Search Results (623)

The impacts of climate change on Mediterranean weed flora were investigated to inform future weed management strategies. Projections indicate that rising temperatures and increased atmospheric CO₂ concentrations are likely to favor ruderal species characterized by rapid phenological development and high dispersal capacity. Enhanced abiotic stressors—such as elevated temperatures, water scarcity, and increased UV-B radiation—are expected to affect crops more severely than weeds, given the latter’s greater evolutionary potential to develop stress-tolerant biotypes. Moreover, the increased frequency and intensity of extreme events (e.g., drought, flooding, and soil salinization) may reduce weed community diversity, potentially leading to dominance by a limited number of highly competitive species and consequently intensifying reliance on chemical weed control. Simplification of weed communities may also increase vulnerability to the introduction and establishment of alien species, particularly those originating from hot and arid regions, some of which may be parasitic, toxic, or allergenic. Climate change-induced phenological mismatches between flowering plants and pollinators are likely to favor wind-pollinated weed species, further compromising the aesthetic and ecological quality of agricultural landscapes. Additionally, increased production of wind-dispersed allergenic pollen, together with the anticipated rise in herbicide applications, may pose significant risks to human health. An effective agronomic strategy to address future weed scenarios should include the genetic improvement in crops to enhance adaptive plasticity, exploiting germplasm from ancestral lines and related wild species. Full article

Excessive CO₂ emissions cause global warming, while CO₂ interaction with crude oil can enhance oil recovery (EOR). To capture and reuse CO₂, nano-SiO₂ was cationically modified to synthesize nanoparticles (SCR₂). The structure and performance of SCR₂ were characterized by FT-IR, DLS, and TEM, confirming its excellent CO₂ adsorption capacity and surface activity. Compared with unmodified nano-silica, SCR₂ increased CO₂ adsorption capacity by 254.3% and reduced the core surface contact angle from 112.1° to 24.5°. Core flooding experiments showed that in low-permeability reservoirs, SCR₂ achieved a plugging rate of 87.5%, an enhanced oil recovery of 24.8%, and an ultimate oil recovery of 74.8% (23.8% higher than unmodified nano-silica). Mechanistically, SCR₂ plugs gas channeling pathways via its inherent nanoparticle properties and adsorption of dissolved CO₂ in the aqueous phase while improving rock surface wettability, thereby enhancing sweep efficiency and total oil recovery during CO₂ flooding. This study provides a promising approach for EOR and CO₂ resource utilization in low-permeability reservoirs. Full article

Ultra-deep high-pour-point oil (waxy crude oil) reservoirs under high-temperature and high-pressure conditions are characterized by severe heterogeneity and poor displacement efficiency, with the crude oil exhibiting a pour point of approximately 47 °C. Using the XH block as a representative ultra-deep reservoir, this study systematically examines the displacement mechanisms of CO₂ flooding and CO₂–water-alternating-gas (WAG) flooding. This study aims to elucidate the CO₂–oil interactions between CO₂ and waxy crude oil, to compare oil recovery and CO₂ retention under different injection modes in media with varying permeability and heterogeneity, and to provide experimental support for field-scale development. Slim tube, swelling, and long-core flooding experiments were conducted under reservoir conditions (139 °C, 57 MPa). The phase behavior between CO₂ and crude oil, as well as its impact on oil volume and flow properties, was analyzed. Moreover, continuous CO₂ flooding and WAG flooding were compared in low-permeability and medium–high-permeability cores, and WAG was subsequently applied to a parallel-core system to quantify the effect of interlayer heterogeneity. Results indicate that while CO₂ achieves miscibility with the waxy crude at reservoir pressure, its contribution to swelling and viscosity reduction is moderate compared to light oils; thus, recovery relies primarily on miscible displacement. Compared with continuous CO₂ flooding, WAG effectively delays gas breakthrough and enlarges the swept volume, leading to higher oil recovery and CO₂ storage efficiency. Increasing permeability reduces flow resistance and significantly enhances the oil recovery factor. In strongly heterogeneous systems, dominant flow through high-permeability channels markedly weakens displacement in low-permeability zones, resulting in lower overall recovery and CO₂ retention. These results indicate that properly designed WAG schemes can improve the development performance of heterogeneous waxy oil reservoirs while simultaneously meeting CO₂ storage requirements. Full article

Urban disaster management frequently relies on isolated single-hazard assessments and static census data. This conventional approach systematically obscures the highly dynamic, time-varying nature of population exposure to co-located environmental hazards. This study develops an observation-based, time-adaptive multi-hazard exposure prioritization framework to quantify these spatiotemporal variations. We integrate seismic amplification susceptibility, derived from shear-wave velocity estimates, and empirical pluvial flooding footprints with hourly dynamic living population data at a 250 m grid resolution in Seoul, South Korea. Results indicate that multi-hazard integration refines spatial prioritization, with 11% of high-priority areas diverging from single-hazard models, primarily driven by highly amplifiable alluvial deposits. Furthermore, dynamic living population data revealed clear diurnal exposure shifts. Business districts exhibited a daytime-to-nighttime exposure ratio of 3.35, whereas residential areas showed an inverse ratio of 0.69, demonstrating that identical physical conditions generate markedly different exposure patterns depending on the daily urban rhythm. Based on these temporal dynamics, we classified high-priority zones into Persistent (79.4%), Day-peak (10.3%), and Night-peak (10.3%) transition types. These findings suggest that urban exposure must be managed as a time-varying attribute rather than a static feature. The proposed classification supports targeted mitigation: structural improvements for Persistent areas, dynamic crowd management for Day-peak zones, and localized alerts for Night-peak zones. Driven by globally accessible mobile data, this framework provides a transferable foundation for exposure-informed urban resilience planning across diverse metropolitan environments. Full article

Public administrations increasingly seek to adopt digital tools for evidence-based policymaking, yet systematic frameworks guiding this adoption remain scarce. This paper aims to develop and apply a co-creation framework for technology adoption roadmaps in public sector policymaking. The objectives are threefold: (1) to systematically identify impacts, facilitators, and barriers through structured stakeholder engagement; (2) to structure these elements into Impact Pathways and Transition Scenarios; and (3) to derive actionable policy recommendations. Using a participatory action research design, a seven-step co-creation methodology was applied across all four cases addressing crisis management challenges: forest fires in Finland, floods and refugee reception in Italy, power outages in Greece, and wildfires in Spain. Through structured stakeholder engagement combining surveys, workshops, and online consultations, the study identified seven categories of policy support results; twelve impacts spanning technology adoption, policy process enhancement, public administration capacity, and citizen empowerment; nine facilitators across financial, organisational, legal, and technical dimensions; and eight frustrators assessed through a risk matrix. These elements were structured into Impact Pathways, visualising causal relationships among policy support tools, enabling factors, and transformation outcomes. Four Transition Scenarios were derived, aligned with the policy lifecycle stages of inception, negotiation, set-up, and operation, accompanied by fifteen actionable policy recommendations classified by thematic area, timeframe, and stakeholder responsibility. The findings reveal that evidence-based policies represent a central transformation target across all result categories, while effective stakeholder engagement and leadership commitment emerge as cross-cutting enablers. The integrated framework contributes to digital governance research by operationalising co-creation for strategic roadmap development and offers practitioners a decision-support tool for planning digital technology-assisted policymaking transformations. Full article

The northeast monsoon prevailing over southeastern China in late seasons, generally from October to March, frequently generates water level anomalies upstream of the Taiwan Strait (TWS) that reach the coastal waters of Guangdong in South China, and, with compounding astronomical high tides, elevate coastal flood risk over the region. The risk of coastal flooding or sea inundation is further heightened when monsoon forcing co-occurs with storm surge brought by late-season tropical cyclones (TCs). This study integrates tide gauge observations from Hong Kong (HK) and its vicinity together with Delft3D Flexible Mesh simulations to diagnose a tide-modulated anomaly wave mechanism. Observations show that anomalies originating in or near TWS arrive in HK with station-dependent phasing. These water level anomalies exhibit a characteristic ~6 h periodicity west of the Taiwan Shoal, and display peaks that systematically align with the astronomical high tide. Time–frequency analysis reveals a wave period transformation from ~12 h north of Dongshandao over the coast of southeastern China to ~6 h west of the Taiwan Shoal. We test the hypothesis that wind-forced water anomalies generated in or near TWS undergo shoal-modulated nonlinear tide–wind interaction and tidal-current advection that transform their dominant period and phase-lock them to the tide, producing four anomaly peaks per day downstream and station-dependent phasing in HK. Hindcasts of the November 2024 monsoon episode reproduce the observed timing, periodicity, and spatial transition, while constituent experiments demonstrate that semi-diurnal forcing entering via the TWS is the primary driver of the ~6 h signal, with the Taiwan Shoal acting as the modulation locus. Accurate water level forecasts for the Guangdong coast, therefore, need to incorporate upstream wind forcing over the TWS and bathymetric controls around the Taiwan Shoal, with practical implications for compound flood risk during spring tides and co-occurring monsoon and/or TC events. Full article

This study explores how demystifying Earth Observation (EO) through co-creation pathways and local language can enhance flood resilience and environmental governance in African informal cities. Using case studies from Maiduguri and Hadejia, Nigeria, the research employed a transdisciplinary mixed-methods design combining rapid evidence assessment, surveys, participatory workshops (n = 50 stakeholders) integrating simplified Sentinel-1/2 demonstrations, indigenous knowledge mapping, and pre-/post-engagement surveys on EO familiarity. Non-expert participants were trained to interpret satellite data using local language, linking distant teleconnections with local flood experiences. The findings revealed significant gains in EO literacy and improvements in interpretive confidence, gender-inclusive participation, and policy engagement. Localizing the curriculum enabled participants to translate technical EO concepts into locally meaningful narratives, fostering cognitive empowerment and practical application in flood preparedness and advocacy. The study demonstrates that data democratization is not only a matter of open access but also of open understanding. It advances a conceptual model linking Demystification, Literacy, Empowerment, Co-Production and Resilience, positioning EO as a social technology that bridges scientific and indigenous knowledge systems. The findings contribute to debates on decolonizing environmental science and propose a potential participatory framework for integrating EO into community-based adaptation, legal accountability, and policy reform across Africa’s rapidly urbanizing landscapes. Full article

Rational design of high-performance viscosifying polymers is critical for enhancing supercritical CO₂ flooding efficiency in enhanced oil recovery (EOR). Traditional experimental and simulation approaches are limited in exploring the vast design space of polymer architecture, flexibility, and intermolecular interactions. This work presents an integrated machine learning (ML) and mesoscopic simulation framework using Dissipative Particle Dynamics (DPD) to accelerate the development of tailored polymeric thickeners. We systematically investigate synergistic effects of linear and branched polymer blends on solvent viscosity under Poiseuille flow, representative of flow in micro-fractures and pore throats. Key molecular descriptors are varied to generate a comprehensive rheological database. This data trains a deep neural network (DNN) surrogate model linking molecular parameters to macroscopic viscosity. The DNN is coupled with gradient ascent optimization for inverse design, enabling rapid virtual screening of thousands of formulations. A focused case study demonstrates that the star-like architectures with associative cores and semi-flexible backbones outperform linear analogs for supercritical CO₂ viscosity enhancement. The optimal candidate—a four-arm star polymer with linear side chains—was validated by DPD simulation. This multiscale “simulation-to-surrogate” methodology bridges molecular design with continuum-scale flow behavior, offering a transformative tool for formulating cost-effective, efficient, and sustainable next-generation EOR chemicals. Full article

Flood control briefings are critical emergency response documents that provide timely decision support for urban safety and regional development under climate change challenges. However, existing large language models (LLMs) face significant difficulties in domain-specific adaptation, content controllability, and logical consistency when processing complex water conservancy data. This study aims to develop a robust automated text generation method that ensures high accuracy and logical rigor for flood prevention in the Lixiahe region. We propose an IP-CoT method that integrates Chain-of-Thought (CoT) reasoning for structured information extraction and an Inverse Prompting (IP) mechanism with beam search to optimize content relevance using the DeepSeek-R1 model. Validated on a constructed dataset comprising flood control records from the Lixia River network from 2010 to 2024, the proposed method achieved an accuracy rate of 95.32% in the verification of emotional attributes, which is 2% to 15% higher than most traditional models. Additionally, in the verification of thematic attributes, fluency and diversity were improved, showing significant enhancements compared to the baseline model. This approach significantly enhances the quality and efficiency of domain-specific text generation, providing a reliable intelligent solution for modernizing regional flood control decision-making systems. Full article

CO₂-enhanced gas recovery (CO₂-EGR) is a crucial technology for achieving both natural gas production increase and CO₂ geological storage. While pure CO₂ flooding demonstrates favorable recovery performance, the technical challenges and high costs associated with purifying CO₂ remain significant. CO₂ purification from exhaust gas incurs prohibitive costs, while direct injection of an unpurified CO₂–N₂ mixture can greatly cut engineering expenditure. Nitrogen also provides synergistic pressure support, working with CO₂ to drive natural gas displacement. Therefore, from an economic and practical standpoint, employing impure CO₂ mixtures (e.g., CO₂–N₂) for flooding presents a more advantageous approach. To clarify the factors influencing the recovery enhancement in tight sandstone gas reservoirs using CO₂–N₂ mixtures, long-core flooding experiments were conducted at 100 °C. This study systematically investigates the impact patterns of three key factors—injection timing, injection rate, and injection gas composition—on the enhanced recovery of tight sandstone gas reservoirs. The experimental results indicate that: (1) Advancing the injection timing significantly improves the recovery performance for both CO₂ and N₂ flooding. However, the cumulative recovery factor (sum of the depletion recovery and the incremental recovery from gas injection) shows a declining trend. (2) The enhanced recovery effect exhibits a trend of first increasing and then decreasing with the increase in injection rate. When the injection rate exceeds 0.05 mL/min, it tends to cause premature breakthrough of the injected gas, thereby reducing the displacement efficiency. (3) As the proportion of CO₂ in the injected gas increases, the enhanced recovery effect shows a nonlinear rise. The highest incremental recovery (17.02%) was achieved with pure CO₂ flooding, while pure N₂ flooding yielded the lowest result (14.64%). The research findings, from a macroscopic perspective, elucidate the influence patterns of three distinct factors on enhancing gas recovery in tight sandstone reservoirs, thereby providing theoretical foundation and scientific guidance for the development of such reservoirs. In summary, the injection timing, injection rate and CO₂ proportion in injected gas are the key controlling factors for gas flooding enhanced recovery in tight sandstone reservoirs. This study clarifies the macroscopic influence law of each factor, and the optimized development parameters proposed can provide direct theoretical support and technical guidance for the on-site application of gas flooding in tight sandstone reservoirs. Full article

European peatlands have been extensively drained for agriculture, resulting in substantial carbon losses and widespread soil degradation. Peatland restoration is therefore a global priority, with rewetting recognised as a key strategy for mitigating greenhouse gas emissions and climate change. This review synthesizes current knowledge on soil transformations following the rewetting of agriculturally drained peatlands in Europe. We describe major degradation processes induced by drainage, including land subsidence, organic matter oxidation, and microbial community shifts from anaerobic to aerobic conditions. We then examine key rewetting approaches—ditch blocking, controlled flooding, and paludiculture—and their intended restoration outcomes. Rewetting fundamentally alters soil physical, chemical, and biological properties by raising and stabilizing water tables, restoring anoxic conditions, and modifying nutrient cycling and microbial processes. Findings indicate long-term stabilization of organic carbon in peat soils under anaerobic conditions, but also reveal trade-offs between reduced CO₂ emissions and increased CH₄ and N₂O fluxes. Vegetation–soil interactions strongly influence recovery trajectories, and paludiculture offers potential to align agricultural land use with climate mitigation objectives. Finally, we evaluate current research methodologies and identify major knowledge gaps, including limited long-term data and insufficient integration of hydrological, chemical, and biological processes. We highlight priorities for future research to support evidence-based rewetting strategies that deliver climate benefits while maintaining ecological and economic sustainability in European peatlands. Full article

This study examined the glacial lake of JiongpuCo in the southeastern Tibet region. According to satellite images obtained by Landsat Thematic Mapper (TM) and Operational Land Imager (OLI) from 1995 to 2025, JiongpuCo’s area expanded from 1.92 ± 0.06 km² to 5.26 ± 0.02 km², which is a 174% increase over 30 years. The lake was in a state of dynamic equilibrium. The bathymetric data showed that JiongpuCo has a basin-like morphology. Its reservoir capacity curve was concave-up, with a maximum water depth of 237 m and total reservoir capacity of 6.35 × 10⁸ m³. A sequential HEC-RAS-MIKE 21 numerical modeling framework was constructed to simulate flood propagation. For three simulated scenarios (with breach volumes of 80%, 60%, and 30%), the peak discharge at the breach outlet was 28,368.45 m³/s, 25,451.67 m³/s, and 17,855.54 m³/s. Analysis of the simulation results shows that the glacier lake outburst flood (GLOF) has continuous attenuation of peak discharge and a gradual lag in arrival time along the flow path. Except for Bagai in Scenarios 2 and 3, all other target research towns and villages were flooded by floodwaters. These findings offer a solid scientific foundation for the reduction in GLOF disasters and the development of an early warning system for JiongpuCo. Full article

Carbon dioxide geological utilization and storage (CGUS) is a pivotal technology for achieving carbon neutrality. Its enhanced recovery and storage efficiency largely depend on whether or not the complex subsurface multiphysical fields can be predicted accurately to optimize the injection–production parameters. This study proposes a novel approach for the injection–production parameters optimization for CO₂ flooding, integrating intelligent algorithms with numerical simulation. For conventional numerical simulation-based parameter optimization, the sensitivity rankings of different parameters through single-factor analysis are purely experience-based. Grey Relational Analysis (GRA) effectively addresses this deficiency. Furthermore, it combines numerical simulation with genetic algorithms, possessing both dynamic simulation and intelligent optimization capabilities. Numerical simulation is utilized to achieve accurate modeling and quantitative evaluation of different CO₂ flooding injection–production parameters, while genetic algorithms enable the quantitative solution for the optimal values of each parameter. Analysis of typical case studies demonstrates that the approach effectively enhances the efficiency of injection–production parameter optimization and reduces the uncertainty in selecting optimal parameter values. It provides a scientific and efficient way for the parameter optimization of CO₂ flooding development plans. Full article

This study addresses high water cut and low recovery in bottom-water sandstone reservoirs by optimizing CO₂ and N₂ foam flooding parameters. The key innovation is the pioneering application of fractal dimension to quantitatively characterize water coning morphology during composite gas flooding. A numerical simulation assessed composite gas type, injection gas ratio, sequence, speed, volume, and injection–production ratio. Fractal dimension quantified water coning. Optimal conditions were: 2:1 injection gas ratio (CO₂ then N₂ foam), 140 t/d injection speed, 0.31 PV volume, and 1:3.2 injection–production ratio. This achieved 39.52% recovery over 15 years—a 4.89% increase, adding 3.17 × 10⁴ t of oil. Fractal dimension fell to 1.672. Sensitivity analysis showed the injection gas ratio most affects oil output. The injection volume best suppresses water coning. The injection speed has low sensitivity. Key interactions exist between volume, gas type, and injection–production ratio. Injection gas ratio, volume, and injection–production ratio are crucial for development control. The proposed methodology presents a viable strategy for enhancing oil recovery in similar reservoirs, with broader implications for advancing CO₂ utilization and supporting carbon management objectives in the petroleum industry. Full article

Conventional centralized drainage systems exacerbate urban flooding, pollution, and water stress. Low-impact development (LID) is a decentralized alternative; however, its multifunctional benefits, which go beyond the control of stormwater, are often undervalued in planning. This study fills this gap by developing an integrated benefit valuation framework to systematically quantify and estimate the economic value of the co-benefits of five widely implemented LID facilities (vegetated swale, green roof, in-filtration ditch, infiltration trench, and permeable pavement) in Seoul, South Korea. The framework combines annual benefits in four key sectors: water management (runoff reduction), energy savings (building cooling/heating demands), air quality (pollutant deposition and avoided emissions) and climate change (carbon sequestration and mitigation). Applying a transparent, localized spreadsheet model, the results indicate significant multifunctional value for LID systems. While water management provides the primary benefit, there is substantial added value in energy, air quality, and climate co-benefits. In the case of green roofs, such ancillary benefits can exceed hydrological values. The analysis further reveals a consistent scale-benefit relationship and a clear trade-off between the magnitude of benefits and the cost of implementation. This provides evidence of the need for context-sensitive, portfolio-based LID planning. The proposed framework is a practical decision support tool for urban planners and policymakers to consider LID not only as a stormwater solution but also as multifunctional green infrastructure that simultaneously promotes urban water security, energy efficiency, environmental quality, and climate resilience. Full article