Search Results (131)

Microplastic pollution of ecosystems is considered a modern problem. Freshwater ecosystems, despite the interest shown in their study, remain poorly understood. Lake Baikal (Russia) is one of the least studied freshwater ecosystems in this regard. This large lake is distinguished from others by its high level of biodiversity and clean drinking water. The aim of this study is a multi-matrix investigation of microplastic pollution in one of the lake’s bay. The following matrices are used: surface water, water column, sediment, macrophytes, macroinvertebrates, and fish, as well as ice and snow during the winter. The results show that certain locations exhibit high concentrations of microplastic particles. In some cases, this was due to the properties or characteristics of these locations (littoral zones near the water’s edge, macrophytes with mucus sheaths, ice and snow (potentially, the near-surface water layer after ice melt)), while in others, it was due to localized pollution (pier and ship mooring areas). An analysis of the polymer types of the detected microplastic particles reveals the presence of both common (polypropylene, polyethylene terephthalate, polystyrene, polyethylene, polyvinyl chloride) and rare (polyvinyl alcohol and alkyd resin). Moreover, in some locations, the latter two polymers predominate, a phenomenon rarely observed in other studies. Further research was recommended to focus on the chronic effects of microplastic particles on organisms associated with areas of elevated particle concentrations. Full article

This study uniquely explores the impact of a novel natural antifreeze peptide derived from grass carp (GCAFP) on the freeze–thaw characteristics and structural stability of wet gluten protein, providing new insights into the development of natural cryoprotectants for frozen foods. The effects of GCAFP on the physicochemical and structural properties of gluten protein were investigated using differential scanning calorimetry (DSC), nuclear magnetic resonance imaging (NMR), rheology, and scanning electron microscopy (SEM). The results showed that the addition of 0.5% GCAFP significantly reduced the freezing temperature (T_f, from −8.50 ± 1.31 °C to −10.75 ± 2.49 °C) and expanded the melting temperature range (T_m,δ, from 3.60 ± 1.40 °C to 5.65 ± 0.12 °C), indicating improved freezing stability. After five weeks of frozen storage, the ice crystal melting enthalpy (ΔH_m) of gluten protein in the GCAFP group increased by only 20.17 J/g, compared with 27.23 J/g in the control, representing a 6.35% reduction (p < 0.05). Similarly, after five freeze–thaw cycles, the freezable water fraction (F_w) and ΔH_m were reduced by 5.19% and 1.55%, respectively, demonstrating that GCAFP inhibited water migration and ice recrystallization. Low-field NMR revealed that GCAFP maintained a higher proportion of bound water (T21) and decreased free water (T23), confirming its role in restricting water mobility. Rheological analysis showed that GCAFP preserved the viscoelasticity of gluten protein, maintaining higher storage (G′) and loss (G″) moduli than the control after five freeze–thaw cycles, thus mitigating the decline in network elasticity. Structural characterization indicated that GCAFP stabilized the α-helix and β-sheet contents, reduced glutenin macropolymer depolymerization from 24.85% to 18.95%, and strengthened hydrogen bonding within the protein matrix. Overall, GCAFP effectively protected wet gluten protein against ice crystal damage by maintaining water distribution, viscoelasticity, and secondary structure integrity, highlighting its potential as a natural antifreeze ingredient for frozen food applications. Full article

This study investigates the effects of laser and cryogenic (dry ice) surface treatments on enhancing surface characteristics of Ti-6Al-4V titanium alloy components produced using the Selective Laser Melting (SLM) technique. Components produced via additive manufacturing often exhibit increased surface irregularities and residual unmelted powder, which can deteriorate their mechanical strength and resistance to corrosion. In this study, SLM samples manufactured with two laser powers (176 W and 220 W) were subjected to laser cleaning and dry ice blasting under various process parameters. Surface topography and morphology analyses were performed. The obtained results showed that both methods improved surface uniformity and removed contaminants. Dry ice treatment effectively removed loose powder particles and impurities without causing structural changes—the best results were obtained at a pressure of 10 bar. Laser treatment, depending on the focal length, produced varying degrees of surface remelting—from gentle smoothing (500 mm) to intensive thermal effects and microcracks (250 mm). The research confirmed that cryogenic cleaning is an environmentally friendly and safe post-processing method, while laser cleaning enables deeper surface structure modification, requiring further optimization. Full article

Runoff simulation and forecasting is of great significance for flood control, disaster mitigation, and water resource management. Alpine regions are characterized by complex terrain, diverse precipitation patterns, and strong snow-and-ice melt influences, making accurate runoff simulation particularly challenging yet crucial. To enhance predictive capability and model applicability, this study takes the Upper Jinsha River as a case study and comparatively evaluates the performance of a physics-based hydrological model BTOP and the data-driven deep learning models LSTM and BiLSTM in runoff simulation and short-term forecasting. The results indicate that for daily-scale runoff simulation, the LSTM and BiLSTM models demonstrated superior simulation capabilities, achieving Nash–Sutcliffe efficiency coefficients (NSE) of 0.82/0.81 (Zhimenda Station) and 0.87/0.86 (Gangtuo Station) during the test period. These values are significantly better than those of the BTOP model, which achieved a validation NSE of 0.57 at Zhimenda and 0.62 at Gangtuo. However, the hydrology-based structure of the BTOP model endowed it with greater stability in water balance and long-term simulation. In short-term forecasting (1–7 d), LSTM and BiLSTM performed comparably, with the bidirectional architecture of BiLSTM offering no significant advantage. When it came to flood events, the data-driven models excelled at capturing peak timing and hydrograph shape, whereas the physical BTOP model demonstrated superior stability in flood peak magnitude. However, forecasts from the data-driven models also lacked hydrological consistency between upstream and downstream stations. In conclusion, the present study confirms that deep learning models achieve superior accuracy in runoff simulation compared to the physics-based BTOP model and effectively capture key flood characteristics, establishing their value as a powerful tool for hydrological applications in alpine regions. Full article

De-icing agents play a crucial role in winter road maintenance, yet their excessive application can result in pavement deterioration and environmental issues. Existing dosage guidelines lack comprehensive data on the dynamic response of de-icing agents under low-temperature conditions, particularly regarding stage-specific characteristics and multi-factor interactions. This research systematically evaluated the effectiveness of four de-icing agents (NaCl, CaCl₂, MgCl₂, CH₃COOK) within a temperature range of −5 °C to −25 °C, elucidating the two-phase ice-melting process (solid-phase followed by salt solution de-icing) with distinct kinetic mechanisms—a previously underexplored temporal pattern. The study quantified the differential impacts of particle size (small-particle CaCl₂ exhibiting 12% higher efficiency than sheet-like forms), dosage linear correlation, and negligible effects of ice layer thickness and road surface composition, which have not been systematically validated in prior studies. Temperature sensitivity was further refined: NaCl showed a 42.4% efficiency drop between −5 °C and −25 °C, while MgCl₂ maintained stable performance, supporting its potential as an environmentally sustainable alternative. This work provides a quantitative basis for dynamic dosage regulation by integrating stage characteristics and multi-factor optimization, addressing gaps in existing guidelines. Full article

A comprehensive understanding of the evolution and phase transitions of hydrometeors during the development of tropical cyclones (TCs) is essential for advancing research on the mechanisms of TC intensity change. In this study, utilizing the Weather Research and Forecasting numerical model, we simulate the evolution of Super Typhoon Nangka (No. 1511), explore the relationship between the TC intensity variations and the internal hydrometeor distribution, and examine the secondary circulation characteristics. The results indicate that the total content of hydrometeor particles increased during the intensification of Typhoon Nangka. Ice-phase particles expanded outward radially as the typhoon intensified, while liquid-phase particles contracted inward. Ice-phase hydrometeor distributions varied in conjunction with TC intensity variations, whereas liquid-phase hydrometeor variations were closely related to the complex dynamic–thermodynamic–microphysical processes within the typhoon. The spatial pattern of the secondary circulation exhibits high consistency with the distribution of hydrometeor particles. Low-level radial inflow, upper-level radial outflow, and middle-level vertical updrafts played dominant roles in regulating the distribution and transport of particles at different stages. The intensification of Typhoon Nangka was primarily driven by water vapor convergence and the latent heat released by ascending liquid-phase particles near the eyewall, while the stagnation of its intensification was mainly attributed to the resistance exerted by descending ice-phase particles from upper levels and the heat consumption associated with their melting. These findings provide a foundation for better understanding how hydrometeors modulate TC intensity variations and offer valuable insights into energy conversion mechanisms during hydrometeor phase transitions under the influence of secondary circulations. Full article

Ice cream is a frozen aerated dessert composed of milk solids, sugars, stabilizers, and fat—with the latter being a key component in defining its structural and sensory properties. This study evaluated the influence of four fat sources—low-trans vegetable fat (T1), butter (T2), UHT cream (T3), and fresh cream (T4)—on the physical and structural characteristics of ice cream, including overrun, melting resistance, texture, color, and rheology, at different stages of processing (before and after maturation). Oscillatory rheological analysis revealed predominantly elastic behavior (G′ > G″) after maturation in all samples, indicating a stable viscoelastic solid structure. Formulations containing T3 and T1 showed the highest overrun values, indicating greater air incorporation, whereas the butter-based formulation (T2) showed the lowest overrun values. Melting resistance followed the following order: T3 > T4 > T2 > T1; therein, the UHT cream formulation exhibited the greatest thermal stability, which was likely due to protein denaturation and aggregation induced by high-temperature processing. Texture analysis showed that the T1 formulation required the lowest maximum extrusion force, while T2 required the highest, reflecting an inverse correlation with overrun values. T1 also displayed the most distinct rheological profile, which was likely due to its specific crystallization behavior and reduced destabilization of the fat globule membrane—which favored the development of a more structured internal network. These findings demonstrate that both the source and processing of fat have a significant impact on the formation of the structural matrix and the final functional properties of ice cream. The results offer technical insights for the development of formulations tailored to specific physical characteristics, optimizing texture, stability, and performance throughout the production process. Full article

Mountain glaciers are the most direct and sensitive indicators of climate change. In the context of global warming, monitoring changes in glacier elevation has become a crucial issue in modern cryosphere research. The Global Ecosystem Dynamics Investigation (GEDI) is a full-waveform laser altimeter with a multi-beam that provides unprecedented measurements of the Earth’s surface. Many studies have investigated its applications in assessing the vertical structure of various forests. However, few studies have assessed GEDI’s performance in detecting variations in glacier elevation in land ice in high-mountain Asia. To address this limitation, we selected the Southeastern Tibetan Plateau (SETP), one of the most sensitive areas to climate change, as a test area to assess the feasibility of using GEDI to monitor glacier elevation changes by comparing it with ICESat-2 ATL06 and the reference TanDEM-X DEM products. Moreover, this study further analyzes the influence of environmental factors (e.g., terrain slope and aspect, and altitude distribution) and glacier attributes (e.g., glacier area and debris cover) on changes in glacier elevation. The results show the following: (1) Compared to ICESat-2, in most cases, GEDI overestimated glacier thinning (i.e., elevation reduction) to some extent from 2019 to 2021, with an average overestimation value of about −0.29 m, while the annual average rate of elevation change was relatively close, at −0.70 ± 0.12 m/yr versus −0.62 ± 0.08 m/yr, respectively. (2) In terms of time, GEDI reflected glacier elevation changes at interannual and seasonal scales, and the trend of change was consistent with that found with ICESat-2. The results indicate that glacier accumulation mainly occurred in spring and winter, while the melting rate accelerated in summer and autumn. (3) GEDI effectively monitored and revealed the characteristics and patterns of glacier elevation changes with different terrain features, glacier area grades, etc.; however, as the slope increased, the accuracy of the reported changes in glacier elevation gradually decreased. Nonetheless, GEDI still provided reasonable estimates for changes in mountain glacier elevation. (4) The spatial distribution of GEDI footprints was uneven, directly affecting the accuracy of the monitoring results. Thus, to improve analyses of changes in glacier elevation, terrain factors should be comprehensively considered in further research. Overall, these promising results have the potential to be used as a basic dataset for further investigations of glacier mass and global climate change research. Full article

The increasing global interest in fish consumption leads to a greater generation of fish waste. Fish waste, rich in nutrients such as protein, bioactive compounds, and vitamins, is attracting growing attention for its potential applications in food. In this study, gelatin hydrolysate obtained from fish skin waste was utilized as a stabilizer and/or emulsifier in ice cream production. It was found that gelatin hydrolysate significantly increased the protein content of the ice cream samples. The K and n values in different ice cream compositions varied between 0.009 and 1.012 Pa.sⁿ and 0.356 and 0.863, respectively. The consistency coefficients of samples D1 (sahlep and mono-diglyceride) and D3 (sahlep and gelatin hydrolysate) were almost the same, indicating that the mono-diglyceride was replaced by an equivalent amount of gelatin hydrolysate. All the ice cream mixtures tested showed non-Newtonian, pseudoplastic flow, as indicated by their n values being less than 1. All mixtures demonstrated greater elasticity than viscosity, as their storage modulus (G′) was higher than their loss modulus (G″). In the third interval of 3-ITT, all ice cream mixtures displayed thixotropic behavior, indicating that their viscoelastic properties could be restored after a sudden deformation. The overrun levels of the samples ranged from 9.55% to 21.74%; the use of gelatin hydrolysate resulted in a statistically significant increase (p < 0.05). The highest hardness and stickiness values in the samples were determined in the specific sample containing equal amounts of emulsifier, stabilizer, and gelatin hydrolysate. Furthermore, gelatin hydrolysate prolonged the first dripping time and melting rate of the samples. Full article

This study examines a Mei-Yu rainfall event using rain gauges (RG) and OTT Parsivel disdrometers to observe precipitation characteristics and raindrop size distributions (RSD), with comparisons made against Weather Research and Forecasting (WRF) model simulations. Results show that Parsivel-derived rain rates (RR) are slightly underestimated relative to RG measurements. Both observations and simulations identify 1–3 mm raindrops as the dominant precipitation contributors, though the model overestimates small and large drop contributions. At low RR, decreased small-drop and increased large-drop concentrations cause corresponding leftward and rightward RSD shifts with decreasing altitude—a pattern well captured by simulations. However, at elevated rainfall rates, the simulated concentration of large raindrops shows no significant increase, resulting in negligible rightward shifting of RSD in the model outputs. Autoconversion from cloud droplets to raindrops (ATcr), collision and breakup between raindrops (AGrr), ice melting (MLir), and evaporation of raindrops (VDrv) contribute more to the number density of raindrops. At 0.1 < RR < 1 mm·h⁻¹, ATcr dominates, while VDrv peaks in this intensity range before decreasing. At higher intensities (RR > 20 mm·h⁻¹), AGrr contributes most, followed by MLir. When the RR is high enough, the breakup of raindrops plays a more important role than collision, leading to a decrease in the number density of raindrops. The overestimation of raindrop breakup from the numerical parameterization may be one of the reasons why the RSD does not shift significantly to the right toward the surface under the heavy RR grade. The RSD near the surface varies with the RR and characterizes surface precipitation well. Toward the surface, ATcr and VDrv, but not AGrr, become similar when precipitation approaches. Full article

Based on a laboratorial analysis of nitrous oxide (N₂O) concentrations collected in gas bottles (glass flask) at the Zhongshan Station on the East Antarctic coast from 2008 to 2021, the variation characteristics and trends in the background concentration of N₂O at the station were analyzed and compared with the N₂O data from other Antarctic stations. The results showed that the annual average concentration of atmospheric N₂O along the East Antarctic coast increased from 320.40 ppb in 2008 to 333.31 ppb in 2021, with an overall increasing trend of 0.99 ppb per year. Pronounced seasonal variability was observed, with elevated concentrations occurring during austral spring–summer and reduced levels in autumn–winter, consistent with the seasonal patterns documented at other Antarctic sites. The overall variation trend of the N₂O concentration at Zhongshan Station is basically consistent with the observation results at other stations in Antarctica, suggesting that the station’s background N₂O measurements are representative of continental-scale atmospheric composition dynamics. Combined with the analysis of air mass tracks, this seasonal variation in N₂O is mainly related to the mass movement of air mass and, to a certain extent, is influenced by the seasonal melting of sea ice and the exchange between the troposphere and stratosphere. The results supplement important basic data on N₂O concentrations along the East Antarctic coast and have potential reference significance for further understanding the causes of atmospheric N₂O variations in the Antarctic region. Full article

Mathematical models and methods serve as fundamental tools for studying ice-related phenomena in the Yellow River. River ice is driven and constrained by hydrometeorological and geographical conditions, creating a complex system. Regarding the Yellow River, there are some uncertainties that manifest in unique features in this context, including ice–water–sediment mixed transport processes and the distribution of sediment both within the ice and on its surface. These distinctive characteristics are considered to different degrees across different scales. Mathematical models for Yellow River ice developed over the past few decades not only encompass models for the large-scale deterministic evolution of river ice formation and melting, but also uncertainty parameter schemes for deterministic mathematical models reflecting the Yellow River’s particular ice-related characteristics. Moreover, there are modern mathematical results quantitatively describing these characteristics with uncertainty, allowing for a better understanding of the unique ice phenomena in the Yellow River. This review summarizes (a) universal equations established according to thermodynamic and hydrodynamic principles in river ice mathematical models, as well as (b) uncertainty sources caused by the river’s characteristics, ice properties, and hydrometeorological conditions, embedded in parametric schemes reflecting the Yellow River’s ice. The intractable uncertainty-related problems in space–sky–ground telemetric image segmentation and the current status of mathematical processing methods are reviewed. In particular, the current status and difficulties faced by various mathematical models in terms of predicting the freeze-up and break-up times, the formation of ice jams and dams, and the early warning of ice disasters are presented. This review discusses the prospects related to the uncertainties in research results regarding the simulation and prediction of Yellow River ice while also exploring potential future trends in research related to mathematical methods for uncertain problems. Full article

To further investigate the heat transfer characteristics of electric heating snow-melting pavement, this study developed two finite element models of such systems and conducted small-scale field experiments. An analysis was performed on the snow-melting pavement systems’ temperature field, temperature change rate, and gradient distribution during summer and winter, with entransy dissipation introduced to further analyze the heat transfer characteristics of asphalt snow-melting pavement. The results indicate that during system shutdown in summer and winter, the pavement structure exhibits reduced heat transfer capacity, leading to progressive decreases in the temperature variation rate and gradient with depth. The primary heat transfer loss occurs in the asphalt layer, with entransy dissipation predominantly concentrated during summer daylight and winter nighttime. During winter operation, the cable heat source modifies the temperature field distribution and gradient, which alters entransy dissipation. Installing an insulation layer improves snow-melting efficiency, and operating the system from 00:00 to 05:00 effectively prevents pavement icing. Full article

Precipitation events have been occurring more frequently in the hyper-arid region of the Taklamakan Desert (TD) under recent climate change. However, in this water-limited environment, the microphysical characteristics of precipitation, as well as their link to rainfall intensity, remain unclear. To address this, this study utilizes dual-frequency precipitation radar (DPR) data of the Global Precipitation Measurement (GPM) satellite from 2014 to 2023 to analyze the microphysical characteristics of different precipitation types (stratiform and convective) in the TD during the summer. The results show that liquid water path (LWP) is a key factor influencing precipitation type: when LWP is insufficient, stratiform precipitation is more likely to occur (84.1%), while convective precipitation is difficult to occur (15.9%). Microphysical process analysis indicates that in convective precipitation, abundant low-level moisture leads to the growth of liquid particles primarily through the collision–coalescence process (59.7%), resulting in larger raindrop diameters (1.7 mm) and lower concentrations (31.9 mm⁻¹ m⁻³). In contrast, stratiform precipitation, with limited LWP, primarily involves the melting and breaking-up of high-level ice-phase particles, leading to smaller raindrop diameters (1.2 mm) and higher concentrations (34.3 mm⁻¹ m⁻³). The warm rain process plays a significant role in raindrop formation in both types of precipitation. The greater (lesser) the amount of LWP, the larger (smaller) the contribution of collision–coalescence (break-up) processes, and the larger (smaller) the raindrop diameter and precipitation intensity. Full article

The sampling and observation of subglacial lakes play a vital role in studying the physical and chemical properties as well as the microbial characteristics of water within these Antarctic subglacial lakes. Compared to existing techniques, such as deep ice core drilling and clean hot water drilling, recoverable autonomous sondes, inspired by the spinning and reeling silk behavior of spiders, offer several advantages, including lightweight design, low power consumption, and minimal external pollution. Over the past six years, Jilin University, with support from the Ministry of Science and Technology of China, has developed an environmentally friendly sampling and observation system for Antarctic subglacial lakes, utilizing a recoverable autonomous sonde. The whole system includes a melting sonde, detection and control unit, scientific load platform, and ice surface auxiliaries. Extensive laboratory and joint system tests were conducted, both on key components and the complete system, including field tests in ice lakes. The results of these tests validated the feasibility of the underlying principles, the long-term reliability of the system operation, and the cleanliness of the drilling process. Ice penetration speed up to 2.14 m/h was reached with 6~6.5 kW melting tip power and a 660 mL lake water sample was collected. The relevant design concepts and technologies of the system are expected to play an important role in the clean detection and sampling of subglacial lakes in Antarctica, Greenland, and other regions. Full article