainable future. Full article

The hospitality sector is undergoing a rapid digital change due to smart technology and artificial intelligence. This presents both possibilities and problems for the development of sustainable innovation. Yet, little is known about how leaders’ technological competencies affect employees’ capacity to engage in environmentally responsible innovation. This study addresses this gap by examining how leaders’ competencies in smart technology, artificial intelligence, robotics, and algorithms (STARA) shape employees’ green innovative behavior in hotels. Anchored in person–job fit theory and cognitive appraisal theory, we propose that when employees perceive a strong alignment between their skills and the technological demands introduced by STARA, they are more likely to appraise such technologies as opportunities (challenge appraisals) rather than threats (hindrance appraisals). These appraisals, in turn, mediate the link between leadership and green innovation. Convenience sampling was used to gather data from staff members at five-star, ecologically certified hotels in Sharm El-Sheikh, Egypt. According to structural equation modeling using SmartPLS, employees’ green innovation behaviors are improved by leaders’ STARA abilities. Crucially, staff members who viewed STARA technologies as challenges (i.e., chances for learning and development) converted leadership skills into more robust green innovation results. Conversely, employees who perceived these technologies as obstacles, such as burdens or threats, diminished this beneficial effect and decreased their desire to participate in green innovation. These findings highlight that the way employees cognitively evaluate technological change determines whether leadership efforts foster or obstruct sustainable innovation in hotels. Full article