Search Results (1,268)

Applying selective iconic flow cells, we studied the degradation of organic matter, using urea as a reference pattern to a concentration of 10% and domestic residual waters taken from a characteristic flow of water in the Colombian city of Pasto. The experiments were performed in two hours, and we carried out the analysis in different stages. To assess the chemical demand of oxygen (COD) and to measure the quantity of produced hydrogen by selective ionic flow cells (SIFCs), the monitoring system Mhydros was used. Furthermore, a photovoltaic cell of 100 watts was used as the energy resource for the organic matter oxidation. The results point out that the SIFCs do degrade the organic matter by 64.3% wt and produce hydrogen with an electrical efficiency of 104.7% in two hours. Full article

With the rapid development of the edible fungus industry, the environmental pressure and resource waste caused by the massive generation of fungal residue have become increasingly prominent. Meanwhile, heavy metal wastewater pollution and the growing demand for clean energy pose dual challenges to sustainable development. This study focuses on Auricularia cornea var. Li. fungal residue, exploring the establishment of a multi-level resource utilization pathway integrating “porous carbon material preparation—heavy metal adsorption—photocatalytic hydrogen evolution.” Firstly, the Auricularia cornea var. Li. residue-based porous carbon material was examined by combining hydrothermal carbonization, activation and slow pyrolysis. In optimal conditions, the porous carbon obtained yielded a surface area of 675.56 m²/g and formed a composite pore structure consisting of micropores with coexisting micropore and mesopore. Secondly, we performed batch adsorption experiments to study the effects of solution pH, adsorbent dosage and contact time and the adsorption behavior via fitting adsorbing kinetic models. Under optimal conditions, Cd(II) removal efficiency reached 92.36% and an equilibrium adsorption capacity of 92.47 mg/g. We used Cd(II) adsorbed porous carbon as a cadmium source and converted into a CdS photocatalyst using a hydrothermal sulfidation process. The CdS prepared using sodium sulfide as a sulfur source gave an average hydrogen evolution rate of 668.01 μmol·g⁻¹·h⁻¹ and showed higher photocatalytic performance for water splitting to produce hydrogen. Full article

Coal mine underground reservoirs are increasingly used for mine-water storage and reuse in ecologically fragile mining regions, but the dynamic response of artificial dam structures under coupled water-pressure and seismic loading remains insufficiently understood. This study develops a simplified two-dimensional frame-based dynamic model to compare flat slab, gravity, and arch-equivalent artificial dams. Two water pressure levels, 0.1 and 1.0 MPa, and two seismic intensities, PGA = 0.1 g and 0.5 g, were considered using four representative acceleration histories. The arch dam was represented by a vertical rectangular section with equivalent arch-action lateral restraint. Results show that water pressure primarily controls peak total displacement, whereas PGA mainly governs the dynamic displacement increment and absolute acceleration. Increasing water pressure from 0.1 to 1.0 MPa markedly amplified total displacement and tensile stress demand, while increasing PGA from 0.1 g to 0.5 g produced a clearer effect on dynamic increments than on total displacement. The arch-equivalent dam consistently showed the smallest displacement response, while the gravity-type dam developed higher tensile stress demand under high water pressure in the simplified model. Effective modal frequencies were relatively high, explaining the coexistence of small displacement demand and noticeable acceleration response. The results provide a mechanistic basis for artificial dam-type comparison and preliminary safety assessment in underground reservoirs. Full article

Wastewater membrane bioreactors (MBRs) have become an important advanced treatment technology due to their ability to produce high-quality effluent suitable for discharge and water reuse. However, their broader and more sustainable application remains constrained by membrane fouling, elevated energy demand, and the operational complexity of coupled biological and membrane separation processes. This comprehensive review critically evaluates the growing application of machine learning (ML), explainable artificial intelligence (XAI), and digital twin (DT) technologies in MBR systems. Published studies on fouling prediction, energy optimization, effluent quality estimation, and intelligent operational support are critically evaluated, with explicit attention to model performance, dataset limitations, and generalizability. The reviewed literature shows that ML models, particularly ensemble methods, support vector machines, and deep learning approaches, have demonstrated strong potential for predicting major MBR performance indicators, including transmembrane pressure, permeate flux, fouling resistance, and selected effluent-quality variables. In parallel, XAI methods such as SHAP, LIME, and Anchors are increasingly being used to enhance model transparency and to reveal the dominant factors controlling process performance. Digital twin frameworks further extend this potential by enabling the integration of mechanistic understanding, online sensor data, data-driven prediction, and interpretable decision support within real-time operational platforms. Nevertheless, several barriers continue to hinder practical implementation, including the limited number of full-scale studies, the scarcity of openly accessible and standardized datasets, insufficient consideration of uncertainty and model drift, and the early-stage maturity of DT deployment in operational plants. The evidence reviewed suggests that integrating ML, XAI, and DT can substantially improve the reliability, interpretability, and operational efficiency of MBR systems. Future research should therefore focus on full-scale validation, the development of benchmark datasets, uncertainty-aware modeling, and practical deployment strategies for interpretable intelligent MBR management. Full article

The growing demand for sustainable and economically efficient road maintenance solutions has driven the development of materials that reduce the use of natural aggregates and promote waste valorization. In this context, this study evaluates the use of reclaimed asphalt pavement (RAP) and greywacke aggregates derived from Panasqueira mining by-products as partial or total substitutes for granite aggregates in cold asphalt mixtures intended for rapid pothole repair. Reference mixtures and recycled mixtures were produced with controlled proportions of RAP and greywacke, using cationic bituminous emulsion and hydrated lime, as well as an additional mixture composed only of RAP with a fluxing cold binder. Three commercial mixtures, identified as CCM1, CCM2, and CCM3, were also evaluated. Performance was analyzed through Cantabro particle loss, Marshall stability and flow, indirect tensile stiffness modulus, and water sensitivity (ITSR). The results show that greywacke provides a robust granular skeleton, while RAP content and binder type influence stiffness, cohesion, and moisture resistance. Overall, the combination of RAP and greywacke proved to be technically viable and, in several cases, superior to the commercial mixtures studied. Full article

Grape pomace, the main solid by-product of winemaking, is a promising feedstock for the recovery of trans-resveratrol, a high-value stilbene of increasing interest for food, nutraceutical, and pharmaceutical applications. However, its efficient isolation remains challenging because of matrix complexity, the co-occurrence of structurally related stilbenes and polyphenols, and the chemical instability of trans-resveratrol. This review critically examines recent advances in the recovery of trans-resveratrol from grape pomace, while also incorporating relevant findings from other grapevine-derived matrices to distinguish matrix-specific recovery potential and to place grape pomace within the broader context of grapevine by-product valorization from extraction intensification and selective purification to analytical determination. Various extraction technologies, including ultrasound-, microwave-, and enzyme-assisted extraction, natural deep eutectic solvents, and subcritical water extraction, are assessed alongside conventional solvent extraction with emphasis on yield, selectivity, solvent compatibility, and process feasibility. Downstream separation methods such as liquid–liquid partitioning, solid-phase isolation, adsorbent resins, counter-current chromatography, molecularly imprinted polymers, and foam fractionation are compared in terms of selectivity, enrichment efficiency, solvent demand, and scale-up potential. Although significant progress has been achieved, major challenges remain regarding process integration, solvent sustainability, product stability, and industrial feasibility. Combining mild extraction with selective downstream purification is essential for producing stable, high-purity trans-resveratrol fractions suitable for future use in functional ingredients, natural preservation strategies, and other value-added applications within sustainable food systems. Full article

Road freight transport is an important driver of global greenhouse gas (GHG) emissions. Decarbonizing this sector demands a comprehensive assessment of emerging powertrain technologies, which are currently lacking in the literature. To fill this knowledge gap, we performed a life cycle assessment (LCA) on 10 impact categories to evaluate road freight transport in the Netherlands of four truck alternatives, assuming similar performance: fuel-cell electric (FCEV), hydrogen internal combustion engine (HICEV), battery electric (BEV), and diesel internal combustion engine (DICEV). We compared locally produced green hydrogen, according to EU regulations, with electricity and diesel as alternative fuel chains, while also considering the environmental impact of road infrastructure. We found that FCEV and HICEV trucks achieve the lowest global warming impact when green hydrogen is used. We identified discrepancies between the transport alternatives, highlighting key factors influencing NO_x and particulate matter emissions. Our research also showed that water consumption (WC) for green hydrogen is strongly influenced by upstream processes, with solar-powered electricity emerging as a crucial contributor. Our results highlight the need for more exploration on the environmental impact of green hydrogen and can be used by researchers and practitioners to further understand the complexity of reducing emissions in road freight transport. Full article

The increasing demand for sustainable agricultural inputs has driven interest in biodegradable polymers from agro-industrial residues. Pineapple crown biomass (PCB), a widely available lignocellulosic waste, represents a promising feedstock for producing carboxymethylcellulose (CMC). However, the optimal pulping and bleaching conditions for CMC synthesis from this residue remain underexplored. Nevertheless, the combination of CMC derived from PCB with Bacillus subtilis as a seed coating agent for the bean cultivar has not yet been investigated. Here, we produced cellulosic pulps from PCB using a bioreactor, varying NaOH concentration (1–3%), pulping time (1.5–2.5 h), bleaching volume (55–75 mL) and time (60–120 min). The selected pulping condition (2% NaOH, 1.5 h) yielded pulp with high purity (83.9%) and crystallinity (76.35%). After bleaching (65 mL, 90 min), the material was suitable for CMC synthesis under two conditions: CMC1 and CMC2. CMC2 showed a higher degree of substitution (1.010) than CMC1 (0.620) but led to reduced seed germination (77.67%) due to excessive water retention and fungal growth. In contrast, CMC1, with or without B. subtilis, maintained high germination (91%) and significantly increased seedling length (21.30 cm). We conclude that PCB is a viable feedstock for CMC production, and CMC1 exhibits strong potential as an effective seed coating agent for sustainable agriculture. Full article

A growing global demand exists for natural alcoholic beverages produced through spontaneous fermentation with reduced use of commercial additives. In this context, the present study evaluated the impact of bee pollen addition as a nutrient source for wild yeasts on the physicochemical composition, color, phenolic compound profile, and antioxidant capacity of mead. Three distinct meads were produced by applying spontaneous fermentation of Apis mellifera honey: a control (honey diluted in water to 22 °Brix); honey diluted in water and supplemented with bee pollen (30 g L⁻¹); and honey diluted in water and supplemented with a commercial fermentation activator composed of ammonium phosphate (0.4 g L⁻¹). The use of nitrogen sources for wild yeasts reduced the fermentation time by up to 14 days. Notably, only bee pollen caused darkening of the mead, resulting in a more yellowish color. Seventeen phenolic compounds were identified in the meads, including phenolic acids, flavonols, and flavanols. The mead supplemented with bee pollen exhibited higher antioxidant capacity and a greater content of identified phenolic compounds, particularly quercetin-3-β-D-glucoside, at a concentration 100 times higher than that in the control (23.5 mg L⁻¹). These findings indicate that bee pollen acts as a multifunctional fermentative modulator, improving the fermentative performance of wild yeasts and promoting phenolic enrichment, thereby supporting its application in the development of mead. Full article

This paper develops a novel coupled model to predict the thermal behavior of a high-temperature fast heat storage unit, integrating Power-to-Heat technology with steam generation. A phase change material (PCM) made of a ZnAl₆ metal alloy is used for heat storage. Electricity is used to charge the battery, and the stored energy is used to produce superheated steam during discharge. The coupled model was based on a 3D multiphase CFD model of the heat storage unit and a 1D multiphase water boiling model implemented in Python language. The CFD model solves the transient conservation equations of mass, momentum, and energy using the enthalpy–porosity method to describe phase change, while heat transfer to water is represented by a coupled 1D boiling model. The paper also presents a preliminary design, a computational strategy, and boundary conditions for the operating modes, providing an analytical foundation for detailed engineering, production, and implementation in real-world industrial environments. The presented results confirmed the correct operation of the model and enabled the evaluation of system performance, discharge behavior, and validation of the geometric assumptions required to achieve the target steam parameters. The proposed modular design allows for system scalability, while the entire system is a response to the daily variability of electricity prices resulting from periodic reductions in demand and overproduction of electricity from renewable sources. Estimated thermal behavior of the thermal storage unit for the discharging scenario allows reaching constant output power at the level of 200 kW for 85 min. Integration with a cooling reduction station allows constant system power output to be maintained by increasing the mass flow rate as the steam parameters decrease from over 400 °C to 200 °C with a lowering state of charge. Full article

Given the increasing concern around greenhouse gas emissions and the decline in the availability of fossil fuels, there is increasing global demand to develop alternate fuels for maritime transportation that are sustainable and which have lower greenhouse gas emissions. Methanol is one such alternative fuel that has garnered considerable attention given its potential to be produced by more sustainable processes and its more favorable greenhouse gas emission profile in comparison with current fossil fuels. Understanding the physical and chemical properties of methanol under a range of conditions is essential for its development as a marine fuel. In this study, we seek to define physical and chemical properties of different methanol samples to simulate real-world storage conditions as these data are lacking in the literature. Several methanol samples were evaluated: nearly pure methanol; International Organization for Standardization (ISO) marine methanol (MM) grades A, B, and C; and methanol plus higher alcohols. We first evaluated all methanol samples for impurities, acetic acid content, density, and distillation range. We then characterized the effects of water absorption and found that methanol can easily absorb unacceptable water content from humid air within hours, necessitating storage conditions that prevent this process. In eight-week aging experiments at 20 °C and 40 °C in ambient air, we did not observe significant oxidation for any of the methanol samples; however, we did observe increases in acid number. We assessed the impact of contamination of methanol with water, marine gas oil (MGO), and an MGO–biodiesel mixture on density, viscosity, distillation range, and lubricity. Finally, we show that MGO contamination of methanol results in a slight increase in sooting tendency. In aggregate, our results provide an in-depth analysis of physical and chemical properties of methanol as well as the impacts of storage conditions and impurities on the properties of fuel methanol. Full article

Avocados produced in Colombia’s Caribbean region represent a biomass with high potential for valorization beyond fresh consumption, particularly when their fractions are exploited as sources of value-added compounds. This study proposes a dual-production system integrating oil extraction from the pulp and biochar generation from the seed under a process approach aimed at maximizing raw material utilization. The process performance was evaluated through the application of the Extended Water–Energy–Product (E-WEP) methodology, which allows for a comprehensive assessment of water, energy, and material consumption, as well as product generation efficiency, based on computer simulation results. The findings indicate an overall process yield of 14.20%, limited by the high raw material demand, although a high oil recovery efficiency of 83.95% was achieved. Water consumption reached 17.84 m³/t, with 99.25% converted into wastewater, highlighting the need for improved water management strategies. The process exhibited an energy demand of 3613.19 MJ/h, predominantly covered by natural gas consumption, which led to an energy intensity of 23,192.65 MJ/t. Furthermore, the obtained NER and EUI values of 0.53 and 2.84, respectively, suggest that the system does not operate under energy self-sufficiency conditions. Nevertheless, the resulting products still present considerable potential for energy recovery and subsequent valorization processes. Full article

The food-packaging sector is undergoing a major transition driven by the environmental burden associated with petroleum-based plastics and the increasing demand for sustainable alternatives. In this context, biodegradable packaging materials capable of extending food shelf life through active preservation functions have attracted considerable interest. Cellulose is the most abundant natural polymer and an attractive candidate for sustainable packaging; however, it lacks intrinsic antimicrobial activity. In the present study, innovative carboxymethyl cellulose (CMC)-based composite films were developed by incorporating zinc oxide (ZnO) nanoparticles (NPs) and thyme essential oil (TEO) as antibacterial active agents. The obtained films exhibited strong antibacterial activity against both Escherichia coli and Staphylococcus aureus, completely eliminating planktonic cell viability after 3 h of contact and producing inhibition zones of up to 30 mm. In addition to their biological performance, the composite films showed improved mechanical and functional properties. ZnO NPs appear to act as multifunctional junctions within the CMC matrix, while the dispersed TEO droplets contribute, together with the inorganic phase, to reduced water-vapor transfer. The films retained good transparency in the visible range while exhibiting UV-A transmittance below 7%, indicating enhanced light-barrier performance. Preliminary tests on soft cheese indicated shelf-life extension up to 14 days at 4 °C, while in inoculated cheese slices packed in the composite films, S. aureus was not detected from the 3rd day. Overall, these results demonstrate the potential of CMC/ZnO/TEO composite films as biodegradable active packaging materials for perishable food products. Full article

The increasing demand for sustainable, affordable smart city infrastructure has heightened the need for low-cost near-real-time water quality monitoring systems. In this study, we propose Water-QI, a low-cost Internet of Things (IoT)-based environmental monitoring platform that combines budget-friendly sensors with deep learning for water quality index (WQI) assessment and forecasting. The sensing platform measures five key physicochemical parameters, namely temperature, total dissolved solids (TDS), pH, turbidity, and electrical conductivity, enabling continuous multi-parameter monitoring in urban water environments. To model temporal variations in water quality under both cloud-based and edge-oriented deployment scenarios, we evaluate multiple gated recurrent unit (GRU) architectures with different widths and depths. Experiments are conducted at two temporal resolutions, hourly and minute-level, in order to examine the trade-off between predictive accuracy and edge computational latencies. In the hourly scenario, the single-layer GRU with 64 units achieved the best overall balance, reaching a validation RMSE of 0.0281 and a test $R^2$ of 0.9820, while deeper stacked GRU models degraded performance substantially. In the minute-resolution scenario, shallow wider GRU models produced the best results, with the single-layer GRU with 512 units attaining the lowest validation RMSE (0.025548) and the 256-unit variant achieving nearly identical accuracy with much lower inference cost. The results show that increasing the GRU model length can yield improvements at high temporal granularity, whereas increasing the GRU layer depth consistently harms convergence and generalization. Overall, the findings indicate that shallow GRU architectures provide the most practical solution for accurate, low-cost, and scalable water quality forecasting. In particular, the 64-unit GRU is the most suitable choice for hourly periodic interval operation, while the 256-unit GRU offers the best edge computational speed and accuracy trade-off for minute-level near-real-time inference on resource-constrained devices. Full article

To overcome the rapid expansion of the drawdown cone, severe inter-well interference, and high operating costs caused by independent geothermal well operation, this study investigated the coordinated optimal scheduling of geothermal water extraction. Fifteen geothermal production wells in the main urban area of Kaifeng City were selected as the study case. The intake intervals of these wells are located at depths of 1020 to 1330 m. Based on the exploitable yield of the geothermal reservoir, user water demand, and well layout, a management model for coordinated scheduling was developed. Design drawdown, water demand, and heating capacity were used as constraints. The objectives were to minimize operating cost, nodal drawdown, and drawdown interference between wells. The results from several optimization algorithms show that the improved Cheetah Optimization Algorithm converged faster and produced more consistent solutions. Compared with the preoptimization scheme, the optimized scheme reduced total operating cost by 31.64%, total drawdown in the study area by 69.5%, and the sum of inter-well drawdown interference by 34.7%. This study provides useful support for selecting efficient optimization algorithms and offers a basis for the scientific development, utilization, and protection of geothermal water resources. Full article