Search Results (309)

Precise photovoltaic (PV) performance modeling is essential for optimizing system design, operational monitoring, and reliable power forecasting—yet spectral correction is often overlooked, despite its significant impact on energy yield uncertainty. This study employs the FARMS-NIT model to assess the impact of spectral irradiance on eight PV technologies across 79 European sites, grouped by Köppen–Geiger climate classification. Unlike previous studies limited to clear-sky or single-site analysis, this work integrates satellite-derived spectral data for both all-sky and clear-sky scenarios, enabling hourly, tilt-optimized simulations that reflect real-world operating conditions. Spectral analyses reveal European climates exhibit blue-shifted spectra versus AM1.5 reference, only 2–5% resembling standard conditions. Thin-film technologies demonstrate superior spectral gains under all-sky conditions, though the underlying drivers vary significantly across climatic regions—a distinction that becomes particularly evident in the clear-sky analysis. Crystalline silicon exhibits minimal spectral sensitivity (<1.6% variations), with PERC/PERT providing highest stability. CZTSSe shows latitude-dependent performance with ≤0.7% variation: small gains at high latitudes and losses at low latitudes. Atmospheric parameters were analyzed in detail, revealing that air mass (AM), clearness index (K_t), precipitable water (W), and aerosol optical depth (AOD) play key roles in shaping spectral effects, with different parameters dominating in distinct climate groups. Full article

Monitoring soil moisture (SM) using permanently installed gamma radiation (GR) detectors is a promising non-invasive method based on the inverse relationship between SM and soil-emitted GR. In a previous study, we successfully estimated SM from environmental gamma radiation (EGR) measured by a low-cost counter-tube detector. Since this detector type provides a bulk GR response across a wide energy range, EGR signals are influenced by several confounding factors, e.g., soil radon emanation, biomass. To what extent these confounding factors deteriorate the accuracy of SM estimates obtained from EGR is not fully understood. Therefore, the aim of this study was to compare the accuracy of SM estimates from EGR with those from reference ⁴⁰K GR (1460 keV) measurements which are much less influenced by these factors. For this, a Geiger–Mueller counter (G–M), which is commonly used for EGR monitoring, and a gamma spectrometer were installed side by side in an agricultural field equipped with in situ sensors to measure reference SM and a meteorological station. The EGR_G–M and spectrometry-based ⁴⁰K measurements were related to reference SM using a functional relationship derived from theory. We found that daily SM can be predicted with an RMSE of 3.39 vol. % from ⁴⁰K using the theoretical value of α = 1.11 obtained from the effective ratio of GR mass attenuation coefficients for the water and solid phase. A lower accuracy was achieved for the EGR_G–M measurements (RMSE = 6.90 vol. %). Wavelet coherence analysis revealed that the EGR_G–M measurements were influenced by radon-induced noise in winter. Additionally, biomass shielding had a stronger impact on EGR_G–M than on ⁴⁰K GR estimates of SM during summer. In summary, our study provides a better understanding on the lower prediction accuracy of EGR_G–M and suggests that correcting for biomass can improve SM estimation from the bulk EGR data of operational radioactivity monitoring networks. Full article

Understanding spatial variations in land surface temperature (LST) is critical for analyzing urban climate dynamics, especially within the framework of two-dimensional (2D) turbulence theory. This study assesses the spatial sampling behavior of urban thermal fields across eight metropolitan areas, encompassing diverse morphologies, surface materials, and Köppen–Geiger climate zones. We analyzed thermal infrared (TIR) imagery from two remote sensing platforms—MODIS (1 km) and Landsat (30 m)—to evaluate resolution-dependent turbulence indicators such as spectral slopes and breakpoints. Power spectral analysis revealed systematic divergences across spatial scales. Landsat exhibited more negative breakpoint values, indicating a greater ability to capture fine-scale thermal heterogeneity tied to vegetation, buildings, and surface cover. MODIS, in contrast, emphasized broader thermal gradients, suitable for regional-scale assessments. Seasonal differences reinforced the turbulence framework: summer spectra displayed steeper, more variable slopes, reflecting increased thermal activity and surface–atmosphere decoupling. Despite occasional agreement between sensors, spectral metrics remain inherently resolution-dependent. MODIS is better suited for macro-scale thermal structures, while Landsat provides detailed insights into intra-urban processes. Our findings confirm that 2D turbulence indicators are not fully scale-invariant and vary with sensor resolution, season, and urban form. This multi-sensor comparison offers a framework for interpreting LST data in support of climate adaptation, urban design, and remote sensing integration. Full article

Laser ranging technology holds a key position in the military, aerospace, and industrial fields due to its high precision and non-contact measurement characteristics. As a core component, the performance of the photon detector directly determines the ranging accuracy and range. This paper systematically reviews the technological development of photonic detectors for laser ranging, with a focus on analyzing the working principles and performance differences of traditional photodiodes [PN (P-N junction photodiode), PIN (P-intrinsic-N photodiode), and APD (avalanche photodiode)] (such as the high-frequency response characteristics of PIN and the internal gain mechanism of APD), as well as their applications in short- and medium-range scenarios. Additionally, this paper discusses the unique advantages of special structures such as transmitting junction-type and Schottky-type detectors in applications like ultraviolet light detection. This article focuses on photon counting technology, reviewing the technological evolution of photomultiplier tubes (PMTs), single-photon avalanche diodes (SPADs), and superconducting nanowire single-photon detectors (SNSPDs). PMT achieves single-photon detection based on the external photoelectric effect but is limited by volume and anti-interference capability. SPAD achieves sub-decimeter accuracy in 100 km lidars through Geiger mode avalanche doubling, but it faces challenges in dark counting and temperature control. SNSPD, relying on the characteristics of superconducting materials, achieves a detection efficiency of 95% and a dark count rate of less than 1 cps in the 1550 nm band. It has been successfully applied in cutting-edge fields such as 3000 km satellite ranging (with an accuracy of 8 mm) and has broken through the near-infrared bottleneck. This study compares the differences among various detectors in core indicators such as ranging error and spectral response, and looks forward to the future technical paths aimed at improving the resolution of photon numbers and expanding the full-spectrum detection capabilities. It points out that the new generation of detectors represented by SNSPD, through material and process innovations, is promoting laser ranging to leap towards longer distances, higher precision, and wider spectral bands. It has significant application potential in fields such as space debris monitoring. Full article

The Activity Concentration Index (ACI), defined in Directive 2013/59/Euratom, serves as a criterion for the radiological significance of Naturally Occurring Radioactive Materials (NORMs) concentrated in building materials, considering related exposures due to the external gamma radiation field but not due to radon concentration levels. This study proposes a simple way of applying the ACI to interior spaces when concrete is the dominant construction material. Three calculation methods were examined, using four spaces within existing buildings, namely Method A, using the building elements’ mass proportions as a weighting factor; Method B, using only the geometrical characteristics of the internal space; and Method C, combining the mass proportions and inverse square distances. This methodology proposes a way of calculating the ACI based on data provided by existing studies about NORM concentrations in building materials and, thus, no sampling and subsequent NORM concentration measurements were required. The spatial data could be easily determined using either building plans or in situ measurements, using a handheld laser distance meter. The advantages and disadvantages of all three methods were analyzed, along with a comparison to in situ gamma radiation field measurements, performed with a portable Geiger–Müller detector. All the methods showed proportionality to the measured values. Method C was found to be the most suitable, especially for existing buildings, and Method A is recommended for early-stage design assessments. Full article

Ecuador faces a significant housing deficit, prompting government policies aimed at improving access to social housing for vulnerable families. Despite its relatively small geographic size, the country exhibits substantial climatic diversity, encompassing ten distinct Köppen–Geiger climate zones. These range from tropical rainforests to high-altitude Andean regions, each requiring specific housing strategies. However, social housing units are typically designed using a standardized model that disregards regional climatic variations, leading to suboptimal thermal performance and energy inefficiencies. This study evaluates the thermal comfort performance of standardized free-running social housing across six distinct cantons, using the ASHRAE 55-2020 adaptive comfort model. Dynamic simulations were conducted for both current climatic conditions and future scenarios for 2050 and 2100, employing tools such as Meteonorm 8.1 (for weather data), EnergyPlus 9.4.0, and DesignBuilder 7.0 (for thermal modeling). The findings reveal significant differences in indoor comfort levels among identical housing units due to localized climate conditions. Notably, high-altitude regions showed improved thermal performance under future scenarios, whereas coastal lowland areas experienced increased discomfort. These results underscore the urgent need for climate-responsive, adaptive housing designs tailored to local climatic realities across all regions of Ecuador. Full article

Background: Traumatic brain injury (TBI) remains a significant global health concern with a substantial socioeconomic impact. Although computed tomography (CT) is the primary initial neuroimaging technique, magnetic resonance imaging (MRI) offers a superior detection of subtle brain injuries. However, the ideal timing for MRI in critically ill patients with TBI remains unclear. Methods: This systematic literature review focused on the timing and utility of MRI in moderate and severe TBI in the early treatment phase. A comprehensive search was conducted using PubMed, employing specific search terms related to MRI timing and prognostication in TBI. The mean duration from admission to first MRI was examined in the conducting medical center for reference. Results: Early MRI, within 72 h post-injury, demonstrated a prognostic value compared with later scans. Diffusion tensor imaging (DTI) performed within 48 to 72 h captured critical pathophysiological changes. The presence of bilateral traumatic axonal injury in the brainstem or thalami on MRI served as a significant predictor of outcome in severe TBI. In pediatric TBI, most institutions performed MRI between seventy-two hours and two weeks post-injury, highlighting variability in practices. The mean interval until the first MRI at the conducting center was 16 days. Conclusions: MRI appears to be a valuable tool for prognostication in moderate to severe TBI, offering additional insights beyond those provided by CT. However, the optimal timing and modality for accurate diagnostic and prognostic utility remain uncertain. Current evidence suggests that MRI performed within 72 h after injury in ICU-treated patients with moderate and severe TBI offers valuable prognostic insights compared with delayed MRI, although further research is needed to establish standardized timing protocols and confirm the clinical impact. Full article

Desmoid tumors are rare, locally invasive soft-tissue tumors with unpredictable clinical behavior. Imaging plays a crucial role in their diagnosis, measurement of disease burden, and assessment of treatment response. However, desmoid tumors’ unique imaging features present challenges to conventional imaging metrics. The heterogeneous nature of these tumors, with a variable composition (fibrous, myxoid, or cellular), complicates accurate delineation of tumor boundaries and volumetric assessment. Furthermore, desmoid tumors can demonstrate prolonged stability or spontaneous regression, and biologic quiescence is often manifested by collagenization rather than bulk size reduction, making traditional size-based response criteria, such as Response Evaluation Criteria in Solid Tumors (RECIST), suboptimal. To overcome these limitations, advanced imaging techniques offer promising opportunities. Functional and parametric imaging methods, such as diffusion-weighted MRI, dynamic contrast-enhanced MRI, and T2 relaxometry, can provide insights into tumor cellularity and maturation. Radiomics and artificial intelligence approaches may enhance quantitative analysis by extracting and correlating complex imaging features with biological behavior. Moreover, imaging biomarkers could facilitate earlier detection of treatment efficacy or resistance, enabling tailored therapy. By integrating advanced imaging into clinical practice, it may be possible to refine the evaluation of disease burden and treatment response, ultimately improving the management and outcomes of patients with desmoid tumors. Full article

This study presents an innovative approach for repurposing depleted clastic hydrocarbon reservoirs in Hungary as High-Temperature Aquifer Thermal Energy Storage (HT-ATES) systems, integrating numerical heat transport modeling and machine learning optimization. A detailed hydrogeological model of the Békési Formation was built using historical well logs, core analyses, and production data. Heat transport simulations using MODFLOW/MT3DMS revealed optimal dual-well spacing and injection strategies, achieving peak injection temperatures around 94.9 °C and thermal recovery efficiencies ranging from 81.05% initially to 88.82% after multiple operational cycles, reflecting an efficiency improvement of approximately 8.5%. A Random Forest model trained on simulation outputs predicted thermal recovery performance with high accuracy (R² ≈ 0.87) for candidate wells beyond the original modeling domain, demonstrating computational efficiency gains exceeding 90% compared to conventional simulations. The proposed data-driven methodology significantly accelerates optimal site selection and operational planning, offering substantial economic and environmental benefits and providing a scalable template for similar geothermal energy storage initiatives in other clastic sedimentary basins. Full article

Under accelerated global warming, frequent droughts pose mounting threats to vegetation productivity, yet the spatiotemporal patterns and primary controls of drought resilience (DR) in China remain insufficiently quantified. This study aimed to characterize DR trends across Köppen–Geiger climate zones in China from 2001 to 2020 and to identify the dominant drivers and their interactions. We constructed a hazard–exposure–adaptability framework, combining multi-source satellite observations and the station data. A Bayesian-optimized Light Gradient Boosting Machine (LightGBM, version 4.3.0) model was trained under five-fold cross-validation. Shapley Additive exPlanations (SHAP) analysis decomposed each driver’s main and interaction effects on DR. The results indicated that DR was better in tropical regions, whereas arid and polar regions require more attention. From 2001 to 2020, 45.3% of China’s land area saw DR increases, while 36.4% declined. The key drivers influencing DR were temperature, sunlight hours, potential evapotranspiration, and precipitation. Notably, an increase in sunlight hours was often accompanied by a decrease in precipitation, resulting in suboptimal DR in China. When the normalized precipitation fell within the range of 0.12 to 0.65, elevated temperature exhibited an inhibitory effect on DR. Overall, this study established a DR assessment framework, elucidated its spatiotemporal dynamics, and revealed key driver interactions, offering timely insights for ecosystem research and management in the face of climate change. Full article

Indoor environmental quality (IEQ), encompassing thermal comfort and indoor air quality (IAQ), plays a crucial role in occupant well-being and operational performance. Although widely studied individually, integrating thermal comfort and IAQ assessments remains limited, particularly in large-scale tropical commercial settings. Hypermarkets, characterised by spatial heterogeneity and fluctuating occupancy, present challenges that conventional HVAC systems often fail to manage effectively. This study investigates thermal comfort and IAQ variability in a hypermarket located in Gombak, Malaysia, under tropical rainforest conditions based on the Köppen–Geiger climate classification, a widely used system for classifying the world’s climates. Environmental parameters were monitored using a network of IoT-enabled sensors across five functional zones during actual operations. Thermal indices (PMV, PPD) and IAQ metrics (CO₂, TVOC, PM2.5, PM10) were analysed and benchmarked against ASHRAE 55 standards to assess spatial variations and occupant exposure. Results revealed substantial heterogeneity, with the cafeteria zone recording critical discomfort (PPD 93%, CO₂ 900 ppm, TVOC 1500 ppb) due to localised heat and insufficient ventilation. Meanwhile, the intermediate retail zone maintained near-optimal conditions (PPD 12%). Although findings are specific to this hypermarket, the integrated zone-based monitoring provides empirical insights that support the enhancement of IEQ assessment approaches in tropical commercial spaces. By characterising zone-specific thermal comfort and IAQ profiles, this study contributes valuable knowledge toward developing adaptive, occupant-centred HVAC strategies for complex retail environments in hot-humid climates. Full article

This data descriptor presents δ-MedBioclim, a newly developed dataset for the Euro-Mediterranean region. This dataset applies the delta-change method by comparing the values of 25 General Circulation Models (GCMs) for the reference period (1981–2010) with their projections for future periods (2026–2050, 2051–2075, and 2076–2100) under the SSP1-RCP2.6, SSP2-RCP4.5, and SSP5-RCP8.5 scenarios. These anomalies are added to two pre-existing datasets, ERA5-Land and CHELSA, yielding resolutions of 0.1° and 0.01°, respectively. Additionally, this manuscript provides a ranking of GCMs for each major river basin within the study area to guide model selection. δ-MedBioclim includes, for all the aforementioned scenarios, monthly mean temperature, total monthly precipitation, and 23 bioclimatic variables, including 9 (biorm1 to biorm9) from the Worldwide Bioclimatic Classification System (WBCS) that are not available in other databases. It also provides two bioclimatic classifications: Köppen–Geiger and WBCS. This dataset is expected to be a valuable resource for modeling the distribution of Mediterranean species and habitats, which are highly affected by climate change. Full article

In terms of climate change, while tourism’s natural resources may be considered climate vulnerable, a large part of tourism’s primary industries are high carbon consumers. With the growth of worldwide efforts to adopt climate resilience actions across all industries, Destination Management Organizations could become focal points for raising awareness and leadership among local tourism stakeholders. The manuscript communicates a simple, reproducible approach to observing and analyzing climate change at a high territorial granularity to empower local destinations with the capability to disseminate quantifiable information about past, current, and future climate projections. In relation to Slovakia’s 39 local destinations, the approach utilizes six sub-sets of the latest high-resolution Köppen–Geiger climate classification grid data. The main climate categories’ similarity for local destinations was measured across six periods through the Pearson Correlation Coefficient of Pairwise Euclidean Distances between the linkage matrices of hierarchical clusters adopting Ward’s Linkage Method. The Shannon Entropy Analysis was adopted for the quantification of the homogeneity of the DMOs’ main climate categories, and Weighted Variance Analysis was adopted to identify the main climate categories’ weight fluctuations. The current results indicate not only a major shift from destination climates classified as cold to temperate, but also a transformation to more heterogeneous climates in the future. Full article

This paper introduces an innovative, environmentally sustainable, and climatic study analysing the impact of overhang depths on heating and cooling building energy demands in the Mediterranean Basin via dynamic energy simulations of a south-oriented reference residential building zone. The adopted bioclimatic approach aims at increasing building sustainability and suggests, for representative Köppen–Geiger climate subtypes, optimal overhang depths and climate-correlated depth domains. The definition of a large geoclimatic study based on 80 locations and the classification of results based on climate subtypes are two novelties introduced in this work. From the energy point of view, overhangs can reduce local building cooling needs by, on average, 27%, while decreasing the total final energy needs (Q_TOT) by 17%. A new approach is also introduced: comparing the energy reduction due to the addition of an overhang to commonly applied envelope retrofitting solutions, such as wall insulation or window substitutions. Overhangs show great potential in sites with arid climate subtypes and are more effective than other solutions in several locations. This study underlines the need to increase the adoption of passive cooling solutions by local retrofitting regulations in places with a Mediterranean climate, following a bio-regionalist approach able to increase the local buildings’ sustainable development. Full article

This study addresses the optimization of actuator arrangements in adaptive cable–strut tension structures to enhance structural controllability and performance. Two novel optimization criteria are proposed: (1) a weighted sensitivity criterion that integrates nodal displacements and internal force increments, and (2) a system strain energy criterion reflecting overall structural stiffness. Nonlinear optimization models are formulated for these criteria, with actuator positions as design variables, and solved using a robust multi-population genetic algorithm. The weighted sensitivity criterion prioritizes targeted control of specific nodes and members, while the strain energy criterion ensures balanced global response. Numerical validation is conducted on a Geiger cable dome and a four-layer tensegrity structure. Results demonstrate that both criteria yield actuator arrangements satisfying geometric symmetry while achieving high sensitivity in displacement and internal force control. The proposed framework offers practical insights for optimizing adaptive structures under static control requirements, and advances the field by bridging localized and global response optimization, enabling smarter, more resilient tension structures. Full article