Search Results (1,130)

A thorough understanding of the resistivity response characteristics of ethanol-contaminated soil is of great significance for the development of non-destructive geophysical detection techniques and for supporting contaminated site investigation and assessment. This experimental study aims to systematically investigate the resistivity behavior of ethanol-contaminated sandy soils, with a focus on the coupled mechanisms of multiple factors, including water content, ethanol concentration, particle size distribution, and contamination time. It is hypothesized that water content serves as the dominant factor controlling resistivity, whereas ethanol concentration and contamination time regulate resistivity by altering the physicochemical properties of the pore fluid. Under laboratory conditions, silt, fine sand, and medium sand were selected as the test materials. Resistivity was systematically measured using a Miller Soil Box with increasing water content, Wenner array configuration across varying water contents (3–24%), ethanol concentrations (40–98%), and contamination durations (0–144 h). The experimental results indicate the following: (1) Regardless of the presence of ethanol contamination, the resistivity of sandy soil decreases with increasing water content following a power-law relationship. The decrease is most pronounced at low water contents (3–9%), and gradually stabilizes at higher water contents. The results show that, at a constant water content, resistivity systematically and consistently follows the order: silt > medium sand > fine sand. (2) The influence of ethanol concentration on resistivity is constrained by water content levels, and the overall increase in resistivity is primarily attributed to ion dilution and the obstruction of conductive pathways. (3) Over time, resistivity exhibits a two-stage increasing trend, associated with ethanol volatilization and water loss. Resistivity changes in fine sand samples contaminated with ethanol at concentrations ranging from 75% to 95% follow a two-stage pattern. The initial phase of growth is characterized by a gradual increase over a period of 0–48 h, followed by a more rapid increase during the subsequent phase, which extends from 48 to 144 h. The results show that higher initial ethanol concentrations enhance the sensitivity of resistivity to temporal changes. Comprehensive analysis indicates that the resistivity variation mechanism under multi-factor coupling conditions can be summarized as follows: the water content is the dominant factor in the regulation of the conductive pathways; the particle size distribution determines pore structure and the characteristics of the particle interface; ethanol concentration and contamination time dynamically alter pore fluid properties, collectively regulating the resistivity response. Although the experiments were conducted under controlled laboratory conditions and the results have certain limitations, they provide a preliminary reference for interpreting resistivity responses in relatively homogeneous sandy contaminated sites and offer theoretical support for the application of resistivity methods in contamination identification and dynamic monitoring. Full article

Runway microtexture is a key parameter governing pavement friction. In recent years, several microtexture assessment methods have been developed; however, understanding of microtexture evolution under operational conditions, as well as the effects of maintenance techniques, remains limited. In this study, a runway at an Australian airport was investigated using laser profilometry. Measurements were conducted across multiple transverse sections, including aircraft touchdown and mid-runway zones. Microtexture deterioration rates were evaluated based on the estimated number of tire–pavement contacts, and aggregate polishing was assessed at different locations. Measurements were also performed after rubber contamination removal and rejuvenation treatments. The results indicate that approximately 25% of total microtexture reduction can be attributed to surface polishing, with a lower contribution in touchdown zones due to the protective effect of rubber deposits. A non-linear degradation trend was observed in touchdown zones, where approximately 1100 tire contacts reduced average microtexture roughness from 18 μm to 11 μm. Rubber removal effectively restored microtexture close to its original levels across the runway width. A rejuvenation treatment with a covering of fine sand initially improved microtexture; however, rapid deterioration occurred due to loss of the sand coating. These findings improve the understanding of microtexture evolution under operational runway conditions, albeit only at a case study level, and support more effective runway maintenance planning and intervention strategies. Full article

The Middle Triassic Tredian Formation of the Salt Range, Pakistan, consists of sandstones with interbedded shale in the lower part and minor dolomite in the upper part. Conventional grain-size analysis has been widely used as a sedimentological tool to elucidate depositional environments and the mode of transportation of detrital sediments. This study presents the first integrated application of a Decision Tree Classifier (a machine learning model) with field and petrographic evidence to interpret grain-size statistics for the analysis of depositional environments of the Tredian Formation in the Salt Range, Pakistan. Stratigraphic sections of the Tredian Formation were measured and sampled in the Nammal Gorge and Zaluch Nala in the Salt Range for detailed sedimentological and grain-size analyses. The lower part of the Tredian Formation (Landa Member) consists of interbedded sandstone and shale (LF-1) characterized by large-scale slumps, parallel lamination, ripple marks, and cross-bedding. The LF-1 is overlain by the Katkhiara Member, which is dominated by thick sandstone (LF-2) with planar and trough cross-bedding and contains dolomite beds (LF-3) in the upper part. Grain-size statistics show that the sandstones are fine-to-medium-grained, well-to-very-well-sorted, near-symmetrical, and very platykurtic. Machine learning-based bivariate plots suggest that most of the samples are grouped, with some showing scattered trends. The Linear Discriminant Function (LDF) analysis indicates that the Tredian Formation was deposited in fluvial–deltaic to shallow marine environments with sand reworking and redistribution under aeolian/beach settings. The Decision Tree Classifier Model (DTCM) predicted fluvial to shallow marine depositional environments for the Tredian Formation and shows strong agreement with field-based lithofacies interpretation, demonstrating its reliability as a predictive tool. Thus, the present study demonstrates that integrating grain-size-based machine learning and statistical analysis with traditional sedimentology provides valuable insights into depositional settings and enhances the reliability of interpretations of ancient sedimentary environments. Full article

With the increasing frequency of desilting in urban drainage systems, the safe disposal and resource reuse of sewer sediments have become a prominent practical challenge. Screened sand, the most promising component for resource recovery from sewer sediments, still lacks systematic insight into its pollution risks and the necessity of pretreatment. In this study, 120 raw sewer sediment samples were collected from sanitary, storm, and illicitly connected (IC) storm sewers in Shanghai, alongside seasonal screened sand samples. We systematically characterized their physicochemical properties and heavy metal and antibiotic pollution profiles, and evaluated the purification performance of ultrasonic treatment, sodium hexametaphosphate (SHMP) washing, and their coupled processes. Results revealed significant differences in sediment properties across pipeline types. Screened sand, dominated by SiO₂ and CaO, shows preliminary potential for reuse as a low-grade bulk building material, but its organic loss on ignition (LOI) of 5.29–13.42% exceeded the reuse limit. Concentrations of heavy metals and antibiotics were generally higher in screened sand than in raw sediments, with further enrichment in the fine sand fractions, indicating that screening only redistributed contaminants rather than eliminated them. The coupled ultrasonic–SHMP process, applied for the first time to screened sand from sewer sediments, achieved optimal performance, with a maximum LOI reduction and over 85% removal of certain antibiotics, without damaging the sand’s mineral skeleton. This study provides a scientific basis for the safe resource reuse of screened sand. Full article

Small Mediterranean coastal lagoons are sensitive sedimentary environments where basin morphology, hydrodynamic processes, and inherited coastal structures interact to control sediment dispersal. This study investigates modern sedimentary patterns in Lake Porto Vecchio, a shallow coastal brackish pond within the Oliveri–Tindari lagoon system (NE Sicily, Italy), by integrating grain-size statistical and petrographic analyses, and morpho-bathymetric data. A total of 115 surface sediment samples were collected from the coastal pond’s shallow bottom, shoreline, adjacent beach, and shallow marine sector. Grain-size distributions were analyzed using mechanical sieving and laser diffraction, and textural parameters were calculated following Folk and Ward’s formula. Results reveal a well-defined spatial organization of siliciclastic sediments characterized by a grain-size gradient from gravelly coarse-grained sands along the shallow marginal platform to fine-grained sands and silts toward the deeper central basin. This pattern reflects a progressive decrease in hydrodynamic energy from the lagoon margins toward the basin depocenter. A partially lithified beachrock belt forms a shallow platform controlling sedimentation, trapping coarse sediments along the margins while promoting the accumulation of finer fractions in the inner basin. Grain-size discrimination diagrams further distinguish lagoonal sediments from adjacent marine deposits, highlighting the effectiveness of classical statistical approaches in reconstructing modern sedimentary processes. These results support a conceptual model in which inherited beachrock platforms act as key morphological control on sediment architecture in microtidal coastal lakes. Lake Porto Vecchio, therefore, represents a useful modern analog for interpreting similar lagoonal deposits preserved in the Quaternary sedimentary record. Full article

Although the accurate lithological segmentation of outcrops plays a key role in hydrocarbon exploration, complex field environments and substantial scale variations within outcrops, particularly in extremely thin sand–mudstone interbeds, present considerable obstacles to precise segmentation. To overcome these complexities, we propose a Residual Attention Mechanism-Guided Asymptotic Feature Pyramid Network (AFPN-ResUNet). This architecture employs a structurally optimized RE-CBAM, which seamlessly integrates a Convolutional Block Attention Module (CBAM) into the residual network framework. This mechanism dynamically recalibrates channel and spatial feature responses, thereby effectively suppressing background artifacts while accentuating salient geological boundaries. Furthermore, we abandon traditional naive feature concatenation and instead utilize automatically generated spatially adaptive weights to guide the asymptotic fusion of features across different layers. This asymptotic fusion strategy effectively resolves the semantic discrepancies between distinct network levels, preserving the fine-grained spatial details crucial for delineating ultra-thin interbedded lithologies. To evaluate the architecture, a dedicated outcrop dataset was constructed. Compared to representative baselines (UNet, Vision Transformer, DeepLabV3+, PSPNet, and SegNeXt), AFPN-ResUNet achieves an mIoU of 93.41%, outperforming the baseline models by margins of 23.20%, 23.92%, 12.40%, 12.38%, and 26.04%, respectively. Additionally, ablation studies indicate that incorporating RE-CBAM and AFPN modules improves the mIoU by 13.11% and 13.98% over the backbone, respectively. These quantitative results demonstrate that AFPN-ResUNet effectively mitigates boundary blurring and preserves spatial continuity, an advantage visually corroborated by the Grad-CAM heatmaps. Notably, despite a relatively longer inference latency (33.99 ms), the model maintains a low computational overhead (179.79 G FLOPs), underscoring its practical application potential for outcrop lithology segmentation. Full article

Sand ridge lines serve as key geomorphological indicators for interpreting aeolian dynamics and assessing desertification intensity. However, automated extraction of continuous ridge structures from remote sensing imagery remains challenging due to the multi-scale morphology of dunes, complex surface textures, and strong shadow interference. Conventional edge detection models often rely on computationally heavy backbones or suffer from structural discontinuities in subtle ridge branches, limiting their applicability in large-scale desert monitoring. To address these challenges, we propose Rid-HRNet, a lightweight high-resolution network specifically designed for efficient and structurally coherent sand ridge extraction. Unlike traditional encoder–decoder architectures, Rid-HRNet maintains parallel high-resolution representations throughout the network to preserve fine spatial details. A Multi-Scale Information Aggregation (MSIA) module enhances cross-scale feature interaction by integrating shallow structural cues with deeper semantic representations. In addition, an Improved Contextual Fusion Module (ICFM) employs pixel-wise attention to adaptively fuse multi-level predictions, reinforcing ridge continuity while suppressing background interference. Experiments on Landsat-8 desert imagery demonstrate that Rid-HRNet achieves an Optimal Dataset Scale (ODS) of 0.790, an Optimal Image Scale (OIS) of 0.806, an Average Precision (AP) of 0.710, and an AC(R50) score of 0.744. The proposed model outperforms classical VGG-based detectors, including HED and RCF, as well as recent lightweight baselines such as PiDiNet and LDC, in terms of overall accuracy and structural consistency. Notably, Rid-HRNet contains only 0.20M parameters and requires 0.55 GFLOPs, operating at 279.23 FPS with a GPU memory footprint of 0.02 GB. These results indicate that Rid-HRNet achieves a favorable balance between detection performance and computational efficiency, supporting large-scale geomorphological mapping and operational desert monitoring based on high-resolution satellite imagery. Full article

The large-scale generation of asphalt dust waste (ADW) has raised increasing environmental concerns, while its high-value utilization in cementitious materials remains insufficiently explored, particularly in terms of mechanical performance, durability-related properties, and integrated sustainability evaluation. In this study, a graded utilization strategy based on particle size was proposed to incorporate ADW into alkali-activated concrete paving blocks, in which fine ADW fraction (<0.075 mm) was used as a partial replacement of blast furnace slag (BFS), while the coarser ADW fraction was used as a partial replacement of river sand, aiming at sustainable pavement applications. In addition, two types of ADW with different lithologies, namely limestone ADW and basalt ADW, along with their combined system, were investigated. The results show that the incorporation of ADW effectively enhances the engineering performance of paving blocks. The compressive strength increased from 45.3 MPa to 56.6 MPa, while water absorption decreased from 5.3% to 4.1%. All mixtures satisfied the requirements for abrasion resistance and slip resistance, demonstrating their compliance with the performance criteria for pedestrian pavement applications. Among all mixtures, the combined use of limestone ADW and basalt ADW exhibited the best overall performance. The improved performance may be attributed to the combined effects of graded particle utilization and the potential compositional complementarity between calcium-rich limestone ADW and silica–alumina-rich basalt ADW, which is consistent with the denser microstructure observed in SEM images. In addition, the proposed strategy contributes to improved solid waste utilization and reduced consumption of natural resources, as reflected in the quantitative sustainability assessment. Overall, this study demonstrates that graded utilization of ADW is a feasible approach for developing alkali-activated paving materials, with promising performance and sustainability potential. Full article

To explore the regulatory mechanisms of different vegetation types on soil crust grain-size characteristics in sandy lands, this study focused on five typical plant species (Haloxylon ammodendron, Artemisia ordosica, Nitraria tangutorum, Agriophyllum squarrosum, and Phragmites australis) in an artificial vegetation restoration area on the northeastern edge of the Ulan Buh Desert. Using laser granulometry and graphical methods, we systematically determined the soil particle size composition and parameters of the crust (Layer A) and sub-crust (Layer B) layers, and analyzed their correlations with plant morphological parameters (crown width, plant height, basal diameter). The results showed that (1) different vegetation types significantly increased the content of soil fine particulate matter (silt and clay), with fine sand accounting for 42.85% and silt accounting for 23.64%; (2) there are significant differences in the impact of different vegetation types on particle size parameters. The average particle size of soil crust under Phragmites australis is the smallest (1.91), and the sorting is the worst (standard deviation 2.01). Under the vegetation type of Nitraria tangutorum, the average particle size of the soil crust layer is the largest (5.25), and the fractal dimension is the highest (2.46). (3) The crown width, plant height, and basal diameter of vegetation are negatively correlated with mean particle size, kurtosis, and fractal dimension (r= −0.62 to −0.45), and positively correlated with standard deviation and skewness (r = 0.51 to 0.68). (4) The frequency curve indicates that vegetation types broaden the distribution range of soil particles, and Phragmites australis and Artemisia ordosica exhibit bimodal characteristics. This study reveals the impact of vegetation restoration on soil grain size parameters in arid regions. These findings provide actionable strategies for optimizing vegetation configuration in actual desert restoration projects, notably proposing a “herbs first, shrubs follow” approach that can be directly applied to enhance restoration efficiency. Full article

The thermal conductivity (λ) of porous rocks as a function of total porosity, grain size, and fluid saturation is measured and modeled by combining high-precision experiments with a Staged Differential Effective Medium (SDEM) modeling framework. A 1-D divided-bar apparatus with computer-controlled guard heaters with an integrated ultrasonic pulse-transmission system was developed to measure the thermal conductivity and P and S-wave velocities simultaneously. Measurements were made on Fontainebleau sandstone cores and quartz sand packs of varying grain size and effective stresses up to 2000 psi. The sample properties were measured in both dry and water-saturated states. The SDEM model performs significantly better at predicting the saturated thermal conductivities in the sand packs. For the sand packs, the thermal conductivity and compressional velocity are the highest and most stress-sensitive for the fine-grained material. In contrast, the shear velocity is largest in the coarse-grained material. The SDEM model is adapted from previous acoustic models for use in understanding thermal conductivity. These joint models accurately reproduce the evolution of both thermal conductivity and bulk modulus during increasing compaction and varying saturation. A single parameter fits both the dry and saturated data, which allows Gassmann-style fluid substitution for the thermal conductivity. This model improves the prediction of in situ thermal conductivity from sonic well logs. Full article

Soil thermal conductivity is a key parameter in modeling heat transfer, temperature-driven moisture migration, artificial ground freezing, and geothermal systems. However, most existing thermal-conductivity models do not account for temperature effects. This study aims to determine the temperature-dependent thermal conductivity of silty and fine sandy soils at elevated temperatures using a steady-state heat cell method, addressing the limitations of transient probe techniques, which are affected by air voids and heat loss at the needle–soil interface. The experiment employs a heat cell under one-dimensional steady-state heat-transfer conditions, with sufficiently small temperature gradients to prevent temperature-induced moisture migration, and measures the soil’s thermal properties at steady state by indirect temperature and heat-flux measurements using various sensors. The test observations showed well-correlated thermal conductivity readings from steady state and transient probe methods at room temperature. Furthermore, the measured thermal conductivity of the sandy soil demonstrated a near-linear increase with temperature, with the highest dependence at 15.1% and 22.5% saturation for Benbrook (SM) and fine-grained Ottawa (SP) sands, respectively. Several commonly used existing thermal conductivity models were used to fit the measured thermal conductivity. A new thermal conductivity model was developed, incorporating a temperature-dependent correction based on the best-fit model. The proposed model could more accurately capture the increased thermal conductivity of soils with temperature. The findings will significantly improve the modeling of soil-temperature-dependent multi-physics behavior. Full article

Riparian ecosystems are being increasingly threatened by hydrological alteration and biological invasions, yet the role of local environmental heterogeneity in shaping invasion dynamics remains poorly understood. To address this, we tested the hypothesis that invasion patterns are spatially structured and therefore cannot be fully captured by global statistical models. We evaluated this hypothesis by analysing the relationship between soil sand content and the abundance of Gleditsia triacanthos in a riparian forest of the Esteros de Farrapos and Islands of the Uruguay River National Park, Uruguay. Generalized Linear Mixed Model revealed no significant relationship between soil sand content and G. triacanthos abundance (χ² = 1.93, p = 0.17). In contrast, spatially explicit analyses showed that relationships between sand content and abundance were spatially contingent. Positive linear relationships predominated in areas with low sand content (mean 24.5%, n = 12), while negative relationships were restricted to the highest sand levels (mean 87.6%, n = 3). Intermediate sand-content zones (mean 47%, n = 16) showed no consistent patterns. These results suggest that invasion patterns vary across spatial contexts and may reflect the influence of different processes operating locally, indicating that relying solely on global analyses risks misinterpreting drivers and overlooking fine-scale variation. Our findings emphasize that understanding invasive species in heterogeneous systems requires considering whether mechanisms operate at local or broad scales, and that explicitly analyzing spatial structure can guide both hypothesis formulation and field study design. Full article

Durability of clay-based mixes is often considered a limitation for their use in modern construction projects, especially in those involving additive manufacturing techniques. This study focuses on developing sustainable extrudable cob mixes and investigating the effect of sand particle grading, curing regime and mix composition on compressive strength, flexural strength, stress–strain response, capillary water absorption, wetting-drying cycles effect, and abrasion resistance. Results showed a significant positive impact of fine-sized sand addition into the mix on the mechanical strength and durability, due to better compaction and denser final cob mixes. Extending oven curing improves the compressive and flexural strength of all mixes due to the accelerated strength development from the higher temperature exposure. Lastly, the addition of high clay content allows for improving the compressive and flexural strength at prolonged curing aging under normal air-drying conditions. These mixes also exhibit low water absorption. Conversely, results revealed that the lime content plays a crucial role in reducing surface wear, with lime-rich mixes exhibiting lower erosion rates than the other mixes. Lime-stabilized cob mixes also demonstrate improved durability under cyclic wetting and drying. Full article

The conservation of tuff- and coral rock-built architectural heritage structures (AHS) is challenging because access to original tuff and coral rock has become difficult and severely limited due to urbanization, land reclamation, the depletion of stone quarries, anti-mining and anti-quarrying legislation. An emerging approach to address this issue is to create compatible “replacement” rocks via geopolymerization, a process that is more sustainable and greener than the use of conventional cement and concrete. To explore the potential of geopolymers for AHS conservation strategies, the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines were implemented; 103 eligible articles were identified and classified into geopolymers for AHS (34 articles), tuff-built AHS (60 articles), and coral rock-built AHS (9 articles). Tuff substrates in AHSs appear in a variety of colors (yellowish-brown, grayish-cream, reddish-brown, pale greenish-gray and pink hues), densities (1.0–2.5 g/m³), and compressive strengths (3–100 MPa). Meanwhile, coral rock substrates in AHSs appear in whitish-cream color and are coarse-pored (1–5 MPa), fine-grained (8–15 MPa), and calcarenite (50–60 MPa). In terms of geopolymer formulation, metakaolin was reported as the most popular main precursor or admixture, while NaOH and Na₂SiO₃ were used simultaneously as alkaline activators. Aggregates used in geopolymer formulations depended on local availability, including quartz sand, river sand, crushed stones, carbonate stones, volcanic rock, volcanic sand, tuff, brick, ceramic tiles, and waste materials. Aesthetics, chemical composition, physical attributes, and mechanical properties have been identified as key criteria to ensure geopolymer compatibility for AHS conservation application. To date, geopolymers have been applied for AHS conservation as repair mortars, consolidants (i.e., grout and adhesives), and masonry strengthening (i.e., fiber-reinforced mortar). Finally, geopolymers formulated for AHS conservation have similar durability as the original substrate based on accelerated aging tests (i.e., salt mist, wet-dry, and freeze–thaw) and long-term outdoor exposure experiments. Full article

Nabkhas are a common type of biogenic aeolian landform in arid and semi-arid regions. Their morphological characteristics, surface sediment grain size composition, and spatial distribution patterns can, to some extent, be associated with the interactions between vegetation and the aeolian environment. In this study, nabkhas formed around Caragana tibetica shrubs in the desert steppe of Damao Banner, Inner Mongolia, were selected as the research object. Based on field investigations, UAV image identification, grain size analysis, and spatial point pattern analysis, the characteristics of nabkhas were comparatively analyzed among a control plot without shrubs (CK) and three shrub-covered plots: a low coverage plot (LCP), a medium coverage plot (MCP), and a high coverage plot (HCP). The results showed that (1) some morphological parameters of nabkhas varied among plots with different vegetation cover, but the responses of various indicators were not entirely consistent. The MCP exhibited relatively higher values in indicators such as shrub long axis (L_g), short axis (W_g), and windward slope length (L_y). (2) The surface sediments of nabkhas were mainly composed of silt and fine sand, followed by very fine sand. Compared with the CK, the silt content was generally lower in the shrub-covered plots, whereas the contents of fine sand and very fine sand were higher. The mean grain size (Mz, Φ value) tended to decrease, while the skewness (SK_G) and kurtosis (K_G) tended to increase, and the sorting coefficient (σ_G) showed relatively limited variation. (3) In the LCP, MCP, and HCP, the fractal dimension (D) was significantly positively correlated with the Mz and σ_G (p < 0.05), and significantly negatively correlated with the SK_G and K_G (p < 0.01), suggesting that the D may be associated with variations in sediment grain size structure. (4) Overall, the nabkhas around Caragana tibetica shrubs exhibited a spatial distribution pattern characterized by aggregation at small scales and randomness at large scales, with small-scale clustering being more evident in the MCP and HCP. In general, nabkhas around Caragana tibetica shrubs under different vegetation cover conditions showed observable differences in morphological characteristics, surface sediment grain size composition, and spatial distribution patterns, providing a comparative case reference for the study of nabkhas in desert steppe areas. Full article