Search Results (1,272)

Spatiotemporal heterogeneity of land-use multifunction (LUMF) is crucial for the preservation and management of large-scale national cultural parks in alleviating potential human-land conflicts. Using 28 multidimensional indicators across economic, social, and environmental dimensions, this study established an LUMF index system for the Long March National Cultural Park of China (CLMNCP). LUMF values for 77 prefecture-level cities were quantified from 2008 to 2023, and their spatiotemporal heterogeneity was examined using a spatial autocorrelation model. Subsequently, the Optimal Parameters-based GeoDetector (OPGD) model was applied to identify key driving factors. The main findings are as follows: (1) From 2008 to 2023, the total, economic (EF), social (SF), and environmental (EnF) functions in the CLMNCP exhibited a consistent upward trend. (2) Significant spatial heterogeneity characterized the trade-offs and synergies among these functions. The EF-EnF interaction displayed a concave synergistic relationship, while the EF-SF and SF-EnF interactions showed convex, fluctuating patterns during their transitions between trade-off and synergy. (3) The primary drivers varied across function pairs. The EF-SF synergy was predominantly influenced by agricultural production, resource supply, and cultural service factors. The EF-EnF interaction was mainly shaped by natural conditions and environmental improvement factors. In contrast, the SF-EnF interaction was primarily driven by economic development, cultural services, and resource supply. These findings support functional zoning and targeted management of large-scale national cultural park to balance development and conservation while reducing human-land conflicts. Full article

The transition from a linear to a circular, resource-efficient economy is crucial in order to address the growing scarcity of resources, environmental degradation and the rapid increase in electronic waste and end-of-life products. Artificial Intelligence (AI) has emerged as a key enabling technology, capable of enhancing decision making, automation and optimization across Circular Economy (CE) pathways, including reuse, remanufacturing and recycling. This perspective paper presents a comprehensive and critical overview of AI’s role in supporting the transition to a circular, resource-efficient economy, introducing the Digital CE Architecture (DCEA-4) as a novel framework for integrating AI across the circular value chain. Recent advances in machine learning, deep learning and data-driven optimization are analyzed in the context of electronic waste and used battery management. This highlights how AI-based solutions can improve material recovery rates, reduce environmental impact and enhance system-level efficiency. Additionally, we examine major challenges concerning data availability, model generalization, industrial deployment, and explainability, together with relevant industrial case studies. Although AI offers substantial potential for optimizing circular resource systems, its environmental benefits must be balanced against the computational energy demands of large-scale AI models. This perspective discusses the potential rebound effects associated with AI deployment and emphasizes the importance of energy-efficient algorithms and sustainable digital infrastructures. By bringing together current developments and highlighting future opportunities, this paper aims to help researchers, practitioners and policymakers leverage AI to speed up the transition to sustainable, circular and resource-efficient systems. Full article

Accurately assessing dynamic water resource carrying capacity (WRCC) is essential and challenging, particularly in regions like the Gansu sections of the Yellow River Basin (GSYRB), a core water source protection zone in the arid northwest of China, due to its pressing challenge of balancing water resources for socioeconomic needs and ecological security. This study proposes a novel integrated computational assessment framework named SD-VIKOR to address the complexities arising from nonlinear interactions within the “water resources–socioeconomic–ecological environment” (W–S–E) system. The core of this framework is the tight coupling of a system dynamics (SD) simulation model with a VIKOR multi-criteria evaluation module, where indicator weights are objectively–subjectively determined via an Analytic Hierarchy Process (AHP)–entropy weight method. This integrated SD-VIKOR engine enables dynamic, scenario-based WRCC trajectory simulation. To move beyond simulation and enable mechanistic insight, the framework further incorporates a diagnostic suite: a Geodetector module quantifies dominant drivers and their interactions; an obstacle degree model pinpoints key limiting factors; and a coupling coordination degree model evaluates subsystem synergies. Together, they form a closed-loop “dynamic simulation → multi-criteria assessment → driving mechanism analysis and constraint diagnosis → subsystem coordination analysis” workflow. Applied to the GSYRB from 2012 to 2030 under five development scenarios, the framework demonstrated high efficacy. It successfully captured path-dependent WRCC evolution, revealing that the ecological-priority scenario (B2), which shifts system drivers from economic-scale expansion to resource-efficiency and environmental governance, yielded optimal WRCC and the highest system coordination. In contrast, business-as-usual and single-minded economic expansion scenarios underperformed. Six key obstacle factors were quantitatively identified, linking WRCC constraints to natural endowments, economic patterns, and domestic demand. The results reveal pronounced spatial–temporal heterogeneity in WRCC across the GSYRB, with socioeconomic development, water resource use efficiency, and ecological conditions acting as the primary joint drivers of WRCC evolution. Critically, several key indicators are identified as persistent constraints on regional water sustainability. In contrast to conventional static evaluations, the integrated framework captures the complex dynamics and multi-subsystem interactions governing WRCC, offering a more robust diagnostic of resource–environment systems. These insights provide a transferable analytical basis for designing sustainable water management strategies in arid river basins. Full article

The agri-food sector is undergoing a profound transformation driven by the combined pressures of climate change, resource scarcity, policy frameworks, and evolving consumer expectations. In this context, digital and green technologies have emerged as key enablers of more sustainable, transparent, and resilient food systems. This review provides a comprehensive overview of the conceptual foundations, technological drivers, and policy frameworks shaping the digital and green transition of the agri-food sector. Digital technologies—including precision agriculture, sensing and data acquisition systems, artificial intelligence, blockchain, and data platforms—are examined in relation to their role in improving resource-use efficiency, traceability, and decision-making across the food value chain. In parallel, green technologies and sustainable practices in food production, processing, and waste management are discussed, with emphasis on resource optimization, circular economy approaches, and environmental impact reduction. This review further highlights the role of European and global policy frameworks, such as the European Green Deal and the Farm to Fork strategy, in steering technological adoption and aligning innovation with sustainability objectives. By synthesizing technological, environmental, and policy perspectives, this work underscores the importance of integrated digital–green strategies for achieving long-term sustainability, competitiveness, and resilience in agri-food systems. Full article

Resource-based regions (RBRs) are vital to socio-economic development, yet intensive resource exploitation strains water, energy, and food (WEF) security and causes environmental stress. Optimizing collaborative management of the WEF nexus is crucial for their sustainable development. This study developed an integrated model (WEFN) for optimizing the WEF nexus in RBRs by combining multi-objective optimization and the efficacy coefficient method. The WEFN model incorporates internal couplings and external linkages of the WEF nexus into objectives and constraints. Using Daqing, China, as a case study, six policy scenarios were designed. S1 follows the 2030 planning scheme, while S2–S5 prioritize energy-food supply, environmental protection, water conservation, and economic gains, respectively. S6, formulated via the WEFN model, integrates the objectives of S2–S5 into a collaborative management policy. A comprehensive benefit evaluation system was established, yielding an Evaluation Index (EVI) to quantify WEF system benefits and identify the optimal scenario. Results show that collaborative policy S6 best supports coordinated socio-economic and environmental development in Daqing. The findings offer a valuable reference for WEF nexus management in other RBRs. Full article

The beneficial reuse of reclaimed water is a legislative objective of the State of Florida and a critical element in the optimization of water management in areas facing scarcity of freshwater. Aquifer storage and recovery (ASR) of reclaimed allows for the balancing of variations in seasonal and longer-term supply and demand. Destin Water Users, Inc. (DWU), which serves a barrier island community in the Florida panhandle, implemented a groundbreaking ASR system that stores reclaimed water in a shallow sand-and-gravel aquifer. Institutional controls were used to provide additional assurance that public health is protected, and natural contamination attenuation processes are taken advantage of to address arsenic leaching into stored water and disinfection byproducts (trihalomethanes) removal. The DWU ASR system eliminated the need for more expensive and environmentally impactful options for the disposal of excess of reclaimed water and increases the reliability of the reuse system, having the benefit of reserving higher-quality fresh groundwater resources for potable use. Full article

The proposed study investigates the key factors influencing UAV adoption and proposes an integrated educational–operational framework to enhance implementation in agricultural practice. A case study in Sibiu County, Romania, combined survey-based empirical analysis (n = 80), strategic environmental assessment and the deployment of a demonstration aerial crop monitoring system for educational purposes (ACMS-E). We integrated the Technology Acceptance Model (TAM) and Theory of Planned Behavior (TPB) to examine adoption intentions, revealing perceived usefulness (β = 0.355, p = 0.021) and positive attitudes (β = 0.382, p = 0.005) as the strongest predictors, explaining 44.1% of variance. Based on these findings, a modular training curriculum was designed, combining theoretical instruction, flight operation exercises, remote sensing techniques, data analytics and farm-management integration. ACMS-E provides hands-on training and promotes capacity-building, bridging the gap between technological availability and real-world adoption. By linking technological capabilities with structured training, ACMS-E bridges the gap between UAV availability and effective implementation, offering a scalable model for precision agriculture. This framework provides a pathway to accelerate UAV adoption, optimize field-level monitoring and support evidence-based, resource-efficient farm management in emerging and developed agricultural contexts. Full article

Sustainable tourism is essential for preserving natural habitats and represents a vital component of sustainable development. This study addresses a business decision-making problem related to natural resource conservation and habitat protection through waste management and IT applications in the Serbian hotel sector. Tourism in Serbia and the Western Balkans represents a sensitive issue concerning the balance between economic development and environmental protection. Therefore, the multi-criteria optimization methods Analytic Hierarchy Process (AHP) and Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) are applied to address this problem. To achieve this goal, a hierarchical model was developed that considers nine criteria and four alternatives. The alternatives considered are: service user satisfaction, service cost, waste minimization, and service quality. The developed model was analyzed using a hybrid AHP–TOPSIS approach to identify the optimal alternative. The results indicate that environmental waste prevention ranks highest among all considered alternatives and plays a significant role in the development of sustainable tourism in Serbia. Full article

Precision Agriculture (PA) is increasingly applied to nutraceutical cropping systems, where agronomic productivity must be integrated with the stabilization of phytochemical quality and environmental sustainability. This structured narrative review synthesizes scientific evidence (primarily 2010–2025) on the use of Unmanned Aerial Vehicle (UAV)-based multispectral and thermal sensing, LiDAR-derived canopy characterization, Internet of Things (IoT) monitoring, and artificial intelligence (AI)-driven analytics in medicinal, aromatic, and functional crops. The literature indicates that PA enhances high-resolution monitoring of crop–environment interactions, supporting site-specific irrigation, nutrient management, and stress detection. Under validated conditions, these interventions are associated with improved yield stability, resource-use efficiency, and modulation of secondary metabolite accumulation. However, reported outcomes vary substantially across species, agroecological contexts, and experimental scales, and most studies remain plot-scale or pilot-scale, limiting large-scale generalization. Moringa oleifera Lam. is examined as a model species for Mediterranean and semi-arid systems. Evidence suggests that integrated spectral, structural, and environmental monitoring can support optimized irrigation scheduling, canopy uniformity, and phytochemical consistency. Nonetheless, genotype-specific calibration, multi-season validation, standardized metabolomic benchmarking, and cross-regional transferability remain significant research gaps. Overall, PA represents a scientifically promising but still maturing framework for nutraceutical agriculture. Future progress will require rigorous multi-site validation, improved model robustness, standardized sustainability metrics, and comprehensive economic assessments to ensure scalability and long-term impact. Full article

The delivery of energy and water meter data, management and control information on separate networks is expensive and defeats the gains of the Advanced Metering Infrastructure (AMI) Smart Grid (SG). In most cases, energy, gas and water services are offered by the same organizational entity, hence the use of different infrastructure for data, service delivery, control and management is expensive and highly illogical. There is a need for a combined energy and water infrastructure to reap the benefits of the AMI SG. Furthermore, combined metering will result in accurate billing, potential cost savings, and improved resource management. This work therefore develops and investigates a combined energy and water AMI smart metering framework. This is possible through a thorough understanding of the AMI technological standards. The implementation of such a system is not trivial, as it depends on many factors: environmental, geographical, technological, economical, regulatory and the existing legacy infrastructure. Optimal technological implementation choices are developed towards an integrated AMI infrastructure. An experimental test bed is developed for delivering energy and water metering data to the utility. The optimal placement results favor the system of separating energy and water actuators at the home area network of the SG while using an integrated communication system. Such a system is feasible, given the different evolution of electricity and water meters and their placement at the home area network, and enables water metering to benefit from the more advanced electrical metering infrastructure. Full article

This study investigates the typology of the pastoral farming systems in the arid region of southern Tunisia, with a particular focus on the governorate of Tataouine. A field survey was conducted among 111 livestock farmers distributed across different agro-ecological zones. The typology of breeding systems was established using a Factor Analysis of Mixed Data (FAMD), which identified eleven dimensions explaining 69.74% of the total data variance. The first three dimensions accounted for 15.91%, 8.79%, and 7.67% of the variability, respectively, and were defined by herd composition, resource availability, and management strategies, including variables such as the number of goats, sheep, and camels, distance to water sources, infrastructure, reproductive practices, and workforce availability. Hierarchical clustering revealed three distinct systems: System 1, regrouping “Small Urban Farmers”, defined by small-scale operations relying on family labor, localized feed resources, and market-driven production targeting urban consumers; System 2, representing large livestock, composed of professionalized operations with improved infrastructure, hired labor, and transhumance practices to optimize resource use and productivity; and System 3, for herds with camels, characterized by extensive systems utilizing collective rangelands and camels to adapt to arid conditions and ensure ecological resilience. The results emphasize how ecological constraints, infrastructure, and spatial organization shape the diversity of these systems. This typology provides critical insights into the challenges and potential of livestock farming in arid environments and offers a foundation for designing targeted interventions to support the sustainability of pastoral systems under increasing environmental and economic pressures. Full article

Hospitals generating waste daily need to identify efficient, cost-effective, and sustainable alternatives to conventional disposal methods. Therefore, we formulated a mathematical model to evaluate emerging healthcare waste treatment (HCW) methods by developing a multiple-criteria framework. The framework enables an evidence-based evaluation that supports better HCW management-related decisions in resource-limited settings. Results found that ozone is the optimal method for hospitals with a waste profile mostly made up of infectious and pathological wastes. Methods such as promession, for stricter environmental priorities, and superheated steam, for better performance on all evaluation criteria, may be preferred if hospital priorities shift. Full article

In recent years, Nature-Based Solutions (NBS), defined as interventions inspired by ecosystem processes and aimed at generating environmental, social, and economic benefits, have taken on a central role in urban regeneration and climate change adaptation processes. Despite widespread recognition of their advantages, the spread of NBS is still limited by uncertainties related to performance over time, management costs, and governance models. With the intent of overcoming this limitation, this paper proposes a comparative analysis of case studies of green infrastructure in urban areas, with the aim of identifying the main factors that determine their effectiveness and sustainability throughout their entire life cycle. The research, conducted through a critical review of the literature and the application of a SWOT analysis, highlights the technical, economic, and management conditions that influence the performance of NBS in relation to different contexts of application. The outcome of the study is the definition of an interpretative framework to support designers and decision-makers, geared towards the replicability of solutions, the optimization of resources, and the structural integration of NBS into urban and environmental planning and regeneration processes. Full article

The growing demand for sustainable soil management strategies has intensified interest in hydrochar (HC), a waste-derived amendment produced via hydrothermal carbonization (HTC). This review synthesizes recent advances in HC production, characterization, and agri-environmental applications within a waste-to-resource framework. It covers studies conducted mainly over the last decade, encompassing a wide range of feedstocks, including agricultural residues, sewage sludge, animal manures, and food waste. HTC is typically performed at 130–280 °C under autogenous pressure (2–15 MPa), generating HCs with low intrinsic surface area (<50 m²g⁻¹) and oxygen-containing functional groups that govern nutrient dynamics and soil interactions. Reported application rates vary broadly between 10 and 60 t ha⁻¹, with most experiments conducted under greenhouse conditions. Positive effects on soil pH, cation exchange capacity, water retention, and phosphorus availability are frequently observed. However, plant responses vary according to the type of stimulation promoted by HC, as well as its processing conditions, application rates, and the soil characteristics in which it is applied. Advanced molecular-level analyses (e.g., FT-ICR-MS, GC-MS, and ¹³C-NMR) have provided mechanistic insights into carbon stability, nutrient release, and interaction with soil organic matter. Reusing HTC process water offers an additional pathway for nutrient recovery, although concerns about phytotoxic compounds remain. Despite promising short-term results, long-term field evaluations and standardized assessment protocols are still limited. This review integrates structural, functional and agri-environmental perspectives to identify critical knowledge gaps and guide the optimized and context specific use of hydrochar in sustainable agricultural systems. At the same time, it emphasizes its role in advancing carbon sequestration and in operationalizing resource-circular strategies, thereby underscoring its broader practical and strategic relevance. Full article

Due to the significant challenges faced by healthcare systems, medical establishments strive to set the tone by integrating new concepts to bridge this gap. Here, Lean Healthcare (LH) has been inspired by Lean Management (LM). Utilizing LM to optimize industrial processes and reduce waste presented a real opportunity to enhance the quality of medical services. For more improvement, healthcare systems pushed themselves to keep up with progress by implementing Industry 4.0 (I4.0) tools, such as IoT, Big Data analytics, and AI with LH and sustainability practices. The results promised better quality of care. Although this concept offers significant potential for more efficient workflows and optimizing medical processes, studies examining their combined implementation are still scarce. This research fills the gap via a literature review (LR) of peer-reviewed articles published between 2015 and 2025. The review investigates the impact of integrating smart technologies into LH frameworks and highlights how LH contributes to sustainability across multiple dimensions: economic, social, technological and environmental. Key findings show the impact of combining advanced tools with lean principles by reducing waiting times (25%) and length of stay while also improving satisfaction. Sustainability-centered adaptations of LH incorporate social and environmental comparative parameters such as resource consumption, for instance, reducing operational costs by up to 30–40%. Many challenges were faced with this implementation, such as cultural, technical challenges (e.g., complexity of integration with digital systems), and sustainability barriers. However, to overcome these barriers, this paper proposes a holistic implementation that aligns lean processes with organizational change and sustainability goals. Full article