Search Results (1,714)

Soil health monitoring is critical for the sustainable management of the black soil region, a key resource for global food security. However, traditional field surveys are constrained by high operational costs, limited spatial coverage, and low temporal frequency, making them inadequate for high-resolution and time-sensitive soil monitoring. The recently launched ZY1-02E satellite, equipped with an advanced hyperspectral imager, offers a new potential data source, yet its capability for quantitative soil modelling requires rigorous cross-sensor validation. This study conducts a cross-sensor evaluation of ZY1-02E and its predecessor, ZY1-02D, for mapping soil organic matter (SOM) and soil texture (sand, silt, and clay) in Northeast China. Optimal spectral indices were constructed through exhaustive band combination and correlation screening, and quantitative inversion models were established using a hybrid framework integrating Random Frog feature selection with Gaussian Process Regression (GPR) and Boosting Trees, based on synchronous ground observations. Results demonstrate strong cross-sensor consistency, with spectral indices showing significant linear correlations (${\mathrm{R}}^2>0.65$) between ZY1-02E and ZY1-02D. Furthermore, the quantitative retrieval models applied to ZY1-02E imagery achieved robust performance, with cross-sensor retrieval consistency exceeding ${\mathrm{R}}^2=0.60$ for all parameters and SOM exhibiting the highest agreement (${\mathrm{R}}^2=0.74$). These findings confirm the radiometric stability and algorithm transferability of ZY1-02E, demonstrating its capability to generate soil parameter products comparable to ZY1-02D without extensive model recalibration. The validated interoperability of the twin-satellite constellation substantially enhances temporal observation capacity during the narrow bare-soil window, effectively mitigating cloud-induced data gaps in high-latitude agricultural regions. Importantly, the enhanced monitoring framework provides a scalable technical paradigm for high-frequency hyperspectral soil mapping, offering critical spatial decision support for precision fertilization, soil degradation mitigation, and conservation tillage management in the Mollisol belt. Full article

Fine migration is widely recognized as a primary cause of production decline in unconsolidated sandstone reservoirs. Migrated fines may accumulate within pore throats and obstruct flow channels, or they may be transported into the wellbore with the produced fluids, leading to operational issues such as wellbore plugging, pump sticking, and equipment abrasion. Despite extensive studies on fine migration, the role of particle wettability has received limited attention. In this study, the mineralogical composition of formation particles was first characterized using X-ray diffraction (XRD) and quantitative clay analysis. Surface modification experiments were then conducted to investigate the effect of hexadecylamine (HDA) on particle wettability and to determine the optimal reaction conditions. Surface characterization techniques were employed to elucidate the modification mechanism. Subsequently, sand-packed tube displacement experiments were performed to evaluate the influence of wettability alteration on fine migration behavior. The underlying mechanisms were further interpreted through interfacial thermodynamic analysis. Two potential field application schemes are proposed to facilitate practical implementation in oilfield operations. The results indicate that the water contact angle of formation particles increased from 0° to 150° when treated with 0.8 wt% HDA for 24 h. Surface characterization confirms that HDA molecules were physically adsorbed onto the particle surfaces. Displacement experiments demonstrate that the permeability reduction rate decreases significantly with increasing particle hydrophobicity. Thermodynamic analysis suggests that the work of adhesion on the modified particle surface was reduced by 93.3%, thereby weakening fluid–particle interfacial coupling and suppressing fine mobilization. This study provides a wettability-based approach for mitigating permeability damage caused by fine migration in unconsolidated sandstone reservoirs. Full article

Soil salinity poses a major challenge to agricultural productivity, especially threatening food security in arid and semi-arid areas. Traditional soil reclamation methods, such as leaching, chemical amendments, and drainage engineering, usually need large amounts of water, involve high costs, and can lead to environmental problems. This review compiles existing knowledge on innovative strategies for managing saline soils, focusing on buried interlayer systems that use materials like straw, sand, gravel–sand mixtures, and biochar. These interlayers improve soil hydraulic properties by preventing capillary rise, encouraging salt leaching, and reducing surface salt buildup. Biochar stands out as a particularly useful material because of its stability, large surface area, porosity, and high cation exchange capacity. These features help improve soil structure, increase water retention, and effectively retain sodium. Evidence from lab and field tests shows that buried biochar layers can stop salt from moving upward, aid in desalinating the root zone, and boost crop yields. While straw and sand interlayers show potential in reducing salinity, biochar is noted for its multifunctionality and long-term effectiveness in addressing salinity problems. The success of buried biochar systems depends on several factors, including the properties of the biochar, how much is used, how deep it is buried, and the specific soil and climate conditions. This review highlights how these systems work, compares their performance, and points out research gaps, advocating for their potential as a sustainable, resource-efficient way to manage salinity and improve soil health over the long term. A substantial proportion of the existing evidence is derived from controlled laboratory studies, and the buried biochar layer approach remains an emerging technique that requires further validation under field conditions. Still, significant knowledge gaps persist regarding long-term performance and water-salt dynamics, while site-specific soil variability and scalability challenges may limit the effective implementation of biochar interlayer systems under field conditions. Full article

This study explores the use of diatomite from West Kazakhstan as a silica-containing raw material for borosilicate glass production. Three glass batches, based on quartz sand, chalk, and diatomite, were synthesized with varying ratios of network-forming and modifying oxides. Partial replacement of quartz sand with diatomite enabled glass melting at 1150 °C, producing a homogeneous melt. Glasses with higher diatomite content showed improved chemical and water resistance; specifically, the sample containing 52% diatomite achieved hydrolytic class III and water resistance class IV (XA = 1.0 cm³·g⁻¹), whereas quartz-based control samples corresponded to classes IV–V. Heat resistance ranged from 120 to 160 °C depending on composition. These findings demonstrate that amorphous SiO₂ and active oxides in diatomite promote a stronger three-dimensional glass network, highlighting the potential of locally sourced diatomite as an alternative SiO₂ source for sustainable, energy-efficient borosilicate glass production. Full article

The stabilization of soft, organic-rich soils with cement is often hindered by retarded hydration and poor long-term performance under cyclic loads. While nano-silica or sand are known modifiers, their individual efficacy in high-organic environments remains limited, and a systematic comparison of their composite effect across different soil types is lacking. This study investigates the synergistic enhancement of cement-stabilized soils using a combined nano-SiO₂ and sand composite, comparing its effectiveness in high-organic soft soil and low-organic clay. Laboratory tests, including unconfined compressive strength (UCS), cyclic loading, scanning electron microscopy (SEM), and X-ray diffraction (XRD), were conducted. Results showed a stark contrast in 28-day UCS between unmodified soft soil cement (0.13 MPa) and clay cement (1.04 MPa). The optimal composite of 3.5% nano-SiO₂ and 40% sand increased the 28-day UCS to 1.39 MPa for soft soil (a 969% improvement) and 5.51 MPa for clay (a 430% improvement), respectively. Notably, under a cyclic stress ratio (CSR) of 0.7~0.8, unmodified specimens failed after fewer than 120 load cycles, whereas the composite-modified soils withstood 20,000 cycles without failure, demonstrating exceptional fatigue resistance independent of static strength gain. Microstructural analysis revealed that the composite effectively promoted the formation of cementitious hydration products, counteracting the inhibitory effect of organic matter. This research demonstrates that the nano-silica sand composite provides a superior and more broadly applicable improvement for cement-stabilized soils across the tested organic content range (3.3–7.7% LOI) compared to single-additive approaches, significantly enhancing both mechanical strength and long-term durability. Full article

Fractured tight sandstone reservoirs are promising targets for underground energy storage, but their heterogeneous nature and often-incomplete historical test data pose significant challenges for accurate deliverability prediction and reservoir evaluation. To address this, a novel hybrid methodology is proposed. For wells with complete historical data, deliverability is calculated using a binomial inflow performance relationship (IPR) model. For wells with incomplete data, a weighted fusion model integrating a Random Forest algorithm and least squares regression is developed to predict natural blowout capacity, a key proxy for energy storage injectivity/productivity. The fusion model achieved superior performance with a mean absolute error (MAE) of 7.19 × 10⁴ m³/day and a Mean Relative Error (MRE) of 8.5%, outperforming standalone methods. Based on the predicted deliverability, reservoirs in the Bozi–North block (Kuche Depression, Tarim Basin) were classified into three potential grades (I, II, III). The study provides a data-adaptive framework for deliverability prediction and offers tailored reformation process recommendations (e.g., sand fracturing for Grade I reservoirs), thereby providing a more reliable and practical decision support tool for the efficient development of tight sandstone energy storage reservoirs. Full article

Sand, a widely used material in construction, often presents challenges in engineering applications due to its loose granular structure. To address this issue, lignosulfonate (LS), an eco-friendly industrial by-product, is explored as a stabilizing agent in this study. This research investigates the effects of LS on the static and dynamic properties of sand, including its impact on compaction, compressive strength, and shear strength. A combination of laboratory tests, including unconfined compressive strength (UCS), direct shear tests, and resonant column tests, was used to evaluate the performance of LS-treated sand under different conditions. The study reveals that LS enhances the compaction, shear strength, and dynamic stiffness of sand, with an optimal LS content of 8%. This work contributes to the development of sustainable geotechnical materials and offers valuable insights for improving soil properties in foundation and subgrade applications under dynamic loading conditions. Full article

The chemical agent injection modes and displacement characteristics of chemical compound flooding, consisting of a plugging agent, an oil displacement agent, and a viscosity reducer, were investigated by laboratory experiments for target heavy oil reservoirs after multiple cycles of huff-and-puff. The performances of the oil displacement agent, viscosity reducer and plugging agent were evaluated, and the formulation and concentration were optimized. The oil displacement effects and displacement characteristics of different injection modes were studied by sand-filled two-pipe models. The experiment results showed that alternating injections of the oil displacement agent and viscosity reducer yielded better results than their mixed injection, and small segments alternating injections achieved the highest recovery. The larger the dosage of the oil displacement agent, the larger the maximum liquid production ratio between the high- and low-permeability layers, but with the smaller the liquid production reverse duration. The larger the dosage of the viscosity reducer, the greater the water cut decrease but the smaller the maximum liquid production ratio. For chemical compound flooding in the Zhong’er block in the Gudao oilfield, the recommended injection mode was 0.1 PV plugging agent + 2000 mg/L of oil displacement agent + 0.5% viscosity reducer, with small segments of the oil displacement agent being followed by a viscosity reducer at an injection slug ratio of 6:4. However, the injection mode depends on the prices of oil and the chemical agent. When prices fluctuate, the chemical agent concentration should be adjusted accordingly. Full article

Removal of micropollutants from wastewater is currently drawing a lot of attention in the field of municipal wastewater treatment plants. Firstly, this is because of their unpredictable and potentially damaging fate in the environment, and secondly, due to newly established requirements in the relevant European Union Directive (EU) 2024/3019. This article assesses coagulation, oxidation with chlorine dioxide, sand biofilter, and their combinations as potentially cheaper and sustainable alternatives to well-established, but more expensive methods. For the experiments, citalopram, carbamazepine, and diclofenac were chosen as representatives of micropollutants. Removal efficiencies were evaluated using HPLC, COD, and absorbance UV/VIS at different wavelengths. The demand for chlorine dioxide was assessed using the chlorophenol red method. Owing to analytical limitations, the concentrations examined were in mg/L, which significantly exceeds actual concentrations found in wastewater. The application of stand-alone chlorine dioxide oxidation exhibited the best performance as it sufficiently removed citalopram and diclofenac. On the contrary, biodegradation was found to be the least efficient method, as none of the compounds tested were sufficiently removed in a short period of time. However, the results may be partially biased owing to high concentrations of the micropollutants assessed. In the following stage of the research, the evaluation of transformation products is desired to prevent such potentially harmful chemicals from entering the environment. Full article

This study investigates the preparation and performance of ultra-high-performance concrete (UHPC) incorporating manufactured sand as a full replacement for quartz sand. The mix design was optimized by integrating the compressible packing model (CPM) with an orthogonal experimental design. The influence of stone powder content in manufactured sand—0, 5, 10, and 15% by mass of fine aggregate—on fresh-state fluidity and 7d-mechanical properties was systematically evaluated. Hydration products and microstructural features were analyzed using X-ray diffraction (XRD), scanning electron microscope (SEM), and mercury intrusion porosimetry (MIP). Results show that the manufactured sand-based UHPC achieved a fresh-state fluidity of 185 mm and a 7-day compressive strength of 152.4 MPa. Both fluidity and compressive strength exhibited a unimodal trend with increasing stone powder content, reaching maxima at 10%. Microstructural analysis revealed intimate interfacial bonding between unhydrated particles and calcium silicate hydrate (C–S–H) gel; notably, the UHPC matrix with 10% stone powder displayed the densest microstructure. MIP results further demonstrated that an optimal stone powder content effectively reduced total porosity, with the lowest overall porosity and the highest volume fractions of harmless (≤20 nm) and less harmful (20–100 nm) pores observed at 10%. These microstructural refinements collectively underpin the superior mechanical performance of manufactured sand-based UHPC. Full article

The reconstruction of detrital flux, paleoclimate, paleosalinity, paleo-primary productivity, paleohydrodynamic conditions, and paleo-water depth enhances understanding of sedimentary processes and their drivers during deep-time greenhouse-icehouse transitions, such as the Eocene–Oligocene transition. This study uses detailed geochemical analyses of major oxides and trace elements in sediment samples collected from the Beni Suef Formation (Bartonian–Priabonian) and the Maadi Formation (Priabonian) in the southern Tethys shelf (Egypt, northeastern Desert). Detrital proxies, including Si/Al, Ti/Al, and Zr/Al, indicate an enhanced influx of terrigenous sediments in the middle portion of the Qurn Member of the Beni Suef Formation, as further supported by noticeable facies variations, particularly the transition from shale to coarser silt- and sand-sized fractions. Paleoclimate indicators (Sr/Ba, Rb/Sr, K₂O/Al₂O₃, and Sr/Cu) point to a climatic shift from humid to arid conditions, consistent with the regional Late Eocene aridification across the Tethyan realm. Paleosalinity proxies (Sr/Ba, Ca/Al, and Mg/Al×100) suggest episodic intensification of open-marine influence and a reduction in freshwater input, with an upsection increase in Sr/Ba ratios, reflecting phases of enhanced marine water settings or decreased terrestrial runoff. Primary productivity was evaluated using multiple geochemical proxies, including P, Ni/Al, Cu/Al, P/Al, P/Ti, and Babio ratios. These collectively indicate generally low primary productivity interrupted by intervals of enhanced paleoproductivity or increased organic matter export to the sediments. This interpretation is further supported by the low total organic carbon (TOC) values. These results highlight the sensitivity of the southern Tethys shelf to Middle–Late Eocene climatic variability and the key role of prevailing paleoenvironmental conditions in controlling sediment supply, water chemistry, and biological productivity. Full article

To address the challenges of low accuracy and complex influencing factors in predicting horizontal well fracturing productivity during the development of unconventional oil and gas resources such as tight oil, this paper proposes a productivity prediction framework based on an improved feature selection method and an ensemble learning model. This study employs a fusion analysis using the entropy weight method to combine Pearson correlation analysis and improved gray relational analysis (IGRA) for feature selection. Thirteen machine learning models were tested with six distinct parameter combinations to construct a Stacking-based ensemble learning model, with base models including Random Forest (RF), Ridge Regression (RR), and Artificial Neural Network (ANN). Particle Swarm Optimization (PSO) was employed to optimize hyperparameters, followed by interpretability analysis using SHapley Additive exPlanations (SHAP). The results indicate that the model with fused weights demonstrated optimal performance. The Stacking model achieved significantly improved accuracy after PSO optimization, with the coefficient of determination increasing by 4.9%, outperforming all comparison models. Engineering guidance is provided: Under current geological conditions, sand ratio and displacement fluid volume require fine-tuning to prevent over-treatment. Fracturing design should implement differentiated strategies based on the target sand body thickness. This study not only delivers a high-precision production prediction tool but also offers decision support for efficient unconventional oil and gas field development through its exceptional interpretability. Full article

Sustainable materials are increasingly being incorporated into high-strength concrete (HSC) to reduce environmental impact while maintaining structural performance. This study experimentally investigates the combined use of steel scale waste (SSW) as a replacement for natural fine aggregates and graphite nano/micro platelets (GNMPs) as a nano-modifying additive in HSC. Natural sand was replaced with SSW at levels of 0%, 50%, and 100%, while GNMPs were incorporated at dosages of 0%, 0.1%, 0.3%, and 0.5% by weight of cement. The results indicate that partial replacement of sand with SSW significantly improves concrete density and mechanical performance due to enhanced particle packing and the high specific gravity of steel scale particles. At the nanoscale, GNMPs contribute to pore refinement, improved nucleation of hydration products, and crack-bridging within the cement matrix, thereby strengthening the interfacial transition zone and delaying crack propagation. The combined effect of these mechanisms produces a synergistic enhancement in concrete performance. The optimum mixture containing 50% SSW and 0.3% GNMPs achieved a compressive strength of 68.2 MPa and splitting tensile strength of 7.6 MPa, representing improvements of approximately 54% and 52%, respectively, compared with the control mix. Durability-related properties such as water absorption and sorptivity were also significantly improved due to matrix densification and pore structure refinement. Although the incorporation of SSW and GNMPs reduced workability, all mixtures remained within a practical range for casting. The developed concrete is particularly suitable for structural applications requiring high strength and durability, such as high-rise building components, bridge elements, and precast structural members. The findings demonstrate that the combined use of industrial steel waste and nano-reinforcement offers a promising pathway toward sustainable and high-performance concrete. Full article

This study evaluated cherry tomato seedling production using pirapitinga RAS wastewater as the sole nutrient source in four substrate formulations: T1 (sand, gravel and coconut fiber), T2 (sand and gravel), T3 (gravel and coconut fiber), and T4 (sand and coconut fiber). No differences were observed for germination quality, germination percentage, seedling vigor index, germination vigor index, moisture content, total wet biomass, total dry biomass, or mortality. For small plants, leaf number (LN) was higher in T2 and lower in T4, while root length was greater in T3. The number of medium plants was higher in T3 and lower in T4; LN was higher in T1 and T2 and lowest in T3. For large plants, LN was higher in T1 and T2 and lower in T3; total length was higher in T1 and lower in T3 and T4. Visual differences in substrate water retention were observed: T4 exhibited rapid surface drying, T1 and T2 showed moderate moisture persistence, and T3 maintained surface water. Leaf yellowing was observed after 25 days, suggesting possible nutrient limitation or reduced nutrient availability at the measured pH. These findings indicate that substrate physical characteristics influence early seedling growth performance, whereas pirapitinga RAS wastewater can serve as a viable nutrient source. Full article

The pronounced heterogeneity of high-Andean soils constitutes a critical constraint to the sustainable productivity of quinoa in southern Peru, where current yields (1.6 t ha⁻¹) remain well below potential (>5 t ha⁻¹). This study aimed to develop a spatially predictive model of a weighted soil quality index (SQIw), the edaphic supply of nitrogen (N), phosphorus (P) and potassium (K), and the agricultural gypsum requirement by integrating edaphoclimatic covariates through regression–kriging. A total of 198 quinoa-cultivated soil samples were analysed; a minimum data set (MDS) was defined using correlation and principal component analyses, and regression–kriging was applied to map SQIw and the variables of interest. The MDS comprised electrical conductivity (EC), organic matter (OM), available P, exchangeable Na, sand, clay, and effective cation exchange capacity (ECEC); exchangeable Na (Wi = 0.160) and available P (Wi = 0.158) received the largest weights in the SQIw. SQIw values ranged from 0.22 to 0.84 and supported a five-class soil quality taxonomy; spatial modelling revealed a dominance of moderate-quality soils across the territory (85.21% of the agricultural area, 13,461.19 ha). The model achieved R² = 0.56, RMSE = 0.05, and MAE = 0.04 for SQIw. Most of the area (12,175.65 ha; 77%) exhibited an intermediate gypsum requirement (9.73–14.33 t ha⁻¹). Nitrogen and phosphorus showed the greatest territorial limitations, whereas potassium was largely non-limiting (84.82–570.17 kg ha⁻¹). These results indicate that sodicity and N–P deficiencies are the primary functional constraints; the generated maps enable prioritisation of gypsum amendments and targeted variable-rate fertilisation strategies to optimise the sustainability of quinoa production in the Altiplano. Full article