Search Results (420)

The reservoir quality and gas-bearing properties of the Wufeng Formation–Longmaxi Formation shale vary significantly across different structural units in the Luzhou area of the Sichuan Basin. The mechanisms of shale gas enrichment, tectonic controls, and accumulation models are critical determinants of the potential for three-dimensional (3D) development. Integrating data from core analyses, logging interpretation, focused ion beam scanning electron microscopy (FIB-SEM), and high-resolution core scanning, this study investigates the control exerted by fracture development and tectonic activity on shale gas enrichment and preservation. A conceptual model for shale gas enrichment and accumulation is established, and the potential for 3D development of deep shale gas in the Luzhou block is evaluated. The results indicate that: (1) Reservoir heterogeneity in deep shale gas plays is jointly governed by reservoir space characteristics, diagenesis, structural position, tectonic evolution, and fracture-fluid activity. Organic-rich siliceous shales retain favorable reservoir properties, characterized by an organic matter (OM) pore-dominated pore structure, relatively high porosity and permeability, and good gas-bearing potential due to overpressure preservation. (2) Structural style exerts dominant control over the gas-bearing variability. Synclines are significantly more favorable than anticlines, with free gas migration governing the enrichment pattern. The cores and flanks of synclines form zones of high gas content due to structural integrity, whereas the gas content decreases in anticlinal areas near faults. (3) Shale gas enrichment relies on the synergistic configuration of “high organic carbon content + high-quality pore reservoir space + robust structural preservation conditions.” Well L213 in the syncline core, distant from faults, exhibits good structural integrity and preservation conditions. Free gas from structurally lower positions migrates laterally toward the flanking anticlines, with a portion preserved in the syncline flanks. Concurrently, microfractures enhance reservoir storage and permeability, rendering syncline structures more conducive to shale gas preservation. (4) The high-quality shale succession in the study area is thick and laterally continuous, characterized by “vertical stacked pay zones.” This provides an excellent geological foundation for 3D development. By optimizing the well trajectory design and employing efficient fracturing technologies, such as “intensive fracturing” combined with temporary plugging and diversion, full and balanced utilization of vertically stacked sweet spot reservoirs can be achieved, significantly enhancing the single-well productivity and estimated ultimate recovery (EUR). Full article

Treated wastewater (TWW) reuse mitigates water scarcity but may induce soil salinization and trace metal accumulation if improperly managed. This field study evaluated the combined effects of irrigation water quality (TWW vs. well water) and irrigation method (surface vs. subsurface drip irrigation, SDI) on soil chemical properties, okra growth, yield, and nutrient/trace element dynamics under semi-arid Mediterranean conditions. Soil pH remained stable across treatments. Electrical conductivity was not significantly affected by water quality but increased in deeper layers under surface drip irrigation, indicating salt migration. SDI promoted more uniform nutrient distribution and favored Na⁺ displacement toward deeper layers, reducing root-zone exposure. Cations stratified vertically, with Ca²⁺, Mg²⁺, and K⁺ concentrated in surface layers and Na⁺ at depth. Water quality exerted a stronger influence than irrigation method. The fertilizing effect of TWW significantly enhanced plant height (53%), leaf dry matter (43%), aboveground biomass (81%), and fruit yield (16.3%). When combined with SDI, TWW improved irrigation water use efficiency by 20%. Although fruit Cd concentrations increased under TWW irrigation, all trace metals remained below international food safety standards. These findings indicate that integrating TWW with SDI enhances productivity and water use efficiency while maintaining short-term food safety, though long-term monitoring remains essential. Full article

Methane (CH₄) is a major component of natural gas and a potent greenhouse gas. Increasing atmospheric methane concentrations are attributed to emissive anthropogenic activities by an average of 13 ppb per yr since 2020 and are linked to a changing global climate. Mitigating CH₄ emissions from oil and gas production sites has recently become a target to reduce overall greenhouse gas emissions; however, monitoring the efficacy of mitigation strategies depends on accurate quantification of CH₄ emissions at the facility-level. Near-field quantification of methane (CH₄) emissions from oil and gas (O&G) facilities remains challenging due to the effects of atmospheric variability and sensor configuration on atmospheric dispersion models. This study evaluates the performance of two atmospheric dispersion models, the Gaussian plume (GP) and backward Lagrangian stochastic (bLS), by comparing calculated CH₄ emissions to controlled single-point emissions between 0.4 and 5.2 kg CH₄ h⁻¹. Emissions were calculated by both models using 121 individual sets of measurements comprising five-minute averaged downwind methane mixing ratios and matching meteorological data. The comparison shows that the bLS approach achieved a higher proportion of emission estimates within a factor of two (FAC2) of the known emission rates compared to the GP approach. The emissions calculated by the bLS model also had a lower multiplicative error and reduced bias relative to GP. Other error-based metrics further confirmed the bLS model performed better, as it yielded lower RMSE and MAE than GP. Statistical analysis of the emission data shows that the lateral and vertical alignment of the source and the sensor plays a critical role in emission estimations, as measurements made closer to the plume centerline and at a distance between 40 and 80 m downwind yielded the best FAC2 agreement. High wind meander degraded the ability of both approaches to generate representative emissions, particularly with the GP approach, as it violates the modeling approach’s assumption of steady-state emissions. Data suggest emissions calculated by the bLS model are comprehensively in better agreement, but the computational demands of the modeling approach and integration into fenceline systems limit real-time applicability. While these results provide insight into model performance under controlled near-field conditions, their applicability to more complex or heterogeneous oil and gas production environments (e.g., the regions Marcellus or Unita Basins) remains limited and uncertain. Full article

The distribution and evolution of complex formation pressures fundamentally control natural gas accumulation patterns and the prediction of favorable zones. To elucidate the controlling factors behind complex pressure distribution in tight sandstone gas reservoirs with source-reservoir separation, this study investigated the Shaximiao Formation in the central-western Sichuan Basin. Integrating statistical, physical, and rock mechanics analyses with reservoir properties and gas compositional data, this study characterized the present-day pressure regime using seismic interpretation, well logs, measured pressure data, and drilling records. This study clarifies the genetic mechanisms, establishes a differential enrichment model, and identifies future exploration targets. Results reveal a present-day pressure distribution trending from high in the north and west to low in the south and east. Erosional unloading and strata cooling, mechanisms that lead to an average pressure reduction of about 4–15 MPa, jointly contribute to the development of abnormally negative pressure in the central Sichuan Basin. Vertically, pressure magnitude within sand groups shows a positive correlation with productivity. The pressure evolution is governed by a quadruple mechanism: hydrocarbon-generation pressurization, fault-mediated transmission, gas charging, and uplift-induced release. Consequently, future exploration should prioritize areas where high-quality reservoirs adjacent to active hydrocarbon kitchens, significant source-reservoir pressure differentials, and effective fault-sandbody transport pathways are optimally combined. Full article

This study evaluates GNSS water-vapor tomography across the Lisbon metropolitan area and explores how increasing network density with low-cost receivers improves three-dimensional humidity fields for meteorological applications. Three configurations were tested for December 2022, a month characterized by several rainfall events, including a severe urban-impacting one: (i) a hybrid setup combining permanent and low-cost stations (TOMO_PL), (ii) a dense network of only low-cost stations (TOMO_L), (iii) a sparse arrangement using only permanent stations (TOMO_P). Tomographic water vapor density fields were compared with independent references from the Weather Research and Forecasting (WRF) model, ERA 5 reanalysis, and radiosonde data. All products show the expected exponential decline in water vapor with increasing altitude. Tomography consistently underestimates moisture in the lowest 2.0 to 2.5 km and tends to overestimate it at higher levels, with a weaker correlation above mid-tropospheric heights. Vertical RMSE remains below 2 g m⁻³ for all solutions, but TOMO_P performs the worst due to weak and uneven spatial geometry. Time–height analysis reveals that densified setups capture the changing moisture in the lower atmosphere, including increased near-surface humidity during December 11–13, when rainfall exceeded 120 mm in 24 h, although mid-level intrusions and dry layers observed by radiosondes are not captured. Mean PWV patterns show realistically low points over the Sintra mountain range and align best with TOMO_PL (spatial RMSE 0.6 g m⁻³, bias 0.4 g m⁻³, correlation 0.9), while TOMO_P creates artifacts that mimic mesoscale gradients. Categorized skill analysis shows the highest accuracy under high-moisture conditions and limited ability to detect dry conditions, with TOMO_PL showing the best overall performance against both ERA5 and WRF. Overall, low-cost densification significantly enhances boundary-layer humidity and PWV retrievals, supporting their use for urban heavy-rain monitoring and, with error-aware integration, for short-term forecasting. Full article

Surface ozone monitoring remains challenging due to sparse ground networks and limited satellite boundary-layer sensitivity. This study evaluates, for the first time, China’s Environmental Trace Gases Monitoring Instrument II (EMI-II) for estimating surface ozone over the Beijing–Tianjin–Hebei (BTH) region. EMI-II total ozone columns (TOCs) are retrieved using the differential optical absorption spectroscopy (DOAS) algorithm and validated against the TROPOspheric Monitoring Instrument (TROPOMI) (R = 0.96), Geostationary Environment Monitoring Spectrometer (GEMS) (R = 0.97), and the World Ozone and Ultraviolet Radiation Data Centre (WOUDC) ground measurements (R > 0.92, bias < 4%). TOCs are then combined with ERA5 meteorology, satellite NO₂/HCHO, and surface observations within machine learning models, achieving cross-validated R² of 0.94 and RMSE of 12.05 μg/m³ for surface ozone estimation. EMI-II estimates show strong agreement with independent observations (R = 0.91, RMSE = 10.83 μg/m³) and reproduce seasonal gradients, with summer concentrations (131 μg/m³) more than double winter levels (61 μg/m³). Estimation skill is regime-dependent: performance comparable to TROPOMI occurs under strong photochemical activity, while reduced sensitivity occurs under weak radiation and stable boundary layers—consistent with averaging kernel diagnostics. This first comprehensive validation demonstrates that EMI-II, despite vertical sensitivity limitations, provides meaningful surface ozone constraints under favorable atmospheric conditions. The framework is potentially applicable to other regions and sensors under similar conditions, providing a case study for integrating national satellite products into multi-source surface ozone estimation. Full article

Additive manufacturing in construction is expanding production possibilities for housing, however its integration into architectural design workflows remains limited. This research proposes a computational workflow for the early-stage form-finding of housing volumes intended for additive construction. A parametric design system was developed to generate a wide range of residential volumetric configurations based on geometric parameters derived from conventional housing typologies and emerging 3D-printed construction practices. The design space was explored through user-driven experimentation and automated evolutionary optimization targeting predefined surface area conditions. Besides design alternatives were visualized using AI-assisted image generation to support comparative evaluation, translated into BIM models for further architectural development, and tested through physical 3D-printed scale models to assess material expression and constructability. Five design exploration activities involving architects and graduate students produced nearly 200 volumetric alternatives, in order to review its use and possibilities. The results show that the parametric system enables efficient exploration of both conventional and novel housing forms potentially compatible with additive construction. Vertically articulated volumes with curved envelopes and spatial variation emerged as promising alternatives. The study demonstrates the potential of integrating parametric modeling, evolutionary search, AI-assisted visualization, and physical prototyping to support architectural decision-making and facilitate the incorporation of 3D printing into housing design processes. Full article

Road maintenance remains one of the most resource-intensive and hazardous operations in infrastructure management. Traditional inspection practices rely heavily on manual labour and discrete procedures, often resulting in limited scalability, operator exposure to traffic hazards, and inefficiencies in data collection. This paper presents a novel automated methodology that integrates Unmanned Aerial Vehicles (UAVs) and autonomous mobile robots (AMRs) to enable automated inspection and measurement of road assets through a digital twin (DT) system. The system leverages data fusion and real-time synchronisation between field agents and a centralised digital twin to monitor the retro-reflectivity of vertical and horizontal signage, detect obstacles and vegetation, and support data-driven maintenance planning. A case study conducted on the Italian highway network demonstrated improvements in operational safety, inspection efficiency, and measurement consistency. The results confirm that the integration of UAVs and AMRs within a digital twin framework can significantly improve sustainability, productivity, and workers’ safety in road maintenance operations. Full article

Ensuring experimental reproducibility and reliable isolation of crop responses remain critical challenges in vertical farming and controlled-environment horticulture, where minor microclimatic fluctuations can mask treatment effects and compromise comparability across experiments. This study presents an intelligent, low-cost IoT-based climate management system designed as a methodological framework to stabilize environmental conditions and support reproducible crop responses in vertical horticulture. The system integrates real-time multi-sensor monitoring of temperature, relative humidity, atmospheric pressure, and CO₂ concentration with automated high-power actuation for lighting and ventilation within a unified control framework. The platform was validated using lettuce (Lactuca sativa L. cv. Ofelia) cultivated under controlled vertical farming conditions, where environmental stability enabled the reliable detection of plant responses to contrast light spectra. Crop performance was evaluated through biomass accumulation, morphological traits, and nutritional quality parameters. The intelligent control system maintained environmental setpoints within narrow ranges throughout the cultivation cycle, minimizing microclimatic variability across vertical tiers. As a result, observed differences in plant growth and biochemical composition were less likely to be confounded by environmental drift. By shifting the role of IoT technologies from simple automation tools to experimental enablers, this work illustrates how intelligent climate control can support reproducibility, scalability, and methodological robustness in vertical horticulture research. The proposed open, modular architecture provides a transferable framework for reproducible crop experimentation and production in controlled-environment systems. Full article

Modern agriculture faces significant challenges, such as population growth, the reduction in productive agricultural land, and, most importantly, climate change. To address these issues, non-thermal plasma treatment of seeds and plants has emerged as a promising alternative to conventional chemical-based methods. This advanced technology, a powerful chemical reactor in the gas phase, has various applications, from stimulating seed germination and plant growth to controlling pathogens. The effects of non-thermal plasma on seeds include morphological and chemical changes in the seed coat, increased permeability and water uptake, and the activation of some internal biochemical mechanisms. Studies have demonstrated improvements in germination, plant development, and the activation of internal biochemical mechanisms with the intensified production of secondary metabolites. Non-thermal plasma also contributes to reducing the microbial load, providing an effective and environmentally friendly method of disinfection. This review synthesises the current knowledge on non-thermal plasma sources used in plasma agricultural applications for seed treatments, emphasising that in some cases the exposure of seeds to such discharge stimulates germination and also promotes early seedling growth. In addition, it highlights reported biochemical and nutraceutical improvements, including changes in antioxidant capacity, phenolic content and other bioactive compounds which add considerable value to the resulting plants. Finally, the decontamination potential is discussed, along with results discussing the potential of NTP to decontaminate seeds, associated with an extension to the shelf-life of products and identifying key challenges and research gaps for implementing this technology in agricultural practices. The integration of this technology into modern agriculture, including vertical farms and hydroponic systems, opens up the prospect for more sustainable and productive agriculture. However, scaling up the process and optimising processing parameters remain important challenges that require further attention, research and technological development. Full article

In Northeast China’s degraded croplands, nitrate (NO₃⁻-N) leaching is the dominant pathway for fertilizer-nitrogen (N) loss, which presents an increasing threat to the quality of groundwater. Conservation tillage, defined as no-tillage (NT) and straw retention, is a widely adopted management strategy to maintain cropland fertility in the black soil (BS) regions. At present, however, the impact of shifting from conventional to conservation tillage on the vertical distribution and regulatory mechanisms of NO₃⁻-N derived from applied fertilizer-N (F_NO3) remains poorly understood. Based on a 12-year field experiment, we integrated ¹⁵N-tracing field monitoring with ¹⁵N-paired-labeling incubation to quantify the vertical migration of F_NO3 into deep soil profiles, and specify the dominant processes regulating N retention and supply. Across the tested BS croplands, total NO₃⁻-N production rates (4.06–6.58 mg N kg⁻¹ soil day⁻¹) were faster than their consumption rates (0.36–0.92 mg N kg⁻¹ soil day⁻¹), leading to a net accumulation of NO₃⁻-N, and implying a potential for leaching of NO₃⁻-N, from the perspective of substrate availability. The results of the field ¹⁵N micro-plot experiment also indicated that, by maize maturity in the first growing season, an average of 7.5% of F_NO3 had migrated to the 80–100 cm soil layer. During the following two growing seasons, the maximum accumulation of F_NO3 had shifted downward to 140–160 cm and 180–220 cm, respectively. Such a pattern, particularly in light of the increased extreme precipitation in the studied regions, raises clear concerns about NO₃⁻-N leaching losses. Compared with conventional management, no-tillage with full-rate straw mulching decreased net rates of NO₃⁻-N production from 6.22 to 3.14 mg N kg⁻¹ soil day⁻¹. This reduction resulted from a decline in the gross oxidation of NH₄⁺-N to NO₃⁻-N (from 6.39 to 3.70 mg N kg⁻¹ soil day⁻¹) and an increase in DNRA (from 0.35 to 0.85 mg N kg⁻¹ soil day⁻¹), which collectively delayed the downward transport of F_NO3. Conservation tillage also increased the gross rate of heterotrophic nitrification (from 0.19 to 0.36 mg N kg⁻¹ soil day⁻¹) and its proportion relative to total nitrification (from 2.8% to 8.9%). Despite this shift, autotrophic nitrification remained the dominant process for NO₃⁻-N production in the tested BS croplands, likely due to a pH constraint on heterotrophic nitrification. With the increasingly widespread promotion of conservation tillage for soil fertility improvement, heterotrophic nitrification warrants greater attention, particularly in BS regions where pH < 6.5 and C/N contents are relatively high. Collectively, our findings provide a scientific basis for tailoring tillage practices to maintain sustainable agriculture in Northeast China. Full article

This study examines the influence of photobioreactor (PBR) configuration on the cultivation performance of Chlorococcum sp. using aquaculture wastewater as the growth medium. Four systems were compared: horizontal without aeration (H-Plain), horizontal with aeration (H-Aerated), vertical with aeration (V-Aerated), and vertical with aeration and red LED illumination (V-LED). Over 14 days, the V-LED system achieved the highest biomass concentration (0.50 g L⁻¹) and volumetric productivity (0.063 g L⁻¹ day⁻¹), accompanied by nitrate and phosphate removals of 94% and 55.6%, respectively. Statistical analysis (ANOVA, p < 0.05) confirmed significant differences among configurations, demonstrating that light quality and aeration act synergistically to enhance growth and nutrient assimilation. While aeration improved CO₂ transfer and mixing, it was insufficient without adequate photon delivery. Conversely, red LED illumination mitigated photolimitation in vertical systems, promoting efficient photosynthesis and nutrient uptake. Energy assessment revealed that V-LED offered the highest productivity in expense of power input (1.08 kWh day⁻¹). These findings highlight the critical role of integrated PBR design, emphasizing that optimal combinations of geometry, aeration, and spectral lighting as keys to achieving high biomass yields and efficient nutrient removal in sustainable microalgae-based wastewater treatment systems. Full article

Digital Elevation Models (DEMs) constitute a core data source for Archeological Predictive Modeling. However, how quality differences among multi-source DEM propagate through complex models and subsequently affect predictive accuracy and geographic interpretation remains insufficiently understood. This study aims to develop an integrated evaluation framework that combines machine learning with SHAP-based interpretability analysis to systematically compare the suitability of mainstream open access DEM products for archeological site prediction. The results indicate that (1) in terms of vertical accuracy, Copernicus DEM and TanDEM-X achieved the best performance, with RMSE values of 2.19 m and 2.31 m, respectively, whereas ASTER exhibited the lowest accuracy (RMSE = 6.44 m) and exaggerated terrain. (2) Regarding model performance, Copernicus DEM-driven models demonstrated the highest robustness, achieving an AUC of 0.966 under the XGBoost algorithm. (3) Interpretability analysis revealed that different DEM products significantly reallocate the importance of key variables such as slope and the Topographic Wetness Index, potentially distorting scientific interpretations of ancient military defensive site-selection patterns. Copernicus DEM is recommended as a priority data source. Moreover, while pursuing higher spatial resolution, equal attention must be paid to vertical accuracy and consistency with geomorphological logic. Full article

In China, a majority of the proven crude oil reserves are found in clastic rock reservoirs, which typically exhibit low natural energy levels. Water injection has become the most widely adopted technique for maintaining reservoir pressure and enhancing oil recovery in such formations. However, conventional water injection strategies heavily rely on empirical knowledge, often failing to accurately characterize the dynamic inter-well connectivity between injection and production wells. This limitation hinders the effective management of fluid injection and production processes. To address this challenge, we propose an intelligent optimization method for water allocation in high-water cut, low-permeability reservoirs. Our approach employs a Bidirectional Long Short-Term Memory (BiLSTM) neural network to learn the complex patterns from historical injection data in a data-driven manner. Furthermore, we design a well distance and time joint attention mechanism, which is integrated after the dual BiLSTM layers to enhance the model’s ability to capture the critical dynamic relationships among wells. This mechanism decouples temporal pattern recognition and the spatial physical constraints, laying the foundation for interpretable injection strategy optimization. We name this architecture “AttBiLSTM”, which is designed for optimizing injection strategies for individual layers in separate-layer water injection wells (The layer refers to the basic geological unit or flow unit within a vertically heterogeneous reservoir that is delineated and requires independent water injection regulation). Using field data from the Xinjiang Oilfield, we validate the proposed method and compare its performance against traditional water injection schemes and mainstream data-driven models. The experimental results demonstrate that the AttBiLSTM model effectively establishes a nonlinear mapping between the injection volumes and oil production rates, showing strong performance in both production prediction and injection optimization. An independent numerical reservoir simulation verification confirms that the optimized scheme increases well group oil production by over 3.6%, with no premature water breakthrough risk in a 5-year development cycle. This study provides a novel and practical technical framework for efficiently developing low-porosity, low-permeability, and highly heterogeneous reservoirs. Full article

Controlled Environment Agriculture (CEA) has become a key driver of vertical farming (VF), offering innovative solutions for the sustainable production of ornamental plants in urban environments with limited arable land. This review examines recent advances in VF technologies and their applications in foliage and flowering ornamental plant production. The literature indicates that precise environmental control, including optimized LED lighting spectra, hydroponic and aeroponic nutrient delivery, and automated climate regulation, can significantly enhance plant growth, morphological characteristics, color intensity, and overall market quality of ornamental species. In addition, VF systems demonstrate substantial reductions in water consumption, pesticide use, and land requirements compared with conventional cultivation methods. However, several challenges remain, including high-energy demand, economic feasibility, and the need for crop-specific environmental optimization for different ornamental species. This review synthesizes current research on VF systems, highlights the integration of emerging technologies such as the Internet of Things (IoT), artificial intelligence (AI), and data-driven management tools, and evaluates their potential to improve production efficiency and sustainability in ornamental horticulture. Overall, vertical farming represents a promising approach for high-quality ornamental plant production, although further research is required to optimize energy efficiency and cultivation protocols for diverse ornamental crops. Full article