Search Results (1,319)

An EU-funded project was implemented to enhance efficiency and reliability in the water supply system of Antalya city in Türkiye to support climate change adaptation by reducing Non-Revenue Water (NRW). Extensive fieldwork and targeted actions of continuous Minimum Night Flow monitoring, Active Leakage Control, pressure management, and replacement of aging meters were applied to identify and reduce NRW. The project demonstrated that the commonly used percentage water loss indicator in Türkiye, the regulatory performance indicator, is biased and that the Infrastructure Leakage Index provides a more accurate performance measure. Training and experience-sharing workshops were conducted for district, provincial, and metropolitan municipalities in addition to an international regional conference, strengthening institutional capacity for sustainable water loss management. The project demonstrated that substantial gains in efficiency, reliability, and climate resilience can be achieved through integrated water loss management, advanced monitoring technologies, and performance-based evaluation frameworks. Full article

Heraclitus’ phrase “everything flows and nothing remains” perfectly captures the modern era, as conditions are changing at high speed and scientific knowledge is growing exponentially. Academic fields that attract significant attention often experience rapid expansion, driven by the growing global pool of researchers, the increased accessibility of scientific publishing platforms, and the overall rise in scientific output. Literature concerning energy security, a topic as old as fire, has become vital to modern economies due to geopolitical upheaval, adapting traditional considerations to new realities, and the extensive body of literature serves as clear evidence of this fact. Thus, there is a clear need for innovative, scalable, and objective methodologies to systematically assess the existing body of knowledge and prioritize areas for further study. This paper proposes implementing a novel machine learning approach leveraging the BERTopic topic modeling algorithm to conduct a comprehensive and efficient exploratory analysis of energy security literature. The analysis is based on a bibliographic corpus extracted from the Scopus database covering the period 1999–2025, and identifies 14 distinct thematic clusters which indicate that energy security research is undergoing structural transformation, marked by strong emphasis on technology-specific renewable energy transitions, geographic concentration on China and Europe, and increasing integration with climate and sustainability frameworks. While contextual embedding improves semantic coherence, topic interpretation still requires expert validation as model performance is sensitive to hyperparameter configuration, potentially affecting topic stability and reproducibility. Full article

Offshore renewable energy is widely recognised as a critical pathway for decarbonising electricity systems, but the integration of floating offshore wind turbines with wave energy converters remains technically challenging. This paper presents a structured literature review of hybrid wave–wind offshore energy platforms, drawing on 114 reviewed sources published between 2000 and 2026. The review classifies hybrid concepts using a three-axis framework based on floating platform type, wave energy converter (WEC) integration approach, and energy-dominance category. It then compares representative configurations, including point absorbers, oscillating water columns, flap-type devices, and heaving torus concepts, with emphasis on hydrodynamic response, energy contribution, structural complexity, mooring implications, validation status, and optimization suitability. The findings show that no single hybrid configuration can be ranked as universally superior because reported performance depends strongly on platform geometry, WEC scale, site wave climate, modelling assumptions, and validation maturity. Point absorber systems offer modularity and lower integration complexity, oscillating water column (OWC)-based systems provide protected power take-off (PTO) integration and moderate hydrodynamic interaction, flap-type systems can provide stronger motion-control potential but impose higher structural and mooring demands, and spar–torus concepts remain geometrically compatible with spar platforms but are generally wind-dominated. The review further shows that optimization method selection should depend on problem class: gradient-based methods are most suitable for local PTO tuning, evolutionary methods for non-convex multi-objective layout problems, surrogate-based methods for high-cost coupled simulations, and data-driven methods for adaptive control. The paper concludes that future progress requires standardized benchmark models, transparent evidence-level reporting, multi-physics co-optimization, techno-economic assessment, and systematic experimental or field validation before definitive concept ranking or commercial-readiness claims can be made. For decision-makers, industry stakeholders, and policymakers, the framework supports early-stage concept screening, identification of technology-specific risk factors, prioritisation of validation and investment pathways, and alignment of hybrid-platform development with site conditions, infrastructure constraints, and policy objectives. Full article

Global food production systems are increasingly challenged by population growth, climate change, water scarcity, and environmental degradation, necessitating the adoption of sustainable, resource-efficient food production strategies. Aquaponic systems integrate recirculating aquaculture with hydroponic crop cultivation, enabling nutrient recycling and improved water-use efficiency. Simultaneously, CRISPR/Cas9 genome-editing technology has emerged as a powerful tool for precise genetic improvement of economically important aquaculture traits. This review critically evaluates current progress in CRISPR/Cas9 applications in aquaculture, with emphasis on Nile tilapia (Oreochromis niloticus). Evidence from peer-reviewed studies indicates that targeted modification of genes associated with growth regulation, disease resistance, nutrient metabolism, feed efficiency, and stress tolerance can significantly enhance fish productivity and physiological resilience. Genes involved in hypoxia adaptation and nitrogen metabolism may further improve environmental performance in intensive recirculating systems by reducing ammonia accumulation and enhancing nutrient utilization. However, most genome-editing studies have been conducted under laboratory or conventional aquaculture conditions, with limited information available regarding the long-term performance, ecological interactions, microbial dynamics, and biosafety of genome-edited fish in aquaponic environments. Technical limitations including off-target effects, mosaicism, delivery efficiency, regulatory uncertainty, and public acceptance continue to constrain large-scale implementation. In the short term, CRISPR/Cas9 applications are likely to focus on practical trait enhancement under controlled aquaculture systems, whereas longer-term research may explore fish lines specifically optimized for nutrient cycling, environmental resilience, and integrated aquaponic sustainability. Overall, CRISPR/Cas9-mediated genome editing represents a promising but still emerging strategy for improving sustainable aquaculture and aquaponic food production systems. Full article

Climate change intensifies hydrological variability and threatens agricultural water security. This review synthesizes literature on agricultural water system resilience under climate change through a structured critical narrative approach informed by PRISMA/SALSA reporting principles. We examine four linked domains: resilience concepts and indicators, assessment methods under uncertainty, climate impact and vulnerability evidence, and adaptation/governance pathways. The synthesis indicates a broad shift from engineering-centered water-supply approaches toward socio-ecological resilience frameworks that combine infrastructure, ecosystem processes, farmer behavior, and institutions. Methodologically, deterministic optimization is increasingly complemented by stochastic, robust, integrated-assessment, remote-sensing, and machine-learning approaches, although data requirements, uncertainty propagation, and interpretability remain important constraints. Evidence suggests that crop water demand and irrigation requirements may increase substantially under high-emission scenarios, with acute risks in arid and semi-arid regions. Effective adaptation is unlikely to rely on single technologies alone; precision irrigation, nature-based solutions, climate services, and infrastructure investments require complementary demand-side rules, water accounting, equity safeguards, and participatory governance to avoid maladaptation such as the irrigation-efficiency rebound effect. We identify priority research needs in transparent review protocols, uncertainty quantification, cross-scale governance, farmer decision-making, digital inclusion, and monitoring systems. The review provides a moderated conceptual framework and policy-oriented research agenda for strengthening agricultural water resilience. Full article

Given the enormous span of potential strategies to address climate change, it is difficult to build consensus on what to prioritize. In 2021, we conducted 63 semi-structured interviews with climate change experts in the U.S. (N = 33) and India (N = 30). Experts indicated how they would address climate change through mitigation, adaptation, carbon dioxide removal (CDR), and solar geoengineering (SG). Our experts studied climate change from a variety of disciplines and were not necessarily subject matter experts in CDR or SG. Most experts stated that while more research is needed on CDR and SG, there is low appeal to deploying them in responding to climate change. Across our entire sample, we find that 44% of experts supported deploying CDR compared to 3% for SG. We also find that 17% of experts opposed the deployment of CDR, while twice as many (35%) opposed deploying SG. While there is far more support for traditional measures like mitigation and adaptation, most experts were hesitant to support technologies like CDR and SG to limit warming to 1.5 °C or 2 °C to prevent dangerous climate impacts, with statements tending toward a precautionary principle. Deep interdisciplinary engagement by climate change experts on CDR and SG is essential to understanding these technologies’ potential roles in addressing climate change and the perceptions of risk of these technologies held by experts who work on other areas of the climate problem. We highlight the potential for follow-up studies on broader expert opinions of CDR and SG, as well as evaluating whether perceptions and opinions are lagging behind fast-changing developments in the field. Full article

Unmanned aerial vehicle (UAV)-based remote sensing combined with artificial intelligence (AI) has emerged as a key enabler of climate-smart agriculture (CSA). However, the extent to which these technologies operationalize CSA’s three pillars, productivity, adaptation, and mitigation, remains unevenly assessed. This study presents a PRISMA-guided systematic review of 59 peer-reviewed studies examining UAV–AI applications in agricultural systems. The synthesis categorizes platform configurations, sensor modalities, analytical architectures, geographic distribution, and data integration strategies, and evaluates their alignment with CSA objectives. Results indicate that productivity-oriented applications, including yield estimation, biomass mapping, and nutrient assessment, are the most mature, while adaptation-focused stress detection is also well established. In contrast, mitigation-oriented applications, such as carbon quantification and greenhouse gas monitoring, remain comparatively underrepresented. The analysis further reveals a growing convergence toward multimodal sensing and cross-scale data integration linking UAV observations with satellite and environmental datasets. However, substantial variability in validation approaches and dataset representativeness limits generalizability and scalability. Advancing UAV–AI contributions to CSA therefore requires methodological standardization, interoperable data governance, and strengthened institutional capacity. Collectively, the findings position UAV–AI systems as emerging components of climate-smart agricultural intelligence infrastructure rather than isolated monitoring tools. Full article

The water, food, and energy nexus has become central to debates on sustainability and climate adaptation, yet students’ capacity to understand these interdependencies remains unclear. This study examined knowledge and attitudes toward the nexus among 397 students enrolled in nine faculties at Bursa Uludağ University in Türkiye. Data were collected through a structured questionnaire covering demographic characteristics, conceptual knowledge, attitudes, behavioural tendencies and perceived barriers. Nexus knowledge was operationalised as a summative index of ten equally weighted items scored as correct (1) or incorrect/uncertain (0). Hierarchical regression was used to identify the determinants of nexus knowledge, and path analysis was used to test the indirect effects of knowledge on behavioural intention through professional confidence. Only 38.8% of respondents correctly identified the nexus as an interconnected resource framework and 60.7% reported no prior coursework on sustainability or climate change. Information exposure and course participation explained substantially more variance in nexus knowledge (ΔR² = 0.192) than demographic (ΔR² = 0.043) and socioeconomic variables (ΔR² = 0.074) combined. Knowledge had a significant indirect effect on behavioural intention through professional confidence (indirect effect = 0.16, 95% CI [0.09, 0.24]; final model R² = 0.398, Adjusted R² = 0.385). Attitudes were generally moderate rather than strongly environmental, and behavioural responses were highly polarised, pointing to a persistent gap between concern and action. Students identified knowledge deficits and technological limitations as the main barriers to nexus management and strongly preferred interdisciplinary coursework as the most effective educational intervention. The findings indicate that formal educational exposure plays a larger role than background characteristics in shaping nexus literacy and that embedding systems thinking into disciplinary curricula may strengthen sustainability competence among future professionals. Full article

Climate change is significantly impacting sustainable agriculture and poses a threat that is likely to motivate farmers to adapt by applying AI technology to reduce risks, costs, expenses, and the impact on greenhouse gas emissions. In other contexts related to climate change, it is important to assess whether perceived climate threats and perceived vulnerability to climate change influence farmers’ intention to use artificial intelligence and whether farmers believe AI is an effective method for addressing climate change, as well as their confidence in its effectiveness. This research examines whether the ability to learn about AI independently affects the intention to use AI, aligning with Protection Motivation Theory. It further evaluates whether perceived ease of use of AI influences perceived usefulness, considering the core factors of perceived ease of use and perceived usefulness based on the Technology Acceptance Model as influencing the intention to use AI. Furthermore, it investigates whether PEOU (Perceived ease of use) and PU (Perceived usefulness) affect attitude (a key factor in the Theory of Planned Behavior) and subjective norm (another core factor in TPB (Theory of Planned Behavior)) influencing farmers’ behavioral adaptation to AI use. Therefore, exploring farmers’ behavioral intention to use AI integrates three theories: PMT (Protection Mo-tivation Theory), TPB, and TAM (Technology Acceptance Model), presenting them as a conceptual model to examine the motivating factors influencing behavioral change. This research surveyed 471 farmers in Thailand using data analyzed from PLS-SEM (Partial Least Squares Structural Equation Mod-eling). The findings revealed that only eight hypotheses (AI self-efficacy, PEOU, PU, ATT (Attitude), and SN (Social Norm)) significantly influenced the intention to use AI, while three hypotheses (PS (Perceived severity), PV (Perceived vulnerability), and RE (Response efficacy)) did not. This will be useful for planning or strategizing AI adoption among farmers, focusing on reducing problems and obstacles from insignificant factors to achieve sustainable agriculture and minimize the impact that may lead to inequality from AI use, or the AI divide, in the future. Full article

This paper examines whether total factor productivity (TFP) in Israeli agriculture has genuinely slowed or declined in recent years, or whether the reported trend is primarily driven by methodological choices, data limitations, and measurement error. We compare two widely used approaches to TFP measurement—those of the Bank of Israel and the U.S. Department of Agriculture (USDA)—which differ in their definitions of output, treatment of inputs, and assumptions regarding factor shares. We reconstruct and refine the underlying datasets, addressing important limitations in the existing measures, including the omission of foreign labor, inconsistencies in agricultural land measurement, and the application of non-representative input shares. Despite data improvements and methodological adjustments, both approaches yield similar qualitative conclusions. Following rapid increase in earlier decades, TFP growth in Israeli agriculture appears to have stagnated or declined since the early 2010s. A decomposition of output growth further indicates that recent production patterns have been driven primarily by greater input intensity per unit of land rather than by technological progress or efficiency gains. As a result, agricultural output has shown little or no net growth over the past decade. We discuss potential explanations for this slowdown, including climate change, the growing reliance on reclaimed and other marginal water sources, and the long-term decline in agricultural research and development (R&D) investment relative to sectoral output. Overall, the findings suggest that the productivity slowdown is real rather than an artifact of measurement and underscore the need for renewed investment in agricultural innovation and climate adaptation to sustain domestic production and strengthen food security. Full article

City Information Modelling (CIM) and Urban Digital Twins (UDT) are pivotal for advancing smart urban planning and city management, yet empirical evidence on their real-world implementation is scarce. Following a sequential mixed-methods design, this study addresses this gap through a global investigation analyzing 33 projects across diverse geographic contexts. Findings reveal that these technologies are predominantly applied in 3D visualization (60.6%) and urban planning (48.5%), with significant underutilization in climate adaptation (9.1%) and AI-driven robotics (3.0%). A pronounced physical–social data divide exists, with infrastructure data prioritized over human-centric inputs. Technology stacks converge on GIS, IoT, and BIM. However, an interoperability paradox persists, as internal integration outpaces cross-organizational connectivity. Governance is predominantly public-sector-led, but multi-actor ecosystems are also involved. The study concludes with actionable recommendations to rebalance implementation portfolios, integrate socio-economic data, and advance both technical and institutional interoperability, thereby harnessing CIM and UDT for transformative urban planning and city management. Full article

Adaptation to climate change is crucial for the resilience of rural communities, especially in semi-arid regions like Chicualacuala district, Mozambique. This study assesses the factors influencing the adoption of climate change adaptation technologies in the semi-arid region of Chicualacuala, Mozambique. Data collection involved direct observation, semi-structured interviews with key informants, and questionnaires administered to 191 households selected by simple random sampling. Descriptive statistics and a logistic regression model were used for analysis. The findings indicate that the agriculture sector is the primary beneficiary of the implemented adaptation technologies, with impacts perceived as predominantly positive. Logistic regression analysis revealed that factors such as cultivated land size, full-time engagement in farming, household income, and membership in producer groups significantly influence the adoption of agricultural technologies. Two key factors driving this uptake are the performance of extension services and whether the household head is employed. This suggests that technology adoption could be further strengthened if government policies expand and diversify the educational content of extension services, with a stronger focus on climate change adaptation practices. Such improvements are particularly important in sectors where perceived climate impacts remain limited, as better information may increase awareness and adoption. Full article

Croatia’s diverse agroecological zones, from Mediterranean coastal areas to continental lowlands, enable the cultivation of a broad portfolio of traditional fruit species that contribute simultaneously to biodiversity conservation, rural livelihoods, and the development of value-added food and beverage products. This review compiles and harmonizes evidence on six economically and culturally relevant crops and product chains—grapevine and wine, apple, pear, quince, sour cherry, mulberry, and plum with the traditional spirit šljivovica—focusing on genetic resources and cultivar diversity, agronomic and environmental performance, bioactive composition and potential health relevance, processing routes and by-product valorization, and the socio-economic roles of geographical indications, gastronomy, and tourism. Across species, the literature highlights recurring sustainability levers: safeguarding indigenous and old cultivars as reservoirs of adaptive traits under climate change; reducing chemical inputs through cultivar choice, organic and low-input systems, cover crops, and resistant genotypes; strengthening circularity by converting pomace and other residues into spirits, vinegars, functional ingredients, feed, compost, or energy carriers; and increasing rural value capture through branding, protected origin schemes, and experiential tourism. At the same time, production systems face shared constraints, including fragmentation of holdings, labour shortages, phytosanitary pressures, and the need to optimize processing technologies to preserve sensory and bioactive quality while meeting safety and regulatory requirements. By integrating crop-specific evidence with cross-cutting sustainability themes, this review outlines a coherent framework for positioning traditional Croatian fruit resources and their derived products within contemporary sustainable food system transitions. Full article

Drought stress is the most pervasive abiotic constraint on global crop productivity, with projected intensification under climate change threatening the yields of staple crops including wheat, rice, maize, and legumes. Conventional breeding approaches have delivered limited gains against drought tolerance, constrained by the polygenic and multifactorial nature of stress adaptation, the complexity of genotype-by-environment interactions, and the inadequacy of field-based phenotyping under variable stress conditions. Omics technologies, including genomics, transcriptomics, proteomics, metabolomics, epigenomics, and phenomics, have substantially advanced the molecular dissection of drought tolerance by enabling high-resolution characterization of stress-responsive genes, regulatory networks, adaptive proteins, and metabolic reprogramming pathways. Specific traits targeted include root system architecture and depth, osmotic adjustment capacity through proline and glycine betaine accumulation, antioxidant defense mechanisms, ABA-mediated stomatal regulation, LEA protein accumulation, epigenetic stress memory, and yield stability under water deficit. This review systematically examines omics-based strategies for drought stress mitigation across major crops, highlighting individual omics contributions, multi-omics integration frameworks, computational tools including machine learning and AI-driven predictive modelling, and translational breeding applications. Case studies in wheat, rice, maize, and legumes illustrate how omics-driven approaches accelerate precision breeding for drought resilience through marker-assisted selection, genomic selection, and CRISPR-based gene editing. Challenges including data integration complexity, high implementation costs, limited cross-species transferability, and the need for field-scale validation of microbiome-based strategies are critically addressed. Future perspectives encompassing single-cell and spatial omics, AI-driven predictive breeding, digital agriculture integration, and international data governance frameworks are discussed. By aligning with climate-smart agriculture principles, multi-omics approaches provide a robust and transformative foundation for developing drought-resilient crop cultivars suitable for water-limited production systems worldwide. Full article

This systematic review examines the global sustainable urban planning strategies used worldwide and whether they are applicable to the United Arab Emirates. This study reviewed 150 peer-reviewed articles and identified 14 of the most significant sustainable urban planning strategies in use today, including green infrastructure, smart city technologies, compact urban development, transit-oriented development, circular economy principles, mitigation of urban heat island effects, renewable energy integration, sustainable drainage systems, biophilic design, fifteen-minute city concepts, mixed-use development, vertical farming, participatory planning, and urban resilience frameworks. The methodologies applied by the authors to identify the sustainable urban planning strategies employed in the research were thematic analysis and the classification of the strategies into five main categories: environmental sustainability, technological innovation, social equity, economic viability, and cross-cutting. Case studies from Singapore, Copenhagen, Melbourne, and Amsterdam, and examples of current sustainable urban planning initiatives underway in Dubai and Abu Dhabi show how the models can be successfully implemented. The results indicate that multi-strategy approaches produce better results than the application of single strategies. Based on the results of the research, green infrastructure, smart city technologies, and the mitigation of urban heat island effects have been identified as strategies whose characteristics are closely aligned with the UAE’s arid climate conditions, while emphasizing that all fourteen strategies contribute to comprehensive sustainability outcomes and that their relative importance depends on local relevance. The researchers also concluded that for sustainable urban planning to be successful in the UAE, it will require the best practices from around the world be adapted to the unique environmental conditions, cultural contexts, and economic structures of each country. The findings of this study will contribute to the growing body of knowledge related to sustainable urbanism and provide practitioners with useful information and practical guidance when implementing sustainable urban planning practices in the UAE and other arid regions. Full article