In extra-thick coal seams under a protective layer, the advanced coal mass (ETUPAC) may experience stress recovery and even abnormal concentration after a prolonged mining cessation, leading to rockburst occurrences under strong mining-induced tremors. In this study, a 'combined cantilever + voussoir beam' overburden structure model was established, and a surface vertical well multi‑strata hydraulic fracturing (SVMSHF) method was proposed to regulate the overburden structure for rockburst control. The proposed method was validated through engineering practice at the Haishiwan coal mine. The results show that under the combined effects of the rotation of the 'combined cantilever' and the pressure arch formed by the high-position key strata, the goaf above the ETUPAC was progressively compacted. The vertical stress in the ETUPAC increased from 4.73 MPa to 29.18 MPa, which is 25.94
The growing deterioration of water quality caused by emerging contaminants has intensified the search for efficient, low-cost, and sustainable remediation materials. Among natural mineral resources, serpentinite has attracted increasing attention because of its abundance, Mg-rich layered silicate structure, hydroxyl-rich surface chemistry, and high potential for physicochemical modification. This review provides a comprehensive and integrative assessment of serpentinite-derived materials as multifunctional platforms for water remediation, linking mineralogical characteristics with material engineering strategies and environmental applications. The review first examines the crystal structure, polymorphism, surface functional groups, charge behavior, and textural properties of serpentine minerals and explains how these features control adsorption reactivity and interfacial interactions with aqueous pollutants. It then analyzes the physicochemical mechanisms governing pollutant removal, including surface complexation, ion coordination, dissolution-assisted immobilization, and precipitation pathways. Particular attention is given to material-engineering strategies that transform raw serpentinite into high-performance remediation materials, including thermal activation, acid and alkali modification, mechanochemical treatment, exfoliation into nanosheets, nanostructuring, and organic or inorganic surface functionalization. These modifications significantly enhance surface area, defect density, reactive hydroxyl environments, and pollutant accessibility, enabling remarkable adsorption capacities and improved catalytic interfaces. The review also highlights the emerging role of serpentinite as a support matrix and precursor for photocatalytic composites, where its surface chemistry facilitates pollutant preconcentration, catalyst dispersion, and charge-transfer processes. The synthesis of recent advances reveals key structure–property–function relationships that govern adsorption and photocatalytic performance and identifies major research opportunities in hybrid systems, emerging contaminant removal, and scalable environmental technologies.
Public attention to water-related hazards is shaped by the interaction of physical conditions, lived experience, media coverage, institutional communication, and access to digital information. This study examines how hydroclimatic anomalies correspond with public information-seeking behavior by constructing a global country-year panel covering 2004–2025. Six hydroclimatic screening indices derived from NASA POWER meteorological data, including drought, flood and extreme rainfall, water deficit, heat-related water stress, hydroclimatic volatility, and overall water risk, are matched with corresponding Google Trends topics. Heat-related water stress shows the strongest contemporaneous association with search interest, followed by flood and extreme rainfall, indicating that visible and immediately experienced hazards are particularly likely to stimulate online information seeking. The fixed-effects results reinforce this ordering and show that changes in hydroclimatic conditions are reflected in variations in search salience within countries over time. The analysis also reveals substantial geographical heterogeneity, demonstrating that the relationship between physical anomalies and public attention depends on national and local contexts. Country-year comparisons identify both convergence, where elevated hydroclimatic risk coincides with heightened search interest, and divergence, where environmental and informational signals follow different trajectories. These findings contribute to socio-hydrological research by integrating physical and digital indicators within a harmonized global framework. Google Trends is most valuable as a complementary measure of public information seeking that can help identify where hydroclimatic conditions become socially visible and where mismatches warrant closer investigation using local environmental, institutional, media, and communication data.
This study demonstrates both displacement and vibration monitoring of earth dams undergoing breach events using a computer vision-based measurement monitoring (CVMM) system. The system comprises a microcomputer equipped with computer vision algorithms to measure and compute changes in pixels of the chessboard images with 100 frames per second. In the study, the CVMM system was applied to indoor shake table and in-situ dam test using the analysis of vibration data from displacement, velocity, and acceleration. When dam breaching in the in-situ test, the maximum vertical displacement in the Y axis of the chessboard recorded by the CVMM system was 26.77 cm before the chessboard collapsed. There are two indicators evaluated for the dam breach in the case study. First is the amount of cumulative displacement that continued to increase until dam failure occurred. Second is the instantaneous energy of Hilbert–Huang Transform that showed a significant surge for an initial phase of dam breach. Consequently, the innovative CVMM system enables simultaneous monitoring of surface displacements, vibrations, and images. The vibration frequency of the CVMM instrument ranges from 0.1 to 50 Hz in the shake table and in-situ dam test, suggesting a non-contact monitoring and early-warning method in the dam breach test.
The rapid expansion of pumped storage power stations in China highlights a critical engineering challenge: ensuring the stability of large-span underground caverns excavated in intensely fractured, mosaic-fragmented rock masses under low in-situ stress. Taking the Liyang Pumped Storage Power Station as a case study, this research systematically investigates cavern instability mechanisms and corresponding support control technologies. Field investigations and theoretical analysis identify three predominant failure modes: block fall, crown collapse, and sidewall sliding. Cavern geometry and construction sequences were optimized via coupled Discrete Fracture Network (DFN) and Discrete Element Method (DEM) simulations, indicating a project-specific recommended rise-span ratio of 0.235–0.314 for a 25.5 m span and a recommended spacing of 40–50 m between the main and auxiliary caverns. Mechanistic evaluations further clarify the differentiated reinforcement effects of support elements using block beam thrust line and compressed arch theories; specifically, inclined bolts stabilize the arch by enhancing horizontal thrust, while vertical bolts improve load-bearing capacity through layer-integration effects. Guided by these insights, a collaborative support system—integrating mortar bolts, prestressed anchor cables, and steel arch ribs—was developed and implemented. Both field monitoring and numerical validation confirm that this system effectively constrains surrounding rock deformation and ensures construction safety. This work establishes a systematic, practical design framework for similar large-span underground projects in complex geological environments.
Groundwater-induced land subsidence is one of the most widespread geohazards associated with excessive groundwater exploitation, characterized by broad spatial extent and significant socio-economic impacts. However, conventional point-based monitoring techniques are unable to characterize the regional distribution of groundwater-induced subsidence. To address this limitation, this study integrates Persistent Scatterer Interferometric Synthetic Aperture Radar (PS-InSAR), terrestrial water storage (TWS), and distributed fiber optic sensing (DFOS) to establish a regional-to-stratigraphic framework for identifying groundwater-induced land subsidence and interpreting its subsurface deformation characteristics. First, PS-InSAR was employed to derive the regional surface deformation patterns. Subsequently, the temporal correspondence between InSAR-derived deformation and regional TWS variations was quantified using Pearson correlation analysis to identify areas strongly associated with groundwater-induced subsidence. Finally, borehole DFOS observations were used to identify the dominant compressible strata responsible for subsurface deformation. A case study in Suzhou, China, shows that surface deformation exhibited a strong temporal correspondence with regional TWS during periods of intensive groundwater exploitation, whereas this correspondence weakened following groundwater recovery because of delayed consolidation within low-permeability strata. The borehole observations further indicate that the dominant deformation is concentrated within the Ad2 and Ad3 aquitards adjacent to the Af2 confined aquifer. Overall, the proposed framework links regional surface deformation with depth-dependent subsurface deformation, providing an effective approach for investigating groundwater-induced land subsidence and supporting groundwater management and geohazard assessment.
Urban roadside soils are important repositories of traffic-derived contaminants; however, the coupled influence of anthropogenic emissions, contaminant transport, and soil-controlled retention processes remains insufficiently understood, particularly in rapidly urbanizing environments. This study developed and validated an integrated Source-Pathway-Sink framework by combining environmental magnetism, heavy-metal geochemistry, geotechnical characterization, spatial modelling, multivariate statistical analysis, and machine-learning techniques to investigate roadside contamination in Minna, North-Central Nigeria. Low- and high-frequency magnetic susceptibility, heavy-metal concentrations, contamination indices, and geotechnical parameters were integrated to evaluate contaminant distribution, transport, and retention behaviour. Spatial analyses revealed pronounced contamination gradients, with increase low-frequency magnetic susceptibility (χlf ) and heavy-metal concentrations occurring adjacent to major road corridors and decreasing systematically with increasing distance from traffic sources, confirming the dominant influence of vehicular emissions. Strong magnetic-geochemical relationships, particularly between χlf and Lead (Pb), demonstrated that magnetic susceptibility is a reliable proxy for traffic-derived contamination. Five-fold cross-validation of Simple Linear Regression and Random Forest models further confirmed the predictive capability of χlf for estimating the Heavy Metal Pollution Index (HPI). Vertical retention analyses showed maximum contaminant confinement within the 10–20 cm soil horizon, where low permeability, high plasticity, and enhanced adsorption capacity promoted contaminant accumulation. The proposed Vertical Retention Capacity Index (VRCI), supported by multivariate statistical analyses, successfully differentiated anthropogenic contaminant inputs from soil-controlled retention processes. The integrated SPWS framework provides a robust, rapid, and cost-effective approach for urban roadside contamination assessment, offering a transferable methodology for environmental monitoring, pollution mitigation, and sustainable urban planning in rapidly urbanizing regions.
Geological storage of CO₂ requires understanding how reservoir properties and operational parameters influence plume migration, pressure evolution, and long-term containment security. This study applies fully three-dimensional, physics-based simulations of continuous supercritical CO₂ injection into the Hammam Faraun member in the Gulf of Suez using COMSOL Multiphysics. A sensitivity analysis workflow was designed to include three scenarios to focus on the effects of fault permeability anisotropy, injector location, and operational parameters, including injection rate and the Brooks-Corey exponent (λ), on the dynamic behavior of CO2 in the porous medium. Results show that fault permeability anisotropy exerts control on plume size and geometry, with enhanced fault permeability in the z-direction. Injector locations strongly govern CO₂ plume geometry and propagation along faults. Injection rate influences plume size and migration extent in the reservoir and faulted zone. Variations in λ showed less influence on CO2 propagation and plume geometry. Despite these contrasts, well-bore pressures maintained consistent values across all cases, stabilizing between 13.8 and 14.8 MPa after 100 years of simulation time. The injector locations and injection rates influence the CO2 propagation more noticeably than fault permeability anisotropy and Brooks-Corey exponent, λ. Total amount of injected CO2 is estimated to be 7.9 Mt over 25 years injection period. This study provides a first reference case of a dynamic model for offshore CO2 storage in the Gulf of Suez. Hence, this research contributes to Egypt’s decarbonization goals and highlights the application of geological storage of CO2 in offshore reservoirs.
Microplastic (MP) pollution constitutes a pervasive and complex environmental crisis, with particles infiltrating ecosystems globally and posing multifaceted risks to ecological integrity and human health. The inherent heterogeneity of MPs (in size, shape, polymer type, and degree of weathering) coupled with their presence in complex matrices, presents formidable analytical challenges that constrain traditional detection, quantification, and source-tracking methods. This review synthesizes the transformative potential of Artificial Intelligence (AI) and machine learning (ML) in overcoming these bottlenecks and advancing every facet of MP research. This review details how AI-driven computer vision automates the morphological analysis of MPs, while ML algorithms enhance the speed and accuracy of spectroscopic polymer identification. Beyond analytics, AI facilitates predictive modeling of MP fate and transport, enables intelligent source apportionment, and optimizes emerging remediation technologies. Using the United States as a critical case study, we examine the interplay between a fragmented regulatory landscape and AI innovation. However, significant challenges persist, including data scarcity, algorithmic limitations, and the gap between laboratory validation and field deployment. The reviewed findings argue that the integration of AI represents a necessary paradigm shift, moving from descriptive observation to predictive and prescriptive science. For this potential to be fully realized, concerted efforts in standardized data generation, interdisciplinary collaboration, and the development of transparent, robust AI frameworks are urgently required to inform effective mitigation policies and remediation strategies on a global scale.
Gabbro is a coarse-grained mafic intrusive rock dominated by calcic plagioclase and clinopyroxene and widely used as a durable construction aggregate. This review evaluates gabbro as an application-specific sustainable geomaterial by linking its mineralogy, texture, alteration state, particle size, and Ca–Mg–Fe silicate chemistry to engineering, environmental, and carbon-management performance. Fresh plagioclase–pyroxene gabbro provides high strength, abrasion resistance, and durability for aggregates, pavements, and dimension stone, whereas quarry fines, stone powders, and selected altered fractions may support value-added applications in cementitious binders, alkali-activated systems, mineral wool, glass–ceramics, soil remineralization, reactive filtration, and mineral carbonation. The review emphasizes that gabbro is not a uniform or universally applicable material; its suitability depends on modal mineralogy, geochemistry, alteration degree, processing route, leaching behavior, and site-specific deployment conditions. The United Arab Emirates is presented only as a representative case study where abundant ophiolitic gabbro resources, mature quarrying infrastructure, industrial CO₂ sources, and sustainability priorities provide a practical context for evaluating integrated gabbro-based applications. Key research needs include mineral-specific reactivity data, standardized petrographic and geochemical screening, leaching and environmental-risk assessment, life-cycle analysis, techno-economic evaluation, and field-scale validation to support responsible and standards-compatible use of gabbro-derived materials.
Abandoned underground slate mines pose an increased collapse hazard within otherwise stable and well-managed landscapes. This paper presents three examples of remarkable gravity-driven processes in Czech slate mines—flexural toppling, rockfall, and sinkhole collapse—that have developed within broader geosystem interactions. These failures were investigated through field inspection, speleological mapping, and geological analysis. Dendrogeomorphological survey of flexural toppling at the Kunz Mine provides unique, pioneering data on the historical development of this type of gravitational failure. Rock mass failure and subsequent collapse depend not only on long-term factors—such as mineral composition, geological structure, topography, and methods of underground excavation—but also on current environmental conditions, including water and airflow, humidity, freeze–thaw cycles, and mineral weathering. The resulting cascades of weathering and erosional processes repeatedly drive the mines into states of instability. To better understand the chain of processes leading to the loss of stability equilibrium, it is therefore essential to consider the broader spatiotemporal relationships among the individual landscape features in which the abandoned mines are embedded.
The apportionment of naturally occurring radionuclides (238U, 232Th, and 40K) within granite samples supplies essential data related to heat generation and thermal properties of the crust. Radiogenic heat production (RHP) was estimated in this work for granite rocks gathered from the Raparin region within Kurdistan, Iraq. A total of 45 granite samples were examined through HPGe gamma-ray spectrometry to evaluate the concentration levels of 238U, 232Th, and 40K. The radionuclide concentrations displayed substantial discrepancy across the investigated rock samples, indicating variation in fundamental enrichment and geological development within the granitoid bodies. The average value of RHP is 2.55 µW m− 3 and the range varied from 1.72 to 3.76 µW m− 3. The obtained RHP values recommended moderate radiogenic heat contribution. The contribution of three nuclides to total heat production is sequenced as 238U> 232Th> 40K. The heterogeneous distribution patterns of the radionuclides and RHP were revealed through spatial analysis. Thus, the differentiation in magmatic and irregularity in regional geology could impact the thermal properties of the Zagros structure. Finally, this study provides advanced baseline radiogenic information for granite rocks for the Zagros Fold-Thrust Belt and contributes a new database for limited geothermal for the Kurdistan region of Iraq.
Conventional data-driven methods for slope stability analysis often exhibit an over-reliance on data while neglecting underlying physical principles. To address this limitation, this study proposes a physics-informed neural network (PINN) framework that integrates a neural network surrogate with the elastoplastic deformation mechanism of soil slopes. The governing equations incorporating the elastoplastic constitutive model based on the Mohr–Coulomb yield criterion, along with the boundary conditions, are embedded into the training framework of the PINN. The PINN functions as a surrogate model that requires no pre-constructed training dataset and automatically satisfies both the governing equations and the boundary conditions. Consequently, the developed PINN can directly predict the displacement field of a slope and automatically derive the associated stress–strain fields that comply with the deformation mechanism. These outputs are coupled with the multi-initial point sequential quadratic programming (MSQP) algorithm and the slip surface stress analysis (SSSA) method, enabling the efficient identification of the critical slip surface and the calculation of the corresponding factor of safety (FOS). The proposed method is validated through two illustrative examples. Comparisons of the results with those from commercial software confirm the high accuracy of the proposed method in predicting the stress–strain response and the FOS. This study provides a data-driven and physics-informed paradigm for slope stability analysis grounded in clear physical mechanisms.
This study maps the global landscape of geospatial-based landslide susceptibility research through a bibliometric analysis of Scopus-indexed publications from 2015 to 2025. OpenRefine was used for metadata cleaning and VOSviewer version 1.6.20 was applied for keyword co-occurrence and country co-authorship mapping. A total of 2,002 articles were identified, with a clear increase in publication output after 2019. The analysis identified five main thematic clusters: remote sensing and geospatial technologies, machine learning-based vulnerability modeling, geotechnics and slope dynamics, multi-hazard approaches and climate adaptation, and GIS-based empirical approaches. China, India, Italy, and the United States emerged as the main contributors in publication output, citation performance, and collaboration strength, while Remote Sensing, Landslides, and Natural Hazards were the leading publication outlets. These findings suggest an emerging shift from conventional GIS-based mapping to an integrated Geospatial-AI approach, supported by big earth data, cloud computing, and artificial intelligence. This study highlights the need for cross-regional collaboration, multi-source data integration, and transparent predictive models for environmental risk reduction.
Dam failures represent a significant hazard to downstream, particularly when combined with extreme hydrological inputs and uncertainties in breach development. In this study, a comprehensive hydrological and dam breach modeling framework was applied to the Kanlikoy Dam in Cyprus. The HEC-HMS model was calibrated with the 2010 Flood event. Subsequently, a comprehensive sensitivity analysis identified the Curve Number (CN) and Muskingum K as the most influential parameters. Uncertainty analysis produced maximum and minimum inflow hydrographs for both the calibrated hydrograph and 100-year return period hydrograph. These hydrographs were coupled with probabilistic overtopping and piping failure simulations in McBreach, where breach width, side slopes, failure mode, and formation time were sampled stochastically. The probabilistic dam breach framework was then applied to evaluate flood responses at probabilistic breach scenarios of 1
Reactive magnesium oxide (MgO), characterized by its high reactivity, large specific surface area, and mesoporous structure, can rapidly sequester CO2 through hydration-carbonation reactions. Hence, MgO is a promising material for carbon sequestration. However, the effects of MgO on soil CO₂ fluxes and carbon storage dynamics remain unveiled. In this study, a 180-day incubation experiment was conducted to assess the effects of MgO with different effective contents (92
Groundwater is a vital resource that supplies nearly half of the world’s population and sustains ecosystem integrity. In the Santa Rosa River basin (SW Ecuador), groundwater plays an essential role due to the variable quality of surface water resources. This study assessed groundwater contamination risk based on the premise that floodplain sectors with shallow water tables and high permeability are more susceptible to contamination, with the aim of supporting environmental management priorities. Cartographic and secondary data were integrated with field investigations. Intrinsic vulnerability was assessed using the GOD and DRASTIC methods, whereas contamination hazards were evaluated using the POSH approach, supported by in-situ measurements of water-table levels and physicochemical parameters. The GOD method classified the basin into negligible (371.18 km²; 49.31
Based on hierarchical cluster analysis, this paper used the Kolmogorov–Zurbenko filter and the Hysplit model to analyze the causes of O3-8 h concentration exceedances and the potential source contribution areas across various sub-regions in the Yangtze River Delta urban agglomeration in China. The results indicated that the number of days affected by ozone exceedances in the Yangtze River Delta urban agglomeration averaged 168.1 ± 1.7 days·yr− 1 from 2015 to 2024, and its annual increase was 3.5 ± 0.4 days·yr− 1. During the warm season, the phenomenon of exceedances in the regions surrounding the estuaries of the Yangtze River and Qiantang River, as well as the northern plains and the southern Anhui hilly areas, was primarily attributed to abnormal weather, anthropogenic emissions, or intensity of medium- to small-scale atmospheric circulation transport. Among them, the potential sources of excess ozone in the plains were not only locally concentrated but also concentrated in areas along the coastal economic belt of the North Yellow Sea. However, the formation of heavy pollution was mostly controlled by abnormal anthropogenic emissions during the local weather change process under low wind speeds. The potential sources in the latter were similar to those in the Zhejiang-Fujian hilly area. The local sources were the causes of small-scale ozone pollution formation, while the external input was not only the cause of large-scale pollution, but also the main cause of heavy pollution that exceeded the Grade II Standard. In the southeastern coastal area, the sea-land breeze could not only promote the diffusion of ozone pollutants controlled by local meteorological variables, but also promote the input of pollutants from the Zhejiang-Fujian hilly area along the westward path to form excessive ozone.
Soil organic matter (SOM) is a crucial indicator of soil quality and carbon sequestration capacity. In regions with complex topographic and climatic gradients such as Anhui Province, the spatial patterns of SOM and its environmental controls remain insufficiently characterized. This study collected 151 soil samples in 2010 across Anhui Province and derived environmental covariates using GIS and RS technologies. Random Forest, Gradient Boosting, Extra Trees, and LightGBM models were constructed and compared. The Extra Trees model achieved the best performance, with a test-set R² of 0.79, RMSE of 4.55 g/kg, and MAE of 3.66 g/kg. In four-block spatial cross-validation, the R² decreased to 0.60, indicating moderate but limited spatial transferability. The predicted SOM pattern was higher in the southern mountainous region and lower in the northern plains. Nitrogen had the largest model contribution (56.8
