Search Results (2,668)

Historically, the electricity sector in Greece was based on local lignite, which provided a stable and affordable base for electricity production. However, current European policy directions, including decarbonization and climate neutrality by 2050, have accelerated the transformation of traditional energy models, resulting in a gradual phasing-out of fossil fuels and an increasing integration of Renewable Energy Sources (RES). In line with EU policy priorities and in light of the new dynamics shaped by the EU Emissions Trading System (EU ETS), lignite gradually became unprofitable for the national economy, leading the Greek government to announce an accelerated lignite phase-out plan. However, the phase-out of domestic lignite, although consistent with climate objectives, rapidly increased the country’s energy dependency on natural gas and its exposure to natural gas price volatility. At the same time, increased investment in solar and wind technologies has reshaped the electricity mix; yet market design, limited system flexibility and inadequate infrastructure and storage capacity have not allowed the full utilization of RES benefits. This structural gap, in turn, raises critical questions about resilience and affordability. The paper provides evidence on these issues and offers a critical evaluation of the decarbonization pathway that has reshaped the country’s energy dependency. Full article

Industrial volatile organic compound (VOC) emissions from large-scale petroleum storage represent a persistent environmental challenge, particularly in agricultural perimeters where atmospheric “breathing” cycles drive localized soil loading. This study investigates the thermodynamic and spatial relationship between gasoline storage emissions and chemical contamination in the Constanta South terminal area using a multi-layered analytical approach. By integrating gas chromatography (GC-MS) headspace analysis with an artificial intelligence (AI) framework utilizing high-order polynomial regression, we quantified the source–path–receptor dynamics across a thermal gradient (12 °C to 70 °C). The results reveal a non-linear surge in VOC emissions at temperatures exceeding 37 °C, characterized by a shift toward medium-weight hydrocarbons (C4–C6) that act as carriers for heavier aromatics. The AI risk model identified a significant spatial gradient, identifying a 500 m “critical zone” where the Hazard Quotient (HQ) is elevated, necessitating technological upgrades like Vapor Recovery Units (VRUs) to mitigate ecological risks. Full article

Urbanization alters the hydrological and structural functioning of tropical urban streams, influencing organic matter transport and retention processes. This study investigated leaf litter retention dynamics in the Bindá Stream in central Amazonia. A six-month leaf release experiment (100 leaves per 12 trial; 1200 leaves total) was conducted alongside hydrological monitoring and floristic surveys of riparian vegetation (adult and regeneration strata). Leaf retention remained consistently low (<33%) across sampling periods. Generalized linear models indicated that flow velocity and discharge were the primary predictors of retention probability, with higher hydrodynamic intensity significantly reducing in-stream storage. Riparian vegetation exhibited moderate structural complexity (Shannon H′ = 1.80; Structural Complexity Index = 3.80), yet limited channel roughness and physical obstructions constrained retention efficiency. Anthropogenic debris locally increased retention, but represents a structurally altered retention mechanism. Hydrodynamic forcing, rather than precipitation totals alone, governed organic matter transport dynamics. Reduced retention capacity suggests limited buffering of downstream material export under high-flow conditions. Although direct water-quality or epidemiological indicators were not measured, findings align with ecohydrological frameworks linking structural simplification and flow flashiness to diminished ecosystem regulation. These results inform riparian restoration and urban stormwater management strategies aimed at enhancing ecosystem regulation and water-quality buffering in tropical cities. Full article

To address voltage over-limit and transformer overload issues in distribution grids caused by large-scale distributed PV integration, this paper proposes a distributed cooperative-based intelligent load optimization technique for distribution grids. First, by analyzing the limitations of traditional centralized control in communication burden, response speed, and fault tolerance, the necessity of distributed cooperative control is demonstrated. Subsequently, leveraging the bidirectional power regulation capability of energy storage systems, a distributed PV-storage system cooperative control model based on a consensus algorithm is constructed. This model comprehensively considers PV output fluctuations, energy storage state of charge, and grid regulation demands. Through multi-node information exchange and iterative updates of consensus variables, the model achieves coordinated power allocation among systems and voltage overlimit mitigation. Simulation results demonstrate that the proposed method effectively smooths PV fluctuations and alleviates local overloads in distribution grids. It simultaneously accommodates capacity differences and operational constraints across energy storage systems, enhancing system response speed and robustness. This provides effective technical support for the safe operation of distribution grids under high penetration of distributed renewable energy. Full article

Seeds of Paeonia lactiflora Pall. ‘Hangshao’ contain over 20% oil, of which more than 90% are unsaturated fatty acids, showing its high potential as an oil crop. Triacylglycerol (TAG) is the main storage form of fatty acids, and diacylglycerol acyltransferase 2 (DGAT2) is a key enzyme in TAG biosynthesis. In this study, the full-length cDNA of PlDGAT2 (326 amino acids) was cloned. Subcellular localization assays further indicated that it localized in the endoplasmic reticulum. Functional verification showed that silencing PlDGAT2 in herbaceous peony decreased the level of total fatty acids, palmitic acid (C16:0, PA) and α-linolenic acid (C18:3, ALA), but increased linoleic acid (C18:2, LA) in leaves. Overexpressing PlDGAT2 in tobacco elevated the content of total fatty acids, PA, and ALA in seeds, while also enlarging the seed sizes, but it reduced the LA content in tobacco seeds. This study suggests that PlDGAT2 contributes to the accumulation of ALA and total fatty acids, offering a potential gene target for improving the oil quality of herbaceous peony seeds. Full article

With the advancement of IoT technology, a vast amount of floating-point time series data has emerged, posing significant challenges for data storage and transmission. To address this issue, the efficient compression of floating-point time series data has become increasingly important. In the field of lossless compression where precision loss is not allowed, compression and decompression are a symmetrical and reversible transformation. The optimization of its encoding and decoding strategies remains the current optimal path for lossless compression. Based on the existing lossless compression algorithms for time series, this paper proposes Rabbit, which is a new floating-point time series data stream lossless compression algorithm. This method can perceive the data characteristics and, by leveraging the temporal locality of the time series, predict the branch distribution of the data stream during compression, thereby dynamically encoding the flag bits. This algorithm designs a TOE encoding method specifically for the significant bits to reduce the number of compressed bits. Compared with traditional floating-point compression schemes, its performance has been significantly improved. Experimental evaluations on 28 datasets show that this algorithm consistently outperforms existing methods with an average improvement of 4.15% over the baseline ACTF algorithm. Notably, on datasets such as server31, server34, and server41, the compression ratio can be reduced by up to 43.04%. Additionally, the compression and decompression time metrics have improved by 4.27% and 3.74%, respectively. Overall, Rabbit offers an effective lossless compression approach for floating-point time-series data, improving the compression ratio without compromising encoding/decoding throughput. Full article

Phase-change materials (PCMs), such as paraffin wax, are widely used in latent heat storage (LHS) because they store substantial thermal energy at nearly constant temperature; however, their low thermal conductivity limits heat transfer and slows melting/solidification. In this work, two flat-plate solar collectors are coupled with a paraffin-based LHS unit for low-temperature solar heating, and the design is optimized by introducing improved fin-geometry combinations on both the heat transfer fluid (HTF) tube and shell side. The M-shaped fins combined with rectangular fins significantly enhanced convective heat transfer by generating localized vortices, while the extended surface area improved conduction within the solid PCM, facilitating efficient heat dissipation and accelerating the phase transition. The LHS unit without fins showed complete melting in 67 min. However, fin introduction remarkably mitigated charging duration to 44 min, 52.3% faster than bare tubes having no fins. The experimental melting process exhibited a 7 min delay by comparing experimental and numerical results, achieving complete melting in 51 and 44 min, respectively. Discharging was completed in 48 min. During PCM charging, sensible heating produces a rapid temperature rise with only a small energy increase, but once the PCM entered into the melting range (320–324 K), the energy changed more steeply. Adding fins boosts stored energy from 2.10 MJ to 3.25 MJ (54.8%) and exergy from 0.15 MJ to 0.27 MJ (80.0%), yet exergy remains far smaller than energy (92.9% lower without fins and 91.7% lower with fins), indicating fins enhance total heat storage more than recoverable work potential. Full article

Aqueous zinc-ion batteries (AZIBs) are promising for large-scale grid storage due to inherent safety, low cost, environmental compatibility, high theoretical capacity (820 mAhg⁻¹), and suitable redox potential (−0.763 V vs. SHE). However, practical deployment is hindered by coupled challenges at the zinc anode–hydrogen evolution, dendrite growth, and corrosion/passivation, which severely limit cycle life and coulombic efficiency. This review systematically summarizes key advances in AZIB research. It first elucidates working principles and four cathode energy storage mechanisms: Zn²⁺ insertion/extraction, H⁺/Zn²⁺ co-insertion, chemical conversion, and dissolution/deposition. Second, it examines four mainstream cathodes (manganese-based, vanadium-based, Prussian blue analogs, and organic compounds), analyzing performance bottlenecks and corresponding optimization via structural modification. Third, it explores functional mechanisms of advanced separators (polymer, inorganic/ceramic composite, MOF-based, and cellulose-based) in regulating uniform Zn²⁺ deposition and suppressing dendrites. Fourth, it summarizes anode optimization strategies: artificial protective layers for interface stabilization, electrolyte additives to modulate Zn²⁺ solvation/deposition, and 3D porous structures to reduce local current density and provide nucleation sites. Finally, key scientific challenges and future directions are discussed—multi-strategy synergy, in situ characterization, practical battery construction, and sustainable technological development, offering theoretical guidance for advancing AZIBs toward large-scale applications. This review aims to provide a comprehensive perspective spanning from materials to systems, and from mechanisms to applications. Its core objective is not merely to list the types of cathode materials, but to establish a logical bridge directly connecting “key challenges” to “optimization strategies,” with a particular emphasis on the issues and solutions related to the cathode side. Full article

Supercapacitors (SCs) are highly attractive energy storage devices, and modern research is focused on using waste materials to reduce environmental impact. This study processed biowaste from local brewery production to produce a highly specific mesoporous activated carbon (AC) for SC electrode scaffolds. Polyaniline (PANI) was synthesized and incorporated into the AC scaffold, thereby enhancing performance. The AC and PANI combination (ACP) achieved a specific capacitance of 173.7 F/g at 1 A/g, with 92% retention after 5000 cycles. Using NdFeB (ACN) particles, the anode showed a specific capacitance of 127 F/g and over 99% retention. An asymmetrical ACN//ACP cell demonstrated promising performance with 70% efficiency. This study highlights the potential of using biowaste for high-performance SC electrodes and the effective synergy between AC and PANI. Full article

Samothrace is a Greek island in the northern Aegean Sea. Though connected to the mainland grid and demonstrating strong wind potential, it is challenged by seasonal shortages in both electricity and potable water. This study assesses a Hybrid Renewable Energy System designed to meet local energy and water demands while maintaining economic viability. The system consists of 10 wind turbines (23.5 MW), a reverse osmosis desalination plant yielding 876,000 m³/year, and four alternative storage configurations: green hydrogen, pumped hydro, lithium-ion batteries, and a combined green hydrogen–pumped hydro option. Using identical climatic and demand data, system performance was simulated for the years 2011–2020. Wind generation reached 113,000 MWh annually, of which 81–84% was exported to the mainland. Potable water demand was met at a rate of 99% in all scenarios, with monthly production ranging from 17,500 m³ in February to almost 50,000 m³ in August, thus requiring 1.80% of wind output. Investment costs ranged from 34.4 M € to 39.8 M €; net present values remained around 75 M € for all scenarios. Results demonstrate that complete autonomy can be achieved; however, economic sustainability is maximized by leveraging the interconnection and sizing storage below full-autonomy levels. Full article

Climate change is increasingly affecting groundwater resources in the Carpathian Basin, while rising temperatures are likely to increase irrigation demand and pressure on aquifers. We assessed climate- and pumping-driven impacts on the Nyírség recharge–discharge system (north-eastern Hungary) by combining shallow groundwater monitoring (1970–2022) with hydroclimate indicators from CHIRPS precipitation and ERA5-Land air temperature and snow depth (1981–2024). Using these datasets, we developed and calibrated a MODFLOW groundwater-flow model for representative wet (2010) and dry (2022) conditions, incorporating permitted abstraction and scenario-based estimates of unregistered pumping. We then ran scenario simulations to evaluate mid-century (2050) conditions and managed aquifer recharge (MAR) options. Precipitation exhibits strong interannual variability, but the region shows marked warming and a pronounced decline in snow storage, implying reduced cold-season buffering and higher evaporative demand. Simulations reproduce the observed post-2010 decline in shallow groundwater, with the largest decreases in higher-elevation recharge areas, whereas increased pumping mainly intensifies localized drawdown near major well fields. Scenario results indicate that climate-driven reductions in recharge dominate basin-scale declines by 2050, while MAR provides primarily local benefits; direct subsurface injection performs best among the tested options. These findings support practical groundwater management by prioritizing measurable and enforceable abstraction (including unregistered withdrawals), demand-side irrigation efficiency and adaptive caps in recharge areas, and targeted subsurface MAR where source water and infrastructure are available. Full article

Photovoltaic (PV) self-consumption systems are increasingly adopted as part of the energy transition, yet residential users often lack the technical background needed to compare alternatives, particularly when storage (ST) is included. To support informed, technically consistent, and sustainable decision-making, this work presents a techno-economic tool for assessing and sizing PV self-consumption systems through hourly energy-balance simulation. Using real consumption, meteorological data, and electricity tariffs, the tool evaluates technical and economic performance and introduces the Mismatch Index (MI) to quantify the temporal alignment between PV production and demand. Combined with self-consumption (SC) and self-sufficiency (SS) metrics, MI supports consistent comparison of PV–ST configurations under real operating conditions and helps identify solutions that improve local energy use without unnecessary oversizing. The approach is applied to a residential consumer and to an energy community, comparing individual and centralized solutions. In the residential case, the selected configuration reached a SC of 87%, SS of 66%, and an IRR of 4.92%. For the energy community, the centralized solution increased the 20-year NPV from €1370 for individual systems to €20,060. Analysis of two years of hourly consumption data from 118 households indicated an uncertainty of 10–15% in average hourly consumption when one-year data is used. Full article

The effective cleaning of corn prior to storage is crucial for ensuring grain quality and safety. Traditional Convolutional Neural Network (CNN)-based detection methods often struggle to maintain accuracy in scenarios with dense occlusions. Furthermore, limitations in image quality and feature representation hinder their generalization to diverse impurity types. To address these challenges, this paper proposes an enhanced real-time detector transformer model named RT-DETR-CD (Real-Time Detector Transformer with Convolution and Dynamic Upsampling) for corn impurity detection based on industrial vision. This approach integrates Receptive Field Attention Convolutions (RFAConv) to enhance sensitivity to local texture details and employs the dynamic upsampling operator DySample to restore high-frequency edge information. Additionally, a novel Inner-Shape-IoU loss function is introduced to accelerate bounding box regression for objects with varying aspect ratios. Images were captured using FLIR industrial cameras under controllable annular LED illumination. Experiments on a self-built dataset demonstrate that the proposed model achieves a 4.7% improvement in mean average precision (mAP) and operates at 68 frames per second (FPS), outperforming the original RT-DETR model in both accuracy and speed. This work provides a practical solution for real-time, high-precision impurity detection on grain processing lines. Full article

Energy thriftiness and metabolic adaptations have had a crucial role in the emergence and spreading of the Homo lineage in the world. A higher-energy demand was required not only for the growing body mass, encephalization and human proliferation, but also for the survival adaptations to the environmental stresses. Because lean body mass lacks the energy-storage capacity required to supply the body’s demands, dedicated fat-storing cells originated. To feed such fat stores, the hominid evolution developed “meat-adaptive” genes to detect, digest and metabolize higher fat diets, and body-fat stores can be affected by lifestyle through hormonal-controlled daily energy balance. In energy surplus conditions, hypertrophy and hyperplasia of adipocytes can occur, with hypertrophic adipocyte signaling both a neo-adipocyte differentiation (leading to hyperplasia) and a local macrophage density (resident + infiltrated macrophages) for fat surplus scavenging. Adiposity-induced inflammation is caused by fat-overstored (hypertrophied) adipocytes that may operate as an overactive endocrine organ secreting an array of pro-inflammatory adipokines that, in combination with resident-macrophage activity and infiltrated blood-recruited, monocyte-derived macrophages, amplify the inflammatory process by spurting pro-inflammatory cytokines into the bloodstream. From an evolutionary perspective, obese humans represent a natural selection overexpressing the “thrifty” genes evolved for efficient food collection and fat deposition intended to help in survival in prolonged periods of famine. However, genetically speaking, obesity is a polygenic multifactorial disorder. Considering the rapidity of obesity-epidemic growth worldwide, epigenetic sets forth the key assumption of the mismatch between our human genome molded over thousands of generations, coping with the unprecedented dietary and physical conditions. Consequently, obesity would be due to our evolutionary-adapted polygenic-charge expressed by a deteriorated lifestyle characterized by high energy-dense food intake coupled with a reduction in caloric expenditure stemming from new mobility-reducing technologies. As a model of lifestyle change (LiSM), our 28-year on-going longitudinal study (“Moving for Health”) has shown effectiveness in the reduction not only of obesity but especially of its comorbidities, in a (10 week to 3 year) length-dependent LiSM. However, a disappointing progressive decrease in compliance with the study has been observed and attributed to the resistance of people to change their actual “obesogenic” lifestyle, basically represented by the individuals’ demand for labor-saving technologies and convenient, affordable, palatable foods. Full article

Underground gas storage (UGS) in salt caverns is increasingly important for a flexible and secure energy supply and for stabilizing the gas market. However, cavern operations can induce surface ground movements that must be monitored to safeguard infrastructure integrity and environmental compatibility. This research analyzes horizontal (W–E) and vertical ground movements above the cavern field Gronau-Epe in northwestern Germany, using radar interferometry (InSAR), specifically the SBAS (Small Baseline Subset) approach, combined with clustering and multi-criteria analysis. The study was conducted in cooperation between Uniper Energy Storage GmbH, the Research Center for Post Mining at THGA Bochum, and the company EFTAS. Freely available Copernicus Sentinel 1 data were integrated with public soil maps and operational storage information. A multistage workflow quantified deformation patterns, classified coherent deformation zones via clustering, and evaluated geological and technical drivers using multi-criteria analysis to better distinguish operational (primary) from overburden (secondary) influences. Results reveal long term deformation trends closely linked in time and space to injection/withdrawal cycles. Locally confined vertical and horizontal movements near caverns are attributed to salt convergence triggered by cyclic pressure changes, but they are linked to (hydro)geological and pedological factors. The developed approach shows strong monitoring potential in addition to classic mine surveying. Full article