Search Results (666)

Radionuclide contamination of surface water bodies poses a significant environmental challenge, particularly for low-productivity dystrophic systems where natural self-purification capacity is limited. This study aimed to assess the potential of phytoplankton and bottom sediments as biogeochemical barriers for radionuclides. Laboratory modeling of ⁹⁰Sr, ²³³U, ²³⁹Pu, and ²⁴¹Am accumulation was conducted using samples of Lake Dryazlo (Tver Oblast) water and bottom sediments as a representative dystrophic model system. Sorption onto phytoplankton biomass over a single growing season was estimated at 1.89 × 10⁴, 5.41 × 10⁴, 6.64 × 10⁴, and 4.04 × 10⁴ Bq g⁻¹ dry biomass for ⁹⁰Sr, ²³³U, ²³⁹Pu, and ²⁴¹Am, respectively. Actinide immobilization in bottom sediments depended on mineral composition and microbial community activity. Ammophos addition increased radionuclide removal from the liquid phase by 2–5-fold through enhanced phytoplankton productivity, and promoted actinide fixation via phosphate mineral phase formation and stimulation of anaerobic sulfur- and iron-cycling bacteria. These results demonstrate a viable biogeochemical barrier approach applicable to the decommissioning of radioactive waste storage ponds and remediation of radionuclide-contaminated water bodies. Full article

Variability in life cycle assessment (LCA) results for metal recycling technologies arises from multiple sources, including allocation methods, recycling route, regionality of impacts, and type of waste treated. Among these factors, waste composition is particularly critical, as it directly influences process performance by affecting auxiliary material consumption and emissions. This work investigates four waste categories: metals from incineration bottom ash (MBA), waste-printed circuit boards (WPCBs), industrial waste from gold refining (GRA), and spent automotive and industrial catalysts (SCs). The Climate Change (CC) for 1000 kg of waste was estimated at 3251 × 10³ kg CO₂eq for WPCBs, 3923 × 10³ kg CO₂eq for MBA, 1569 × 10³ kg CO₂eq for GRA, and 2101 × 10³ kg CO₂eq for SCs. A sensitivity analysis was performed to assess the influence of allocation methods on results for 1kg of recycled metal. The highest variability in CC across waste categories was observed for gold (up to 8477%) with the black-box economic allocation method, while different allocation methods reached 21,700% for WPCBs. These results highlight the strong influence of methodological choices and waste characteristics, emphasizing the need for transparent and consistent LCA reporting. Full article

Sustainable renovation of existing residential building stocks is essential to reduce greenhouse gas emissions, improve energy performance, and support long-term climate-neutral housing strategies. However, decisions based only on operational indicators may overlook important product-stage embodied impacts, especially in highly integrated renovation solutions. This study evaluates how alternative renovation pathways for a public residential building portfolio in the Comunitat Valenciana (Spain) perform from a stock-level sustainability perspective, comparing five INFINITE industrialised retrofit kits (Kit 1–Kit 5) with five paired conventional renovation scenarios (S1–S5). A bottom-up building stock modelling workflow is applied, combining building-energy simulation to quantify operational performance and emissions (B6) with a screening life-cycle assessment of product-stage embodied carbon reported as GWP (A1–A3). To relate upfront and in-use impacts, the study computes carbon payback, cumulative emissions avoided, and a horizon-based partial life-cycle climate indicator, PLC(H), assessed for 2030, 2035, and 2050. The results show a clear sustainability trade-off: renovation packages that sharply reduce operational emissions often require higher upfront embodied carbon, shifting net climate benefits towards longer time horizons. Low-embodied options provide earlier benefits, with Kit 1 reducing PLC(H) by 15.5% by 2030, whereas deeper decarbonisation packages achieve stronger long-term outcomes, with S5 reducing PLC(H) by 70.7% by 2050. A bounded electricity-decarbonisation sensitivity further shows that these long-horizon rankings are affected by lower grid-emission factors, particularly for highly electrified pathways, although the strongest 2050 pathways remain robust across the tested cases. Overall, the findings show that sustainable stock-level renovation planning should jointly consider operational and embodied carbon, carbon payback, and milestone-based cumulative impacts in order to support balanced portfolio sequencing between broadly deployable fast-payback measures and selective deep retrofits. Full article

Finite-volume gravity currents frequently encounter bottom obstacles, particularly in underwater environments such as lakes and oceans. However, how obstacle–current interactions reorganize Lagrangian transport pathways and ultimately determine the fate of fluid elements over the full current life cycle remains unclear. Using large-eddy simulations, we focus on a low-volume lock-exchange gravity current impinging on an isolated two-dimensional triangular obstacle. Fluid-element trajectories are tracked from collapse through propagation, obstacle interaction, and final dilution and decay, and are classified using K-means clustering into five transport modes linked to characteristic flow structures. We find that increasing obstacle slenderness strengthens upstream reflection and reduces downstream overflow, thereby shifting the fate of tracer particles from downstream delivery toward upstream retention. In addition, the obstacle standoff distance controls the dynamical state of the current at impact, producing systematic yet non-monotonic changes in the fractional population of the transport modes. This study establishes an explicit correspondence between evolving flow structures and clustered Lagrangian pathways. Comparative cases with varying geometric configuration, density contrast, flow depth, and release volume indicate that the identified transport patterns are reasonably robust. Therefore, the present results provide a fate-oriented predictive framework and theoretical basis for the transport of finite-volume gravity currents near obstacles, with important implications for engineering applications. Full article

This study investigates the geochemical behavior and transport mechanisms of Rare Earth Elements (REEs), Yttrium (Y), Zirconium (Zr), and Hafnium (Hf) in three natural water systems under reducing conditions: the Santa Barbara and Occhio dell’Abisso mud volcanoes and a sulphureous spring at Villafranca Sicula. A comprehensive fractionation approach was applied to isolate the truly dissolved fraction (TDF < 10 kDa), the colloidal fraction (10 kDa < CF < 450 nm), the suspended particulate matter (SPM > 450 nm), and the associated bottom sediments. Analytical results reveal that REE distribution is significantly influenced by redox conditions and solid–liquid interface processes. The absence of negative Cerium (Ce) anomalies and the presence of pronounced positive Europium (Eu) anomalies in the Santa Barbara and Occhio dell’Abisso waters suggest strongly reducing environments where Eu²⁺ stability is enhanced. Shale-normalized patterns indicate that, while SPM and sediment fractions often exhibit Middle REE (MREE) enrichment, linked to Mn-bearing and Fe-oxyhydroxide phases, the dissolved phase reflects dissolution processes governed by a non-CHARAC (CHarge-and-RAdius-Controlled) behavior. Furthermore, the study highlights a significant decoupling in the Zr/Hf and Y/Ho pairs. While these pairs remain coherent during magmatic processes, they undergo mutual fractionation in aqueous systems due to differential reactivity toward colloidal surfaces and organic ligands. Specifically, Zr/Hf ratios in the colloidal and dissolved fractions deviate from chondritic values, driven by the preferential scavenging of Hf onto mineral surfaces. These findings underscore the utility of REE and Zr-Hf systematics as high-resolution tracers for reconstructing water–rock interaction processes and elemental cycling in complex hydrological environments. Full article

Tiankeng ecosystems are characterized by strong microenvironmental gradients that influence plant adaptation; however, the molecular mechanisms underlying plant responses to altitudinal variation remain poorly understood. In this study, transcriptome sequencing and bioinformatic analyses were conducted to investigate the environmental adaptation mechanisms of three representative plant species (Hydrangea strigosa Rehder, Pilea martini, and Pilea sinofasciata) distributed along the vertical gradient of the Hanzhong Tiankeng in Shaanxi Province, China. Differential gene expression and functional enrichment analyses were performed to explore transcriptional responses under different altitude conditions. The results showed that flower coloration in Hydrangea strigosa Rehder was associated with the activation of sugar metabolism and triterpenoid biosynthesis pathways, suggesting potential indirect roles in modulating cellular metabolism and physiological conditions linked to flower coloration, while poor growth at the tiankeng bottom was associated with enhanced cellular respiration under low-light conditions, suggesting a potential link between energy metabolism and growth performance. In contrast, Pilea martini and Pilea sinofasciata exhibited better growth in the pit-bottom environment. Pilea martini promoted growth through enhanced carbohydrate metabolism and tricarboxylic acid cycle activity, whereas Pilea sinofasciata responded to environmental stress through hormone signaling, triterpenoid biosynthesis, and light signaling pathways. These findings reveal species-specific molecular strategies for plant adaptation to altitude-related environmental gradients in tiankeng ecosystems and provide insights into plant survival mechanisms in karst habitats. Full article

Large, shallow lakes lacking rooted aquatic vegetation are susceptible to wind-induced wave action that results in increased shear stress on the lake bottom, sediment resuspension and poor water clarity. The relationship between meteorological, hydrographical and sediment characteristics, and sediment dynamics has implications for internal phosphorus cycling and bioavailability, the frequency and duration of harmful cyanobacterial blooms, lake level management and restoration potential. In this study, a multi-parameter water quality sonde was deployed at various sites at the bottom of Utah Lake to measure water quality variables. Sediment cores were collected at each of the deployment sites and analyzed for common physical and chemical properties. Several machine learning regression techniques, including polynomial, decision tree, artificial neural network, and support vector machine, were applied to predict turbidity, a measure of water clarity and surrogate for sediment dynamics, using the observed explanatory variables wind speed and direction, fetch, water depth, sediment properties, algae, and cyanobacteria. The decision tree estimators, random forest and histogram-based gradient boosting had the best model performance, explaining 86–89% of the variability in turbidity when including all the explanatory variables. The artificial neural network estimator multi-layer perceptron and the polynomial regression models also performed well (81%), whereas the support vector machine estimator exhibited poor performance. Chlorophyll and phycocyanin, components of turbidity, were amongst the most important variables to the decision tree and artificial neural network models. Wind speed and water depth were also of high importance, which conforms with mechanistic explanations of sediment mobility caused by wave action and shear stress. Carbonate content was consistently a good predictor due to the calcareous nature of Utah Lake, whereas the importance of the other sediment properties was dependent on the machine learning technique applied. This case study demonstrated the potential for machine learning models to predict water clarity and has promise for more general applications to other shallow lakes and serves as a useful tool for lake management and restoration. Full article

Tritium self-sufficiency is a fundamental design requirement of a fusion fuel cycle, necessitated by the limited global availability of tritium relative to the fuelling demands of a fusion reactor. Minimising tritium losses within a fuel cycle is therefore essential. The Hydrogen Isotope Separation System (HISS) employs cryogenic distillation technology to remove excess protium and deuterium while rebalancing the deuterium–tritium (DT) mixture required for reactor operation. However, the HISS design involves a trade-off between reduced tritium emissions and increasing internal tritium inventory, both contributing to the overall tritium losses. In this work, a multi-objective Bayesian Optimisation (BO) framework based on an ε-constraint formulation is developed to construct Pareto-optimal solutions to compare alternative HISS architectures. Gaussian Process surrogate models derived from physics-based Aspen Plus simulations are used to resolve the non-linear relationships between design variables and performance metrics, including tritium inventory, tritium emission losses, and bottom-product purity. Application of the framework to representative case studies demonstrates that tritium emission losses significantly exceed tritium decay losses associated with internal inventory hold-ups across the investigated operating conditions. The proposed framework enables quantitative comparison of equilibrator integration strategies to compare HISS architectures and assess their impact on tritium losses within the fusion fuel cycle. Full article

Fieldwork carries a high risk of irregular, non-compressible traumatic wounds, which often initiate a vicious cycle of “traumatic bleeding-insect bite-secondary infection”. Conventional dressings cannot combine rapid hemostasis with physical protection against venomous insects, creating an urgent demand for multifunctional field trauma dressings. To solve this problem, this study developed a shape-adaptive bilayer hydrogel that concurrently provides rapid hemostasis, promotes wound repair, and acts as a robust physical barrier. The hydrogel adopts a layered design: the bottom layer (PPTY) achieves autogelation within 3 s upon blood contact, while the top armor protective layer (AP) withstands pressures up to 942 kPa. By incorporating chitosan and sodium citrate into the AP precursor solution, the hydrogel achieved in situ formation within 50 s and developed a stable self-renewing armor layer. The tightly bonded bilayer showed complementary functions. In rat models of femoral artery puncture and tail vein bleeding, PPTY-AP hydrogel significantly reduced blood loss and shortened hemostasis time. Moreover, the hydrogel demonstrated excellent tissue adhesion and moisture retention capacity, promoting full-thickness skin wound healing. This multifunctional, rapidly deployable hydrogel presents a promising solution for field trauma management and offers a new design paradigm for advanced wound dressings. Full article

The service behavior of polyurea used for joint sealing and seepage control in concrete arch dams is governed by complex material, geometric, and interfacial nonlinearities. This study developed a generalized interface element model incorporating damage evolution based on the nonlinear Ogden constitutive theory of polyurea materials. Using the Xiaowan Arch Dam as the engineering case, a multiple-nonlinearity coupled numerical model was established, covering the construction period, impoundment period, and temperature cycles during the operation period. The mechanical responses of surface polyurea at different locations and under varying material parameters were systematically investigated. Results show that the proposed coupled model accurately captures nonlinear contact behavior. Governed by the structural stress pattern of the arch dam, the impermeable coating is predominantly subjected to compression, while regions of high tensile stress are confined to the bottom joint areas. In seepage-control design, the coating’s restraining effect on macroscopic dam deformation can be neglected; however, dam deformation must be treated as the primary boundary condition. It is recommended that polyurea with an elastic modulus of 50 MPa and a 3 mm thickness be adopted. Blindly increasing coating thickness or stiffness may instead significantly elevate the risk of internal tensile stress. Full article

Municipal solid waste incineration bottom ash (MSWIBA) represents both a resource opportunity and an environmental challenge in waste-to-energy systems. This comprehensive review examines MSWIBA’s physicochemical properties, heavy metal behavior, and applications in construction materials, alongside metal recovery techniques and risk mitigation strategies. The research introduces an integrated management framework combining property assessment with coordinated stream processing to reconcile resource recovery with environmental safety. Future studies should focus on advanced analytical methods, hybrid processes, long-term immobilization mechanisms, and life cycle assessment. These innovations aim to transform MSWIBA into a sustainable resource, supporting circular economy principles and low-carbon development. Full article

In light of the global issue of “Carbon Neutrality”, a high proportion of renewable energy integrated into modern power systems has become the key to energy strategic transformation, which has escalated the demand for high-gain, high-power converters for DC energy conversion. In this paper, a non-isolated double-layer multi-port parallel-connected high-gain DC–DC conversion system has been proposed. The system consists of two energy layers: the upper layer is designed as a non-isolated high-gain three-port DC conversion topology, which includes two energy inputs and one output port, and the bottom layer is a three-port constant current output module. The output ports of these layers are connected in parallel, while the input ports are independent. Thus, both high output voltage gain and power capacity were fulfilled for the renewable power application condition. The system is capable of operating in both input-parallel–output-parallel (IPOP) and multi-input–independent-output-parallel (MIIOP) modes, thereby enabling multi-port high-gain DC power conversion. Detailed analysis of the operation strategies under a switching cycle for both energy layers is presented. A small signal was introduced to establish the mathematical model of both energy topologies. In order to simultaneously regulate the output voltage and achieve dynamic current sharing between the layers, an adaptive current-sharing control strategy was developed based on the established system models. The proposed control strategy can control the output voltage through the upper-layer topology and dynamically allocates output current between the layers based on the output power level, which will effectively enhance the system’s power rating. The simulation mode was built in the PSIM environment, open-loop simulations were carried out for obtaining system characteristics, and closed-loop simulations were conducted for control efficiency validation. Finally, a 2000-W experimental prototype was developed based on the digital control center dsPIC33FJ64GS606. Open-loop and closed-loop experiments were carried out for system performance evaluation. Both simulation and experimental results successfully evaluated the power transfer performance and control system performance of the proposed system, and a peak efficiency of 95.7% under 10 times voltage gain was achieved. Full article

Ground subsidence and shaft lining deformation caused by compressed dewatered bottom aquifers in deep unconsolidated strata mining areas are critical engineering challenges, making the study of the seepage–soil deformation coupling mechanism during groundwater injection remediation vital. This study built a visual cylindrical model (1025 mm × 150 mm); formulated well-graded analogous materials based on the D₂₀ principle to simulate sandy gravel layers; embedded FBG sensors at 200/400/600 mm depths, combined with a dial indicator on the model top; and conducted two water injection–dewatering cycles. Results indicate: water injection generates excess pore water pressure, placing the entire model in a tensile stress state with top rebound; post-injection vertical stress redistributes (tension above the injection point, compression below, and an interlaced transitional band), validating the necessity of full-section injection; during the second injection–dewatering cycle, tensile strain at the upper monitoring point reaches 597.77 με, while compressive strain at lower depths reaches −253.90 με, internal deformation stabilizes within 6.5–10.0 days, injection improves the in situ stress state by reducing effective stress, and the deformation of the field strata remains in a stabilization period, with the stabilization time decreasing as the depth of the strata increases. This study clarifies the temporal evolution and representative spatial variation in internal strain at monitored depths during injection, providing theoretical and design references for optimizing water injection schemes to mitigate coal mine shaft damage. Full article

The self-directed channel (SDC) class of memristors employs a multilayer architecture that is designed to enable robust Ag ion conduction, long cycling lifetime, and thermal stability. While several layers contribute to mechanical and chemical reliability, two layers primarily govern the electrical behavior: the amorphous Ge–chalcogenide active layer that is adjacent to the bottom electrode and the overlying metal–chalcogenide source layer. In this work, we investigate how the variation in the chalcogen species in these two layers influences switching characteristics in the pre-write regime, both in the pristine state and after a write/erase cycle, as well as the conduction behavior at room temperature. The devices were fabricated using Ge-rich chalcogenides containing O, S, Se, or Te, combined with SnS, SnSe, or Ag₂Se metal–chalcogenide layers. The DC current-voltage measurements were analyzed using the standard linearization approaches to examine whether the transport behavior in the pre-write regime exhibits characteristics that are associated with Ohmic, Schottky, Poole–Frenkel, or space charge limited conduction. These measurements specifically probe the pre-write region of the I-V curve, where early ionic redistribution and structural rearrangement precede the abrupt formation of the conductive channels responsible for the resistive switching. The results show that the chalcogen composition strongly affects the threshold voltage, the resistance window, and the onset of field-enhanced transport, reflecting the differences in ionic distribution and channel formation dynamics. The results indicate that transport evolves with a bias and a compliance current, transitioning between regimes that are influenced by the interface injection and bulk-limited conduction, depending on the material stack. These findings clarify the role of chalcogen chemistry in governing the SDC switching behavior and provide guidance for the material selection in application-specific device design. Full article

Eukaryotic microorganisms, including microalgae, protists, fungi, and micro-metazoans, act as drivers of energy flow and nutrient cycling, collectively forming the microbial food loop, and also serve as important indicators of environmental health. To investigate the seasonal variation in eukaryotic microorganisms in a mussel farming area, a total of 96 seawater samples were collected from surface and bottom layers of water across different seasons. High-throughput sequencing of the 18S rRNA gene was employed to characterize shifts in microbial community structure and identify key influencing factors. Our results indicated significant seasonal differences in eukaryotic microbial communities between surface and bottom waters. Redundancy Analysis (RDA) revealed that seasonal variations in community structure were primarily driven by environmental factors such as temperature, dissolved oxygen (DO), and salinity. Co-occurrence network analysis indicated that surface water networks exhibited higher numbers of nodes and edges, as well as greater modularity, suggesting more distinct niche differentiation and higher natural connectivity within the community. These findings provide fundamental data for understanding the response mechanisms of eukaryotic microbial communities to seasonal changes in the mussel cultivation area of Gouqi Island. Full article