Search Results (7,827)

Wind is an important renewable energy source, and even minor variations in wind speed will significantly impact wind power generation. The objective of this study was to systematically assess the impacts of climate change on wind energy resources in the South China Sea (SCS) under future climate projections. To achieve this, we employed a multi-model ensemble approach based on Coupled Model Intercomparison Project Phase 6 (CMIP6) data under three Shared Socioeconomic Pathways (SSP1-2.6, SSP2-4.5, and SSP5-8.5). The results demonstrated that, in comparison with scatterometer wind data, the CMIP6 historical results (1995–2014) showed good performance in capturing the spatiotemporal distribution of wind power density (WPD) in the SCS. There were regional discrepancies in the central SCS due to the complex monsoon-driven wind dynamics. Future projections revealed an overall increase in annual mean wind power density (WPD) across the entire SCS by the mid-21st century (2046–2065) and late 21st century (2080–2099). The seasonal analyses indicated significant WPD increases in summer, especially in the northern SCS and the region adjacent to the Kalimantan strait. The increase in summer (>40 × 10⁻⁴ m/s/year under SSP5-8.5) is about triple that in winter. In the late 21st century, an increase in WPD exceeding 10% can be generally anticipated under the SSP2-4.5 and SSP5-8.5 scenarios in all seasons. The extreme wind in the northern and central SCS will further increase by 5% under the three scenarios, which will add an extra extreme load to wind turbines and related marine facilities. These assessments are essential for wind farm planning and long-term energy production evaluations in the SCS. Based on the findings in this study, specific areas of concern can be targeted to conduct localized downscaling analyses and risk assessments. Full article

To address the flood risks driven by climate change and urbanization, this study proposes the DRIRA model (Driving Force, Resistance, Influence, Recoverability, Adaptability). Distinct from BRIC (Baseline Resilience Indicators for Communities) and PEOPLES (Population, Environmental/Ecosystem, Organized Governmental Services, Physical Infrastructure, Lifestyle, Economic Development, Social–Cultural Capital), the model emphasizes dynamic interactions across the entire disaster lifecycle, introduces the “Influence” dimension, and integrates SNA (Social Network Analysis) with a modified gravity model to reveal cascading effects and resilience linkages among cities. Based on an empirical study of 30 cities in the Central Plains Urban Agglomeration, and using a combination of entropy weighting, a modified spatial gravity model, and social network analysis, the study finds that: (1) Urban flood resilience increased by 35.5% from 2012 to 2021, but spatial polarization intensified, with Zhengzhou emerging as the dominant core and peripheral cities falling behind; (2) Economic development, infrastructure investment, and intersectoral governance coordination are the primary factors driving resilience differentiation; (3) Intercity resilience connectivity has strengthened, yet administrative fragmentation continues to undermine collaborative effectiveness. In response, three strategic pathways are proposed: coordinated development of sponge and resilient infrastructure, activation of flood insurance market mechanisms, and intelligent cross-regional dispatch of emergency resources. These strategies offer a scientifically grounded framework for balancing physical flood defenses with institutional resilience in high-risk urban regions. Full article

The fragile karst ecosystem in Southwest China faces severe water scarcity. Since 2000, large-scale ecological restoration programs (e.g., the “Grain for Green” Program) have substantially increased vegetation coverage. Concurrently, climate change has manifested as a distinct warming trend and heightened drought risk in recent decades. Therefore, understanding the synergistic and competing effects of climate change and vegetation restoration on regional evapotranspiration (ET) is critical for projecting water budgets and ensuring the sustainability of ecosystems and water resources within this vital ecological barrier region. This study employs a dual-scenario PT-JPL model (simulating natural vegetation dynamics versus constant coverage) integrated with Sen + MK trend analysis to quantify the spatiotemporal patterns of ET and its components—canopy transpiration (ETc), interception evaporation (ETi), and soil evaporation (ETs)—in Southwest China’s karst region (2000–2018). Furthermore, multiple regression analysis and SEM were utilized to investigate the driving mechanisms of vegetation and climatic factors (temperature, precipitation, radiation, and relative humidity) on changes in ET and its components. The key results demonstrate the following: (1) Vegetation restoration exerted a net positive effect on total ET (+0.44 mm/a) through enhanced ETi (+0.22 mm/a) and ETs (+0.37 mm/a), despite reducing ETc (−0.08 mm/a), revealing trade-offs in water allocation. (2) Radiation dominated ET variability (66.45% of the area exhibiting >50% contribution), while temperature exhibited the most extensive spatial dominance (44.02% of the region), and relative humidity exhibited drought-mediated dual effects (promoting ETi while suppressing ETc). (3) Precipitation exhibited minimal direct influence. Vegetation restoration and climate change collectively drive ET dynamics, with ETc declines indicating potential water stress. These findings elucidate the synergistic regulation of vegetation restoration and climate change on karst ecohydrology, providing critical insights for water resource management in fragile ecosystems globally. Full article

Dam collapse is a catastrophic event involving an artificial reservoir usually filled with water for hydropower or irrigation purposes. Several cases of dam collapses have overwhelmed entire valleys, reconfiguring their geomorphology, redesigning their landscape, and causing several thousand casualties. These episodes led to more careful regulations and the activation of more effective monitoring and mitigation strategies. A fundamental tool in defining appropriate procedures for alert and risk scenarios is the Dam Emergency Plan (PED), an operational document that establishes the actions and procedures required to manage potential hazards (e.g., geo-hydrological and seismic risk). The aim of this study is to describe a reference methodology for identifying geo-hydrological criticalities based on historical and geomorphological data, applied to civil protection activities. A further objective is to provide a structured inventory of Italian reservoirs, assigning each a potential risk index based on an analytical approach considering several factors (age and construction methodology of the dam, morphological and environmental settings, anthropized environment, and exposed population). The approach identifies that the most significant change in risk over time is not only the dam itself but also the transformation of the territory. This methodology does not incorporate probabilistic forecasting of flood or climate change; instead, it objectively characterizes the exposed territory, offering insights into existing vulnerabilities on which to base effective mitigation strategies. Full article

Risk assessment for moisture safety—particularly in the context of future climate scenarios—is not yet a routine component of building design practices. Key challenges include: (1) uncertainty over who is responsible for conducting assessments, (2) ambiguity regarding the appropriate timing, and (3) a lack of clear guidance on integrating climate data into the process. To meet the challenges, this article explores and evaluates the development of a national climate adaptation framework for designing moisture-resilient buildings in alignment with projected future climate conditions and the requirements of the Norwegian Planning and Building Act. In noteworthy detail the article presents the general approach/steps followed in the research and the qualitative climate risk assessment elements to be considered in the design process of buildings. The framework has been co-produced with the Norwegian construction industry and public sector and introduces structured checklists and division of responsibilities (architects, engineers, etc.) to clarify and operationalize this. The mainstreaming of climate adaptation requires further refinement and broader integration of climate indices into building guidelines. These indices enable more accurate moisture performance predictions and help eliminate unsuitable solutions for specific zones. The framework—reinforced by tools such as the SINTEF Building Research Design Guides (Byggforskserien)—offers a comprehensive, evolving approach to moisture resilience, dependent on ongoing tool development, clarified roles, and wider uptake of climate-sensitive risk assessments. Full article

In the context of climate change and energy transition, the growing frequency of extreme weather events threatens the safety and stability of power systems. Given the limitations of existing research on load characteristic analysis and load forecasting during extreme weather events, this paper proposes a load-integrated forecasting model that accounts for extreme weather. First, an improved power load clustering method is proposed, combining Kernel PCA for nonlinear dimensionality reduction and an enhanced k-means algorithm, enabling both qualitative analysis and quantitative representation of load characteristics under extreme weather. Second, an optimal combination forecasting model is developed, integrating improved SVM and enhanced LSTM networks. Building upon the improved power load clustering algorithm, a load-integrated forecasting model considering extreme weather is established. Finally, based on the proposed load-integrated forecasting model, a time-series production simulation model considering extreme weather is constructed to quantitatively analyze the power and electricity balance risks of the system. Case studies demonstrate that the proposed integrated forecasting model can effectively analyze load characteristics under extreme weather and achieve more accurate load forecasting, which can provide guidance for the planning and operation of new power systems under extreme weather conditions. Full article

The increased presence of harmful algal blooms (HABs) is a concern for many aquatic environments, especially with the increasing effects of climate change. Members of the dinoflagellate genus Dinophysis have been shown to produce toxins that can cause Diarrheic Shellfish Poisoning (DSP) in humans who consume infected shellfish. The advancing oyster aquaculture industry in Delaware will require the development of management practices and monitoring HAB species to protect environmental and human health. Temperature, nutrients, and prey abundance can be drivers of Dinophysis blooms. D. acuminata has been historically identified at high concentrations (>200,000 cells L⁻¹) in water samples from Rehoboth Bay, DE, USA. However, the reach of spring blooms and how far they extend to aquaculture sites have not been determined. This study monitored an emergent HABs threat of a toxin-producing dinoflagellate, Dinophysis acuminata, by assessing a transect during the first recorded winter bloom in Torquay Canal and analyzing concentrations of chemical nutrients of combined nitrate and nitrite, and orthophosphate. Pearson correlation coefficient analysis between cell density (cells L⁻¹) and environmental variables across all sites was conducted to determine significant relationships between water temperature, Chl-a concentration, conductivity, dissolved oxygen (DO), combined nitrate and nitrite concentrations (NO_x), and orthophosphate concentrations (PO₄³⁻). Genetic techniques and PCR were utilized to determine the presence of Dinophysis using genus-specific primers to monitor cell density or abundance within the sediments during winter months. There were no significant correlations between environmental variables, and nutrient concentrations did not exceed EPA regulations. Molecular analyses of benthic sediments detected Dinophysis spp., offering insight into potential bloom origins. Overall, there is limited ecological data on Dinophysis acuminata in Rehoboth Bay, DE, USA. The results of this study will help strengthen resources for monitoring HAB species and understanding potential risks to oyster aquaculture in Delaware. Full article

Transportation networks are critical lifelines in national infrastructure but are increasingly exposed to risks arising from climate variability, cyber threats, aging assets, and limited resources. This paper presents a scoping review of 58 peer-reviewed studies published between 2015 and 2025 that examine the role of Artificial Intelligence (AI) in strengthening infrastructure resilience, with transportation systems adopted as the strategic case. The review classifies applications along five dimensions: technological approach, infrastructure sector, transportation linkage, resilience/security aspect, and key research gaps. Findings show that AI, machine learning (ML), and the Internet of Things (IoT) dominate current applications, particularly in predictive maintenance, intelligent monitoring, early-warning systems, and optimization. These applications extend beyond transport to energy, water, and agri-food systems that indirectly sustain transport resilience. Persistent challenges include affordability, data scarcity, infrastructural limitations, and limited real-world validation, especially in Sub-Saharan African contexts. The paper synthesizes cross-sector pathways through which AI enhances transport resilience and outlines practical implications for policymakers and practitioners. A targeted research agenda is also proposed to address methodological gaps, enhance deployment in resource-constrained settings, and promote hybrid and explainable AI for trust and scalability. Full article

The Australian built environment is pivotal to achieving national net-zero targets, yet progress remains slow due to fragmented policy frameworks, low retrofit adoption, and uneven integration of emerging technologies. Despite these challenges, little research has applied a foresight perspective that both defines reproducible scenario thresholds and provides semi-quantitative comparisons tailored to Australia. This study integrates strategic foresight with international benchmarking to develop four scenarios for 2050: Business as Usual, Accelerated Sustainability, Technological Transformation, and Climate Resilience. Each scenario is underpinned by measurable thresholds for renovation rates, electrification, digital penetration, and low-carbon material uptake, and is evaluated through a scorecard spanning five outcome domains, with sensitivity and stress testing of high-leverage parameters. Findings indicate that an Accelerated Sustainability pathway, driven by deep retrofits of ≥3% annually, whole-life carbon policies, and renewable penetration of at least 70%, delivers the strongest combined performance across emissions reduction, liveability, and resilience. Technological Transformation offers adaptability and service quality but raises concerns over equity and cyber-dependence, while Climate Resilience maximises adaptation capacity yet risks under-delivering on mitigation. The study contributes a reproducible framework and transparent assumptions table to inform policy and industry road mapping, suggesting that a policy-led pathway coupling retrofits, electrification, and digital enablement provides the most balanced route towards a net zero and climate-resilient built environment by 2050. Full article

Background: Urban disasters expose persistent gaps in the operational picture and timely decision-making for response teams, which require user-centred systems that connect analysis to action. This study proposes and formatively validates an integrated framework that couples digital twins and augmented reality for humanitarian logistics. Methods: A mixed methods design combined a structured literature synthesis with a practitioner survey across architecture, engineering, planning, BIM, and construction to assess perceived value and adoption conditions. Results: Findings indicate that practitioners prioritised digital twins for enhancing situational awareness (71.4%) and augmented reality for providing real-time information overlays (64.3%). A majority judged that integrating these technologies would yield substantial improvements in disaster response (67.9%), despite implementation challenges. Conclusions: The framework links live state estimation and short-horizon simulation to role-specific, in-scene AR cues, with the aim of reducing decision latency and improving coordination. Adoption depends primarily on human and organisational factors, including user accessibility, preparation needs, and clear governance. These results suggest a viable pathway to operationalise the bridge between analysis and field action and outline priorities for pilot evaluation. Full article

Local communities in many parts of the West Bank, Palestine have very limited water resources available for irrigation. In addition, since these communities are traditionally agricultural communities, water shortage and the lack of innovation in the agricultural sector led to loss of jobs in this sector. This in turn led young people to start looking for jobs in different sectors and even increased migration to urban centers. The reuse of treated wastewater can provide a viable solution to irrigation water shortage. It can help in creating jobs in the marginalized communities in the West Bank, especially in areas under full Israeli control (Area C according to the Oslo Accord). Furthermore, it is important to select crops that can resist the effects of climate change and create revenue for the farmers at the same time. In this research, we studied the impact of irrigating marigold (Tagetes erecta), which is a flower plant commonly used in the Palestinian market, with treated wastewater from the Nablus West Wastewater Treatment Plant (NWWTP). The quality of the treated wastewater, as indicated by parameters such as COD, BOD5, pH, EC, and TSS, shows its suitability for agricultural reuse. With low levels of organic matter, a near-neutral pH, and minimal suspended solids, the water poses minimal environmental risks and is ideal for irrigation, though monitoring for salinity buildup is necessary. Twenty-six marigold plants were planted, half of them were irrigated with the treated wastewater and the other half with tap water. Observations of length, number of roses, rose size, days to flower, and flowering days were recorded for both cases. The statistical analysis of the results shows that there is no significant difference between marigolds irrigated with treated wastewater and those treated with tap water, in terms of Plant Height, Rose Number and Rose Diameter. Full article

In the context of increasing climate variability and flood risk, this study explores how long-standing agricultural practices in the Hunter Valley, New South Wales, Australia, have fostered flood resilience through the integration of local agro-environmental knowledge and geomorphologic conditions. Employing a morpho-typological framework, the research identifies three flood adaptation landscape types (FALTs)—rolling hills, foot slopes, and flood plains—each reflecting distinct interactions between landform, soil, biodiversity, hydrology, and viticultural management. Through geospatial analysis, field surveys, and interviews with local farmers, the study reveals how adaptive strategies—ranging from flood avoidance to attenuation and acceptance—have evolved in response to site-specific hydrological and ecologic dynamics. These strategies demonstrate a form of ‘sponge landscape’ design, where agricultural systems are co-shaped with natural processes to enhance systemic resilience and long-term productivity. The findings underscore the value of preserving biocultural legacies and suggest that spatially explicit, context-based approaches to flood adaptation can inform sustainable landscape planning and climate resilience strategies in other rural regions. The FALT framework offers a replicable methodology for identifying flood adaptation patterns across diverse agricultural systems in Australia, supporting proactive land use planning and nature-based solutions. This research contributes to the discourse on climate adaptation by bridging traditional environmental knowledge with contemporary planning frameworks, offering practical insights for policy, landscape management, and rural development. Full article

Songhua River Basin, northeast China, has seen significant changes due to climate change and human activities from 1990 to 2000, when forests were largely reclaimed and agricultural land was taken up to change the terrestrial water cycle drastically. This paper investigates hydrological changes in three basins: the main stream basin of the Songhua River, the Second Songhua River Basin, and the Nenjiang River Basin. Machine learning and signal processing techniques have been applied to reconstruct historical river records with high accuracy, achieving determination coefficients exceeding 0.97. The physically based WEP model effectively simulates both natural hydrological patterns and human-induced hydrological processes in the northern Nenjiang region. Climate projections indicate clear temperature increases across all scenarios. The most significant warming is observed under the SSP5-8.5 scenario, where runoff increases by 8.52% to 12.02%t, with precipitation driving 62% to 78% of the changes. Summer runoff shows the most significant increase, while autumn runoff decreases, particularly in the Nenjiang Basin, where permafrost loss alters spring melt patterns. This change elevates flood risk in summer, with the rate of increase strongly dependent on the scenario. Water resources show strong scenario dependence, with the average growth rate of SSP5-8.5 being 4 times that of SSP1-2.6. A critical threshold is reached at a 2.5 °C increase in temperature, triggering system instability. These results emphasize the need for adaptation to spatial differences to address emerging water security challenges in rapidly changing northern regions, including nonlinear hydroclimatic responses, infrastructure resilience to flow changes, and cross-basin coordination. Full article

Wastewater treatment plants (WWTPs) function as engineered ecosystems in which microbial consortia mediate nutrient cycling, xenobiotic degradation, and heavy metal detoxification. This review discusses a forward-looking roadmap that integrates microbial ecology, multi-omics diagnostics, and artificial intelligence (AI) for next-generation treatments. Meta-analyses suggest that a globally conserved core microbiome indicates sludge functions, with high predictive value for treatment stability. Multi-omics approaches, including metagenomics, metatranscriptomics, and environmental DNA (eDNA) profiling, have integrated microbial composition with greenhouse gas (GHG) emissions, showing that WWTPs contribute 2–5% of anthropogenic nitrous oxide (N₂O) emissions. Emerging AI-enhanced eDNA models have achieved >90% predictive accuracy for effluent quality and antibiotic resistance gene (ARG) prevalence, facilitating near-real-time monitoring and adaptive control of effluent quality. Key advances include microbial strategies for degrading organic pollutants, pesticides, and heavy metals and monitoring industrial effluents. This review highlights both translational opportunities, including engineered microbial consortia, AI-driven digital twins and molecular indices, and persistent barriers, including ARG dissemination, resilience under environmental stress and regulatory integration. Future WWTPs are envisioned as adaptive, climate-conscious biorefineries that recover resources, mitigate ecological risks, and reduce their carbon footprint. Full article

The Amazon hosts one of the richest diversities of mosquitoes in the family Culicidae, which are key both as arbovirus vectors and as environmental bioindicators. However, the state of Amapá remains poorly studied regarding its mosquito fauna. This study aimed to characterize the diversity and seasonal composition of Culicidae in the municipality of Mazagão, Eastern Amazon, within a rural landscape influenced by human activity and extreme climatic events. Three sampling campaigns were conducted between 2023 and 2024, covering rainy, intermediary, and dry periods. Mosquitoes were collected using Protected Human Attraction (PHA) and CDC light traps at both ground and canopy strata. A total of 3500 specimens were obtained, representing 38 species across 15 genera. The intermediary period yielded the highest abundance and richness, whereas the dry season presented very low diversity, probably because of severe drought and forest fires. Dominant species included Coquillettidia (Rhy.) venezuelensis, Cq. albicosta, and Mansonia titillans. There were significant differences in community diversity between dry and wetter periods, underscoring the strong role of seasonality in shaping mosquito populations. These findings represent the entomofaunistic survey of the region, contributing to biodiversity knowledge and highlighting potential public health risks, thus reinforcing the need for continuous entomological monitoring. Full article