Search Results (7,761)

Urban areas are increasingly affected by geological and climate-driven processes that influence their safety, functionality, and long-term resilience. Conventional sustainability indicators mainly focus on anthropogenic impacts on the environment, while the role of subsurface conditions and physical processes shaping urban vulnerability remains underrepresented. To address this gap, the Urban Geo-climate Footprint (UGF) introduced an inverse perspective, assessing how geological and climatic factors exert pressure on urban systems. The methodology is based on the classification of geological effects into five drivers: Geology, Deep Geological Processes, Surface Processes, Exogenous and Climatic Processes, and Subsurface Anthropogenic Pressure. These drivers, within the proposed framework, are articulated into 22 parameters evaluated using public datasets and expert judgment. These parameters are combined into a synthetic, standardised, reproducible and comparable index, the UGF Score Index (UGF-SI), ranging from 0 to >500 which enables direct comparison across cities and contexts. The application to 21 Italian cities highlights distinct spatial patterns, dominant drivers, and groups of cities facing similar geo-climatic challenges. The UGF framework constitutes a significant advancement in urban geoscience, supporting urban planning, risk awareness, and climate adaptation strategies by enhancing the understanding of subsurface-related pressures and promoting informed decision making. Full article

Historic residential buildings in Lingnan are affected by hot–humid and disaster-prone weather conditions, including high temperature, high humidity, intense solar radiation, monsoon winds, and typhoon-related climate stress, which challenge indoor thermal comfort, daylighting, natural ventilation, and adaptive reuse. Taking Jingzu Jiashu, a historic Chaoshan residence associated with overseas remittance culture, as a case study, this study develops a simulation workflow for climate-adaptive green retrofit. Digital documentation, architectural survey, material investigation, and climate data were integrated to establish a baseline model. PMV, DA300, and ACH/ACR were used to evaluate thermal comfort, daylighting, and natural ventilation. The baseline results show summer overheating, insufficient daylighting in deep rooms, and inadequate ventilation in representative rooms. Comfortable hours accounted for only 7.29–7.78%, thermally uncomfortable hours reached 42.84–51.53%, and the maximum PMV reached 4.65 in the rear hall and 3.54–3.65 in representative rooms. The effective daylight areas of the front and rear rooms were approximately 40% and 31%, while baseline ACH values ranged from 1.06 to 1.89 h⁻¹. An integrated retrofit strategy was proposed, including functional reorganization, envelope optimization, opening adjustment, ventilation-path organization, and courtyard/transitional-space improvement. After retrofit, comfortable hours increased to 32.00–42.45%, thermally uncomfortable hours decreased to 17.25–21.28%, maximum PMV values decreased to 1.82–1.86, daylight areas increased to 81% and 74%, and ACH values rose to 2.97–4.49 h⁻¹. The results indicate that building performance simulation can provide quantitative support for climate-adaptive green retrofit of historic Chaoshan residences in Lingnan, offering a methodological reference for healthier, lower-carbon, and more resilient reuse of similar historic dwellings. Full article

Climate change is increasingly altering forest ecosystems worldwide, reshaping species phenology, productivity, and resilience. In this study, we evaluate the phenoclimatic responses of European beech (Fagus sylvatica L.) forests across Europe by assessing their phenological responses to climate change across climatic zones and altitudinal gradients using remote-sensing data. We used 24 years of satellite-derived land-surface phenology and climate data to quantify phenological trends at 356 beech-dominant locations from the EUFGIS database, of which 274 remained after land-cover homogeneity and data-quality filtering. To reduce land-cover mixing at the MODIS resolution, we applied a land-cover homogeneity filter based on ESA WorldCover. The analysis was structured across the seven climatic zones in Europe. Phenological responses to climate change were assessed through climate–phenology sensitivity analyses and a composite phenoclimatic departure index integrating climatic trends, phenological shifts, and interannual variability. Phenological sensitivity varied across climatic zones and phenological phases. Temperature-related sensitivity was most evident in spring in several continental zones, whereas precipitation sensitivity was more apparent for growing-season length and autumn timing in some regions. The composite phenoclimatic departure analysis showed that regional profiles were not uniform across the European beech range. Although warming was widespread, precipitation trends, phenological shifts, and interannual variability differed strongly among zones. These findings demonstrate heterogeneous and location-specific phenoclimatic responses across Europe, but the departure index should not be interpreted as a direct measure of ecological vulnerability or risk. Full article

Background and Objectives: Dengue is emerging as a multifaceted public health challenge that extends beyond traditional vector-borne disease frameworks. Climate change, rapid urbanisation, environmental transformation, global mobility, and digital ecosystems are progressively reshaping transmission dynamics, outbreak patterns, and preparedness needs worldwide. This narrative review aimed to examine dengue from an integrated public health perspective, focusing on climate-sensitive transmission, urban health, surveillance and preparedness, digital epidemiology, artificial intelligence (AI), and health communication. Materials and Methods: A structured narrative review was conducted through targeted literature searches in PubMed, Scopus, and Web of Science between April and May 2026. To this end, a series of separate thematic search strategies were developed to explore the principal conceptual domains addressed in the review. The synthesis was organised around five interconnected preparedness domains: climate change and environmental transformation; urbanisation and urban health; surveillance, vaccination, and integrated preparedness; digital health, artificial intelligence, and mathematical modelling; and health communication and community engagement. The retrieved literature was analysed using a thematic narrative synthesis approach. Results: The retrieved evidence indicated the progressive expansion and redefinition of dengue risk across both endemic and historically non-endemic regions. Climate variability, environmental transformation, rapid urbanisation, and increasing human mobility have emerged as interconnected drivers capable of influencing vector ecology, transmission dynamics, outbreak frequency, and healthcare system vulnerability. Urbanisation has been frequently associated with infrastructural inequalities, environmental degradation, inadequate water and waste management, and territorial conditions favourable to vector proliferation. The extant literature has also placed significant emphasis on the growing importance of integrated surveillance systems and early warning approaches combining epidemiological, environmental, climatic, entomological, and mobility-related data. Digital epidemiology, AI-based predictive models, and digital surveillance tools may contribute to strengthening outbreak forecasting and preparedness capacity, although important limitations related to data quality, interoperability, interpretability, and implementation remain. In parallel, misinformation, risk communication challenges, and digital communication ecosystems emerged as relevant factors influencing public perception, preventive behaviours, institutional trust, and adherence to public health interventions. Conclusions: Dengue is a systems-level public health challenge shaped by climate change, urbanisation, environmental disruption, human mobility, health-system preparedness, and digital ecosystems. Conventional vector-control strategies alone are unlikely to adequately address this growing complexity. Strengthening dengue preparedness should therefore be considered a broader indicator of public health resilience and long-term health-system adaptation. Full article

The increasing threat posed by wheat rust diseases caused by Puccinia spp. necessitates the development of resistance strategies that extend beyond conventional race-specific mechanisms. Although recent reviews (2023–2025) have emphasized gene discovery and genomic approaches, comparatively less attention has been given to the potential roles of metabolic regulation and micronutrient homeostasis in host–pathogen interactions. Here, we present a narrative synthesis of current evidence and propose a conceptual framework in which induced mutagenesis (ethyl methanesulfonate, EMS, and γ-irradiation) serves as a tool for investigating interactions among redox regulation, iron (Fe) homeostasis, and disease resistance. A key component of this framework is the proposed interplay between reactive oxygen species (ROS) signaling and Fe partitioning. Vacuolar iron transporters (VITs), ferritins, and associated transport networks regulate intracellular Fe distribution and may influence Fe availability at the host–pathogen interface, potentially affecting fungal development and host defense responses. This concept of “iron-withholding immunity” may operate alongside ROS-mediated defense processes, linking metabolism with immune function. Observations from mutant wheat populations are broadly consistent with the hypothesis that these processes may contribute to durable adult-plant resistance (APR), which is characterized by reduced disease development, coordinated defense responses, and relative stability across environments. In some studies, Fe-enriched mutant lines have been associated with enhanced expression of pathogenesis-related genes and the occurrence of combined APR and seedling-resistance phenotypes, suggesting possible links between micronutrient homeostasis and immunity. Integration of high-throughput phenotyping with genotype × environment × time (G × E × T) frameworks may further improve our understanding of quantitative resistance and disease-associated traits. Overall, this review highlights the potential importance of nutrient homeostasis, redox regulation, and susceptibility modulation as components of future research aimed at developing climate-resilient and nutritionally improved wheat cultivars. Full article

Leaf color in tomato (Solanum lycopersicum L.) is a complex and highly informative trait that reflects pigment metabolism, chloroplast development, genetic regulation, hormonal signaling, and environmental influences. This review synthesizes current knowledge on the biological basis and diversity of tomato leaf coloration, with a particular focus on the roles of chlorophylls, carotenoids, anthocyanins, and flavonoids in generating distinct visual phenotypes. It further discusses the molecular and physiological mechanisms associated with key leaf color types, including dark green, pale green, chlorotic, purple, albino, and variegated leaves, and describes how these phenotypes develop through coordinated regulation of pigment biosynthesis, chloroplast biogenesis, and stress-responsive pathways. The review also summarizes the effects of environmental factors such as light, temperature, water availability, nutrient status, salinity, heavy metals, and biotic stress on leaf pigmentation through changes in photosynthetic efficiency and oxidative balance. In addition, hormonal regulation of leaf color is discussed with emphasis on the roles of abscisic acid (ABA), ethylene (ET), cytokinins (CKs), auxins, jasmonic acids (JA), and salicylic acid (SA) in regulating chlorophyll retention and senescence-associated color transitions. Importantly, leaf coloration functions not only as a morphological trait but also as a sensitive biomarker of plant physiological status, enabling early detection of nutrient deficiencies, abiotic stress, and disease. Recent advances in multi-omics approaches, imaging technologies, and machine learning have significantly improved the understanding of the regulatory networks controlling leaf pigmentation and their relationship with crop performance. However, important gaps remain in integrating molecular mechanisms with whole-plant and field-level responses. Future progress will depend on combining systems biology, high-throughput phenotyping, and predictive modeling to translate leaf color studies into practical applications for improving tomato productivity, stress resilience, and climate adaptation. Full article

Pearl millet (Pennisetum glaucum) is a widely cultivated C4 cereal crop in tropical and subtropical regions, serving as a food and feed source in developing countries across Africa and Asia. Despite its agronomic importance, research efforts aimed at developing improved millet varieties under the current climatic changes remain limited, particularly in Africa, including Egypt. This study aimed to establish an efficient regeneration system for the “Shandaweel-1” Egyptian pearl millet variety using immature inflorescences as explants. Six different callus induction media (CIM) treatments were evaluated for their effects on somatic embryogenesis, callus type, vitrification rate, and regeneration efficiency. Among the tested treatments, Murashige and Skoog (MS) media additionally supplemented with 1.0 mg L⁻¹ of l-proline, 1.0 mg L⁻¹ of l-asparagine, 10 mg L⁻¹ of silver nitrate (AgNO₃), 0.32 mg L⁻¹ of copper sulfate (CuSO₄), 1.0 mg L⁻¹ of 2,4-dichlorophenoxyacetic acid (2,4-D), and 0.5 mg L⁻¹ of 6-benzylaminopurine (BAP) produced a high callogenesis rate (93%) and the highest regeneration efficiency (47.6%). The combination of l-proline and l-asparagine enhanced the callus quality and regeneration potential more effectively than casein hydrolysate alone, whereas AgNO₃ addition did not have any significant impact on the vitrification or callogenesis rates. This study represents the first successful establishment of an in vitro regeneration system for an Egyptian pearl millet variety, providing a valuable platform for future genetic modification aimed at enhancing stress resilience and crop productivity. Full article

The increasing stresses imposed on forests by climatic changes require agile and adaptive management, in which tree breeding plays a crucial role. Assessment of G×E interactions has been highlighted as an explicit source of information for targeted breeding for resilience and productivity via better coupling of the demands of genotypes and locally anticipated climatic changes. Commonly, the genetic effects are evaluated for morphometric traits, which are a cumulative representation of the past conditions. In this study, the variability of increment and its relation to weather fluctuations were addressed as a climate-sensitive functional trait. Parallel Scots pine (Pinus sylvestris) progeny trials representing hemiboreal conditions and a local productivity (edaphic) gradient in Lithuania were studied to evaluate G×E effects on increment, combining tree-ring analysis and quantitative genetics. Scots pine progenies showed low environmental sensitivity of radial increment, which, however, showed complex region-specific relationships with Full article

Due to climate change and urbanization, green roofs are vital for urban climate resilience. However, there is currently no consensus on the photosynthetic carbon uptake capacity of green roof plants in cities. This study investigated and compared nine common green roof plant species in Xiamen, a typical coastal city in southeastern China. Their photosynthetic parameters were measured across all four seasons to evaluate photosynthetic carbon uptake capacity, and the differences among the nine plant species were evaluated. Results show: (1) Significant interspecific differences exist. Ligustrum japonicum (Lj) had the highest seasonal average daily carbon uptake per unit leaf area (8.86 g m⁻² d⁻¹) and per unit area (93.10 g m⁻² d⁻¹), approximately 9 times that of the lowest-performing species per unit leaf area (Pedilanthus tithymaloides) and 11 times that of the lowest-performing species per unit area (Tradescantia spathacea). (2) The variation in carbon uptake capacity among different green roof plant species followed a pattern consistent with that of their net photosynthetic rate and leaf area index. (3) Overall, the carbon uptake capacity of the nine plant species exhibited a trend of trees > shrubs > herbs. In summary, Lj demonstrated the highest photosynthetic carbon uptake capacity among the nine species examined, suggesting its potential as a promising species for enhancing photosynthetic carbon uptake on green roofs in southeastern coastal cities. Full article

Background: Buildings and construction account for a substantial share of global energy use, carbon dioxide emissions, and material extraction, making both operational and embodied carbon central to climate-resilient building policy. Methods: This article is framed as a critical scoping review with a structured narrative synthesis. It synthesizes peer-reviewed studies, standards, and policy reports published mainly from 2020 to June 2026, while retaining older foundational standards where they define life-cycle boundaries or verification methods. The counted revision documents a reproducible screened search in OpenAlex plus targeted website and standards searching, with Google Scholar retained only for citation chasing and sensitivity checking; reporting is aligned to PRISMA-ScR and PRISMA-S principles. Results: The evidence shows that operational carbon reduction remains the most immediately measurable pathway through HVAC optimization, envelope improvement, smart energy management systems, and digital measurement, reporting, and verification. However, embodied carbon management through Environmental Product Declarations, material passports, low-carbon procurement, prefabrication, and circularity is necessary to avoid shifting emissions from operation to construction. Contribution: The review develops a four-layer digital life-cycle carbon governance mechanism linking life-cycle boundary setting, data capture, verification and assurance, and policy-market conversion. Singapore pathway: Singapore’s five-phase pathway is repositioned as an operational carbon MRV entry point that must be expanded to whole-life carbon through embodied carbon datasets, EPD-based procurement, and ASEAN-specific localization. The revised pathway identifies implementation risks, including data governance, additionality, double-counting, auditor capacity, SME access, market liquidity, and cross-country transferability. Conclusions: Digital MRV and carbon-market mechanisms can accelerate building decarbonization only when they are coupled with whole-life carbon boundaries, embodied carbon safeguards, transparent review methods, and context-specific financing. Full article

Background and Objectives: Hospitals increasingly use AI tools that give nurses on-screen alerts and recommendations (AI-supported clinical decision support, AI-DSS). When nurses override these alerts too often, useful guidance can be lost; when they trust them blindly, errors can slip through. We examined which work and wellbeing factors are associated with nurses’ self-reported intention to override AI alerts, rather than observed override behavior. Methods: We surveyed 239 registered nurses (76.6% female; mean age 33.7 years) at a large hospital in Timișoara, Romania, from January to March 2025. Questionnaires measured alert fatigue, moral distress, mental workload, sleep problems, resilience, team psychological safety, and how strongly nurses intended to override AI alerts. Results: Nurses fell into three groups: those who tended to over-trust AI (26.8%), those with balanced trust (41.0%), and those who resisted it (32.2%). The resistant group had the strongest intention to override alerts and the weakest sense of psychological safety. Alert fatigue was the factor most strongly associated with override intention, and this association was partly accounted for by moral distress. The indirect association was weaker among nurses reporting higher team psychological safety. An exploratory model using these factors distinguished nurses with high self-reported override intention with acceptable accuracy. Because all variables were measured at a single time point, findings are associative and hypothesis-generating rather than causal. Conclusions: How nurses respond to AI alerts depends less on the technology than on their workload, ethical strain, and team climate. Cutting unnecessary alerts, easing moral distress, and building psychological safety may help nurses use AI more safely. Full article

The increasing frequency of high-impact, low-probability climate events has highlighted the limitations of conventional reliability criteria, including N-1 planning assumptions, and the need for dynamic resilience architectures in electrical systems. This article analyzes the evolution, trends, and technological challenges associated with microgrid resilience under extreme-weather disruptions. The study adopts a hybrid research design that combines quantitative bibliometric mapping of 283 Scopus-indexed article records for 2016–2025 using CiteSpace version 7 with a structured technical synthesis of the selected literature. The structural analysis identified nine thematic clusters and indicated a transition from service restoration and component-level recovery toward multi-energy energy-management systems, resilient distribution-system planning, and mobile restoration resources. The technical synthesis shows that modern resilience is increasingly associated with hierarchical control architectures: optimization and forecasting methods support tertiary-level energy management, while grid-forming inverters can provide primary-layer voltage references that support islanded operation and black-start sequences under appropriate design, protection, and validation conditions. The article concludes that future research should bridge stochastic planning and real-time physical operation through standardized interoperability frameworks, reproducible dynamic metrics, and experimentally validated control strategies for autonomous critical microgrid operation under extreme-weather conditions. Full article

A central premise of climate adaptation is that better information and smarter decisions can keep escalating hazards within manageable bounds. We test this premise for one of the most information-sensitive decisions in disaster management—ordering a hurricane evacuation—and find that it has limits. Taking Hurricane Irma (2017), the storm behind Florida’s largest evacuation (6.5 million people, 4 million vehicles), as a reference event, we add Coupled Model Intercomparison Project Phase 6 (CMIP6) perturbations to the historical storm and use the Pangu-Weather artificial intelligence (AI) forecasting system to generate 20,000 ensemble members for present-day and future climates (Shared Socioeconomic Pathway (SSP) 2-4.5 and SSP5-8.5; 2050s and 2080s). As the climate warms, storm intensity rises by 15–20% and forecast uncertainty roughly doubles. A reinforcement learning (RL) framework that optimizes evacuation orders under these conditions then exposes a paradox: although RL’s advantage over fixed policies grows from 7% today to 17% under the 2080s SSP5-8.5, absolute evacuation performance still deteriorates by 44% despite optimization. The optimized future climate outcome (objective: 0.239) is in fact worse than that of suboptimal fixed policies today (0.178)—better decisions cannot compensate for a decision environment that has itself degraded. This is direct, scenario-specific evidence that optimization-based adaptation has a ceiling, with consequences for the long-term sustainability of hazard-exposed coastal regions: keeping such communities safe and livable will require coupling evacuation optimization with structural risk reduction, equitable access to decision-support technology, and aggressive greenhouse gas mitigation that holds future risk within adaptable—and therefore sustainable—bounds. The framework supplies quantitative support for sustainable disaster risk reduction and resilient infrastructure planning aligned with global sustainability goals. Full article

In the context of increasing beef import dependence, global feed-market volatility, climate risks, and sustainability-oriented livestock transformation, strengthening the resilience of China’s beef cattle industry is essential for food security, rural livelihoods, and green livestock development. Using panel data from 31 Chinese provinces from 2012 to 2022, this study constructs a four-dimensional resilience evaluation system covering foundational, resistance, recovery, and sustainability capacities, and applies the entropy weight method, kernel density estimation, the Dagum Gini coefficient, spatial autocorrelation analysis, and an obstacle degree model. The results show that the national resilience index of China’s beef cattle industry increased from 0.105 in 2012 to 0.167 in 2022, although the overall level remained relatively low. Sustainability capacity exhibited a shallow U-shaped trajectory, while foundational, resistance, and recovery capacities improved more steadily. The average Dagum Gini coefficient was 0.277, indicating persistent regional imbalance in beef cattle industry resilience. Provincial disparities widened, positive spatial agglomeration weakened, and local spatial heterogeneity became more pronounced. The key constraints included insufficient forage supply, a low level of production scale, weak breeding infrastructure, and lagging innovation capacity, with clear spatial heterogeneity. This study develops a resilience evaluation framework for long-cycle livestock industries and provides empirical evidence and policy implications for the sustainable development of the beef cattle industry in China and other developing livestock systems. Full article

Urban heat island effects increasingly challenge pedestrian mobility by intensifying thermal stress and reducing the attractiveness of walking during hot periods. However, most pedestrian routing systems still prioritize distance or travel time, while environmental conditions such as heat exposure and shade are rarely incorporated into operational route generation. Existing comfort-aware approaches often rely on static maps, simulated microclimatic indicators, or descriptive greenery measures, limiting their direct integration into user-configurable pedestrian navigation. This study develops a thermal comfort-aware pedestrian routing framework that integrates heterogenic data sources including observed land surface temperature, pedestrian-perspective tree-canopy coverage, and network distance into a unified multi-criteria pathfinding model. The workflow proceeds in four steps: first, airborne thermal imagery is processed to derive a high-resolution land surface temperature layer; second, Google Street View images are sampled at street-segment locations and segmented using SegFormer to extract visible tree-canopy coverage; third, both environmental indicators are aggregated to a cleaned pedestrian network; and fourth, normalized distance, temperature, and canopy attributes are combined through a user-adjustable edge-cost formulation and solved using Dijkstra’s algorithm. The framework is implemented as an operational web-based routing tool for the historic center of Clermont-Ferrand, France. The routable graph includes 551 nodes and 796 edges, with 600 segments carrying GSV-derived canopy information and 623 segments carrying airborne-derived LST values. Across the network, we observed LST ranges from 19.5 °C to 39.1 °C, while canopy coverage ranged from 0 to 70.6%. For a representative origin–destination pair, the coolest route reduces average LST by nearly 5 °C and almost triples canopy coverage compared with the shortest path, although at the cost of a 72% longer distance. These results demonstrate that the framework can generate interpretable comfort–efficiency trade-offs and support user-comfort pathfinding as an operational approach for heat-resilient pedestrian navigation. Full article