Search Results (7,347)

This review provides an overview of magnesium-rich compounds and Long-Period Stacking Ordered (LPSO) phases for their hydrogen storage properties. Thanks to their high volumetric density, safety, and exceptional purity, metal hydrides are promising for hydrogen storage. Magnesium is a great candidate as it can form MgH₂, which has a weight capacity of 7.6 wt.%. However, due to its high stability (at 283 °C, equilibrium pressure is 1 bar (i.e., atmospheric pressure)) and slow hydrogen sorption kinetics, Mg is alloyed with TMs (transition metals) and/or REs (rare earths) to overcome these problems. Some alloys that are synthesized with both TMs and REs (ternary system) form LPSO phases, which irreversibly decompose under hydrogenation. The LPSO phases discussed in this review are mostly the 14H- and 18R-type phases, although, rarely, other types of LPSO phases can still be observed as well. These discussed phases may lead to good hydrogen sorption properties depending on the REs and TMs used. This review focuses on the recent literature addressing Mg-rich binary Mg-TM and Mg-RE alloys and ternary (TM_x-RE_y-Mg_z) systems and their hydrogen storage properties with an emphasis on LPSO phases. Full article

Terrestrial ecosystems play a critical role in regulating atmospheric CO₂ through land–atmosphere carbon exchange. While Net Ecosystem Exchange (NEE) serves as a key integrative metric for carbon dynamics, its robust global estimation remains challenging due to profound environmental heterogeneity and nonlinear ecosystem responses. In this study, we propose a dual-track experimental framework to invert annual global terrestrial NEE at a 0.1° spatial resolution for 2000–2024. Initially, a long-term historical baseline inversion (2000–2024) was developed using explicit multi-source environmental predictors. Subsequently, to overcome the representational limitations of conventional spectral indices over complex terrains, we integrated high-dimensional remote-sensing embeddings from the AlphaEarth framework for the 2017–2024 overlapping period. This approach was designed to explicitly quantify the added value of these advanced features. Our results demonstrate that embedding features substantially enhance inversion performance, reducing prediction errors and improving spatial coherence. Adopting the standard meteorological sign convention, global terrestrial NEE remained consistently negative. Based on the 2000–2024 baseline inversion, our predicted global NEE fluctuated between −3.50 and −4.38 Pg C yr⁻¹. To validate these long-term estimates, we systematically cross-validated our results against an independent, recently published multi-network fusion dataset, which reported a comparable range of −3.11 to −3.75 Pg C yr⁻¹. This comparison demonstrates consistent interannual dynamics and corroborates the magnitude of the global terrestrial carbon sink. Spatial patterns exhibit a stable latitudinal structure, with stronger net carbon uptake in low latitudes. Interannual variability is expressed mainly as magnitude fluctuations rather than systematic spatial reorganization. Overall, this study highlights that high-dimensional Earth observation embeddings provide significant, measurable information gains for global NEE inversion without introducing new process-based assumptions, thereby offering a robust and internally consistent basis for evaluating long-term carbon dynamics. Full article

Rice plant height is a key indicator of crop growth and phenology, yet continuous daily estimation remains challenging under limited field observations. This study proposes an interpretable Bayesian LUT-based framework to estimate rice plant height from time-series, satellite-derived GCVI, and sparse in situ measurements. Daily plant height was estimated as a posterior-weighted ensemble of multiple LUT-derived heights, together with uncertainty reflecting ambiguity among plausible growth trajectories. Applied to rice paddies in Ryugasaki City, Japan, using Harmonized Landsat–Sentinel-2 data from the 2025 growing season, the method achieved and RMSE = 7.08 cm on the validation dataset, outperforming simple baseline approaches. The estimated daily height time series also enabled evaluation of the timing at which plant height reached 70 cm, revealing clear spatial variability among fields and an associated uncertainty of approximately 10 days. Although this threshold was discussed with reference to previous studies on L-band SAR sensitivity, the present study relied solely on optical observations. Overall, the proposed framework provides a data-efficient and explainable approach for daily, spatially explicit rice growth monitoring, while current limitations include the single-region, single-year LUT construction and the simplified statistical assumptions used in the Bayesian weighting framework. Full article

The optical high spatial resolution component of the ESA Copernicus Earth Observation program is relying on the Sentinel-2 satellites. To secure the mission continuity, the Sentinel-2C unit was launched and has recently joined the Sentinel-2A and Sentinel-2B operational plan. The objective of the paper is to provide a status and a quantified assessment of the radiometric inter-operability of the latest unit with the constellation. The analyses reported here were performed using different vicarious methods during the commissioning phase of Sentinel-2C. Two of the methods were used for the first time with a Sentinel-2 satellite: lunar calibration and tandem inter-comparisons on selected surfaces. The results of the different methods are compared and the vicarious radiometric adjustment strategy is described. Finally, we discuss the impact of the different sources of uncertainty impacting the radiometric assessment. Full article

The preparation for next-generation Earth Observation missions, such as the European Space Agency’s (ESA) Copernicus Hyperspectral Imaging Mission for the Environment (CHIME) and Land Surface Temperature Monitoring (LSTM), requires robust pre-launch proxy datasets. Because current simulation methodologies frequently rely on isolated, platform-specific approaches, this study proposes a comprehensive, unified multisensor framework capable of dynamically generating operationally realistic CHIME and LSTM datasets from diverse airborne and satellite sources. Three distinct processing pipelines were established. For hyperspectral data simulation, precursor satellite imagery (PRISMA and EnMAP) and high-resolution airborne measurements (HySpex) were harmonized to CHIME’s 30 m specifications utilizing Spectral Response Function (SRF) adjustments, Point Spread Function (PSF) spatial resampling, and 6S atmospheric radiative transfer modeling. For thermal data simulation, archive Landsat 8/9 and ASTER imagery were transformed into LSTM’s target 50 m, 5-band configuration using a synergistic two-step approach: a physics-based Spectral Super-Resolution (SSR) module followed by an AI-driven Spatial Super-Resolution (SpSR) transformer network. Evaluated across highly diverse inland, coastal, and riverine testbeds in Italy, the simulated products demonstrated high spectral, spatial, and radiometric fidelity. While inherently constrained by the native spectral ranges of the input sensors and by the current lack of absolute on-orbit mission data for validation, the downscaled images closely reproduced complex thermal patterns and water-quality gradients. Ultimately, this scalable framework provides the remote sensing community with early access to representative datasets and mission performance assessments, while accelerating pre-launch algorithm development and testing for environmental monitoring applications—particularly those focused on water discharges. Full article

This study investigates the spatial distribution of ambient dose equivalent rates (ADER) on Avala and Kosmaj mountains, two protected landscapes located within the territory of the City of Belgrade, Serbia. Both sites, characterized by rich biodiversity and cultural heritage, were analyzed to assess their radiological safety and suitability for outdoor recreation. In mid-October 2025, in situ measurements were conducted at 42 sampling points using the Radex RD1503+ GM counter. The recorded values ranged from 0.085 to 0.2 µSv/h, remaining below the recommended safety threshold of 0.2 µSv/h. To visualize the gamma dose spatial variability, all field data were georeferenced and processed in QGIS 3.28.10 using the Inverse Distance Weighting (IDW) interpolation method. Integration of GIS and Remote Sensing techniques enabled the correlation between gamma radiation patterns, land cover, and elevation gradients derived from digital elevation models (DEMs). The comprehensive GIS-based approach confirms that Avala and Kosmaj maintain low natural background radiation levels comparable to global averages for similar geomorphological settings, and therefore are safe and suitable for sports, tourism and recreation. The applied combination of field dosimetry, Remote Sensing, and geostatistical modeling provides a valuable framework for continuous environmental monitoring and sustainable landscape management in protected mountainous landscapes in Central Serbia. Full article

Mining wastewater contains complex mixtures of regulated and emerging contaminants that challenge treatment technologies. This study evaluates the bioremediation potential of 10 phytoplankton species, including Chlorella vulgaris, and the aquatic fern Salvinia natans for removing contaminants from synthetic and mine outflow water. Batch screening experiments were conducted using synthetic wastewater containing regulated elements, rare earth elements (REEs), or selected organic flotation reagents, followed by validation using acidic mine outflow water from a decommissioned mine (Romania). All tested phytoplankton species and Salvinia natans showed high removal efficiencies for several priority elements, including Pb, Ag, Cr, Th, U, and multiple REEs. Organic flotation reagents were efficiently removed by all phytoplankton species. Chlorella vulgaris and Salvinia natans emerged as high-performing species and were further evaluated in mine outflow, where species-specific and matrix-dependent removal behavior was observed. Here, Chlorella vulgaris showed a higher average removal. Time-resolved analyses indicated a rapid initial removal followed by equilibrium phases, suggesting biosorption and bioaccumulation mechanisms. Li and Se showed limited removal capacities across all species. Photosynthetic pigment analysis revealed stress responses in Salvinia natans under acidic, multielement exposure. Overall, phycoremediation and phytoremediation represent effective low-chemical treatment strategies with potential for integration into a complementary mining wastewater treatment workflow. Full article

Net surface shortwave radiation (NSSR) is a key parameter in the Earth’s energy cycle, greatly affecting global water and heat balance. Currently, a comprehensive comparative analysis regarding the accuracy of different models remains severely lacking, and there is also a notable deficiency in the systematic exploration of seasonal radiative drivers. Therefore, we developed a machine learning-based seasonal NSSR estimation model. By integrating in-situ observational data with multi-source remote sensing datasets, we achieved precise quantification of radiative fluxes. This proposed model framework employed three cutting-edge algorithms, namely Random Forest (RF), eXtreme Gradient Boosting (XGBoost), and Light Gradient Boosting Machine (LightGBM), to capture the non-linear interactions among radiative drivers across the four seasons. Through mechanistic sensitivity analysis, we quantified the impacts of key variables on NSSR prediction. The results unequivocally demonstrated that the RF algorithm demonstrated the best performance. Its seasonal R² were 0.95 (spring), 0.89 (summer), 0.95 (autumn), and 0.96 (winter). The Solar Zenith Angle (SZA) dominated in spring and winter; its absence reduced R² by 0.23 and raised RMSE by 20.66–26.42 W/m². Meteorological factors mattered most in summer; excluding them cut R² by 0.17 and hiked RMSE by 23.82 W/m². This study provides actionable insights for terrestrial radiation budget research. Full article

The Akseki–Kuyucak bauxite deposits, located in the Western Taurus Belt in southwestern Türkiye, represent karst-type bauxite mineralization derived from carbonate platform phases. This work integrates field observations, X-ray diffraction (XRD) analysis, and extensive geochemical data, including major, trace, and rare earth elements (REEs), to clarify the mineralogical characteristics, geochemical processes, and genetic implications of the deposits. Field and petrographic investigations indicate that the bauxite deposits occur as irregular fills and lens-shaped formations on paleokarstic surfaces of carbonate substrates. The XRD examination reveals that the major minerals in the bauxite samples are boehmite, hematite, and anatase, with some samples exhibiting a predominance of calcite, indicating a strong genetic relationship between the ore bodies and the carbonate host rocks. Major oxide analysis reveals a distinct compositional disparity between bauxitic and carbonate-dominated materials: bauxitic samples exhibit elevated Al₂O₃ and Fe₂O₃ levels, with reduced SiO₂ and CaO concentrations. In contrast, carbonate-rich samples show higher CaO and loss-on-ignition values. Ternary discrimination diagrams categorize most bauxitic samples into the ferritic bauxite and robust lateritization domains, indicating substantial weathering and residual enrichment processes. The trace element and REE studies reveal ΣLREE values ranging from 22.3 to 240.2 ppm, with a right-skewed distribution indicating heterogeneous enrichment. Correlation studies indicate that ΣLREE has a positive correlation with SiO₂ and K₂O, suggesting that the enrichment of REEs is more closely associated with silicate/clay minerals than with iron oxide phases. Furthermore, spider diagrams and the study of immobile components emphasize the significance of residual concentration processes in bauxitization. In contrast, modest TiO₂ levels indicate a composite source derived from both insoluble carbonate remnants and detrital siliciclastic materials. In summary, the Akseki–Kuyucak deposits are categorized as intricate karst bauxite systems, characterized by significant lateritization, regulated accumulation governed by paleokarst characteristics, and a complex geochemical evolution. The results demonstrate that integrating mineralogical, geochemical, and statistical methods provides a thorough framework for evaluating REE behaviors and the effects of source-related factors in karst bauxite deposits. Full article

Alkali-activated concrete can reduce reliance on Portland cement by valorizing industrial by-products. This study evaluates slag-based alkali-activated concretes incorporating natural diatomaceous earth (M2, M3) and residual diatomaceous earth from industrial filtration (V6–V7), benchmarked against an OPC reference. The experimental program measures compressive, tensile and flexural strengths and elastic modulus, and examines steel–concrete bond behavior through bond stress–slip response at multiple slip levels. Member-level performance is assessed using reinforced beams tested under four-point bending, and cracking is compared in the constant-moment region using crack number and average spacing derived from post-test observations. Results show that diatom-based alkali-activated mixtures can achieve mechanical performance comparable to OPC concrete, with clear dependence on diatom source and mixture design. Bond response is markedly mixture-dependent and cannot be inferred from compressive strength alone. All beams exhibited flexural behavior suitable for structural applications, with the RV6 mixture providing the most favorable overall response among the tested members. These findings support the feasibility of residual diatomaceous earth as a viable component in structural alkali-activated concretes. Full article

Accurate quantification of ecohydrological processes is essential for effective water and carbon management in terrestrial ecosystems. Traditional simulations mainly rely on mechanistic models, yet their accuracy is often limited by inconsistencies in representing physical processes and uncertainties in parameterization. Integrating remote sensing signals offers a promising way to reduce these uncertainties and enhance model applicability. In this study, in-situ observations from a wheat cropland in the Guanzhong Plain were used to simulate gross primary productivity (GPP) and latent heat flux (LE) by comparing a forward model (STEMMUS-SCOPE) with a remote sensing-driven inverse model (STEMMUS-MLR). We further examined the role of solar-induced chlorophyll fluorescence (SIF), an emerging proxy for photosynthesis, as an input to improve mechanistic modeling of GPP and LE. Results show that STEMMUS-MLR outperformed STEMMUS-SCOPE in estimating water and carbon fluxes, demonstrating that incorporating SIF effectively reduces bias associated with uncertainties in parameters and forcing data. The contribution of SIF was quantified using Random Forest regression and Shapley additive explanations (SHAP), revealing that SIF markedly reduced the dependence of GPP and LE simulations on shortwave radiation (SW), air temperature (Ta), and leaf area index (LAI). These findings highlight the critical role of SIF in ecohydrological modeling of semi-arid cropland ecosystems and provide a scientific basis for advancing process understanding and improving the precision management of water and carbon budgets in terrestrial ecosystems. Full article

In biological systems, DNA serves as the primary carrier of genetic information, and the stability of its structure is fundamental to cellular function. Metal ions and temperature are critical environmental factors that modulate DNA conformation and activity. However, the differential morphological effects of alkali, alkaline earth, and transition metal ions, especially when combined with thermal treatment, have not been systematically visualized and quantified. In this work, atomic force microscopy (AFM) was employed to investigate the effects of different metal ions (Na⁺, K⁺, Mg²⁺, Ca²⁺, Cu²⁺) and temperature on DNA structure. The results demonstrated that monovalent ions (Na⁺ and K⁺) neutralized the negative charges on the DNA backbone, thereby reducing intermolecular electrostatic repulsion and promoting DNA aggregation into dendritic structures. Divalent ions (Mg²⁺ and Ca²⁺) not only provided more effective charge screening but also formed ion bridges between DNA strands, leading to more compact and cross-linked networks. In contrast, Cu²⁺ ions directly coordinated with DNA bases, causing local structural distortion and strand scission. Elevated temperatures induced DNA melting, with distinct morphological transitions from extended double strands to condensed single-stranded globules observed at temperatures exceeding the melting point (T_m). These findings elucidate the mechanisms by which environmental factors govern DNA morphology, providing in-sights relevant to nanotechnology and molecular biology applications. Full article

The Research and Observation in Medium Earth Orbit (ROMEO) mission, developed at the University of Stuttgart‘s Institute of Space Systems, seeks to demonstrate a cost-effective exploitation of the medium Earth orbit (MEO) for sustainable access to space. It uses a green propulsion system with water as propellant to reach up to 2500 km altitude starting from a 450 km sun-synchronous orbit (SSO). This paper presents the design and intended use of the ROMEO satellite as well as its two in-house developed camera systems, the public relations (PR) and the near-infrared (NIR) camera system. The PR camera system features two silicon sensors with a Bayer color pattern in a compact, lightweight package and in a cold redundant setup to reduce the impact of radiation-related degradation. Their wide field of view (128 × 96°) allows imaging of the complete visible Earth in the mission‘s final orbit and supports calibration of the Earthshine telescope, which is the primary payload. The NIR camera system uses a commercial InGaAs sensor with a high quantum efficiency up to 1700 nm, coupled to a 100 mm focal length optics assembly that yields a ground sampling distance of 45 m in the initial orbit. Its scientific objectives include monitoring gas flares and wildfires, which are relevant to climate change research, and demonstrating an exoplanet transit detection—an unprecedented capability for a small satellite using a commercial off-the-shelf InGaAs sensor in the NIR spectrum. This paper demonstrates that ROMEO’s compact, low-mass camera systems meet mission constraints while enabling a broad spectrum of scientific and outreach activities. Full article

With the increasing number and enhanced sensing capabilities of satellites, the volume of satellite imagery has substantially surpassed the available bandwidth of satellite-to-ground links. Recently, with the adoption of commercial on-board GPUs, Learned Image Compression (LIC) offers the potential to mitigate this bottleneck by virtue of its superior rate–distortion performance over traditional codecs. However, existing LIC solutions operate in isolation on single satellites and underutilize the overlapping observations, which limits further gains in compression performance. In this paper, we propose Distributed Latent Representation Clustering (DLRC), which represents the first attempt to integrate real-time multi-satellite observation redundancy elimination into LIC. DLRC first introduces a local latent representation clustering mechanism. It discretizes the latent representation of LIC into compact cluster signatures on each satellite with lightweight computational overhead. Subsequently, DLRC presents a global cluster signature synchronization strategy. By exchanging signatures with negligible communication overhead, it enables multiple satellites to identify globally redundant local observations on a per-signature basis. By coding and downlinking only the latent representation corresponding to globally unique signatures, DLRC achieves non-redundant downlink in a training-free paradigm while remaining compatible with existing LIC architectures. Through extensive experiments, we demonstrate that DLRC achieves efficient bits per pixel reduction compared to independent LIC solutions while maintaining comparable reconstruction quality. Full article

Mountain regions are highly climate-sensitive, yet long-term observational evidence of elevation and seasonal climate dynamics in Central Asia remains limited. This study examines spatiotemporal trends in temperature (Tmean, Tmax, Tmin, and diurnal temperature range [DTR]) and precipitation across Kazakhstan’s transmountain regions using 74 meteorological stations (1981–2023). Data were analyzed using the Mann–Kendall test and Sen’s slope estimator, stratified across six elevation zones from lowlands (<400 m) to high mountains (>1500 m). Results reveal a robust, spatially coherent warming signal across all zones. Annual Tmean increased at a median rate of ~0.30 °C decade⁻¹, peaking at 0.36 °C decade⁻¹ above 1500 m, corresponding to an absolute increase exceeding 1.5 °C. Warming exhibited strong seasonal and diurnal asymmetries. Spring warmed most rapidly, with Tmean increasing >0.60 °C decade⁻¹ (approaching 3 °C total). Winter warming was driven by Tmin increases (up to 0.44 °C decade⁻¹), causing widespread DTR contraction, whereas summer warming was driven by Tmax increases, expanding DTR at higher elevations. Tmin showed the strongest elevation amplification overall. In stark contrast, precipitation trends were weak, spatially heterogeneous, and largely non-significant. Annual changes ranged from −6.63 to +14.35 mm decade⁻¹, with seasonal tendencies indicating modest, non-significant winter/spring wetting and summer drying. Ultimately, the results demonstrate a profound decoupling between strong, elevation-dependent warming and weak precipitation changes. The acute amplification of temperature, particularly during spring and summer at high elevations, has severe implications for snowmelt timing, glacier mass balance, evapotranspiration demand, and long-term water security in Kazakhstan. Full article