Search Results (378)

The Parnassos-Ghiona region constitutes the most significant bauxite-bearing province in Greece, with a well-documented history of research highlighting its geotectonic complexity and its importance for bauxite exploitation. Among the three principal bauxite horizons, the lower stratum (b1) remains the least thoroughly investigated, in contrast to the upper (b3) and intermediate (b2) strata. This disparity is primarily attributed to the limited surface exposure of the b1 horizon within the broader Parnassos-Ghiona Unit. The present study examines the characteristics of the b1 strata through an integrated mineralogical and geochemical approach. For the first time, the confirmed presence of rare earth element (REE) minerals within the b1 horizon is documented. Geochemical proxies, including REE distribution patterns and elemental ratios, indicate a genetic relationship with igneous parent rocks of intermediate to basic affinity. Full article

The exponential increase in electronic waste (e-waste) from end-of-life electrical and electronic equipment presents a growing environmental challenge. E-waste contains high concentrations of rare earth elements (REEs), which are classified as critical raw materials (CRMs). Their removal and recovery from contaminated systems not only mitigate pollution but also support resource sustainability within a circular economy framework. The present study proposed the use of hazelnut shells as a biosorbent to reduce water contamination and recover REEs. The sorption capabilities of this lignocellulosic material were assessed and optimized using the response surface methodology (RSM) combined with a Box–Behnken Design (three factors, three levels). Factors such as pH (4 to 8), salinity (0 to 30), and biosorbent dose (0.25 to 0.75 g/L) were evaluated in a complex mixture containing 9 REEs (Y, La, Ce, Pr, Nd, Eu, Gd, Tb and Dy; equimolar concentration of 1 µmol/L). Salinity was found to be the factor with greater significance for REEs sorption efficiency, followed by water pH and biosorbent dose. At a pH of 7, salinity of 0, biosorbent dose of 0.75 g/L, and a contact time of 48 h, optimal conditions were observed, achieving removals of 100% for Gd and Eu and between 81 and 99% for other REEs. Optimized conditions were also predicted to maximize the REEs concentration in the biosorbent, which allowed us to obtain values (total REEs content of 2.69 mg/g) higher than those in some ores. These results underscore the high potential of this agricultural waste with no relevant commercial value to improve water quality while providing an alternative source of elements of interest for reuse (circular economy). Full article

Unbalanced accelerations occurring during tram travel have a significant impact on passenger comfort and safety, as well as on the rate of wear and tear on infrastructure and rolling stock. Ideally, these dynamic forces should be monitored continuously in real-time; however, traditional systems require high-precision accelerometers and proprietary software—investments often beyond the reach of municipally funded tram operators. To this end, as part of the research project “Accelerometer Measurements in Rail Passenger Transport Vehicles”, pilot measurement campaigns were conducted in Poland on tram lines in Gdańsk, Toruń, Bydgoszcz, and Olsztyn. Off-the-shelf smartphones equipped with MEMS accelerometers and GPS modules, running the Physics Toolbox Sensor Suite Pro app, were used. Although the research employs widely known methods, this paper addresses part of the gap in affordable real-time monitoring by demonstrating that, in the future, equipment equipped solely with consumer-grade MEMS accelerometers can deliver sufficiently accurate data in applications where high precision is not critical. This paper presents an analysis of a subset of results from the Gdańsk tram network. Lateral (x) and vertical (z) accelerations were recorded at three fixed points inside two tram models (Pesa 128NG Jazz Duo and Düwag N8C), while longitudinal accelerations were deliberately omitted at this stage due to their strong dependence on driver behavior. Raw data were exported as CSV files, processed and analyzed in R version 4.2.2, and then mapped spatially using ArcGIS cartograms. Vehicle speed was calculated both via the haversine formula—accounting for Earth’s curvature—and via a Cartesian approximation. Over the ~7 km route, both methods yielded virtually identical results, validating the simpler approach for short distances. Acceleration histograms approximated Gaussian distributions, with most values between 0.05 and 0.15 m/s², and extreme values approaching 1 m/s². The results demonstrate that low-cost mobile devices, after future calibration against certified accelerometers, can provide sufficiently rich data for ride-comfort assessment and show promise for cost-effective condition monitoring of both track and rolling stock. Future work will focus on optimizing the app’s data collection pipeline, refining standard-based analysis algorithms, and validating smartphone measurements against benchmark sensors. Full article

Residential and agricultural buildings must prioritize environmental sustainability, employing locally sourced, bio/geologically sustainable materials, and reversible construction methods. Hence, adobe construction and earth-based building methods are experiencing a comeback. This article describes the hygrothermal performances of a real scale agricultural building prototype, in real field conditions, built and designed to be energy-efficient, environmentally friendly, and well-suited for the hot, dry climates typical of the Mediterranean region during summer. The building prototype is a small modular two room construction, one room based on wood (for control purpose) and the other one on raw earth. The experimental set up highlights the passive cooling and humidity regulation potential provided by raw earth and adobe brick technology in agricultural buildings used for fruit and vegetable storage. Such passive cooling alternatives in the Mediterranean climate could reduce the need for energy-intensive and environmentally impactful cold storage rooms. Full article

The Tuztaşı low-sulfidation epithermal Au–Ag deposit (Biga Peninsula, Türkiye) records a multi-stage hydrothermal history that can be interpreted through the trace and rare-earth-element (REE) chemistry of quartz. High-precision LA-ICP-MS analyses of five representative quartz samples (23 ablation spots; 10 analytically robust) reveal two fluid stages. Early fluids were cold, dilute meteoric waters (δ¹⁸O₍H₂O₎ ≈ −6.8 to +0.7‰), whereas later fluids circulated deeper, interacted with felsic basement rocks, and evolved in composition. Mineralized quartz displays marked enrichment in As (raw mean = 2854 ± 6821 ppm; filtered mean = 70 ± 93 ppm; one spot 16,775 ppm), K (498 ± 179 ppm), and Sb (57.8 ± 113 ppm), coupled with low Ti/Al (<0.005) and elevated Ge/Si (0.14–0.65 µmol mol⁻¹). Chondrite-normalized REE patterns show pronounced but variable LREE enrichment ((La/Yb)_n ≤ 45.3; ΣLREE/ΣHREE up to 10.8) and strongly positive Eu anomalies (δEu ≤ 9.3) with slightly negative Ce anomalies (δCe ≈ 0.29); negligible Ce–Eu covariance (r² ≈ 0.05) indicates discrete redox pulses. These signatures indicate chemically evolved, reducing fluids conducive to Au–Ag deposition. By contrast, barren quartz is characterized by lower pathfinder-element contents, less fractionated REE profiles, higher Ti/Al, and weaker Eu anomalies. A composite exploration toolkit emerges: As > 700 ppm, As/Sb > 25, Ti/Al < 0.005, Ge/Si > 0.15 µmol mol⁻¹, and δEu ≫ 1 reliably identify ore-bearing zones when integrated with δ¹⁸O data and fluid-inclusion microthermometry from earlier studies on the same vein system. This study provides one of the first systematic applications of integrated trace-element and REE analysis of quartz to a Turkish low-sulfidation epithermal system, offering an applicable model for vectoring mineralization in analogous settings worldwide. Full article

Lignin, the most abundant renewable aromatic biopolymer on Earth, is rapidly emerging as a powerful enabler of next-generation sustainable technologies. This review shifts the focus to the latest industrial breakthroughs that exploit lignin’s multifunctional properties across energy, agriculture, healthcare, and environmental sectors. Lignin-derived carbon materials are offering scalable, low-cost alternatives to critical raw materials in batteries and supercapacitors. In agriculture, lignin-based biostimulants and controlled-release fertilizers support resilient, low-impact food systems. Cosmetic and pharmaceutical industries are leveraging lignin’s antioxidant, UV-protective, and antimicrobial properties to create bio-based, clean-label products. In water purification, lignin-based adsorbents are enabling efficient and biodegradable solutions for persistent pollutants. These technological leaps are not merely incremental, they represent a paradigm shift toward a materials economy powered by renewable carbon. Backed by global sustainability roadmaps like the European Green Deal and China’s 14th Five-Year Plan, lignin is moving from industrial residue to strategic asset, driven by unprecedented investment and cross-sector collaboration. Breakthroughs in lignin upgrading, smart formulation, and application-driven design are dismantling long-standing barriers to scale, performance, and standardization. As showcased in this review, lignin is no longer just a promising biopolymer, it is a catalytic force accelerating the global transition toward circularity, climate resilience, and green industrial transformation. The future of sustainable innovation is lignin-enabled. Full article

White-light-emitting diodes (wLEDs) are central to next-generation lighting technologies, yet their reliance on critical raw materials (CRMs), such as rare-earth elements, raises concerns regarding sustainability and supply security. In this work, we present a simple, low-cost method to produce photoluminescent carbon-based nanostructures—known as oxidative debris (OD)—via alkaline treatment of graphene oxide (GO) using KOH solutions ranging from 0.04 M to 1.78 M. The resulting OD, isolated from the supernatant after acid precipitation, exhibits strong and tunable photoluminescence (PL) across the visible spectrum. Emission peaks shift from blue (~440 nm) to green (~500 nm) and yellow (~565 nm) as a function of treatment conditions, with excitation wavelengths between 300 and 390 nm. Optical, morphological. and compositional analyses were performed using UV-Vis, AFM, FTIR, and Raman spectroscopy, confirming the presence of highly oxidized aromatic domains. The blue-emitting (S2) and green/yellow-emitting (R2) fractions were successfully separated and characterized, demonstrating potential color tuning by adjusting KOH concentration and treatment time. This study highlights the feasibility of reusing GO-derived byproducts as sustainable phosphor alternatives in wLEDs, reducing reliance on CRMs and aligning with green chemistry principles. Full article

Large turbine generators rely on shaft earthing brushes to safely divert harmful shaft currents to ground, protecting bearings from electrical damage. This paper presents a novel deep learning-based diagnostic framework to detect and classify faults in shaft earthing brushes of large turbine generators. A key innovation lies in the use of FFT-derived spectrograms from both voltage and current waveforms as dual-channel inputs to the CNN, enabling automatic feature extraction of time–frequency patterns associated with different SEB fault types. The proposed framework combines advanced signal processing and convolutional neural networks (CNNs) to automatically recognize fault-related patterns in shaft grounding current and voltage signals. In the approach, raw time-domain signals are converted into informative time–frequency representations, which serve as input to a CNN model trained to distinguish normal and faulty conditions. The framework was evaluated using data from a fleet of large-scale generators under various brush fault scenarios (e.g., increased brush contact resistance, loss of brush contact, worn out brushes, and brush contamination). Experimental results demonstrate high fault detection accuracy (exceeding 98%) and the reliable identification of different fault types, outperforming conventional threshold-based monitoring techniques. The proposed deep learning framework offers a novel intelligent monitoring solution for predictive maintenance of turbine generators. The contributions include the following: (1) the development of a specialized deep learning model for shaft earthing brush fault diagnosis, (2) a systematic methodology for feature extraction from shaft current signals, and (3) the validation of the framework on real-world fault data. This work enables the early detection of brush degradation, thereby reducing unplanned downtime and maintenance costs in power generation facilities. Full article

Microstructural, mechanical and qualitative phase identification of durable mullite-based ceramics obtained by utilization of waste clay–diatomite has been studied. Mullite-based ceramics were fabricated using waste clay–diatomite from the Baroševac open-cast coal mine, Kolubara (Serbia). The raw material consists mainly of SiO₂ (70.5 wt%) and a moderately high content of Al₂O₃ (13.8 wt%). In order to achieve the stoichiometric mullite composition (3Al₂O₃-2SiO₂), the raw material was mixed with an appropriate amount of Al(NO₃)₃·9H₂O. After preparing the precursor powder, the green compacts were sintered at 1300, 1400 and 1500 °C for 2 h. During the process, rod-shaped mullite grains were formed, measuring approximately 5 µm in length and a diameter of 500 nm (aspect ratio 10:1). The microstructure of the sample sintered at 1500 °C resulted in a well-developed, porous, nest-like morphology. According to the X-ray diffraction analysis, the sample at 1400 °C consisted of mullite, cristobalite and corundum phases, while the sample sintered at 1500 °C contained mullite (63.24 wt%) and an amorphous phase that reached 36.7 wt%. Both samples exhibited exceptional compressive strength—up to 188 MPa at 1400 °C. However, the decrease in compressive strength to 136 MPa at 1500 °C is attributed to changes in the phase composition, the disappearance of the corundum phase and alterations in the microstructure. This occurred despite an increase in bulk density to 2.36 g/cm³ (approximately 82% of theoretical density) and a complete reduction in open porosity. The residual glassy phase (36.7 wt% at 1500 °C) is probably the key factor influencing the mechanical properties at room temperature in these ceramics produced from waste clay–diatomite. However, the excellent mechanical stability of the samples sintered at 1400 and 1500 °C, achieved without binders or additives and using mined diatomaceous earth, supports further research into mullite-based insulating materials. Mullite-based materials obtained from mining waste might be successfully used in the field of energy-efficient refractory materials and thermal insulators. for high-temperature applications Full article

The global shift to low-carbon energy systems has significantly increased demand for critical raw materials like lithium, cobalt, nickel, rare earth elements, and copper. These materials are essential for renewable technologies and energy storage. However, their extraction and processing produce significant carbon emissions and face challenges from supply chain vulnerabilities and price volatility. This review examines the complex relationship between carbon pricing mechanisms—such as carbon markets and taxes—and raw material markets. It explores the strategic importance of these materials, recent policy developments, and the transmission of carbon pricing impacts through supply chains. The review also analyzes the systemic risks created by carbon pricing, including regulatory uncertainty, market volatility, and geopolitical tensions. We then discuss financial tools and corporate strategies for managing these risks, such as carbon-linked derivatives and supply chain diversification. Finally, this review identifies key challenges and suggests future research to improve the resilience and sustainability of raw material supply chains. Here, resilience is defined as the capacity to adapt to carbon pricing volatility, geopolitical disruptions, and regulatory shocks, while maintaining operations. The paper concludes that coordinated policies and flexible risk management are urgently needed to support a reliable and sustainable energy transition. Full article

Cellulosic raw materials are the most common source of carbon on Earth and are in great demand for the production of high-value-added products. Cellulosic feedstocks represent a strong matrix consisting of cellulose, lignin, and hemicelluloses. The efficient transformation of cellulosic raw materials into fermentable sugars requires the use of effective pretreatment strategies. The methods employed for pretreatment should be efficient, have low operating costs, and exhibit lower environmental impact. The present review describes pretreatment methods like liquid hot water (LHW) and steam explosion (SE) and highlights peculiar features, benefits and disadvantages of these processes. The effectiveness of these pretreatment methods and their effect on cellulosic raw materials strongly depends on the type of feedstock (component composition), pretreatment method, and pretreatment conditions (pressure, temperature, time, etc.). The LHW pretreatment requires neither addition of chemicals and catalysts nor grinding stage, but requires high energy inputs. The SE pretreatment is regarded as environmentally friendly and requires lower energy inputs, but contributes to the formation of toxic compounds. The life cycle assessment approach demonstrated that the SE pretreatment outperforms dilute acid pretreatment methods and allows the reduction of energy inputs, thereby improving the environmental performance of the process, while the LHW method improves long-term energy security and creates a greener future. Full article

Rapid and efficient evaluation of cultivated land quality in black soil regions at the farm scale using remote sensing techniques is crucial for resource protection. However, current studies face challenges in developing convenient and reliable models that directly leverage raw spectral reflectance. Therefore, this study develops and validates a deep learning framework specifically for this task. The framework first selects remote sensing images from typical periods using a Random Forest model in Google Earth Engine (GEE). Subsequently, the raw spectral reflectance data from these images, without any transformation into vegetation indices, are directly input into an optimized BO-Stacking-TabNet model. This model is enhanced through a two-step Stacking ensemble process and a Bayesian optimization algorithm. A case study at Shuanghe Farm in Northeast China shows that (1) compared to the BO-Stacking-TabNet model using vegetation indices as input, the BO-Stacking-TabNet model based on spectral reflectance as the input indicator achieved an improvement of 10.62% in Accuracy, 1.55% in Precision, 11.05% in Recall, and 10.18% in F1-score. (2) Compared to the original TabNet model, the BO-Stacking-TabNet model optimized by the two-step Stacking process and Bayesian optimization algorithm improved Accuracy by 2.13%, Precision by 12.59%, Recall by 1.83%, and F1-score by 2.19%. These results demonstrate the reliability of the new farm-scale black soil region cultivated land evaluation method we proposed. The method provides significant references for future research on cultivated land quality assessment at the farm scale in terms of remote sensing image data processing and model construction. Full article

In recent years, spaceborne Global Navigation Satellite System reflectometry (GNSS-R) technology has made significant progress in the fields of Earth observation and remote sensing, with a wide range of applications, important research value, and broad development prospects. However, despite existing research focusing on the application of spaceborne GNSS-R L1-level data, the potential value of raw intermediate-frequency (IF) signals has not been fully explored for special applications that require a high accuracy and spatiotemporal resolution. This article provides a comprehensive overview of the current status of the measurement of raw IF signals from spaceborne GNSS-R in multiple application fields. Firstly, the development of spaceborne GNSS-R microsatellites launch technology is introduced, including the ability of microsatellites to receive GNSS signals and receiver technique, as well as related frequency bands and technological advancements. Secondly, the key role of coherence detection in spaceborne GNSS-R is discussed. By analyzing the phase and amplitude information of the reflected signals, parameters such as scattering characteristics, roughness, and the shape of surface features are extracted. Then, the application of spaceborne GNSS-R in inland water monitoring is explored, including inland water detection and the measurement of the surface height of inland (or lake) water bodies. In addition, the widespread application of group delay sea surface height measurement and carrier-phase sea surface height measurement technology in the marine field are also discussed. Further research is conducted on the progress of spaceborne GNSS-R in the retrieval of ice height or ice sheet height, as well as tropospheric parameter monitoring and the study of atmospheric parameters. Finally, the existing research results are summarized, and suggestions for future prospects are put forward, including improving the accuracy of signal processing and reflection signal analysis, developing more advanced algorithms and technologies, and so on, to achieve more accurate and reliable Earth observation and remote sensing applications. These research results have important application potential in fields such as environmental monitoring, climate change research, and weather prediction, and are expected to provide new technological means for global geophysical parameter retrieval. Full article

Earth materials in construction demonstrate significant potential attributed to their accessibility, recyclability, and low energy demands for processing. Modern techniques have enhanced their mechanical strength and durability, enabling their application in load-bearing and infill walls while preserving ecological benefits. However, existing studies on indoor heat–humidity regulation primarily emphasize material parameters and macro-level performance. Moreover, the dynamic interactions between the unique thermal storage–release mechanisms and indoor environments have not been systematically analyzed. With the Kelvin equation, capillary mechanics, adsorption theories, and microstructural analysis were integrated in this study to quantify cyclic capillary condensation and evaporation in microvoids. The results reveal that earth materials contain abundant medium-sized pores (19.85–53.83 nm) sustaining vapor exchange with their surroundings. Capillary condensation occurs 0.86–0.96 times the planar surface vapor pressure, influenced by pore size (negatively correlated) and temperature (negatively correlated). During the daytime, capillary evaporation occurs in the nanopores of the raw earth wall under the influence of the outdoor environment’s cyclical temperature and humidity. This process absorbs heat from the indoor environment and raises the ambient humidity. During the nighttime, capillary condensation occurs in the pores, releasing heat to the indoor area and absorbing moisture from the environment, contributing to the balance of the indoor thermal environment of the earth buildings. The findings lay a scientific foundation for quantitatively evaluating earth buildings’ indoor climate control performance, supporting their integration into green building systems. This research bridges knowledge gaps in micro-to-macro thermal dynamics while advancing the ecological optimization of materials for sustainable architecture. Full article

Volatile fatty acids (VFA) are valuable intermediates with growing demand in chemical, pharmaceutical, and environmental applications. Their sustainable production from organic waste is increasingly explored in the context of circular economy and biorefinery models. This study investigates the co-fermentation of waste-activated sludge (WAS) and the organic fraction of municipal solid waste (OFMSW) as a strategy for integrated VFA and biogas production. Semi-continuous experiments were carried out to assess the effect of the substrates ratio (WAS:OFMSW = 90:10 and 30:70), hydraulic retention time (HRT), and pH control (5, 9, no control) on VFA yield and composition. Results showed that higher OFMSW content and alkaline conditions favoured VFA production, with a maximum yield of 144.9 mgHAc·gVS⁻¹ at pH 9 and 70:30 ratio. Acetate dominated, while butyrate production peaked at 114.1 mgHBu·gVS⁻¹ under high sludge conditions. However, the addition of alkali required for pH control may lead to excessive accumulation of alkaline-earth metal ions, which can disrupt biological processes due to their potential toxicity. Anaerobic digestion of fermentation residues enhanced biomethane yields significantly (0.27 NL·gVS⁻¹ vs. 0.05 NL·gVS⁻¹ from raw sludge). The proposed process demonstrates potential for converting wastewater treatment plants into biorefineries, maximising resource recovery while reducing environmental impact. Full article