Search Results (925)

Tunnels excavated in non-coal oil- and gas-bearing strata may experience the seepage and intermittent ingress of an oil–gas–water mixture during construction, creating aggressive corrosive conditions that can compromise the integrity of primary support and the safety margin of the final lining. However, the coupled degradation mechanism of primary support and its cascading effect on lining safety under such conditions remain poorly understood. Based on the Huaying Mountain Tunnel project, this study investigates the corrosion-driven damage evolution of primary support and its implications for the structural safety of the secondary lining under wet–dry cycling exposure. Accelerated wet–dry cycling tests were performed on concrete specimens using an on-site crude-oil–formation-water mixture collected during tunnelling, with exposure levels ranging from 0 to 120 cycles. Laboratory observations were then combined with inverse identification of degradation-dependent material parameters to establish a corrosion-informed mechanical description, which was implemented in numerical simulations for structural response assessment. Results show a staged evolution of mechanical properties, with an initial increase followed by progressive deterioration. After 120 cycles, compressive strength, tensile strength, and elastic modulus decreased by approximately 18.9%, 23.1%, and 17.4%, respectively. Degradation is more pronounced in the corroded zone, with tensile capacity and stiffness deteriorating earlier than compressive resistance. Numerical results indicate that corrosion leads to significant stress redistribution and damage development. The sidewall tensile stress reaches 2.80 MPa after 120 cycles, exceeding the post-corrosion capacity, while the safety factor drops below the code threshold at 90 cycles. The overall safety probability decreases from 1.0 to 0.4, accompanied by a degradation in safety grade from Level I to Level IV. These findings provide a quantitative basis for deterioration assessment, safety verification, and maintenance planning for tunnels subjected to oil–gas corrosive environments. Full article

This study comparatively assesses the Municipal Emission Reduction Plans (MERPs) of Spetses, Platanias, and Souli, examining their role as analytical and strategic tools for local climate planning, with particular emphasis on water-related infrastructure. A descriptive comparative analysis was conducted using secondary data extracted from officially approved MERPs, covering sectoral and total greenhouse gas emissions for 2019 and 2023, as well as reported mitigation actions and 2030 targets. The results reveal significant inter-municipal variations in emission patterns, driven by geomorphological characteristics, infrastructure configuration, and energy consumption, but also by governance structures and system boundaries. Water supply and irrigation systems are identified as highly energy-intensive sectors, particularly in municipalities with extensive, pumping-dependent networks. At the same time, the analysis shows that the inclusion or exclusion of outsourced services—such as water supply and wastewater management—substantially affects the representation of emissions and the prioritization of mitigation actions. The study concludes that MERPs can support climate planning at the municipal level, but their effectiveness is conditioned by data completeness, system boundaries, and governance models. These findings highlight the need to move beyond purely accounting-based approaches toward integrated planning frameworks that capture the full operational scope of municipal systems, enabling more accurate emission assessment and more effective, context-specific mitigation strategies within the water–energy–nexus. Full article

Accurate extraction of impervious surface areas (ISA) is essential for urban environmental monitoring, yet severe spectral confusion among complex urban land-cover types limits the performance of classifications based solely on optical imagery. To address this issue within a localized context, this study proposes a multi-source framework integrating UAV-based LiDAR (UAV-LiDAR) and high-resolution visible imagery for fine-scale ISA extraction. An improved segmentation optimization strategy, termed EGS-Optimizer, is developed to enhance boundary delineation within the object-based image analysis (OBIA) framework by coupling edge detection with global segmentation quality evaluation. A comprehensive feature set including spectral, index, texture, geometric, and terrain features is constructed, and Shapley Additive Explanations (SHAP) is applied to select the most informative variables while reducing dimensionality. The proposed framework is validated in a typical 1.45 km² built-up area in Deyang City, Sichuan Province. Experimental results demonstrate that, within this specific study area, multi-source data fusion improves classification accuracy by 3.59–5.79% compared with single-source data, while feature selection reduces the feature dimension from 45 to 21. Among the evaluated classifiers, the random forest (RF) model achieves the highest performance, with an overall accuracy of 97.24% (Kappa = 0.96). While the high accuracy highlights the efficacy of synergizing spectral and structural information for micro-landscape mapping, these findings are constrained to the demonstrated fine-scale local environment. The results provide an effective, interpretable solution for detailed neighborhood-level ISA mapping, though further validation is required before the framework can be generalized to larger or more heterogeneous urban scenarios. Full article

Groundwater plays an indispensable role in daily life. However, with the continuous advancement of industrialization, more attention should be paid to the quality of groundwater and the associated potential health risks in areas surrounding industrial parks. In this study, groundwater samples collected in the city of the Tibetan Plateau during the wet season (WS) and dry season (DS) were analyzed using Piper diagrams, Gibbs diagrams, and correlation analysis. The results elucidated the hydrochemical characteristics, formation mechanisms, and controlling factors of groundwater in the area. Groundwater potability was assessed using the Entropy-weighted Water Quality Index (EWQI) method. In addition, the health risk assessment model was applied to evaluate potential risks for four population groups, with NO₃⁻ and F⁻ selected as representative groundwater pollutants. The findings revealed that groundwater in the study zone was typically moderately alkaline and characterized primarily as soft–fresh and hard–fresh. The groundwater in both seasons mainly exhibited HCO₃–Ca chemical facies. Water–rock interactions involving silicate and carbonate minerals were identified as key processes controlling the hydrochemical composition in both seasons. EWQI results showed that groundwater quality for drinking purposes was excellent in the seasons. Sensitivity analysis further showed that Cl− exerted the greatest influence on the drinking water quality evaluation in both seasons. Health risk assessments revealed that the risks posed by NO₃⁻ and F⁻ to infants, children, adult females, and adult males remained within acceptable limits (with max values of 0.63, 0.39, 0.28, and 0.33 in the WS, and 0.59, 0.36, 0.26, and 0.31 in the DS, respectively). However, infants exhibited greater susceptibility than the other groups across seasons, with a risk index approximately twice that of adults. Overall, the findings contribute valuable insights for the sustainable management and planning of groundwater resources in the study zone. Future research could refine the risk assessment model with localized data and explore mitigation strategies for elevated risks in specific seasons or regions. Full article

The growing complexity of human systems and the increasing frequency of climate-driven hazards have transformed some disasters from isolated events into cascading phenomena which propagate through critical infrastructure networks, disrupting essential services and amplifying systemic risk. This work examines the impacts of extreme storms and subsequent flooding on critical entities as defined under the new EU Directive (Critical Entities Resilience, CER). This study introduces a structured Critical Entities Disruption Database—Greece (CEDD-GR), as a methodological framework for systematically recording and analysing disruptions to critical entities, and applies it to the case of Storm Daniel (2023), one of the most severe flood events recorded in Greece. The analysis identified direct impacts across eight of the eleven sectors defined in the CER Directive, namely, energy, transport, health, drinking water, wastewater, public administration, digital infrastructure and food production, processing and distribution. A total of 21 different types of critical entities were documented, revealing the mechanisms through which failures affected different subsectors. The results underscore the systemic fragility of critical entities when exposed to extreme storms, compound flooding, and mass wasting processes (landslides, ground subsidence) and highlight the need for integrated resilience planning in line with the CER framework. Full article

The Taoping paleo-landslide poses a significant risk to local residents and critical infrastructure. However, traditional field surveys and deformation monitoring methods are often inadequate for capturing subtle, localized deformation characteristics—particularly at the head scarp and lateral margins—thereby limiting comprehensive assessments of slope instability. Surface strain data offer direct insights into internal stress redistribution during slope evolution and are essential for interpreting landslide mechanisms and forecasting failure. Given the current limitations in dense and wide-area strain monitoring technologies, this study proposes a novel method for modeling landslide strain fields based on Interferometric Synthetic Aperture Radar (InSAR) phase gradients. Using the phase gradient stacking approach, InSAR-derived phase gradients are transformed into strain-related parameters, enabling estimation of shear strain rates, principal strain rates, and their directional distributions. The application to the Taoping paleo-landslide reveals clear spatial patterns of compressive and tensile strain across the landslide body. Field investigations corroborate the InSAR-derived strain features through corresponding geomorphological evidence observed in both compressional and extensional zones. The proposed method enhances the understanding of landslide deformation behavior, supports evaluation of shear surface continuity and evolution, and offers a robust framework for early warning and risk mitigation in complex landslide-prone areas. Full article

This research provides an extensive evaluation of liquefaction induced by earthquakes in the Ionian Islands, specifically Lefkada, Cephalonia, Ithaki, and Zakynthos, through the compilation of a liquefaction inventory and GIS-based liquefaction susceptibility index (LiSI) maps. A total of 49 liquefaction sites from 20 causative earthquakes confirm that liquefaction is a recurrent geohazard in the area, primarily affecting coastal and low-lying areas with unconsolidated post-alpine deposits. The relationship between earthquake magnitude and maximum epicentral distance of observed liquefaction is consistent with global empirical datasets, indicating that moderate to strong earthquakes (M_w = 5.9–7.4) can induce liquefaction at considerable distances. The susceptibility model integrates eleven conditioning variables, classified as geological and geomorphological variables, hydrological indices and optical satellite imagery-derived data, within an analytic hierarchy process (AHP) framework. Lithology, age, and geomorphological unit emerged as the dominant conditioning variables. The LiSI maps confirm the zones previously identified in the inventory. Model validation and sensitivity analysis including confusion matrix components, key performance metrics and ROC analysis in coarser grid sizes demonstrate performance ranging from excellent (Zakynthos) to moderate (Lefkada and Cephalonia), while remaining inconclusive for Ithaki due to data limitations. The model exhibits generally conservative behavior, characterized by high precision and specificity but variable sensitivity, while it is largely stable across spatial resolutions in most cases. Full article

We present an enhanced earthquake catalog for Central Evia and the Northern Gulf of Evia, in Central Greece, between June 2018 and November 2023. The area is characterized by a low background seismicity rate, with occasional clustered events and seismic swarms, including those of February–April 2022 near Drosia and of October 2022 near Styra. The seismic catalog was enhanced by integrating additional data acquired through the application of the EQ-Transformer deep-learning model. A total of ~1400 events were analyzed, with ~1200 of them being successfully relocated with the double-difference method. The available focal mechanisms indicate predominantly normal, oblique-normal, and pure strike-slip faulting. The relocated seismicity was examined in conjunction with known mapped faults to investigate the activated structures at depth, providing insight into their degree of activity. In Drosia, the seismicity, at a depth of ~14 km, can be related to an E–W dextral strike-slip fault, with subtle surficial expression. In Psachna, the epicenters are oriented in an NE–SW direction, not matching the strike of the mainshock’s normal focal mechanism, but roughly coinciding with NE–SW-oriented topographic spurs and the local drainage pattern. In Markates and Prokopi, the seismicity is sparse, but the focal mechanisms are consistent with SW–NE dextral strike-slip faulting, aligned with the trend of the Nileas depression and the Prokopi–Pelion fault zone. Finally, in Mouriki, the seismic cluster is characterized by WNW-ESE normal faulting, most likely related to the SSW-dipping Messapio fault. Full article

Advancing hydropower development is crucial for supporting China’s “Dual Carbon” strategy and ensuring energy security. A key safety challenge in this endeavor is the stability of arch dam abutments under the combined action of high in situ stress and reservoir water loads. This study addresses this issue by proposing an integrated methodology that links detailed geological characterization, in situ stress quantification, and mechanical stability analysis. Using the Guxue high-arch dam as a case study, we first established a three-dimensional geological model to identify controlling discontinuities and delineate potential sliding blocks. A finite difference model was then developed to simulate the in situ geo-stress field and operational water pressures. Through stress tensor transformation, the stress state on potential slip surfaces was accurately determined, and safety factors were calculated based on the Mohr–Coulomb strength criterion. The results show that the critical left and right abutment rock blocks exhibit safety factors of 1.30 and 1.24, respectively, meeting design specifications while indicating a relatively lower safety margin on the right bank. The proposed approach, grounded in precise stress analysis, provides a reliable framework for assessing abutment stability under complex loading conditions, offering practical support for the safety evaluation and targeted reinforcement of high-arch dam projects in similar geological settings. Full article

Global Digital Elevation Models (DEMs) exhibit systematic biases constrained by acquisition geometry and surface penetration. This study aims to evaluate whether the increasing complexity of geometric deep learning (e.g., Graph Neural Networks, GNNs) is justified by performance gains over established feature engineering paradigms (e.g., XGBoost) under the constraints of sparse altimetry supervision. We established a rigorous comparative framework across four mainstream products—ALOS World 3D, Copernicus DEM, SRTM GL1, and TanDEM-X—using Sichuan Province, China, as a representative natural laboratory. Our results reveal a fundamental scale mismatch (where the ~485 m average spacing of sampled altimetry footprints dwarfs the local terrain resolution): despite their topological complexity, Hybrid GNN models fail to establish a statistically significant accuracy advantage over the systematically optimized XGBoost baseline, demonstrating RMSE parity. Mechanistically, we uncover a critical divergence in decision logic: XGBoost relies on a stable “Physics Skeleton” consistently dominated by deterministic features (terrain aspect and vegetation density), whereas GNNs exhibit severe “Attribution Stochasticity” ($\rho \approx$ 0.63–0.77). The GNN component acts as a residual-dependent latent feature learner rather than discovering universal topological laws. We conclude that for geospatial regression tasks relying on sparse supervision, “Physics Trumps Geometry.” A “Feature-First” paradigm that prioritizes robust, domain-knowledge-based physical descriptors outweighs the indeterminate complexity of “Black Box” architectures. This study underscores the imperative of prioritizing explanatory stability over marginal accuracy gains to foster trusted Geo-AI. Full article

This study investigates the long-term durability performance of Portland cement mortars incorporating 5% and 10% Ca-rich fly ash under 24 months of natural marine atmospheric exposure. An integrated experimental methodology was applied, combining gravimetric steel mass loss, half-cell potential monitoring (SCE), water-soluble chloride determination at reinforcement depth, carbonation depth evaluation interpreted through the diffusion-based square-root model (x = k√t), and pore structure characterization by MIP and SEM. After 24 months, cumulative steel mass loss decreased by 26.6% (FA5) and 33.6% (FA10) relative to the reference mortar. The water-soluble chloride concentration at reinforcement depth was reduced from 976 mg/L in CM-REF to 875 mg/L (−10.2%) and 805 mg/L (−17.5%) in CM-FA5 and CM-FA10, respectively. Carbonation depth after 24 months decreased from 5.97 mm in the reference mortar to 4.56 mm (−23.6%) and 2.48 mm (−58.5%) for FA5 and FA10, confirming a transport-controlled mitigation of carbonation progression. Within the investigated replacement range, moderate Ca-rich fly ash incorporation produces measurable reductions in chloride availability, carbonation rate, and cumulative corrosion damage under realistic coastal exposure conditions, demonstrating that limited clinker substitution can yield substantial long-term durability benefits. These findings demonstrate that Ca-rich fly ash incorporation (5%–10%) effectively enhances resistance to chloride ingress, carbonation progression, and reinforcement corrosion under natural marine exposure, supporting its use as a performance-oriented strategy for durable, low-clinker mortar design in coastal infrastructure. Full article

High-altitude mine wastelands in Southwest China present formidable challenges for ecological rehabilitation due to extreme climatic stressors and multi-element contamination. Ecological restoration is closely related to soil environment. However, the mechanism by which parent material-induced heterogeneity governs spontaneous vegetation succession is still poorly understood. We established 36 plots (216 quadrats) to investigate the soil physical and chemical properties and vegetation restoration of propylite, porphyry and siltstone in the Xifanping Copper Mine, Sichuan Province. Furthermore, fifteen metal/metalloid elements (Au, Ag, Mo, W, Cu, Pb, Zn, Hg, As, U, Se, Cr, Sn, Ti, Total Fe₂O₃), soil pollution and vegetation structure were evaluated. The study area exhibited severe composite pollution (mean Nemerow integrated pollution index = 8.09), primarily driven by Au, Ag, Mo, W, and Cu. Vegetation surveys identified 34 vascular plant species from 12 families. Propylite-derived substrates supported significantly higher species richness, Shannon–Wiener diversity, and soil organic matter than porphyry and siltstone. Redundancy analysis (RDA) identified soil organic matter (SOM) and bulk density (BD) as dominant environmental filters, with SOM explaining 14.03% of community variance (p < 0.01). Two native pioneers, Potentilla supina and Cynoglossum wallichii, were identified as specialized uranium (U) accumulators with bioconcentration factors of 13.39 and 4.49, respectively. Lithological inheritance dictates early successional trajectories by influencing edaphic structure and nutrient bioavailability. The identified U-accumulating species provide a valuable genetic resource for implementing Assisted Natural Regeneration (ANR) and developing sustainable phytoremediation strategies in contaminated alpine ecosystems. Full article

Coccolithophores are important components of marine phytoplankton and are found to be useful indicators of the environmental conditions of the upper water column. In this study, we investigate coccolithophore abundance and composition in the Cretan Sea and South Cretan area (Eastern Mediterranean), and their relation to prevailing hydrodynamic conditions during late February/early March 2019. Results showed that total coccolithophore abundance ranged from 26.3 × 10² to 258.8 × 10² coccospheres L⁻¹, averaging at 135.8 × 10² coccospheres L⁻¹. Among the 45 identified species, the opportunistic Emiliania huxleyi was the most dominant, representing 89% of the coccolithophore assemblage. In the Cretan Sea, this species showed relatively homogeneous abundances throughout the upper 100 m depth of the water column; however, towards the Rhodes Cyclone, where a weak stratification had started, and the mixed layer was relatively shallow, higher abundances were found at depths shallower than 50 m. Syracosphaera molischii co-occurred with Emiliania huxleyi, whereas Rhabdosphaera clavigera, Syracosphaera pulchra, and Syracosphaera mediterranea were also present but in lower abundances, reflecting the influence of warm, salty Levantine Surface Water. Based on the morphological analysis, Emiliania huxleyi was mostly represented by heavily calcified forms consistent with winter-spring patterns in the Aegean Sea. The observation of signs of dissolution with high relative abundances of etched/corroded coccospheres indicates the sensitivity of Emiliania huxleyi to the prevailing circulation pattern during the 2019 mixing event within the Rhodes gyre. Full article

To enhance the mechanical properties of bamboo-reinforced concrete slabs, 1%, 1.5%, and 2% of steel fibers (SF) were added to C30 bamboo-reinforced concrete slabs to produce two test groups, each containing 12 slabs. One group was tested under static loads, and the other under impact loads. In each group, the slab thickness was set to 50 mm, 65 mm, and 80 mm, and the steel fiber dosages were 0%, 1%, 1.5%, and 2%. While existing studies on bamboo-reinforced concrete slabs (BRCS) have primarily focused on static flexural behavior, and research on steel fiber-reinforced concrete (SFRC) has mainly addressed fiber network effects in plain or steel-reinforced matrices, the synergistic mechanism between bamboo and SF in steel fiber-reinforced bamboo-reinforced concrete slabs (SFRBCS) under dynamic impact loading remains unexplored. This study innovatively combines bamboo’s elastic energy absorption with SF’s plastic energy dissipation. Static load and drop hammer impact tests were carried out in each group to study the mechanical properties of SFRBCS under static and dynamic loads. The test results show that: under static load, adding SF transforms the failure mode of the slab from brittle shear failure to ductile bending failure, increases the ultimate load, and delays the development of the main crack. Under the action of impact loads, bamboo absorbs impact energy through elastic deformation, while SF dissipates energy through plastic deformation. The combined effect of the two significantly slows down the development speed of cracks. The slab with 80 mm thick and 2% SF dosage exhibits excellent impact ductility. Based on theoretical analysis and tests, the corresponding correction coefficients are introduced to establish the bearing capacity calculation model of SFRBCS under uniformly distributed loads, considering the synergistic effect of the mechanical properties of bamboo and the reinforcing effect of SF. The combination of 1.5% SF dosage and 80 mm slab thickness can effectively enhance the material utilization rate (defined as the ratio of the increment in ultimate bearing capacity to the increment in steel fiber dosage). Test and calculation models provide a theoretical basis for the design and application of SFRBCS, which is applicable to engineering fields such as low-rise buildings and temporary structures. Full article

There are significant safety risks associated with the construction and operation of wind turbines in goaf sites. Investigating the catastrophic mechanisms underlying wind turbine foundations is crucial for addressing these scientific challenges. This study employs the empirical formula method to quantitatively evaluate and analyze the stability of a goaf site. Additionally, the disaster mechanisms of wind turbine foundations in these areas are examined through similar model tests and numerical simulations. The findings indicate that the settlement deformation of the wind turbine foundation is closely related to the magnitude of the applied load. Upon completion of the loading, the maximum settlement of the foundation under rated and extreme wind speed conditions was recorded at 0.16 mm and 0.26 mm, respectively, while the maximum inclination angles were 0.04° and 0.18°, respectively. At the conclusion of the loading process, the soil pressure differences between the leeward and windward sides of the base were measured at 95.3 kPa and 139 kPa under rated and extreme wind speed conditions, respectively. This data suggests that extreme wind speeds significantly influence the distribution of base pressure, resulting in an increased uneven settlement of the foundation. Full article