Search Results (8,377)

As a potential strategic resource of critical metals, deep-sea cobalt-rich crusts represent one of the most promising metal reservoirs within oceanic seamount systems, and their metallogenic mechanism constitutes a frontier topic in deep-sea geoscience research. This review focuses on the cobalt-rich crusts from the Magellan Seamount region in the northwestern Pacific and synthesizes existing geological, mineralogical, and geochemical studies to systematically elucidate their mineralization processes and metal enrichment mechanisms from a microstructural perspective, with particular emphasis on cobalt enrichment and its controlling factors. Based on published observations and experimental evidence, the formation of cobalt-rich crusts is divided into three stages: (1) Mn/Fe colloid formation—At the chemical interface between oxygen-rich bottom water and the oxygen minimum zone (OMZ), Mn²⁺ and Fe²⁺ are oxidized to form hydrated oxide colloids such as δ-MnO₂ and Fe(OH)₃. (2) Key metal adsorption—Colloidal particles adsorb metal ions such as Co²⁺, Ni²⁺, and Cu²⁺ through surface complexation and oxidation–substitution reactions, among which Co²⁺ is further oxidized to Co³⁺ and stably incorporated into MnO₆ octahedral vacancies. (3) Colloid deposition and mineralization—Mn–Fe colloids aggregate, dehydrate, and cement on the exposed seamount bedrock surface to form layered cobalt-rich crusts. This process is dominated by the Fe/Mn redox cycle, representing a continuous evolution from colloidal reactions to solid-phase mineral formation. Biological processes play a crucial catalytic role in the microstructural evolution of the crusts. Mn-oxidizing bacteria and extracellular polymeric substances (EPS) accelerate Mn oxidation, regulate mineral-oriented growth, and enhance particle cementation, thereby significantly improving the oxidation and adsorption efficiency of metal ions. Tectonic and paleoceanographic evolution, seamount topography, and the circulation of Antarctic Bottom Water jointly control the metallogenic environment and metal sources, while crystal defects, redox gradients, and biological activity collectively drive metal enrichment. This review establishes a conceptual framework of a multi-level metallogenic model linking macroscopic oceanic circulation and geological evolution with microscopic chemical and biological processes, providing a theoretical basis for the exploration, prediction, and sustainable development of potential cobalt-rich crust deposits. Full article

Salinization represents a significant threat to freshwater resources worldwide, compromising water quality and security. In the Vieira de Leiria–Marinha Grande aquifer, salinization mechanisms are a complex interaction between seawater intrusion and evaporite dissolution. Near the coast, groundwater is mainly influenced by seawater, evidenced by Na-Cl hydrochemical facies, high electrical conductivity, and Na⁺/Cl⁻, Cl⁻/Br⁻ and SO₄^2−/Cl⁻ molar ratios consistent with marine signatures. In areas affected by diapiric dissolution, besides elevated electrical conductivity, groundwater is enriched in SO₄²⁻ and Ca²⁺ and in minor elements like K⁺, Li⁺, B³⁺, Ba²⁺ and Sr²⁺, and high SO₄²⁻/Cl⁻ and Ca²⁺/HCO₃⁻ molar ratios, indicative of gypsum/anhydrite dissolution. The relationship between δ¹⁸O and electrical conductivity further supports the identification of distinct salinity sources. This study integrates hydrogeochemical tracers to investigate hydrochemical evolution in the aquifer with increasing residence time and influence of water–rock interaction, as well as the accurate characterization of salinization mechanisms in multilayer aquifers. A comprehensive understanding of these processes is essential for identifying vulnerable zones and developing effective management strategies to ensure the protection and sustainable use of groundwater resources. Full article

At present, the global shortage of water resources has led to serious challenges, and traditional water production technologies such as seawater desalination and atmospheric water harvesting have certain limitations due to inflexible operation and environmental conditions. This study proposes a novel water production system (called “NeWater” system in this paper), which combines saline water desalination with atmospheric water-harvesting technologies to simultaneously produce freshwater from brackish water or seawater and ambient air. To evaluate its performance, an integrated thermodynamic and mathematical model of the system was developed and validated. The NeWater system consists of a vapor compression refrigeration unit (VRU), a direct evaporation unit (DEU), up to four heat exchangers, some valves, and auxiliary components. The system can be applied to areas and scenarios where traditional desalination technologies, like reverse osmosis and thermal-based desalination, are not feasible. By switching between different operating modes, the system can adapt to varying environmental humidity and temperature conditions to maximize its freshwater productivity. Based on the principles of mass and energy conservation, a performance simulation model of the NeWater system was developed, with which the impacts of some key design and operation parameters on system performance were studied in this paper. The results show that the performances of the VRU and DEU had a significant influence on system performance in terms of freshwater production and specific energy consumption. Under optimal conditions, the total freshwater yield could be increased by up to 1.9 times, while the specific energy consumption was reduced by up to 48%. The proposed system provides a sustainable and scalable water production solution for water-scarce regions. Optimization of the NeWater system and the selection of VRUs are beyond the scope of this paper and will be the focus of future research. Full article

Northwestern Jiangxi Province is rich in metasilicic acid (as H₂SiO₃) mineral water resources. Investigating their hydrogeochemical characteristics and formation mechanism is crucial for the rational utilization of water resources and the sustainable development of the local mineral water industry. Taking the Taoping water source area in northwestern Jiangxi as a case study, 11 sets of groundwater and surface water samples were systematically collected. By comprehensively applying mathematical statistics, ionic ratios, and isotopic analyses, the hydrogeochemical characteristics and formation processes of metasilicic acid-type mineral water were examined. The results indicate that: (1) The mineral waters in the area are weakly alkaline and belong to the metasilicic acid type, with concentrations ranging from 22.0 to 67.0 mg/L, of which 75% exceed 30 mg/L. (2) The primary hydrochemical types are HCO₃⁻–Ca·Na, HCO₃⁻–Ca·Mg, and HCO₃⁻–Ca. Analysis of stable isotopes (δ¹⁸O and δ²H) and tritium (³H) indicates that metasilicic acid mineral water is primarily recharged by atmospheric precipitation, with an apparent groundwater age of approximately 60 years. (3) The enrichment of metasilicic acid primarily results from the weathering and leaching of silicate minerals, coupled with cation exchange. K⁺ and Na⁺ are mainly derived from silicate minerals such as feldspars and halite, whereas Ca²⁺ and Mg²⁺ originate primarily from carbonate minerals like calcite and dolomite. During recharge, atmospheric precipitation infiltrates the aquifer, dissolving aluminosilicate and siliceous minerals in the surrounding rocks, thereby releasing metasilicic acid into the groundwater and ultimately forming the metasilicic acid-type mineral water. Full article

With the acceleration of industrialization, the problems of water resource pollution and shortage caused by oil spills and industrial wastewater discharge have become increasingly severe, posing a major threat to ecological sustainable development. Therefore, efficient oil–water separation technology has become a key breakthrough to alleviate this crisis. In this study, Janus membranes with asymmetric wettability were prepared by layer-by-layer electrospinning. The influence of the thickness ratio between the hydrophobic layer and the hydrophilic layer on the mechanical properties, separation flux, and oil–water mixture efficiency of the Janus membranes was examined, and an optimized membrane configuration was determined: the optimal thickness ratio between hydrophobic and hydrophilic layers was 4:6. Under these conditions, the fracture stress of the fiber membranes reached 99% MPa, the fracture strain was 55.63 ± 4.77%, the separation flux values were 1888.22 and 1042.66 L m⁻² h⁻¹ for the oil–water mixture and water-in-oil emulsion, respectively, with the separation efficiencies all exceeding 99%. After 50 cycles of separation for two different oil-in-water emulsions, the separation flux and separation efficiency of the optimal sample remained relatively stable, demonstrating strong practicability. In general, the Janus fiber membranes met the expected requirements, laying a good foundation for future applications in oil–water separation, floating oil collection in water, and other fields. Full article

A portable and integrated monitoring device was developed to digitally assess both water levels and surrounding fire-related conditions in forest firefighting water buckets using multi-sensor fusion. The system integrates a hydrostatic liquid-level sensor with temperature–humidity and smoke sensors. Validation was performed through field-oriented experiments conducted under semi-controlled conditions. Water-level measurements were collected over a three-month period under simulated forest conditions and benchmarked against conventional steel-ruler readings. Early-stage fire monitoring experiments were carried out using dry wood and leaf litter under varying wind speeds, wind directions, and representative extreme weather conditions. The device achieved a mean water-level bias of −0.60%, a root-mean-square error of 0.64%, and an overall accuracy of 99.36%. Fire monitoring reached a maximum detection distance of 7.30 m under calm conditions and extended to 16.50 m under strong downwind conditions, with performance decreasing toward crosswind directions. Stable operation was observed during periods of strong winds associated with typhoon events, as well as prolonged high-temperature exposure. The primary novelty of this work lies in the conceptualization of a Collaborative Forest Resource–Hazard Monitoring Architecture. Unlike traditional isolated sensors, our proposed framework utilizes a dual-domain decision-making model that simultaneously assesses water-bucket storage stability and micro-scale fire threats. By implementing a robust ‘sensing–logic–alert’ framework tailored for rugged environments, this study offers a new methodological reference for the intelligent management of forest firefighting resources. Full article

Manual window cleaning in high-rise urban buildings is labor-intensive, risky, and resource-inefficient. This study addresses these challenges by investigating a resource-aware mechatronic architecture through the design, development, and experimental validation of a modular Automated Window Cleaning System (AWCS). Unlike conventional open-loop solutions, the AWCS integrates mechanical scrubbing with a closed-loop fluid management system, featuring precise dispensing and vacuum-assisted recovery. The system is governed by a deterministic finite state machine implemented on an ESP32 microcontroller, enabling low-latency IoT connectivity and autonomous operation. Two implementation variants—integrated and retrofit—were validated to ensure structural adaptability. Experimental results across 30 cycles demonstrate a cleaning efficiency of ~2 min/m², a water consumption of <150 mL/m² (representing a >95% reduction compared to manual methods), and an optical cleaning efficacy of 96.9% ± 1.4%. Safety protocols were substantiated through a calculated mechanical safety factor of 6.12 for retrofit applications. This research establishes the AWCS as a sustainable, safe, and scalable solution for autonomous building maintenance, contributing to the advancement of resource-circular domestic robotics and smart home automation. Full article

Driven by the national policy of total water resources control and efficiency improvement, the behavior of water resource utilization reduction by firms is widespread, which may have an impact on the value of firms. This study integrates dynamic capability theory and signaling theory to construct a dual-path analytical framework, systematically investigating the impact of water utilization reduction on firm value and its intrinsic mechanisms. Based on data from Chinese A-share listed companies spanning 2012–2023, fixed-effect models, mediation-effect tests, and heterogeneity analysis are employed for empirical verification. The results reveal that water utilization reduction exerts a significant dual-path promoting effect on firm value: it enhances financial performance (ROA) primarily through technological innovation, reflecting the process of resource orchestration and dynamic capability construction; concurrently, it boosts market performance (Tobin’s Q) mainly by improving ESG performance as a signaling channel, mirroring the capital market’s positive pricing of green signals. Further heterogeneity analysis indicates that these effects are more pronounced during the policy deepening stage, in non-water-intensive industries, and in humid/sub-humid regions. This study contributes theoretical support and empirical evidence for firms’ green transformation and the formulation of differentiated water resource policies by the government, highlighting the synergistic development of high-quality economic growth and ecological civilization construction. Full article

Accurate delineation of inland waterbodies is critical for applications such as hydrological monitoring, disaster response preparedness and response, and environmental management. While optical satellite imagery is hindered by cloud cover or low-light conditions, Synthetic Aperture Radar (SAR) provides consistent surface observations regardless of weather or illumination. This study introduces a deep learning-based ensemble framework for precise inland waterbody detection using high-resolution X-band Capella SAR imagery. To improve the discrimination of water from spectrally similar non-water surfaces (e.g., roads and urban structures), an 8-channel input configuration was developed by incorporating auxiliary geospatial features such as height above nearest drainage (HAND), slope, and land cover classification. Four advanced deep learning segmentation models—Proportional–Integral–Derivative Network (PIDNet), Mask2Former, Swin Transformer, and Kernel Network (K-Net)—were systematically evaluated via cross-validation. Their outputs were combined using a weighted average ensemble strategy. The proposed ensemble model achieved an Intersection over Union (IoU) of 0.9422 and an F1-score of 0.9703 in blind testing, indicating high accuracy. While the ensemble gains over the best single model (IoU: 0.9371) were moderate, the enhanced operational reliability through balanced Precision–Recall performance provides significant practical value for flood and water resource monitoring with high-resolution SAR imagery, particularly under data-constrained commercial satellite platforms. Full article

The study investigates the presence of emerging contaminants in a river within a watershed located in the Brazilian semiarid region, specifically within the Caatinga biome, emphasizing the importance of environmental monitoring in areas that have historically been underrepresented in scientific research. The analysis focused on the associations between microplastics and pharmaceutical compounds, demonstrating that the discharge of untreated domestic effluents and the low efficiency of sanitation systems increase water resource contamination and threaten water security. The interdependence between these variables underscores the need for integrated public policies for waste management, complemented by environmental education strategies and technological innovations. The work makes an unprecedented contribution to expanding knowledge about emerging pollutants in semiarid environments, highlighting the urgency of holistic approaches, continuous monitoring, and strengthening environmental governance to ensure the sustainability and resilience of ecosystems like the Caatinga in the face of the challenges posed by global environmental change, urban growth, and those outlined in the Sustainable Development Goals. Full article

Under the combined influences of climate change and anthropogenic activities, the variability of basin streamflow has intensified, posing substantial challenges for accurate prediction. Although Generalized Autoregressive Conditional Heteroskedasticity (GARCH) models characterize volatility in time series, many previous studies have neglected changes in series structure, leading to inaccurate identification of the form of volatility. Building on tests for structural breaks (SBs) in time series, this study first removes the series mean using an Autoregressive Integrated Moving Average (ARIMA) model and then incorporates Markov-switching (MS) to develop a multi-state MS-GARCH model. An asymmetric MS-GARCH (MS-gjrGARCH) variant is also incorporated to describe the volatility of streamflow series with SBs. Daily streamflow data from five hydrological stations in the middle reaches of the Yellow River are used to compare the predictive performance of SB-ARIMA-MS-GARCH, SB-ARIMA-MS-gjrGARCH, ARIMA-GARCH, and ARIMA-gjrGARCH models. The results show that daily streamflow exhibits SBs, with the number and timing of breakpoints varying among stations. Standard GARCH and gjrGARCH models have limited ability to capture runoff volatility clustering, whereas MS-GARCH and MS-gjrGARCH effectively characterize volatility features within individual states. The multi-state switching structure substantially improves daily streamflow prediction accuracy compared with single-state volatility models, increasing R² by approximately 5.8% and NSE by approximately 36.3%.The proposed modeling framework offers a robust new tool for streamflow prediction in such changing environments, providing more reliable evidence for water resource management and flood risk mitigation in the Yellow River basin. Full article

The pressure of climate change on water resources has made the development of reliable hydrological models increasingly important, especially for data-scarce regions. However, due to the limited availability of ground-based observations, it considerably affects the accuracy of models developed using these inputs. This also limits the ability to investigate future hydrological behavior. Satellite-based data sources have emerged as an alternative to address this challenge and have received significant attention. However, the transferability of these datasets across different model classes has not been widely explored. This paper evaluates the transferability of satellite-derived inputs to eleven types of models, including process-based (SWAT), data-driven methods (XGBoost and WGAN), and hybrid model structures that utilize SWAT outputs with AI models. SHAP has been applied to overcome the black-box limitations of AI models and gain insights into fundamental hydrometeorological processes. In addition, uncertainty analysis was performed for all models, enabling a more comprehensive evaluation of performance. The results indicate that hybrid models using SWAT combined with WGAN can achieve better predictive accuracy than the SWAT model based on ground observation. While the baseline SWAT model achieved satisfactory performance during the validation period (NSE ≈ 0.86, KGE ≈ 0.80), the hybrid SWAT + WGAN framework improved simulation skill, reaching NSE ≈ 0.90 and KGE ≈ 0.89 during validation. Models forced with satellite-derived meteorological inputs additionally performed as well as those forced using station-based observations, validating the feasibility of using satellite products as alternative data sources. The future hydrological status of the basin was assessed based on the best-performing hybrid model and CMIP6 climate projections, showing a clear drought signal in the flows and long-term reductions in average flows reaching up to 58%. Overall, the findings indicate that the proposed framework provides a consistent approach for data-scarce basins. Future applications may benefit from integrating spatio-temporal learning frameworks and ensemble-based uncertainty quantification to enhance robustness under changing climate conditions. Full article

Polyester fibers are extensively used in textiles, packaging, and industrial applications due to their durability and excellent mechanical properties. However, high-crystallinity polyester fibers represent a major challenge in plastic waste management due to their resistance to biodegradation. This study evaluated the biodegradation potential of environmental Bacillus isolates, obtained from mold-contaminated black bean plastic bags, toward polyethylene terephthalate (PET) and industrial-grade polyester fibers under mesophilic conditions. Among thirteen isolates, five (Bacillus altitudinis N5, Bacillus subtilis N6, and others) exhibited measurable degradation within 30 days, with mass losses up to 5–6% and corresponding rate constants of 0.04–0.05 day⁻¹. A combination of complementary characterization techniques, including mass loss analysis, scanning electron microscopy (SEM), gel permeation chromatography (GPC), and gas chromatography/mass spectrometry (GC/MS), together with Fourier-transform infrared spectroscopy (FTIR), thermogravimetric/differential scanning calorimetry (TGA/DSC), and water contact angle (WCA) analysis, was employed to evaluate the biodegradation behavior of polyester fibers. Cross-analysis of mass loss, surface morphology, molecular weight reduction, and degradation products suggests a surface erosion-dominated degradation process, accompanied by ester-bond hydrolysis and preferential degradation of amorphous regions. FTIR, TGA/DSC, and WCA analyses further reflected chemical, thermal, and surface property changes induced by biodegradation rather than directly defining the degradation mechanism. The findings highlight the capacity of mesophilic Bacillus species to partially depolymerize polyester fibers under mild environmental conditions, providing strain resources and mechanistic insight for developing low-energy bioprocesses for polyester fiber waste management. Full article

Laboratory maintenance of mosquitoes is important for studying vector biology and transmission of diseases, and for testing vector control tools. Standard operating procedures require feeding larvae with commercial fish meal. However, for many insectaries in sub-Saharan Africa, the commonly used feeds are imported and accompanied by procurement challenges. Changing the larval feed abruptly without allowing the larvae to adapt to new brands of feed also leads to a decrease in mosquito colonies in the laboratory. We investigated locally acquired beans, maize, and dried herrings as alternate feeds for mosquito larvae reared under laboratory conditions. Four replicates for each treatment were prepared, each containing 100 first instar larvae of Anopheles gambiae Tiassalé mosquitoes. The larvae were introduced into 500 mL of dechlorinated tap water and maintained under standard environmental insectary conditions. The larvae were provided with 40 mg of the designated powdered feed—beans, maize, and herring fish—in single and combined treatments. Tetra^® goldfish meal was included as a control. The larval mortality, developmental time, and number of pupae were recorded to evaluate the effectiveness of the feeds. Adult mosquitoes were weighed and measured to assess fitness, and females from each treatment were blood-fed and allowed to lay eggs to evaluate fertility. Larval survival differed significantly across diets (Kruskal–Wallis, p = 0.01), with maize-fed larvae showing the highest mortality (41.3%) and those with herring-based diets the lowest. Pupation and adult emergence were poorest in the maize and maize–bean groups, while the maize–herring combination achieved the highest emergence (92.6%, p = 0.03). Although overall differences were detected among the groups, conservative pairwise tests did not pinpoint specific group contrasts, but effect size estimates suggested biologically meaningful patterns. Generally, adult body weight and wing length did not differ by treatment except in maize-fed males (β = 0.371 mm, p = 0.022). Herring fish-based diets consistently supported larval survival, timely development, and robust fecundity, whereas maize-based diets were nutritionally inadequate. These findings highlight herring fish-based diets as a sustainable and cost-effective alternative to commercial feeds for maintaining Anopheles mosquito colonies, with potential to strengthen vector research capacity in resource-limited laboratories. Full article

Urban Water Systems (UWS) are complex infrastructures that interact with energy, food, ecosystems and socio-political systems, and are under growing pressure from climate change and resource depletion. Planning circular interventions in this context requires system-level analysis to avoid fragmented, siloed decisions. This paper develops the Hydrosocial Resource Urban Nexus (HRUN) framework that integrates hydrosocial thinking with the Water–Energy–Food–Ecosystems (WEFE) nexus to guide UWS design. We conduct a structured literature review and analyse different configurations of circular interventions, mapping their synergies and trade-offs across socioeconomic and environmental functions of hydrosocial systems. The framework is operationalised through a typology of circular interventions based on their circularity purpose (water reuse, resource recovery and reuse, or water-cycle restoration) and management scale (from on-site to centralised), while greening degree (from grey to green infrastructure) and digitalisation (integration of sensors and control systems) are treated as transversal strategies that shape their operational profile. Building on this typology, we construct cause–effect matrices for each intervention type, linking recurring operational patterns to hydrosocial functionalities and revealing associated synergies and trade-offs. Overall, the study advances understanding of how circular interventions with different configurations can strengthen or weaken system resilience and sustainability outcomes. The framework provides a basis for integrated planning and for quantitative and participatory tools that can assess trade-offs and governance effects of different circular design choices, thereby supporting the transition to more resilient and just water systems. Full article