Search Results (88)

The variability of solar energy limits its reliability as a thermal resource, motivating the use of thermal energy storage (TES) to extend heat availability beyond periods of direct irradiance. This study numerically compares latent and sensible TES integrated into a solar dish system from a resource-oriented perspective across representative Mexican climates. Rather than focusing only on stored energy, the analysis evaluates how each storage strategy affects the temporal availability and post-irradiation persistence of usable thermal energy over 24 h charge–discharge cycles. A salt-based PCM (58.1LiNO₃–41.9KCl) was assessed against steel-based sensible storage under identical operating conditions. Under average-day forcing, the minimum PCM mass required to effectively utilize latent heat while sustaining a 320 W test load was found to be 13 kg. Under these conditions, the PCM case showed smoother thermal transients and longer post-irradiation energy availability, enabling nocturnal operation. In contrast, a mass-matched 13 kg steel store showed negligible post-irradiation availability, while a volume-matched 55 kg steel configuration achieved similar nocturnal operation only by substantially increasing mass, with limited improvement in accumulated energy. Hot-day forcing extended the operating window, whereas cold-day forcing yielded negligible charging so that operation could not be sustained within a single daily cycle. Full article

This paper presents the design and analysis of solar systems for agricultural applications and the sustainable energy supply of villages, based on a case study of a rural settlement comprising 30 households. The village energy demand is quantified through a detailed assessment of hourly load profiles for daytime and nighttime operation, identifying peak loads and total daily energy consumption. Energy usage patterns are established for residential buildings, agricultural water pumping, public lighting, healthcare facilities, and commercial services. To meet these energy requirements sustainably, a 60 kW photovoltaic (PV) system is proposed in combination with a solar thermal water heating system designed to supply domestic and agricultural hot water. This study details the design methodology and simulation of the solar thermal system, including heat transfer modeling and system dimensioning. MATLAB (V.22b) simulations are conducted to evaluate system performance, covering PV energy generation, battery charge–discharge cycles, and thermal behavior over a 24 h period. Comparative analyses of standalone PV, hybrid PV/T, and combined PV and solar thermal configurations demonstrate that separate PV and thermal systems provide superior cost-effectiveness, operational reliability, and reduced maintenance requirements. The results confirm the technical feasibility, economic viability, and environmental benefits of solar-based solutions for rural electrification and agricultural applications. The results indicate that the analyzed rural settlement has an estimated daily electricity demand of approximately 590 kWh. Based on this demand, a 60 kW photovoltaic system was selected to ensure sufficient daytime electricity production while also allowing battery charging for nighttime consumption. In addition, the solar thermal system can increase the water temperature from approximately 10 °C to 55–80 °C, depending on solar irradiance conditions. The combined PV and solar thermal configuration demonstrates the potential to provide a reliable and sustainable energy solution for rural off-grid communities. Full article

Inland waters exhibit pronounced temporal variability in CO₂ and CH₄ emissions. However, existing research has predominantly focused on seasonal to interannual scales, with most field measurements conducted during daytime hours. Consequently, diel (24 h) emission dynamics remain poorly characterized. This study synthesizes current knowledge on diel variations in CO₂ and CH₄ fluxes across inland water bodies—including rivers, lakes, reservoirs, and ponds—with particular attention to day–night contrasts. Based on the limited available data, the average day-to-night flux ratios are 0.87 for CO₂ and 1.44 for CH₄. Exclusive reliance on daytime sampling may therefore underestimate daily CO₂ emissions by approximately 13% while overestimating CH₄ emissions by a similar magnitude. Diel fluctuations in water temperature and wind speed—driving corresponding changes in surface water gas concentrations and air–water gas transfer velocity—represent primary controls on these emission patterns. Secondary influences include solar radiation, dissolved oxygen, pH, and nutrient availability. Future efforts should prioritize high-frequency monitoring of diel carbon emission cycles and mechanistic analysis of their drivers, ultimately enabling the development of large-scale models that explicitly incorporate diel dynamics. Such advances are essential for accurate quantification and correction of carbon emissions from inland waters at regional to global scales. Full article

This study aimed to evaluate the effects of thermal cycling and restorative material type on surface roughness of material surfaces and dental interfaces using a non-contact profilometer. Ninety Class V cavities (2 mm × 4 mm × 2 mm in height, width, and depth) were prepared on extracted third molars and restored with four bio-interactive materials (Equia Forte, Cention-N, Activa BioActive Restorative, Fuji II LC) and one composite resin (Solare-X) (n = 18/group). After polishing (Optidisc), initial surface roughness (Sa, µm) was measured following 24 h immersion in distilled water. Measurements were performed at cement/material (400 × 1600 μm²), enamel/material (1600 × 400 μm²), and material surfaces (800 × 800 μm²). Samples underwent 10,000 thermal cycles (5–55 °C) to simulate aging, and roughness was re-measured. Data were analyzed with two-way repeated measures ANOVA and Tukey’s post hoc test (p < 0.05). Solare-X showed the lowest roughness, while Fuji II LC and Activa BioActive Restorative were smoother than Cention-N and Equia Forte (p < 0.01). All materials exhibited significant roughness increases after thermal cycling (p < 0.01). Cement/material and enamel/material interfaces consistently showed higher roughness than material surfaces (p < 0.01). Thermal cycling significantly increased surface roughness of all tested materials. Interfaces demonstrated greater roughness than material surfaces, indicating higher susceptibility to plaque retention and potential risk for long-term restoration success. Full article

The increasing electrification of mobility within smart cities has accelerated the need for intelligent energy management strategies that jointly address cost, emissions, and battery health. This study develops a health-aware hybrid reinforcement–predictive energy manager (H-RPEM) designed for photovoltaic–electric vehicle (PV-EV) microgrids. The proposed controller unifies model-based predictive optimisation with adaptive reinforcement learning to achieve both short-term operational efficiency and long-term asset preservation. A comprehensive dataset of solar generation, EV charging behaviour, and stochastic load profiles was employed to train and validate the hybrid control framework under realistic operating conditions. Quantitative results indicate that the proposed H-RPEM controller achieves an 18.7% reduction in total operating cost and a 22.5% decrease in carbon emissions, whilst maintaining the battery state-of-health above 0.95 throughout a 24 h operational cycle. When benchmarked against standard predictive control, the hybrid strategy converges 30–40 episodes faster and delivers a 25% improvement in reward stability, demonstrating enhanced robustness and learning efficiency. The results confirm that H-RPEM achieves robust and balanced performance across economic, environmental, and technical domains, establishing it as a scalable and health-conscious control solution for next-generation smart city microgrids. Full article

The high penetration rate of renewable energy poses significant challenges to the planning and operation of power systems in regions with scarce data. In these regions, it is impossible to accurately simulate the complex nonlinear dependencies among hydro–wind–solar energy resources, which leads to huge operational risks and investment uncertainties. To bridge this gap, this study proposes a new data-driven framework that embeds the natural climate cycle (24 solar terms) into a physically consistent scenario generation process, surpassing the traditional linear approach. This framework introduces the Comprehensive Similarity Distance (CSD) indicator to quantify the curve similarity of power amplitude, pattern trend, and fluctuation position, thereby improving the K-means clustering. Compared with the K-means algorithm based on the standard Euclidean distance, the accuracy of the improved clustering pattern extraction is increased by 3.8%. By embedding the natural climate cycle and employing a two-stage dimensionality reduction architecture: time compression via improved clustering and feature fusion via Kernel PCA, the framework effectively captures cross-source dependencies and preserves climatic periodicity. Finally, combined with the simplified Vine Copula model, high-fidelity joint scenarios with a normalized root mean square error (NRMSE) of less than 3% can be generated. This study provides a reliable and computationally feasible tool for stochastic optimization and reliability analysis in the planning and operation of future power systems with high renewable energy grid integration. Full article

The variation in the maximum usable frequency (MUF) during geomagnetic disturbances is a key parameter for high-frequency (HF) radio communications. This study investigates MUF variability and related ionospheric parameters during the first geomagnetic superstorm of solar cycle 24, on 17 March 2015 (the Saint Patrick’s Day storm). Using Digisondes at Sao Luis (equatorial) and Campo Grande (low-latitude, near the southern crest of the Equatorial Ionization Anomaly), we analyzed storm-time changes in the F region. During the main phase, two episodes of eastward Prompt Penetration Electric Fields produced rapid uplifts of the F2-layer peak height at São Luis, reaching altitudes up to 520 km, accompanied by MUF decreases of approximately 25% relative to quiet-day values. In contrast, Campo Grande exhibited a more subdued response, with MUF deviations generally remaining within 15–20% of quiet-time conditions. During the recovery phase, the likely occurrence of a westward disturbance dynamo electric field was inferred from suppression of the Pre-Reversal Enhancement and decreased F-layer heights at São Luis. Comparative analysis highlights distinct regional responses: São Luis showed strong storm-time deviations, while Campo Grande remained comparatively stable under the impacts of Equatorial Ionization Anomaly effects. These results provide quantitative evidence of localized geomagnetic storm impacts on MUF in the Brazilian sector, offering insights that may improve space weather monitoring and HF propagation forecasting. Full article

In this paper, we investigate the thread oscillations in a quiescent prominence observed by New Vacuum Solar Telescope at the H$\alpha$ line center on 17 April 2024. Each individual thread is traced by the local maximum intensity on the time–distance maps. Although there are numerous threads in this prominence, 24 oscillating threads are identified at eight slits parallel to the solar surface. A sinusoidal function is used to fit them, and about 1.5 cycles of oscillations and a mean period of 27.7 min are detected. We find that all these 24 threads display the oscillation with almost a constant amplitude with an average value of about 0.92 Mm, with no damping or expansion during their lifetimes. Furthermore, we find the oscillations at different positions on a same thread almost have a similar period of 88.7 min in phase, which indicates that the thread oscillations could be triggered by a standing-type wave. Using the typical parameters in the prominence, the magnetic field strength (B) is estimated in the range of 4 G ≤ B ≤ 21 G, which is consistent with the previous results. Our findings would provide the clues for the thread oscillation mechanism in the prominence. Full article

An analysis of the solar differential rotation (DR) during solar cycle No. 24 (SC24) (2009–2019), based on the Kanzelhöhe Observatory for Solar and Environmental Research (KSO) data set, is presented. The white-light images were processed and positions of sunspot groups were extracted using the morphological image processing technique. The sample was constrained to ±58° in central meridian distance (CMD). Two methods were applied to derive the sidereal angular rotation rate (ω) and, in turn, the solar rotation parameters A and B: (a) calculating synodic rotation velocities from daily CMD differences and elapsed time (daily shift method); (b) applying a robust linear least-squares fit to the time series CMD(t) for each sunspot group. To assess the relationship between rotation parameters and solar activity, we analyzed the yearly mean total sunspot number from the Sunspot Index and Long-term Solar Observations (SILSO). This study marks the first complete analysis of SC24 using the KSO sunspot groups’ data. Our goal is to extend the previous analysis of DR from the KSO data to the present, especially because the Solar Optical Observing Network/United States Air Force/National Oceanic and Atmospheric Administration data set (SOON/USAF/NOAA) and Debrecen Photoheliographic Data (DPD) catalogues do not provide data after 2018. Full article

The aim of this study was to find out whether, just like in March 2015, daily regular GPS positioning disturbances caused by ionospheric scintillations occurred in other months of the solar activity cycle 24. The GPS positioning 90-s kinematic solutions of selected 46 months covering 11 years were used to search for regular daily scintillation events. The hypothesis on predictable regular daily ionospheric scintillation was tested. Scintillation waves were discovered as a result of space weather impact with the sidereal day regularity. It leads to the conclusion that the radiation originates from the interplanetary medium. The enhancement of radiation waves by solar activity is similar to Pc1 waves. The regular daily ionospheric scintillation waves are recorded at any time of the day. In the years with low solar activity in 2010 and 2012, regular scintillation waves were not found. It cannot be claimed that the comparison of daily regular ionospheric scintillation cases over time with the mentioned Pc1 wave cases indicates any interrelation. Full article

This study presents the experimental and thermodynamic evaluation of a solar thermochemical refrigeration system (STRS) powered by evacuated tube solar collectors with heat pipes as thermal energy sources, using industrial-grade BaCl₂–NH₃. The system was designed to produce refrigeration and ice using industrial-grade BaCl₂–NH₃ without additional additives or electrical input. Experimental tests were conducted under real-world conditions, with generation temperatures between 55 and 66 °C and solar irradiance of 750 to 900 W/m². The system achieved efficient ammonia desorption, yielding up to 4.2 L of refrigerant and demonstrating repeatable operation over several thermochemical cycles. During the nighttime absorption–evaporation process, the STRS reached evaporation temperatures of −7 to −3 °C and absorption temperatures between 24 and 31 °C, suitable for ice production. The internal coefficient of performance ranged from 0.244 to 0.307, with an overall efficiency of 0.146 to 0.206. The experimental data obtained were used to derive pressure–temperature equilibrium equations for the BaCl₂–NH₃ working pair, yielding correlation coefficients greater than 0.98, which confirms thermodynamic consistency. The results demonstrate that additive-free, industrial-grade BaCl₂ can achieve high efficiency at low temperatures, making this system a cost-effective and sustainable alternative for refrigeration and cold storage in rural areas. This research contributes new experimental knowledge on low-temperature thermochemical refrigeration and supports future development toward quasi-continuous optimization cycles based on experimental data. Full article

This study presents the Level(s)+37 Framework, a decision-support tool consisting of 37 indicators designed to evaluate and enhance passive design performance, social equity, and climate resilience in primary and secondary schools. Aligned with the six macro-objectives of the European Level(s) scheme, the indicators are organised into seven thematic clusters—thermal comfort, indoor air quality, solar control and daylighting, environmental ergonomics, ecological sustainability and circular economy, climate justice and social equity, and educational value with stakeholder participation—covering all life-cycle stages from design to retrofit. The framework was developed through a six-phase mixed-methods protocol, including a systematic review of 210 scientific and regulatory sources, 24 semi-structured interviews with school stakeholders, and a Delphi–AHP involving 170 experts. The resulting hierarchy of indicators (CI < 0.10; Kendall’s W = 0.78) ensures methodological robustness and contextual relevance for the Spanish school building stock. By integrating environmental, technical, and pedagogical dimensions, the Level(s)+37 Framework serves as both an evaluation tool and a catalyst for sustainable transformation, promoting participatory governance and climate-responsive learning environments. Full article

Space weather exerts a significant influence on the Earth’s atmosphere, driving a variety of physical processes, including the production of cosmogenic radionuclides. Among these, ⁷Be is a naturally occurring radionuclide formed through spallation reactions induced by cosmic-ray showers interacting with atmospheric constituents, primarily oxygen and nitrogen. Over long timescales, the atmospheric concentration of ⁷Be exhibits a direct correlation with the cosmic-ray flux reaching the Earth and an inverse correlation with solar activity, which modulates this flux via variations of the heliosphere. The large availability of ⁷Be concentration data, resulting from its use as a natural tracer employed in atmospheric transport studies and in monitoring the fallout from radiological incidents such as the Chernobyl disaster, can also be exploited to investigate the impact of space weather conditions on the terrestrial atmosphere and related geophysical processes. The present study analyzes a long-term dataset of monthly ⁷Be activity concentrations in air samples collected at ground level since 1987 at the ENEA Casaccia Research Center in Rome, Italy. In particular, the linear correlation of this time series with the galactic cosmic ray flux on Earth and solar activity have been investigated. Data from a ground-based neutron monitor and sunspot numbers have been used as proxies for galactic cosmic rays and solar activity, respectively. A centered running-mean low-pass filter was applied to the monthly ⁷Be time series to extract its low-frequency component associated with cosmic drivers, which is partially hidden by high-frequency modulations induced by atmospheric dynamics. For Solar Cycles 22, 23, 24, and partially 25, the analysis shows that a substantial portion of the relationship between stratospheric ⁷Be concentrations and cosmic drivers is captured by linear correlation. Within a statistically consistent framework, the evidence supports a correlation between ⁷Be and cosmic drivers consistent with solar-cycle variability. The ⁷Be radionuclide can therefore be regarded as a reliable atmospheric tracer of cosmic-ray variability and, indirectly, of solar modulation. Full article

Renewable energy systems like solar and wind power are the main source of sustainable energy production; however, their intermittent nature produces challenges for grid integration, so they require realistic forecast models. This study developed a Long Short-Term Memory (LSTM) neural network model to predict solar irradiance and wind power over a 24 h horizon using a 240 h (10-day) dataset. The dataset, being hourly measurements of solar irradiance (W/m²) and wind speed (m/s), was divided and normalized into 193 sequences of 24 h each, with 80% for training and 20% for validation. Two LSTM models, each consisting of 100 hidden units, were trained using the Adam optimizer to predict the next 24 h for each of the variables using forget, input, and output gates to capture temporal dependencies. The results have shown that the model accurately forecasted solar irradiance with a clear day–night cycle, while forecasts of wind speed revealed higher variability, although the PV system was better than the wind system due to low wind speeds. The results reveal that the LSTM model can effectively predict renewable energy output by predicting the wind speed and Solar Irradiance, which are the main parameters that control the output power of wind turbines and PV power, respectively. Full article

Constructing heterojunction photocatalysts with efficient interfacial charge transfer is critical for solar-driven hydrogen evolution. In this study, a highly dispersed MoS₂/g-C₃N₄ composite was successfully synthesized via a stirring-assisted hydrothermal in situ growth strategy. The introduction of stirring during synthesis significantly enhanced the uniform dispersion of MoS₂ nanosheets and exposed abundant edge sites, leading to well-integrated heterojunctions with enhanced interfacial contact. Comprehensive structural and photoelectronic characterizations (XRD, SEM, TEM, EDS mapping, UV–Vis, TRPL, EIS, EPR) confirmed that the composite exhibited improved visible-light absorption, accelerated charge separation, and suppressed recombination. Under simulated solar irradiation with triethanolamine (TEOA) as a sacrificial agent, the optimized 24% MoS₂/g-C₃N₄-S catalyst achieved a high hydrogen evolution rate of 14.33 mmol·g⁻¹·h⁻¹ at a catalyst loading of 3.2 mg, significantly outperforming the unstirred and pristine components, and demonstrating excellent cycling stability. Mechanistic studies revealed that the performance enhancement is attributed to the synergistic effects of Type-II heterojunction formation and edge-site-rich MoS₂ co-catalysis. This work provides a scalable approach for non-noble metal interface engineering and offers insight into the design of efficient and durable photocatalysts for solar hydrogen production. Full article