Search Results (671)

The Union of the Comoros, located in the Indian Ocean, faces persistent energy challenges due to its geographic isolation, heavy dependence on imported fossil fuels, and underdeveloped electricity infrastructure. This study investigates the techno-economic optimization of a hybrid microgrid designed to supply electricity to a rural village in Grande Comore. The proposed system integrates photovoltaic (PV) panels, wind turbines, a diesel generator, and battery storage. Detailed modeling and simulation were conducted using HOMER Energy, accompanied by a sensitivity analysis on solar irradiance, wind speed, and diesel price. The results indicate that the optimal configuration consists solely of PV and battery storage, meeting 100% of the annual electricity demand with a competitive levelized cost of energy (LCOE) of 0.563 USD/kWh and zero greenhouse gas emissions. Solar PV contributes over 99% of the total energy production, while wind and diesel components remain unused under optimal conditions. Furthermore, the system generates a substantial energy surplus of 63.7%, which could be leveraged for community applications such as water pumping, public lighting, or future system expansion. This study highlights the technical viability, economic competitiveness, and environmental sustainability of 100% solar microgrids for non-interconnected island territories. The approach provides a practical and replicable decision-support framework for decentralized energy planning in remote and vulnerable regions. Full article

A shallow quaternary sedimentary aquifer within the river alluvial deposits of eastern Uzbekistan is increasingly vulnerable to the impacts of climate change and anthropogenic activities. Despite its essential role in supplying water for domestic, agricultural, and industrial purposes, the aquifer system remains poorly understood. This study employed a three-dimensional MODFLOW-based groundwater flow model to assess climate change impacts on water budget components under the SSP5-8.5 scenario for 2020–2099. Model calibration yielded RMSE values between 0.25 and 0.51 m, indicating satisfactory performance. Simulations revealed that lateral inflows from upstream and side-valley alluvial deposits contribute over 84% of total inflow, while direct recharge from precipitation (averaging 120 mm/year, 24.7% of annual rainfall) and riverbed leakage together account for only 11.4%. Recharge occurs predominantly from November to April, with no recharge from June to August. Under future scenarios, winter recharge may increase by up to 22.7%, while summer recharge could decline by up to 100%. Groundwater storage is projected to decrease by 7.3% to 58.3% compared to 2010–2020, indicating the aquifer’s vulnerability to prolonged dry periods. These findings emphasize the urgent need for adaptive water management strategies and long-term monitoring to ensure sustainable groundwater use under changing climate conditions. Full article

Cereal-based plant beverages have gained attention as functional ingredients in bakery formulations, offering both nutritional and technological benefits. Replacing water with these beverages may improve the nutritional value of bread by increasing its fiber and unsaturated fatty acid content, while also introducing functional components that affect dough rheology and bread texture. This study examined the effects of substituting water with oat (BO), millet (BM), and spelt (BS) beverages in wheat bread formulations at 25%, 50%, 75%, and 100% levels. Thirteen bread variants were prepared: one control and four substitution levels for each of the three cereal-based beverages, using the straight dough method, with hydration adjusted according to farinograph results. Farinograph tests showed increased water absorption (up to 64.5% in BO100 vs. 56.9% in control) and improved dough stability (10.6 min in BS100). Specific bread volume increased, with BS75 reaching 3.52 cm³/g compared to 3.09 cm³/g in control. Moisture content remained stable during storage, and crumb hardness after 72 h was lowest in BO100 (9.5 N) and BS75 (11.5 N), indicating delayed staling. All bread variants received favorable sensory ratings, with average scores above 3.75 on a 5-point scale. The highest bread yield (149.8%) and lowest baking loss (10.9%) were noted for BS100. Although BO breads had slightly higher fat and energy content, their nutritional profile remained favorable due to unsaturated fatty acids. Overall, oat and spelt beverages demonstrated the greatest potential as functional water substitutes, improving dough handling, shelf-life, and sensory quality while maintaining consumer appeal. Full article

Evapotranspiration (ET) crucially regulates water storage dynamics and is an essential component of the terrestrial water cycle. Understanding ET dynamics is fundamental for sustainable water resource management, particularly in regions facing increasing drought risks under climate change. In regions like southwestern China, where extreme drought events are prevalent due to complex terrain and climate warming, ET becomes a key factor in understanding water availability and drought dynamics. Using the SWAT model, this study investigates ET dynamics and influencing factors in the Jizi Basin, Yunnan Province, a small basin with over 71% forest coverage. The model calibration and validation results demonstrated a high degree of consistency with observed discharge data and ERA5, confirming its reliability. The results show that the annual average ET in the Jizi Basin is 573.96 mm, with significant seasonal variations. ET in summer typically ranges from 70 to 100 mm/month, while in winter, it drops to around 20 mm/month. Spring ET exhibits the highest variability, coinciding with the occurrence of extreme hydrological events such as droughts. The monthly anomalies of ET effectively reproduce the spring and early summer 2019 drought event. Notably, ET variation exhibits significant uncertainty under scenarios of +1 °C temperature and −20% precipitation. Furthermore, although land use changes had relatively small effects on overall ET, they played crucial roles in promoting groundwater recharge through enhanced percolation, especially forest cover. The study highlights that, in addition to climate and land use, soil moisture and groundwater conditions are vital in modulating ET and drought occurrence. The findings offer insights into the hydrological processes of small forested basins in southwestern China and provide important support for sustainable water resource management and effective climate adaptation strategies, particularly in the context of increasing drought vulnerability. Full article

Strategic petroleum reserves are critical for energy security. In Japan, 0.5 million kiloliters of crude oil (12% of the state-owned reserves) is stored using underground rock-cavern tanks, which comprise unlined horizontal tunnels bored into bedrock. Crude oil is held within the tank by water inside the tank, the pressure of which is kept higher than that of the crude oil by natural groundwater and irrigation water. This study applied microbial DNA-based monitoring to assess the water environments in and around national petroleum-stockpiling bases (the Kuji, Kikuma, and Kushikino bases) using the rock-cavern tanks. Forty-five water samples were collected from the rock-cavern tanks, water-supply tunnels, and observation wells. Principal-component analysis and hierarchical clustering indicated that microbial profiles of the water samples reflect the local environments of their origins. Particularly, the microbial profiles of water inside the rock-cavern tanks were distinct from other samples, revealing biological conditions and hence environmental characteristics within the tanks. Moreover, the clustering analysis indicated distinct features of water samples that have not been detected by other monitoring methods. Thus, microbial DNA-based monitoring provides valuable information on the in situ environments of rock-cavern tanks and can serve as an extremely sensitive measurement to monitor the underground oil storage. Full article

Wetlands are critical components of the global carbon cycle, yet their carbon sink dynamics under hydrological fluctuations remain insufficiently understood. This study employed the Carnegie-Ames-Stanford Approach (CASA) model to estimate the net ecosystem productivity (NEP) of the Dongting Lake wetland and explored the spatiotemporal dynamics and driving mechanisms of carbon sinks from 2000 to 2022, utilizing the Theil-Sen median trend, Mann-Kendall test, and attribution based on the differentiating equation (ADE). Results showed that (1) the annual mean spatial NEP was 50.24 g C/m²/a, which first increased and then decreased, with an overall trend of −1.5 g C/m²/a. The carbon sink was strongest in spring, declined in summer, and shifted to a carbon source in autumn and winter. (2) Climate variability and human activities contributed +2.17 and −3.73 g C/m²/a to NEP, respectively. Human activities were the primary driver of carbon sink degradation (74.30%), whereas climate change mainly promoted carbon sequestration (25.70%). However, from 2000–2011 to 2011–2022, climate change shifted from enhancing to limiting carbon sequestration, mainly due to the transition from water storage and lake reclamation to ecological restoration policies and intensified climate anomalies. (3) NEP was negatively correlated with precipitation and water level. Land use adjustments, such as forest expansion and conversion of cropland and reed to sedge, alongside maintaining growing season water levels between 24.06~26.44 m, are recommended to sustain and enhance wetland carbon sinks. Despite inherent uncertainties in model parameterization and the lack of sufficient in situ flux validation, these findings could provide valuable scientific insights for wetland carbon management and policy-making. Full article

As a pivotal technology and infrastructure component for modern power systems, energy storage has experienced significant advancement in recent years. A fundamental prerequisite for designing future energy storage facilities lies in the systematic evaluation of energy conversion capabilities across diverse storage technologies. This study conducted a comparative analysis between pumped hydroelectric storage (PHS) and compressed air energy storage (CAES), defining the concepts of height exergy and temperature exergy. Height exergy is the maximum work capacity of a liquid due to height differences, while temperature exergy is the maximum work capacity of a gas due to temperature differences. The temperature exergy represents innovation in thermodynamic analysis; it is derived from internal exergy and proven through the Maxwell relation and the decoupling method of internal exergy, offering a more efficient method for calculating energy storage capacity in CAES systems. Mathematical models of height exergy and temperature exergy were established based on their respective forms. A unified calculation formula was derived, and their respective characteristics were analyzed. In order to show the meaning of temperature exergy more clearly and intuitively, a height exergy model of temperature exergy was established through analogy analysis, and it was concluded that the shape of the reservoir was a cone when comparing water volume to heat quantity, intuitively showing that the cold source had a higher energy storage density than the heat source. Finally, a typical hybrid PHS–CAES system was proposed, and a mathematical model was established and verified in specific cases based on height exergy and temperature exergy. It was demonstrated that when the polytropic exponent n = 1.2, the theoretical loss accounted for the largest proportion, which was 2.06%. Full article

The rising demand for sustainable energy storage has fueled the development of green batteries as alternatives to conventional systems. However, a major research gap lies in the unified integration of environmentally friendly materials and processes across all battery components—electrodes, electrolytes, and separators—without compromising performance or scalability. This review addresses this gap by highlighting recent advances in eco-conscious battery technologies, focusing on green electrode fabrication using water-based methods, electrophoretic deposition, solvent-free dry-press coating, 3D printing, and biomass-derived materials. It also examines the shift toward safer electrolytes, including ionic liquids, deep eutectic solvents, water-based systems, and solid biopolymer matrices, which improve both environmental compatibility and safety. Additionally, biodegradable separators made from natural polymers such as cellulose and chitosan offer enhanced thermal stability and ecological benefits. The review emphasizes the importance of lifecycle considerations like recyclability and biodegradability, aligning battery design with circular economy principles. While significant progress has been made, challenges such as standardization, long-term stability, and industrial scalability remain. By identifying key strategies and future directions, this article contributes to the foundation for next-generation green batteries, promoting their adoption in environmentally sensitive applications ranging from wearable electronics to grid storage. Full article

Nuclear Magnetic Resonance (NMR) and Magnetic Resonance Imaging (MRI) are powerful techniques that have been employed to analyze foodstuffs comprehensively. These techniques offer in-depth information about the chemical composition, structure, and spatial distribution of components in a variety of food products. Quantitative NMR is widely applied for precise quantification of metabolites, authentication of food products, and monitoring of food quality. Low-field ¹H-NMR relaxometry is an important technique for investigating the most abundant components of intact foodstuffs based on relaxation times and amplitude of the NMR signals. In particular, information on water compartments, diffusion, and movement can be obtained by detecting proton signals because of H₂O in foodstuffs. Saffron adulterations with calendula, safflower, turmeric, sandalwood, and tartrazine have been analyzed using benchtop NMR, an alternative to the high-field NMR approach. The fraudulent addition of Robusta to Arabica coffee was investigated by ¹H-NMR Spectroscopy and the marker of Robusta coffee can be detected in the ¹H-NMR spectrum. MRI images can be a reliable tool for appreciating morphological differences in vegetables and fruits. In kiwifruit, the effects of water loss and the states of water were investigated using MRI. It provides informative images regarding the spin density distribution of water molecules and the relationship between water and cellular tissues. ¹H-NMR spectra of aqueous extract of kiwifruits affected by elephantiasis show a higher number of small oligosaccharides than healthy fruits do. One of the frauds that has been detected in the olive oil sector reflects the addition of hazelnut oils to olive oils. However, using the NMR methodology, it is possible to distinguish the two types of oils, since, in hazelnut oils, linolenic fatty chains and squalene are absent, which is also indicated by the ¹H-NMR spectrum. NMR has been applied to detect milk adulterations, such as bovine milk being spiked with known levels of whey, urea, synthetic urine, and synthetic milk. In particular, T2 relaxation time has been found to be significantly affected by adulteration as it increases with adulterant percentage. The ¹H spectrum of honey samples from two botanical species shows the presence of signals due to the specific markers of two botanical species. NMR generates large datasets due to the complexity of food matrices and, to deal with this, chemometrics (multivariate analysis) can be applied to monitor the changes in the constituents of foodstuffs, assess the self-life, and determine the effects of storage conditions. Multivariate analysis could help in managing and interpreting complex NMR data by reducing dimensionality and identifying patterns. NMR spectroscopy followed by multivariate analysis can be channelized for evaluating the nutritional profile of food products by quantifying vitamins, sugars, fatty acids, amino acids, and other nutrients. In this review, we summarize the importance of NMR spectroscopy in chemical profiling and quality assessment of food products employing magnetic resonance technologies and multivariate statistical analysis. Full article

The proposed study incorporates a stochastic demand side management (SDSM) strategy for a self-sufficient residential system powered from a PV source with a hybrid battery–hydrogen storage system to minimize the total degradation costs associated with key components, including Li-io batteries, fuel cells, and PEM electrolyzers. The uncertainty in demand forecasting is addressed through a scenario-based generation to enhance the robustness and accuracy of the proposed method. Then, stochastic optimization was employed to determine the optimal operating schedules for deferable appliances and optimal water heater (WH) settings. The optimization problem was solved using a genetic algorithm (GA), which efficiently explores the solution space to determine the optimal operating schedules and reduce degradation costs. The proposed SDSM technique is validated through MATLAB 2020 simulations, demonstrating its effectiveness in reducing component degradation costs, minimizing load shedding, and reducing excess energy generation while maintaining user comfort. The simulation results indicate that the proposed method achieved total degradation cost reductions of 16.66% and 42.6% for typical summer and winter days, respectively, in addition to a reduction of the levelized cost of energy (LCOE) by about 22.5% compared to the average performance of 10,000 random operation scenarios. Full article

Groundwater storage refers to the water stored in the pore spaces of underground aquifers, which has been increasingly affected by both climate change and anthropogenic activities in recent decades. Therefore, monitoring their changes and the factors that affect it is of great importance. Although the influence of natural factors on groundwater is well-recognized, the impact of human activities, despite being a major contributor to its change, has been less explored due to the challenges in measuring such effects. To address this gap, our study employed an integrated approach using remote sensing and the Google Earth Engine (GEE) cloud-free platform to analyze the effects of various anthropogenic factors such as built-up areas, cropland, and surface water on groundwater storage in the Lake Urmia Basin (LUB), Iran. Key anthropogenic variables and groundwater data were pre-processed and analyzed in GEE for the period from 2000 to 2022. The processes linking these variables to groundwater storage were considered. Built-up area expansion often increases groundwater extraction and reduces recharge due to impervious surfaces. Cropland growth raises irrigation demand, especially in semi-arid areas like the LUB, leading to higher groundwater use. In contrast, surface water bodies can supplement water supply or enhance recharge. The results were then exported to XLSTAT software2019, and statistical analysis was conducted using the Mann–Kendall (MK) non-parametric trend test on the variables to investigate their potential relationships with groundwater storage. In this study, groundwater storage refers to variations in groundwater storage anomalies, estimated using outputs from the Global Land Data Assimilation System (GLDAS) model. Specifically, these anomalies are derived as the residual component of the terrestrial water budget, after accounting for soil moisture, snow water equivalent, and canopy water storage. The results revealed a strong negative correlation between built-up areas and groundwater storage, with a correlation coefficient of −1.00. Similarly, a notable negative correlation was found between the cropland area and groundwater storage (correlation coefficient: −0.85). Conversely, surface water availability showed a strong positive correlation with groundwater storage, with a correlation coefficient of 0.87, highlighting the direct impact of surface water reduction on groundwater storage. Furthermore, our findings demonstrated a reduction of 168.21 mm (millimeters) in groundwater storage from 2003 to 2022. GLDAS represents storage components, including groundwater storage, in units of water depth (mm) over each grid cell, employing a unit-area, mass balance approach. Although storage is conceptually a volumetric quantity, expressing it as depth allows for spatial comparison and enables conversion to volume by multiplying by the corresponding surface area. Full article

Terrestrial water storage (TWS) is a critical component of the hydrological cycle and plays a key role in regional water resource management. The launch of the Gravity Recovery and Climate Experiment (GRACE) satellite mission in 2002 has provided precise measurements of TWS, enabling systematic investigations into its spatial pattern and driving mechanisms. However, a comprehensive evaluation of the spatial drivers of TWS variations across China is still lacking. In this study, we employed a robust machine learning model to capture the spatial patterns of TWS in China and further applied the Shapley Additive Explanations (SHAP) method to disentangle the individualized effects of hydroclimatic variables. Our findings reveal that precipitation is the dominant driver in northern and southern China, while soil moisture and snow water equivalent are key contributors on the Tibetan Plateau. In northwestern China, air pressure and groundwater runoff are the main influencing factors, whereas temperature shows a pronounced negative effect. Importantly, most variables demonstrate non-monotonic influences: in particular, we found that the importance of precipitation diminishes beyond a certain threshold, and surface pressure shifts sharply toward a negative impact. The explainable machine learning framework demonstrated strong adaptability in identifying complex drivers of TWS, offering a powerful methodological advancement for exploring TWS dynamics and providing valuable insights for water resource management in China. Full article

This study conducts a techno-economic evaluation of an all-electric energy station in China. It assesses the system’s feasibility and sustainability. The all-electric energy station integrates multiple components: chillers, air-source heat pumps, electric boilers, water thermal storage, and gas boilers. These components work together to deliver comprehensive cooling and heating services. The research compares this system with an integrated electricity-gas system. It analyzes performance across three key areas: economic benefits, environmental impact, and energy utilization efficiency. The results show significant advantages for the all-electric energy station. Economic analysis reveals that the net present value (NPV) of the all-electric energy station is positive, the internal rate of return (IRR) is high, and the payback period is significantly shorter compared to traditional systems. Sensitivity analysis highlights that the discount rate and initial investment are the most influential factors affecting NPV, while cooling prices present substantial revenue optimization potential. The all-electric configuration exhibits greater sensitivity to parameter variations, underscoring the importance of strategic risk management. Additionally, the all-electric energy station excels in environmental protection. Carbon emissions are reduced by 11.5% compared to conventional systems. As renewable energy increases in the grid, indirect carbon emissions will decrease further. The all-electric energy station demonstrates strong economic feasibility. It plays a crucial role in achieving carbon neutrality and promoting green energy development. This study provides valuable insights for future regional integrated energy systems. Full article

This paper presents an innovative solution to address agricultural irrigation needs through a hybrid renewable energy system (HRES) that was specifically designed for a farm located in the Skikda region of Algeria. This system is tailored to irrigate 830 fruit trees spread across 3 hectares with a total perimeter of 770 m. The proposed approach integrates two main renewable energy sources (while eliminating the use of traditional batteries for electrical energy storage): solar and wind. Instead, a large water reservoir is employed as an energy storage medium in the form of potential energy. Utilizing gravity, this reservoir directly powers the irrigation system for the fruit trees, thereby reducing the costs and environmental impacts associated with conventional batteries. This innovative design not only enhances sustainability, but also improves the system’s energy efficiency. To ensure precise and customized sizing of the system for the irrigation area, a detailed mathematical modeling of the key system components (solar panels, wind turbines, and reservoir) was conducted. This modeling identifies the critical design variables required to meet technical specifications and irrigation needs. A multi-objective optimization approach was then developed to determine the optimal configuration of the HRES, and this was achieved by considering both technical and economic constraints. The optimization algorithm used was tailored to the formulated problem, ensuring reliable and applicable results. The robustness of the optimization approach was shown by the precise match between energy production (24 kWh at 16,119.40 $) and the minimum demand. This alignment prevents over- or under-designing the system, which increases costs and reduces energy use. The findings highlight the relevance and effectiveness of the proposed methodology, demonstrating its practical utility and significant potential for generalization and adaptation to different agricultural zones with varying conditions. This work paves the way for sustainable and innovative solutions for agricultural irrigation, particularly in remote areas or regions lacking traditional energy infrastructure. Full article

Hyperspectral microscope imaging (HMI) was employed to evaluate the physiochemical properties of and the large intra-variability in individual fruit of ‘Xia Hui 6’ peaches during storage, which gave insights into the heterogeneity of peach fruits at the microscale. The physicochemical characteristics such as firmness (FI), soluble sugar content (SSC), and L* value of peaches showed significant changes, while the microstructure of the tissues broke down. Principal component analysis (PCA) was applied to peach tissues from the sunny side and shady side at different storage stages, which allowed us to clearly visualize the distribution of sugars, water, and pigments at the cellular scale. Single-feature variables were constructed to clarify the correlation between the characteristic bands and physicochemical parameters based on Pearson correlation analysis, with an R² of 0.99 for firmness at 588 nm, 0.98 for titratable acidity (TA) at 432 nm, 0.88 for the L* value at 430 nm and 0.83 for the b* value at 426 nm. This work demonstrated that HMI technology as an accurate and highly effective tool in evaluating the quality of ‘Xia Hui 6’ peaches and targeting, allowing us to visualize the spatial heterogeneity within peach fruit tissues. Full article