Search Results (349)

The CYGMEN (Cyprus GNSS Meteorology Enhancement) infrastructure project aims to establish a meteorological cluster (CyMETEO) in Cyprus of a lightning detection network, a dense GNSS (Global Navigation Satellite System) network for atmospheric water vapor estimation, a Radar Wind Profiler, and a microwave radiometer. Additionally, observational data generated by CyMETEO infrastructure will be assimilated into the Weather Research and Forecasting (WRF) model with the aim of improving short-term weather forecasting. The preliminary results of precipitable water vapor (PWV) estimation by employing (a) a GNSS network, (b) a microwave radiometer, (c) radiosonde, and (d) ERA5 reanalysis datasets over the Athalassas super-site in Nicosia, during May 2025, are intercompared in this study. Full article

This study explores reusing discarded industrial polylactic acid (PLA), such as defective parts, scraps and burrs, for food contact applications. Reprocessing of PLA (PLA-RP) was simulated via melt extrusion, and the obtained pellets were characterized in terms of viscosity average molecular weight (M_v), melt flow index (MFI), the presence of non-intentionally added substances (NIASs) and the absence of metals to ensure that no substances exceeded the specific migration limits (SMLs). A slight reduction in the M_v, accompanied by an increase in the MFI, was observed in PLA-RP. In virgin PLA, fewer compounds were detected, likely related to residual additives. A higher variety and concentration of volatile and non-listed compounds were observed in reprocessed PLA (PLA-RP), with three exceeding their assigned Cramer class thresholds, requiring further evaluation. Most identified substances were typically linked to thermal degradation or potential additives for reprocessing. In both the virgin and reprocessed materials, all substances with SMLs remained below applicable thresholds, including trace metals. The PLA-RP was further processed into films by means of a compression moulding process. The structure, mechanical behaviour, thermal stability and water vapor transmission rate were comparable to those of virgin PLA, indicating no significant changes. The overall migration level tested in a fatty food simulant remained below regulatory limits. The materials fully disintegrated under laboratory-scale composting conditions in less than 3 weeks. Thus, reprocessed PLA shows great potential as a non-migrating material of interest in the sustainable food packaging field. Full article

Microrefugia can be critical in mediating biological responses to climate change, but the location and characteristics of these habitats are often poorly understood. Groundwater-dependent ecosystems (GDEs) represent critical microrefugia for species dependent on cool, moist habitats. However, knowledge of the distribution and stability of GDE microrefugia remains limited. This challenge is typified in the Pacific Northwest, where poorly studied cliff-face seeps harbor exceptional biodiversity despite their diminutive size (e.g., ~1–10 m width). To improve knowledge about these microrefugia, we regionally modeled their distribution and stability. We searched for cliff-face seeps across 1608 km of roads, trails, and watercourses in Washington and Idaho, while monitoring water availability plus air and water temperatures at selected sites. We detected 457 seeps through an iterative process of surveying, modeling, ground-truthing, and then remodeling the spatial distribution of seeps using boosted regression trees. Additionally, we used linear and generalized linear models to identify factors linked to seep thermal and hydrologic stability. Seeps were generally most concentrated in steep and low-lying areas (e.g., edges of canyon bottoms), and were also positively associated with glacial drift, basalt or graywacke bedrock types, high average slope within 300 m, and low average vapor pressure deficit. North-facing slopes were the best predictor of stable air and water temperatures and perennial seep discharge; low-lying areas also predicted stable seep water temperatures. These findings improve possibilities to manage seep microrefugia in the Pacific Northwest and safeguard their associated biodiversity under climate change. Lastly, our iterative method adapts techniques commonly used in species distribution modeling to provide an innovative framework for identifying inconspicuous microrefugia. Full article

This study focused on the development and characterization of polyvinyl alcohol (PVA)- and konjac glucomannan (KGM)-based composite films enriched with natural bioactive additives. A PK (PVA/KGM) matrix with the optimum tensile strength was selected, and five film formulations were prepared by incorporating Aronia melanocarpa extract (AME), red dragon fruit extract (DFE), and thyme essential oil (TEO). TEO was also introduced via a Pickering emulsion (PE) technique. The total phenolic content (TPC) and free radical scavenging activity (FRSA) of extracts and films were determined, where AME exhibited the highest antioxidant activity (TPC: 243 mg GAE/g; FRSA: 81.7%). The additive-free PK film displayed limited antioxidant activity (18%), while antioxidant capacity significantly improved with extract and EO incorporation. The PK-A film (AME-added) demonstrated the highest tensile strength and lowest water vapor permeability, supported by increased local crystallinity detected in XRD. Color analysis indicated dominant red-violet tones in AME films and greenish-yellow tones in DFE films. FTIR confirmed that no new chemical bonds were formed between active compounds and the polymer matrix. DSC thermograms revealed consistent melting peaks (~150 °C) for all films, while Tg varied from 37 to 73 °C depending on additive type, reflecting plasticization effects of extracts and the counterbalancing effect of essential oil. The most hydrophobic (76.8°) and opaque sample was PK-ADO, prepared via the PE technique. Overall, natural extracts improved the structural, thermal, barrier, and antioxidant properties of PK films. Full article

Background: Dark-base hair fibers with Curl Pattern (CP) types 2 and 3 from Asian and European populations, respectively, are very similar, although each presents different behaviors regarding water diffusion and cosmetic treatments, including in relation to dyeing. This study aims to identify the key drivers of water diffusion in hair, particularly the role of lipids in the diffusion processes. Methods: Virgin, externally delipidized, and internally delipidized CP2 and CP3 hair strands were subjected to Dynamic Vapor Sorption (DVS) and ATR-FTIR investigations. In addition, external and internal lipid extracts were quantified and analyzed via thin-layer chromatography–flame ionization detection (TLC/FID). Results: The results obtained indicate that CP2 hairs present lower water regain at all humidity steps and a different diffusion behavior depending on the humidity. Lower diffusion was obtained at low humidity and higher diffusion at high humidity. TLC/FID analyses indicate that CP2 fibers present a significantly higher amount of external lipids (1.4% vs. 0.4%) and internal lipids (3.2% vs. 2.6%) as compared with the CP3 fibers. Conclusions: The higher amount of internal lipids is mainly due to the greater amount of polar lipids (ceramides). Lipid extraction tends to modify the water content, leading to a more hydrated and less permeable lipid-depleted fiber. The similar water properties of the two types of lipid fiber support the fundamental role of lipids, even when present in small quantities, in the differentiation of hair types. This study highlights a potential link between the lipid composition of CP3 and CP2 hair fibers and their differences in behaviors regarding water diffusion, which could also explain varying responses to cosmetic treatments. Full article

Cavitation has been widely explored to enhance physical and chemical processes across various applications. This study aimed to model the key characteristics of a cavitation jet, induced by a triangular-orifice nozzle, using both experimental and numerical methods. Optical instrumentation, a pressure transducer and the Reynolds-Averaged Navier–Stokes (RANS) equations were employed. Optical instrumentation and high-speed photography detected the two-phase flow generated by water vaporization, revealing a mean decay pattern. Irradiance fluctuations and photographic evidence provided results about the light transmission dynamics through cavitating jets. Pressure fluctuations exhibited similar growth and decay, supporting optical instrumentation as a viable method for assessing cavitation intensity. Experimental data showed a strong relationship between irradiance and flow rate (R² = 0.998). This enabled the correlation of the standard deviation of instantaneous pressure measurements and normalized flow rate (R² = 0.977). Furthermore, vapor volume fraction and normalized flow rate reached a correlation coefficient of 0.999. On the simulation side, the SSG-RSM turbulence mode showed better agreement with experimental data, with relative deviations ranging from 2.1% to 6.6%. The numerical results suggest that vapor jet length is related to vapor fraction through a power law, enabling the development of new equations. These results demonstrated that anisotropic turbulence modeling is essential to reproduce experimental observations compared to mean flow properties. Based on the agreement between the numerical model and the experimental data for mean flow quantities, a formulation is proposed to estimate the jet length originating from the nozzle, offering a predictive approach for cavitating jet behavior. Full article

Point-type smoke fire detectors have become one of the most commonly used technical means in the fire detection systems of ancient buildings. However, in practical applications, their performance is easily affected by special environmental interference factors. Therefore, in this study, a full-scale experimental scene of an ancient building with a typical flush gable roof structure was taken as the research object, and the differential influence laws of three typical interference sources, namely wind speed, water vapor, and incense burning, on the response times of point-type smoke detectors were quantified. Moreover, the prediction models of the alarm time of the detectors under the three interference conditions were established. The results indicate the following: (1) Within the range of experimental conditions, there is a quantitative relationship between the detector response delay and the type of interference source: the delay time shows a nonlinear positive correlation with the wind speed/water vapor interference gradient, while it exhibits a threshold unimodal change characteristic with the burning incense interference gradient; (2) under interference conditions, the detector response delay varies depending on the type of fire source: the detector has the best detection stability for smoldering smoke from a smoke cake, while it has the lowest detection sensitivity for smoldering smoke from a cotton rope. Moreover, the influence of wind speed interference is weaker than that of water vapor or smoke from burning incense, and the difference is the greatest in the wood block smoldering condition. (3) Construct a detector alarm time prediction model under three types of interference conditions, where the wind speed, water vapor, and burning incense interference conditions conform to third-order polynomial functions, Sigmoid functions, and fourth-order polynomial functions, respectively. Full article

Extreme precipitation events severely impact agriculture, reducing yields and land use efficiency. The spatiotemporal distribution of Total Column Water Vapor (TCWV), the primary gaseous form of water, directly influences sustainable agricultural management. This study, through multi-source data fusion, employs methods including the Mann–Kendall test, sliding change-point detection, wavelet transform, pixel-scale trend estimation, and linear regression to analyze the spatiotemporal dynamics of global TCWV from 1959 to 2023 and its impacts on agricultural systems, surpassing the limitations of single-method approaches. Results reveal a global TCWV increase of 0.0168 kg/m²/year from 1959–2023, with a pivotal shift in 2002 amplifying changes, notably in tropical regions (e.g., Amazon, Congo Basins, Southeast Asia) where cumulative increases exceeded 2 kg/m² since 2000, while mid-to-high latitudes remained stable and polar regions showed minimal content. These dynamics escalate weather risks, impacting sustainable agricultural management with irrigation and crop adaptation. To enhance prediction accuracy, we propose a novel hybrid model combining wavelet transform with LSTM, TCN, and GRU deep learning models, substantially improving multidimensional feature extraction and nonstationary trend capture. Comparative analysis shows that WT-TCN performs the best (MAE = 0.170, R² = 0.953), demonstrating its potential for addressing climate change uncertainties. These findings provide valuable applications for precision agriculture, sustainable water resource management, and disaster early warning. Full article

Efficient detection of toxic and flammable vapors remains a major technological challenge, especially for environmental and industrial applications. This paper reports on the fabrication technology and gas-sensing properties of nanostructured Ga₂O₃/GaS_0.98Se_0.02. The β-Ga₂O₃ nanowires/nanoribbons with inclusions of Ga₂S₃ and Ga₂Se₃ microcrystallites were obtained by thermal treatment of GaS_0.98Se_0.02 slabs in air enriched with water vapors. The microstructure, crystalline quality, and elemental composition of the obtained samples were investigated using electron microscopy, X-ray diffraction, and Raman spectroscopy. The obtained structures show promising results as active elements in gas sensor applications. Vapors of methanol (CH₃OH), ethanol (C₂H₅OH), and acetone (CH₃-CO-CH₃) were successfully detected using the nanostructured samples. The electrical signal for gas detection was enhanced under UV light irradiation. The saturation time of the sensor depends on the intensity of the UV radiation beam. Full article

Background/Objectives: A critical part of the maize life cycle takes place during the summer, and due to climate change, its growth and development are increasingly exposed to the irregular and unpredictable effects of drought stress. Developing and using new cultivars with increased drought tolerance for farmers is the easiest and cheapest solution. One of the concepts to screen for drought tolerance is to expose germplasm to various growth scenarios (environments), expecting that random drought will occur in some of them. Methods: In the present study, thirty-two maize hybrids belonging to four FAO maturity groups were tested for grain yield at six locations over two consecutive years. In parallel, data of the basic meteorological elements such as air temperature, relative humidity and precipitation were collected and used to compute two indices, scPDSI (Self-calibrating Palmer Drought Severity Index) and VPD (Vapor Pressure Deficit), that were assessed as indicators of drought (water deficit) severity during the vegetation period. Practical implementation of these indices was carried out indirectly by first analyzing yield data using a factor analytic model to detect latent environmental variables affecting yield and then correlating those latent variables with drought indices. Results: The first latent variable, which explained 47.97% of the total variability, was correlated with VPD (r = −0.58); the second latent variable explained 9.57% of the total variability and was correlated with scPDSI (r = −0.74). Furthermore, latent regression coefficients (i.e., genotypic sensitivities to latent environmental variables) were correlated with genotypic drought tolerance. Conclusions: This could be considered an indication that there were two different acting mechanisms in which drought affected yield. Full article

Ammonia (NH₃) detection in liquids and biological fluids is essential for monitoring environmental contamination and industrial processes, ensuring food safety, and diagnosing health conditions. Existing detection techniques are often unsuitable for point-of-care (POC) use due to limitations including complex sample handling, lack of portability, and poor compatibility with miniaturized systems. This study introduces a proof-of-concept for a compact, portable device tailored for POC detection of gaseous ammonia released from liquid samples. The device combines a polyaniline (PANI)-based chemoresistive sensor with interdigitated electrodes and a resistance readout circuit, enclosed in a gas-permeable hydrophobic membrane that permits ammonia in the vapor phase only to reach the sensing layer, ensuring selectivity and protection from liquid interference. The ink formulation was optimized. PANI nanoparticle suspension exhibited a monomodal, narrow particle size distribution with an average size of 120 nm and no evidence of larger aggregates. A key advancement of this device is its ability to limit the impact of water vapor, a known source of interference in PANI-based sensors, while maintaining a simple sensor design. A tailored signal processing strategy was implemented, extracting the slope of resistance variation over time as a robust metric for ammonia quantification. The sensor demonstrated reliable performance across a concentration range of 1.7 to 170 ppm with strong logarithmic correlation (R² = 0.99), and very good linear correlations in low (R² = 0.96) and high (R² = 0.97) subranges. These findings validate the feasibility of this POC platform for sensitive, selective, and practical ammonia detection in clinical and environmental applications. Full article

Thunderstorms downbursts can be hazardous during aircraft landing and take-off. A warming climate increases low- to mid-level troposphere water vapor, typically transported from high sea-surface temperature regions. Consequently, the future occurrence and intensity of destructive wind gusts from wet microburst thunderstorms are expected to increase. Wet microbursts are downdrafts from heavily precipitating thunderstorms and are several kilometers in diameter, often producing near-surface extreme wind gusts. Brisbane airport recorded a wet microburst wind gust of 157 km/h in November 2016. Numerous locations in eastern Australia experience warm season (October to March) wet microbursts. Here, eight machine learning techniques comprising forward and backward linear regression, radial basis forward and backward support vector regression, polynomial-based forward and backward support vector regression, and forward and backward random forest selection were employed. They identified primary attributes for increased atmospheric instability by warm moist air influx from regions of high sea-surface temperatures. The climate drivers detected here are indicative of increased future eastern Australian warm season thunderstorm downbursts, occurring as wet microbursts. They suggest a greater frequency and intensity of impacts on aircraft safety and operations affecting major east coast airports, such as Sydney and Brisbane, and smaller aircraft at inland regional airports in southeastern Australia. Full article

This work demonstrates an ultra-compact optical gas-sensing system, consisting of a pigtailed laser diode emitting at 1392.5 nm for water vapor (H₂O) detection, a silicon nitride (Si₃N₄) optical waveguide to guide the laser light, and a custom-designed, low-frequency, and T-shaped Quartz Tuning Fork (QTF) as the sensitive element. The system employs both Quartz-Enhanced Photoacoustic Spectroscopy (QEPAS) and Light-Induced Thermoelastic Spectroscopy (LITES) techniques for trace gas sensing. A 3.8 mm-wide, S-shaped waveguide path was designed to prevent scattered laser light from directly illuminating the QTF. Both QEPAS and LITES demonstrated comparably low signal-to-noise ratios (SNRs), ranging from 1.6 to 3.2 for a 1.6% indoor H₂O concentration, primarily owing to the reduced optical power (~300 μW) delivered to the QTF excitation point. These results demonstrate the feasibility of integrating photonic devices and piezoelectric components into portable gas-sensing systems for challenging environments. Full article

Multilayer clouds, comprising vertically stacked cloud layers with distinct microphysical characteristics, constitute a critical yet complex atmospheric phenomenon influencing regional to global climate patterns. Advances in observational techniques, particularly the application of high-resolution humidity vertical profiling via radiosondes, have significantly enhanced multilayer cloud detection capabilities. Multilayer clouds are widely distributed around the world, showing significant regional differences. Many studies have been carried out on the formation mechanism of multilayer clouds, and observational evidence indicates a close relationship between multilayer cloud development and water vapor supply, updraft, atmospheric circulation, as well as wind shear; however, a unified and comprehensive theoretical framework has not yet been constructed to fully explain the underlying mechanism. In addition, the unique vertical structure of multilayer clouds exhibits different climate effects when compared with single-layer clouds, affecting global climate patterns by regulating precipitation processes and radiative energy budgets. This article reviews the research progress related to multilayer cloud observations and their climate effects and looks forward to the research that needs to be carried out in the future. Full article

Proximal plant-based monitoring provides high-resolution data about trees, leading to more precise orchard management and in-depth knowledge about tree physiology. The present work focuses on continuous real-time monitoring of olive cv. ‘Ascolana tenera’ over hourly intervals during the third stage of fruit growth (mesocarp cell expansion) under mild water stress conditions (ψStem above −2 MPa). This is achieved by mounting dendrometers on the root, trunk, branch, and fruit to assess and model the behavior of each organ. The diameter variation in each organ over different time intervals (daily, two-weeks, and throughout the entire experiment), as well as their hysteretic patterns relative to each other and vapor pressure deficit, are demonstrated. The results show different correlations between various organs, ranging from very weak to strongly positive. However, the trend of fruit versus root consistently shows a strong positive relationship throughout the entire experiment (R² = 0.83) and a good one across various two-week intervals (R² ranging from 0.54 to 0.93). Additionally, different time lags in dehydration and rehydration between organs were observed, suggesting that the branch is the most reactive organ, regulating dehydration and rehydration in the tree. Regarding the hysteretic pattern, different rotational patterns and characteristics (shape) were observed among the organs and in relation to vapor pressure deficit. This research provides valuable insight into flow dynamics within a tree, models plant water relations and time lags in terms of water storage and transport, and could be implemented for precise olive tree water status detection. Full article