Search Results (4,918)

Accurate Short-term forecasting of gusts at 10 m above ground level is challenging because gridded meteorological variables exhibit persistence, nonstationarity, and abrupt transitions. This study proposes a Temporal Adaptive Difference Polynomial Network (TADPN) using 8760 hourly records from a representative Nanjing grid point in 2025. Surface and pressure-level predictors are temporally aligned ECMWF IFS HRES 9 km fields retrieved through the default Best Match option of the Open-Meteo Historical Weather API, with a 12 h input window. TADPN uses the current gust as a persistence anchor and decomposes the forecast increment into a basic-trend component and a difference polynomial perturbation component. The basic branch uses all 60 variables, whereas the perturbation branch constructs current states, first- and second-order differences, signed-square terms, and within-variable interactions from 18 wind-related variables, with variable- and term-level soft gates. Strictly chronological three-fold rolling validation yields mean MAE, RMSE, and $R^2$ values of 0.4197 m s⁻¹, 0.6079 m s⁻¹, and 0.9373. TADPN reduces MAE by 11.88–29.88% relative to nine baselines. Ablation and significance analyses support the perturbation branch and difference-based features, demonstrating a lightweight and interpretable framework for hourly single-grid gust forecasting. Full article

Fe-based amorphous soft magnets have long been investigated with respect to alloy design and processing strategies to enhance saturation polarization (J_s) while preserving the amorphous phase essential for excellent soft magnetic properties and superior performance. This study demonstrates that Fe80B13Si7 melt-spun ribbons, containing a moderately high ferromagnetic fraction (~80 at%), display excellent amorphous stability, impressive soft magnetic behavior, and extremely low energy losses when processed under a highly efficient quenching atmosphere provided by helium. With the identical processing parameters, soft magnetic ribbons produced in helium gas provide a fully amorphous structure, whereas the ribbons synthesized in nitrogen undergo partial crystallization. The helium-quenched samples exhibit an exceptionally low mean coercivity (H_c) of ~1.3 A/m, in contrast to the nitrogen-quenched ones (mean H_c~14 A/m). The attained maximum permeability (μ_max) in helium (28.4 ± 1.3 (×10³)) is even comparable with commercial Metglas 2605SA1 (33.3 ± 4.8 (×10³)). The average saturation polarization (J_s) of the ribbons fabricated in both helium (~1.63 T) and nitrogen (~1.61 T) gases exceeds the commercial reference (~1.55 T). The helium environment showcases an excellent surface profile relative to nitrogen-induced quenching, which even shows a lower arithmetic mean surface height (S_a) than the reference material. Furthermore, the optimum annealing window for minimizing coercivity is found to lie approximately 15 to 20 K below the Curie temperatures (T_c) of the respective specimens. Core loss (P_core) measurements reveal substantial loss reduction in helium-quenched ribbons relative to nitrogen-quenched ones and even slightly lower than Metglas 2605SA1 at a lower polarization level (J~0.5 T). Therefore, this work establishes a comprehensive understanding of how helium and nitrogen gases, as quenching environments, influence the amorphous formation, magnetic softness, surface morphology, and energy losses of an alloy with a relatively high Fe content from the Fe-B-Si family to harness the material’s maximum potential. Full article

In cold and humid environments in high-latitude, high-altitude, and offshore regions, ice accretion sometimes occurs on airfoil blade surfaces, such as those of wind turbines. Therefore, a potential hazard exists for the equipment. For this reason, the aerodynamic characteristics of the airfoil blade degrade and power generation decreases. In the present study, the icing characteristics of airfoils in cold and foggy environments were investigated. A novel icing wind tunnel with a low LWC of 0.3 g/m³ and a small MVD of 10 μm was designed and built. An airfoil sample with the aerodynamic profile of NACA 0018 was selected, and the effects of the airfoil material and the temperature on the icing area, the thickness of ice, and the coverage scope of ice were tested and analyzed. The experimental results showed that the temperature had a more significant effect on the icing characteristics in comparison with the airfoil material. At the medium temperature, −7 °C in the present study, the icing area, the thickness of ice, and coverage scope all reached their maximum value. Specifically, the maximum cross-sectional icing areas (CIAs) on the aluminum airfoil at −4 °C, −7 °C, and −10 °C for 60 min were 35.088 mm², 66.357 mm^2, and 51.538 mm², respectively, and those on the FRP airfoil were 36.204 mm², 70.352 mm², and 47.814 mm², respectively. The FRP airfoil had a larger icing area and thickness of ice. In contrast, the aluminum airfoil had a larger coverage scope of ice, which was −0.10~0.15. In addition, the aerodynamic performance of the iced airfoil, including C_d and C_m, was also obtained through CFD. The research findings provided a foundation for further exploring the atmospheric icing of wind turbines and other structures with airfoil profiles. Full article

This study investigates the atmospheric corrosion behavior of high-lead bronze alloys within a simulated aggressive environment characterized by high humidity, acidity, chlorides, oxygen, and CO₂. The evolution of surface morphology and corrosion products was systematically monitored using colorimetric analysis and micro-Raman spectroscopy. Results indicate that the initial patina primarily comprised cuprite (Cu₂O) and cassiterite (SnO₂), which are predominantly benign phases. During the early corrosion stage, lead oxidation and carbonation prevailed, generating abundant bright-white cerussite. Subsequently, as copper-driven corrosion became dominant, these white deposits diminished and were progressively replaced by characteristic green “bronze disease”, identified as atacamite (Cu₂(OH)₃Cl). The findings reveal that preferential lead corrosion is likely to induce localized pitting, thereby accelerating degradation of the copper substrate. Consequently, higher lead content may reduce the overall corrosion resistance of bronze artifacts under these specific conditions. These results offer experimental insights into atmospheric corrosion mechanisms and inform the development of evidence-based conservation strategies for bronze cultural heritage. Full article

Trace element contamination represents a persistent environmental issue, particularly in industrialized areas where anthropogenic emissions overlap with natural geochemical backgrounds. This study investigates the atmospheric deposition of trace elements in the Milazzo district (Italy), which is characterized by intense industrial activity. Pinus pinea L. needles were used as biomonitors to assess the spatial distribution and sources of trace elements, combined with lead isotopic analysis for source apportionment. Forty needle samples were analyzed by ICP-OES and ICP-MS for Ca, K, Mg, Na, P, Al, As, Ba, Cd, Co, Cr, Cu, Fe, Mn, Mo, Ni, Pb, Sb, Ti, V, Zn, Y, La, Ce, Pr, Nd, Sm, Eu, Gd, Tb, Dy, Ho, Er, Tm, Yb, and Lu, while 25 samples were selected for Pb isotope ratio determination (²⁰⁶Pb/²⁰⁷Pb and ²⁰⁸Pb/²⁰⁶Pb). Multivariate statistical analyses identified source groups related to industrial and petrochemical emissions, vehicular traffic, crustal resuspension, and mixed combustion processes. Elevated concentrations of As, Cr, Mo, Ni, Pb, Sb, V, and Zn ranged from 16.6 μg g⁻¹ (Zn) to 0.09 μg g⁻¹ (Sb), with the following order of abundance: Zn > Cr > Ni > Pb > Mo > V > As > Sb; these elements were found near industrial facilities and urban areas. Enrichment Factor calculations indicated strong anthropogenic contributions to Cd, Cu, Mo, Sb, V, and Zn, with EF > 10, ranging from 10 (Cd) to 60 (Zn), whereas Al, Fe, and Ti exhibited EF values between 0.5 and 2, reflecting geogenic origins. Pb isotopic ratios (²⁰⁶Pb/²⁰⁷Pb = 1.153–1.192 and ²⁰⁸Pb/²⁰⁶Pb = 2.063–2.108) revealed mixing between industrial emissions and the local geological background, with limited influence from historical gasoline-derived Pb. This integrated geochemical and isotopic approach can effectively identify contamination sources in complex industrial environments. Full article

Airborne viruses are a key driver of infectious disease transmission, highlighting the importance of reliable detection in public health surveillance. As atmospheric viral concentrations are very low, a sampler with a high viral collection efficiency is essential. Although multiple approaches for evaluating collection efficiency have been applied using various samplers, no standardized sampler has yet been developed. We previously developed a wet-type electrostatic precipitator (WT-ESP) and successfully collected severe acute respiratory syndrome coronavirus 2 from the public environment. However, its efficiency for quantitative collection of airborne viruses remains unclear. This study aimed to clarify the collection efficiency of the WT-ESP. We evaluated collection efficiency via two different approaches: direct spray, where virus-containing aerosols were sprayed directly into the WT-ESP inlet, and indirect spray, where aerosols were dispersed into a closed space and then collected using the sampler. The direct spray tests achieved 20.1–50.2% collection efficiency, whereas the indirect spray test achieved an efficiency <12%. These findings highlight that electrostatic precipitation has an advantage of enhancing collection efficiency compared with values reported for impingers in previous studies and provide preliminary insights into the collection efficiencies under direct and indirect spray conditions, providing foundational data that bridge the gap between both methods. Full article

Architectural atmosphere for spirituality holds potential to support the physical and mental health of post-COVID urban populations, and people now spend more of their lives within buildings even as opportunities for spiritual engagement recede. Yet evidence-based knowledge for designing such environments remains limited. This study aimed to identify the architectural atmospheres for spiritual constructs through a systematic literature review and practice-based interviews conducted following the COVID-19 pandemic. Data from Scopus-indexed publications and architects’ relevant expertise were analyzed using thematic content analysis, while word frequency and bivariate association analyses were employed to identify key architectural characteristics and their associations with spiritual constructs. The findings indicate that a holistic atmospheric approach should integrate spatial, perceptual, and natural features. Tangible atmospheric features such as space, natural materials, and object elements emerged as most prominent, alongside intangible features including illumination, acoustics, and temperature conditions. At the use-effect level, spatial experience and perception were most frequently reported. Positive spiritual constructs were linked to symbolic objects, sensory experiences, and lighting conditions, whereas negative spiritual constructs were primarily associated with temperature conditions. Future studies should extend inquiry across diverse linguistic, cultural, and temporal contexts while empirically validating the proposed framework in real-world environments. Full article

Combined drought–heat stress is not adequately described by adding the responses to drought and heat in isolation. Water limitation restricts evaporative cooling, whereas high temperature increases atmospheric demand and threatens photosynthesis, proteostasis, and reproduction. To assess what has been demonstrated rather than merely proposed, we combined a structured narrative review with a study-level evidence map spanning genomics, multi-omics, and emerging artificial intelligence (AI). The PubMed search, updated on 9 August 2026, returned 254 records; targeted and backward searches contributed eight seminal or reviewer-nominated publications. Independent screening retained 90 verified publications: 69 direct combined-stress studies, 11 genomics studies, six original AI or prediction studies, and four reviews or quantitative syntheses used for context. No conserved molecular signature emerged. Response direction varied with soil water status, vapor-pressure deficit, stress order, tissue, and developmental stage. Carbon allocation, redox and proteostasis balance, reproductive failure, and recovery recurred across omics layers, although neither their direction nor their adaptive value was consistent. Genomic loci and predictive performance were also environment dependent. Direct uses of AI remain uncommon and currently support prioritization more convincingly than causal inference. We organize this uneven evidence as a ladder extending from molecular association to functional validation, multi-environment prediction, and cultivar deployment. The main shortage is not another nominal omics layer but harmonized factorial experiments that measure recovery and reproduction, report field-relevant environmental metadata, and include external validation. Full article

Accurately predicting high-energy laser propagation toward fast-moving aerial targets is not straightforward, since the slant range, elevation angle, atmospheric path, accumulated turbulence, and thermal blooming all change along with target motion. Because of this coupled evolution, fixed-path or quasi-static models can hardly describe, in a complete way, the time-varying loss of beam transmission and the weakening of energy concentration. To address this problem, this paper builds on established wave-optics propagation methods to develop a dynamic multi-physics framework for high-speed moving-target engagements. The central idea is to rebuild the propagation environment at every time step according to the instantaneous target position so that the optical path can be linked with height-dependent extinction, refractive-index structure, and absorption profiles; meanwhile, relative motion is represented as an effective transverse sweeping velocity, which helps reduce the accumulation effect of thermal blooming. Based on a unified split-step Fourier method, the model combines Beer–Lambert path attenuation, Kolmogorov-spectrum multilayer phase screens, and thermal-blooming phase modulation, yielding time-resolved indicators such as transmittance, received power, peak irradiance, Strehl ratio, scintillation index, pointing error, and beam-quality factor. Simulation results show that, in a 500 m static horizontal path, the attenuation module reduces to the Beer–Lambert solution, with the maximum relative error kept below ${10}^{-14}$; the turbulence phase-screen implementation is validated against the absolute Kolmogorov prediction. Over the resolved inertial interval, the ensemble-averaged structure function yields a fitted exponent $p_{\mathrm{f}\mathrm{i}\mathrm{t}}=1.671$ (theoretical: $5/3=1.667$) and a relative normalization error of $2.5\mathrm{\%}$, confirming that the generated screens reproduce both the Kolmogorov scaling and the prescribed turbulence strength. For a 1.064 μm, 2 kW Gaussian beam propagating over a 50 s trajectory of about 8 km, when the target speed increases from 0 to 300 m/s, the thermal-blooming-related beam-quality factor decreases from roughly 1.8 to 1.2, which indicates that dynamic geometry, turbulence, attenuation, and thermal blooming need to be considered together when evaluating laser propagation performance. Full article

The 1st International Online Conference on Environments addresses issues of environmental understanding, management, and restoration. Sessions ranged from general frameworks to a broad area of specific investigations: heavy metal removal using inactive yeast, gadolinium’s aquatic toxicity, adsorptive removal of pollutants, energy recovery from waste and wastewater treatment, recycled carbon fibers, climate-resilient urban development, renewable biofuel production, green hydrogen, anthropogenic and volcanic CO₂ emissions, quantifying aging dignity in urban ecosystems and stray dogs as pollution health sentinels. Keynotes covered digital plant phenotyping for restoration, microplastic dynamics, agricultural residue management, carbon credits, air quality, atmospheric pollution, transitional waters, green chemistry, ecotoxicity, micropollutants, and coastal darkening effects on plankton, among others. Applied solutions included phytoremediation of eutrophication in urban streams, circular approaches in aquaculture, biochar for wastewater treatment, AI-assisted mangrove monitoring, and true-cost accounting for food systems. The conference demonstrated that effective environmental policy requires the integration of laboratory findings, field restoration, and shared resource responsibility across terrestrial and marine ecosystems. Full article

To meet the growing demand for reliable space–air–sea-integrated communications and underwater information backhaul, this paper proposes and analyzes a three-hop heterogeneous space–air–sea communication system consisting of a satellite, a high-altitude platform (HAP), a sea-surface buoy, and an autonomous underwater vehicle (AUV). Specifically, the satellite-to-HAP link employs free-space optical (FSO) transmission, the HAP-to-sea-surface buoy link adopts mixed FSO/radio-frequency (RF) transmission, and the sea-surface buoy-to-AUV link utilizes underwater wireless optical communication (UWOC). To enhance the reliability of the HAP-to-sea-surface buoy link in complex atmospheric and maritime environments, a threshold-based adaptive combining scheme for mixed FSO/RF transmission is designed. Meanwhile, nonzero-boresight pointing error models are incorporated into the FSO and UWOC links to characterize practical link misalignment. Based on the proposed system model, analytical expressions for the end-to-end bit error rate (BER) are derived and validated through Monte Carlo simulations. The numerical results show that the proposed adaptive combining scheme achieves better BER performance than conventional dual-hop and hard-switching schemes. In addition, the effects of pointing errors, underwater turbulence, underwater transmission distance, shadowed fading, detection techniques, and modulation schemes on the system BER performance are further investigated. This work provides theoretical guidance for reliable cross-domain heterogeneous transmission in future space–air–sea integrated communication systems. Full article

The ecological status of the two nautical mile (2 nm) coastal waters of Bulgaria (BG) and Romania (RO) is evaluated in terms of eutrophication, focusing on various environmental and chemical indicators related to nutrient enrichment and its effects. Applying the Blue2 Modelling Framework (Blue2MF) Black Sea model, we simulate diverse combinations of nitrogen (N) and phosphorus (P) reduction. By integrating atmospheric and marine conditions, hydrology and environmental dynamics, the model provides a comprehensive framework for analysing the impact of external pressures on the marine environment and can be used to set regional sustainability goals. Each scenario is assessed with respect to environmental impact, such as enhanced water quality and potential alterations in phytoplankton communities. Furthermore, we establish integrated nutrient criteria for eutrophication control, concentrating on the management of both N and P inputs while maintaining the current ratio between them. The model results indicate that a 20% reduction in both N and P from European Union (EU) rivers would result in about a 24% decrease in N within the BG and RO 2 nm coastal waters, whilst sustaining the N:P ratio across various spatial scales—from river inputs to coastal and offshore zones. This approach is valuable for assessing the potential impacts of different nutrient reduction strategies, aiding the effective management of marine ecosystems to address eutrophication challenges. Full article

Accurately simulating the spatiotemporal distribution of global atmospheric CO₂ remains challenging yet essential for reducing uncertainties in carbon source-sink inversions, quantifying the climate effects of heterogeneous CO₂ fields, and supporting the development of CO₂ observation networks. In this study, we simulated global atmospheric CO₂ concentrations (2010–2019) at a horizontal spatial resolution of 1° × 1° using the Aerosol and Atmospheric Chemistry Model of the Institute of Atmospheric Physics (IAP-AACM) without data assimilation, with initial fields and flux data from the CarbonTracker CT2022 (CT2022) reanalysis product. The simulations were comprehensively evaluated against CT2022 and observations from ground-based (NOAA GML), airborne (ObsPack), and satellite (OCO-2) platforms. The results indicate that across all evaluated surface stations, CT2022 exhibits poorer overall statistical performance (R = 0.69, RMSE = 5.37 ppm, MB = 2.05 ppm) primarily due to noticeable overestimations at unassimilated ground stations, while IAP-AACM maintains robust performance across the surface network (R = 0.84, RMSE = 2.62 ppm, MB = 0.28 ppm). Vertically, airborne observations across eight global campaigns confirm that IAP-AACM accurately reproduces the vertical distribution of CO₂, maintaining strong correlations (R = 0.72–1.00) and performance comparable to the CT2022 reanalysis (R = 0.86–1.00). In terms of total column CO₂ concentrations (XCO₂), IAP-AACM exhibits strong agreement with satellite retrievals annually (R = 0.97, RMSE = 1.08 ppm, MB = 0.26 ppm), with seasonal metrics remaining consistently robust across all four seasons (R = 0.96–0.97, RMSE = 0.98–1.20 ppm, MB = 0.13–0.37 ppm), demonstrating large-scale transport fidelity on par with the CT2022 reanalysis. Finally, across representative ObsPack land sites, unassimilated IAP-AACM achieves a high median correlation (R = 0.97), low error (RMSE = 2.01 ppm), and low mean bias (MB = −0.45 ppm), closely approaching the assimilated CT2022 reanalysis product (R = 0.98, RMSE = 1.40 ppm, MB = −0.07 ppm). Further analysis indicates that the optimized IAP-AACM exhibits robust performance under stable boundary layer conditions, where the revised diffusion scheme produces higher vertical diffusion coefficients that help mitigate excessive near-surface CO₂ accumulation during nighttime. Overall, the optimized IAP-AACM effectively simulates the spatiotemporal distribution of global atmospheric CO₂, serving as a reliable tool to support advanced research. Full article

Atmospheric microplastics are increasingly recognized as mobile particulate contaminants that can be emitted, resuspended, transported, and deposited across indoor, terrestrial, marine, high-altitude, and remote environments. However, reported abundances and particle characteristics remain difficult to compare because studies differ in sampling design, reporting units, particle-size limits, contamination control, and polymer identification. This review combines concise bibliometric mapping with a critical narrative synthesis. A Web of Science Core Collection search for 2000–2024 retrieved 356 English-language articles and reviews, of which 280 met the eligibility criteria. Publication output increased rapidly after 2020. Co-citation and keyword analyses identified three major themes: occurrence, transport, and deposition; sampling and analytical characterization; and exposure and potential ecological and health implications. The synthesis shows that active air sampling and passive deposition collection measure different atmospheric processes, while inconsistent blank correction, recovery assessment, and polymer confirmation limit inter-study comparability. Field observations and modelling support long-range transport and the importance of particle morphology, but quantitative source attribution remains uncertain. Current evidence supports inhalation exposure and biological plausibility, yet is insufficient to establish population-level risks or causal links with specific diseases. Future research should prioritize harmonized monitoring, stronger QA/QC, improved detection of small particles and nanoplastics, and integrated transport–exposure assessment. Full article

Unmanned aerial vehicle (UAV)-based multispectral remote sensing has emerged as a promising tool for monitoring crop physiological status and supporting precision disease management. However, the capacity of multispectral vegetation indices to detect foliar diseases under commercial field conditions remains insufficiently understood, particularly in perennial crops grown in humid tropical environments. This study evaluated the potential of UAV-derived multispectral vegetation indices to assess the physiological response of avocado (Persea americana Mill.) canopies affected by anthracnose caused by Colletotrichum fructicola in Amazonas, Peru. Disease incidence and severity were assessed through field evaluations, while multispectral imagery was acquired using a UAV equipped with a MicaSense RedEdge-MX Dual sensor. Vegetation indices including the Normalized Difference Vegetation Index (NDVI), Green Normalized Difference Vegetation Index (GNDVI), Soil-Adjusted Vegetation Index (SAVI), Normalized Difference Red Edge Index (NDRE), Red Edge Chlorophyll Index (CIred-edge), Plant Senescence Reflectance Index (PSRI), and Visible Atmospherically Resistant Index (VARI) were calculated, and their relationships with anthracnose incidence were analyzed using Spearman’s rank correlation. Field observations confirmed a high incidence of foliar anthracnose with a heterogeneous spatial distribution across the orchard. Multispectral imagery successfully characterized spatial variability in the canopy physiological condition, revealing differences in vegetation vigor, chlorophyll-related reflectance, and senescence among experimental blocks. Nevertheless, none of the evaluated vegetation indices showed statistically significant correlations with anthracnose incidence (p > 0.05), indicating that spectral variability primarily reflected the general canopy physiological status rather than a disease-specific spectral response. These findings demonstrate that UAV-derived multispectral vegetation indices are valuable for monitoring spatial variability in the avocado canopy condition but have limited capability for independently detecting anthracnose under humid tropical field conditions. Future studies integrating multi-temporal UAV acquisitions, hyperspectral and thermal imagery, LiDAR, environmental variables, and machine-learning approaches are expected to improve the early detection and spatial prediction of anthracnose in avocado production systems. Full article