Search Results (1,414)

The vacuum drying of cellulose-based insulation is an essential step in the transformer manufacturing process, typically consisting of both heat and vacuum application. The moisture inside cellulose insulation during this process is transferred by various transport mechanisms, some of which are affected by the insulation’s temperature. Moreover, the conditions within the vacuum chamber are generally transient and highly dynamic, depending on the employed process control strategy, and may include various phenomena, such as gas expansion during pump-down and radiative heat transfer. From a modelling perspective, these factors can significantly impact the drying rate by altering the boundary conditions of heat and mass transport equations. To account for such effects, a model that considers the process at both the scale of cellulose insulation and the scale of the vacuum chamber is presented. A simplified drying system with two-point process control is introduced to simulate multiple cases. The results highlight the sensitivity of drying behaviour to both the model parameters and the selected control strategy. A comparison with existing Fickian diffusion models indicates that the proposed model, when properly calibrated, can reliably reproduce drying dynamics and thus provide a powerful tool for optimizing vacuum drying procedures. Full article

The APSIM (Agricultural Production Systems Simulator)-Wheat model has been widely used to simulate wheat growth, but the sensitivity characteristics of the model parameters at different soil moisture levels in arid regions are unknown. Based on 2023~2025 winter wheat field data from the Changji Experimental Site, Xinjiang, China, this study conducted a global sensitivity analysis of the APSIM-Wheat model using Morris and EFAST methods. Twenty-one selected parameters were perturbed at ±50% of their baseline values to quantify the sensitivity of the aboveground total dry matter (WAGT) and yield to parameter variations. Parameters exhibiting significant effects on yield were identified. The calibrated APSIM model performance was evaluated against field observations. The results indicated that the order of influential parameters varied slightly across different soil moisture levels. However, the WAGT output was notably sensitive to accumulated temperature from seedling to jointing stage (T1), accumulated temperature from the jointing to the flowering period (T2), accumulated temperature from grain filling to maturity (T4), and crop water demand (E1). Meanwhile, yield output showed greater sensitivity to number of grains per stem (G1), accumulated temperature from flowering to grain filling (T3), potential daily grain filling rate during the grain filling period (P1), extinction coefficient (K), T1, T2, T4, and E1. The sensitivity indices of different soil moisture levels under Morris and EFAST methods showed highly significant consistency. After optimization, the coefficient of determination (R²) was 0.877~0.974, the index of agreement (d-index) was 0.941~0.995, the root mean square error (RMSE) was 319.45~642.69 kg·ha^–1, the mean absolute error (MAE) was 314.69~473.21 kg·ha^–1, the residual standard deviation ratio (RSR) was 0.68~0.93, and the Nash–Sutcliffe efficiency (NSE) was 0.26~0.57, thereby enhancing the performance of the model. This study highlights the need for more careful calibration of these influential parameters to reduce the uncertainty associated with the model. Full article

Desert steppe ecosystems, characterized by water limitation and high sensitivity to global climate change and anthropogenic disturbance drivers, experience profound alterations in carbon (C) cycling processes driven by the multiplicative interactions among grassland grazing, altered precipitation regimes, and elevated atmospheric nitrogen deposition. However, how historical grazing legacies modulate ecosystem responses to concurrent changes in nitrogen deposition and precipitation regimes remains poorly resolved. To address this, we conducted a field experiment manipulating water and nitrogen addition across grazing intensities (no grazing, light grazing, moderate grazing, heavy grazing) in a Stipa breviflora desert steppe. Over three consecutive growing seasons (2015–2017), we continuously monitored net ecosystem CO₂ exchange (NEE), ecosystem respiration (ER), and gross ecosystem production (GEP) to quantify ecosystem CO₂ fluxes under these interacting global change drivers. Results revealed that water and nitrogen addition did not alter seasonal CO₂ flux dynamics across grazing intensities. Light grazing enhanced ecosystem C sink capacity, whereas heavy grazing reduced NEE and GEP, diminishing C sink strength. Water addition significantly increased CO₂ fluxes, strongly correlated with soil moisture. Nitrogen addition exerted a weak C source effect in a water-deficient year but enhanced the C sink in a water-rich year. Nitrogen plus water addition significantly boosted C sink potential, though this effect diminished along the grazing pressure gradient. Our findings demonstrate that the impacts of climate change on soil C fluxes in desert steppes are mediated by historical grazing intensity. Future manipulative experiments should explicitly incorporate grazing legacy effects, and integrate this factor into C models to generate reliable predictions of grassland C dynamics under global change scenarios. Full article

Methane (CH₄) emissions from the wetlands of the Tibetan Plateau (TP) remain poorly quantified, particularly regarding their historical dynamics, spatial heterogeneity, and response to climate change. This study provides the high-resolution, observation-driven reconstruction of TP wetland CH₄ emissions over the past four decades, integrating a machine learning model with 108 flux measurements from 67 sites. This unique combination of field-based data and fine-scale mapping enables unprecedented accuracy in quantifying both emission intensity and long-term trends. We show that current TP wetlands emit 5.87 ± 1.43 g CH₄ m⁻² yr⁻¹, totaling 97.3 Gg CH₄ yr⁻¹, equivalent to 7.8% of East Asia’s annual wetland emissions. Despite a climate-driven increase in per-unit-area CH₄ fluxes, a 19.8% (8432.9 km²) loss of wetland area since the 1980s has reduced total emissions by 15%, counteracting the enhancement from warming and moisture increases. Our comparative analysis demonstrates that existing land surface models (LSMs) substantially underestimate TP wetland CH₄ emissions, largely due to the inadequate representation of TP wetlands and their dynamics. Projections under future climate scenarios indicate a potential 8.5–21.2% increase in emissions by 2100, underscoring the importance of integrating high-quality, region-specific observational datasets into Earth system models. By bridging the gap between field observations and large-scale modeling, this work advances understanding of alpine wetland–climate feedback, and provides a robust foundation for improving regional carbon budget assessments in one of the most climate-sensitive regions on Earth. Full article

This study investigated the impact of spray-drying conditions, specifically inlet air temperature (Tin: 131–159 °C) and feed rate (FR: 4.9–8.4 g/min), on the microencapsulation of oil in a double-layer emulsion stabilised with orange residue flour (ORF) and soy protein. Powders were analysed separately from the drying chamber and the collector, focusing on yield, encapsulation efficiency, moisture, water activity (aw), oil oxidation, colour, and particle size. Chamber powders were more sensitive to Tin, where higher temperatures (155–159 °C) improved yield (up to 47% dry matter (dm)) but also increased oxidation (up to 134% above initial oil). Excessively high FR (8.4 g/min) reduced yield and raised aw (up to 0.39). Collector powders showed more stable yields (average 30 ± 2% dm) but lower encapsulation efficiency (80–86% for chamber vs. 70–77% for collector). Response surface methodology satisfactorily modelled key parameters (R² up to 0.9). Optimisation showed that chamber performance was maximised at 146 °C and 4.9 g/min (predicted yield and aw of 41% and 0.25, respectively), while collector quality improved with slightly higher Tin (150 °C, predicted aw of 0.32). Separately analysing chamber and collector fractions provided novel insights into spray-drying dynamics. These findings highlight ORF as a promising wall material. Full article

Forests play a vital role in the global carbon cycle; however, the carbon sink capacity of African forests is increasingly threatened by wildfires, rising temperatures, and ecological degradation. This study analyzes the spatiotemporal dynamics of forest carbon fluxes across Africa from 2001 to 2023, based on multi-source remote sensing and climate datasets. The results show that wildfires have significantly disrupted Africa’s carbon balance over the past two decades. From 2001 to 2023, fire activity was most intense in the woodland–savanna transition zones of Central and Southern Africa. In countries such as the Democratic Republic of the Congo, Angola, Mozambique, and Zambia, each recorded burned areas exceeding 500,000 km², along with high recurrence rates (e.g., up to 0.7584 fires per year in South Sudan). These fire-affected regions often exhibited high ecological sensitivity and carbon density, which led to pronounced disturbances in carbon fluxes. Nevertheless, the Democratic Republic of the Congo maintained an average annual net carbon sink of 74.2 MtC, indicating a high potential for ecological recovery. In contrast, Liberia and Eswatini exhibited net carbon emissions in fire-affected areas, suggesting weaker ecosystem resilience. These findings underscore the urgent need to incorporate wildfire disturbances into forest carbon management and climate mitigation strategies. In addition, climate variables such as temperature and soil moisture also influence carbon fluxes, although their effects display substantial spatial heterogeneity. On average, a 1 °C increase in temperature leads to an additional 0.347 (±1.243) Mt CO₂ in emissions, while a 1% increase in soil moisture enhances CO₂ removal by 1.417 (±8.789) Mt. However, compared to wildfires, the impacts of these climate drivers are slower and more spatially variable. Full article

Temperate grasslands are highly sensitive to climate change and play a crucial role in terrestrial carbon cycling. In the context of global warming, heterotrophic respiration (Rh) has intensified, contributing significantly to atmospheric CO₂ emissions. However, seasonal patterns of Rh, particularly differences between the growing season (GS) and non-growing season (non-GS), remain poorly quantified. This study used daily eddy covariance data from multiple flux towers combined with MODIS GPP and NPP products to estimate Rh across temperate grasslands from 2002 to 2021. We examined interannual variations in GS and non-GS Rh contributions and assessed their relationships with key hydrothermal variables. The results showed that mean Rh during GS and non-GS was 527 ± 357 and 341 ± 180 g C m⁻² yr⁻¹, respectively, accounting for 57.8 ± 14.6% and 42.2 ± 14.6% of the annual Rh. Moreover, GS Rh exhibited a declining trend, while non-GS Rh increased over time, indicating a gradual convergence in their seasonal contributions. This pattern was primarily driven by increasing drought stress in GS and warmer, moderately moist conditions in non-GS that favored microbial activity. Our findings underscore the necessity of distinguishing seasonal Rh dynamics when investigating global carbon cycle dynamics. Future earth system models should place greater emphasis on seasonal differences in soil respiration processes by explicitly incorporating the influence of soil moisture on the decomposition rate of soil organic carbon, in order to improve the accuracy of carbon release risk assessments under global change scenarios. Full article

The rapid and accurate assessment of regional soil salinity is crucial for effective salinization management. This study proposes an enhanced remote sensing inversion method by integrating both driving and response environmental variables to address lag effects and incomplete factor consideration in existing models. The Yellow River Delta, a coastal saline–alkaline region, was selected as the study area, where soil salinity-sensitive spectral parameters were derived from Sentinel-2 MSI imagery. Six environmental variables, including precipitation, distance from the sea, and soil moisture, were analyzed. Four scenarios were constructed: (1) using only spectral parameters; (2) spectral parameters with driving variables; (3) spectral parameters with response variables; and (4) combining both types. Four modeling methods were employed to assess inversion accuracy. The results show that incorporating either driving or response variables improved accuracy, with validation R² increasing by up to 0.149 and RMSE decreasing by up to 0.097 when both were used. The suitable model, integrating soil moisture, distance from the sea, and chlorophyll content, achieved a calibration R² of 0.813 and validation R² of 0.722. These findings demonstrate that combining both driving and response variables enhances model performance and provides valuable insights for soil salinization management. Full article

Drought is a critical factor influencing the distribution of forest species in both present and future global terrestrial ecosystems. Therefore, to investigate the sensitivity of typical afforestation tree species on the Loess Plateau to drought and its influencing factors, we conducted field experiments to measure the sap flow, soil moisture content, fine root density, leaf water potential, and xylem hydraulic characteristics of three deciduous trees: apple (Malus domestica), black locust (Robinia pseudoacacia), and jujube (Ziziphus jujube). We found that the canopy conductance (Gc) of black locust and apple trees was highly sensitive to VPD variations. Their transpiration (T) was also sensitive to soil moisture variation, especially for black locust. In contrast, the Gc and T sensitivity of jujube trees was low. The differences in their drought sensitivities can primarily be attributed to variations in xylem hydraulic conductivity and embolism vulnerability. Our results demonstrate that both mature black locust and apple trees on the Loess Plateau have strong drought sensitivity, especially black locust. Therefore, alterations in precipitation patterns driven by climate change may significantly influence the community distribution of black locusts trees on the Loess Plateau. Full article

Amphibians are particularly vulnerable to hydric stress due to their permeable skin, biphasic life cycle, and strong dependence on aquatic and moist terrestrial environments. In the Northwestern Mediterranean Basin—one of Europe’s most climate-sensitive regions—the intensification of droughts associated with climate change poses a critical threat to amphibian populations. Increased aridification, either due to higher temperatures or to more frequent, prolonged, and severe drought episodes, can affect both aquatic and terrestrial life stages, directly altering breeding opportunities, larval development, post-metamorphic survival, and dispersal capacity. This review aims to gather and synthesize current knowledge on the ecological, physiological, and demographic impacts of drought on amphibians of the Northwestern Mediterranean across habitat types, including ephemeral ponds, permanent water bodies, lotic systems, and terrestrial landscapes, including a final section on possible mitigation actions. Drought-induced shifts in hydroperiod can drastically reduce reproductive success and accelerate larval development with fitness consequences while, on land, desiccation risk and habitat degradation could limit access to refugia and fragment populations by reducing structural connectivity. These environmental constraints are compounded by the interactions between drought and emerging infectious diseases. We discuss the current knowledge on how chytrid fungi (Batrachochytrium dendrobatidis and B. salamandrivorans) and ranaviruses may respond to temperature and moisture regimes, and how drought may affect their transmission dynamics, host susceptibility, and pathogen persistence. In these cases, microbiome disruption, pollutant concentration, and increased contact rates between species may amplify disease outbreaks under dry conditions, but a better understanding of the multifactorial effects of drought on amphibian biology and disease ecology is needed for predicting species vulnerability, identifying high-risk populations, and guiding future conservation and management strategies in Mediterranean environments. Full article

Driven by climate change and human activities, the expansion of highly invasive moso bamboo (Phyllostachys edulis) into coniferous forests induces a serious ecological imbalance. Its rapidly spreading underground roots significantly alter soil structure, yet the mechanisms by which this expansion affects soil detachment capacity (Dc), a key soil erosion parameter, remain unclear. While bamboo expansion modifies soil physicochemical properties and root characteristics, influencing Dc and, consequently, soil erosion resistance, the underlying mechanisms, particularly stage-specific variations, are not thoroughly understood. In this study, we examined Japanese white pine (Pinus parviflora Siebold & Zucc.) forest (CF), moso bamboo–Japanese white pine mixed forest (MF), and moso bamboo forest (BF) as representative stages of bamboo expansion. By integrating laboratory-controlled measurements of soil physicochemical properties and root traits with field-based flume experiments, we comprehensively investigate the effects of moso bamboo expansion into CF on soil detachment capacity. The results of the study can be summarized as follows: (1) Expansion of moso bamboo significantly changed soil physicochemical properties and root characteristics. Soil bulk density was the highest in the MF (1.13 g·cm⁻³), followed by the CF (1.08 g·cm⁻³) and BF (1.03 g·cm⁻³); non-capillary porosity increased significantly with expansion (CF 0.03% to MF 0.10%); and although the stability of aggregates (MWD) increased by 24.5% from the CF to MF, root mass density (RMD) in the MF (0.0048 g·cm⁻³) was much higher than that in the CF (0.0009 g·cm⁻³). This intense root competition between forest types, combined with increased macroporosity development, compromised overall soil structural integrity. This weakening may lead to a looser soil structure during the transition phase, thereby increasing erosion risk. (2) There were significant stage differences in Dc: it was significantly higher in the MF (0.034 kg·m⁻²·s⁻¹) than in the CF (0.023 kg·m⁻²·s⁻¹) and BF (0.018 kg·m⁻²·s⁻¹), which revealed that the MF was an erosion-sensitive stage. (3) Our Partial Least Squares Structural Equation Modeling (PLS-SEM) results revealed that soil physicochemical properties (soil moisture content and soil total nitrogen) dominated Dc changes through direct effects (total effect −0.547); in comparison, root properties indirectly affected Dc by modulating soil structure (indirect effect: −0.339). The results of this study reveal the dynamics and mechanisms of Dc changes during bamboo expansion, and for the first time, we identify a distinct Dc peak during the mixed forest transition phase. These findings provide a scientific basis for moso bamboo forest management, soil erosion risk assessment, and optimization of soil and water conservation strategies. Full article

Accurate detection of water in organic solvents is essential for various industrial and analytical applications. In this study, we present a simple, rapid, and sensitive fluorescence-based method for water quantification using 1,5-diaminonaphthalene (1,5-DAN) as a solvatochromic probe. This method exploits the excited-state intramolecular charge transfer (ICT) behavior of 1,5-DAN, which undergoes a symmetry-breaking transition in the presence of protic solvents such as water, leading to a distinct redshift in its emission spectrum and a change from a structured double-band to a single ICT band. We demonstrate that, in solvents like acetonitrile and tetrahydrofuran, the emission maxima of 1,5-DAN correlate linearly with water content up to 100%, while ratiometric analysis of peak intensities allows for sensitive detection in low concentration ranges. This method achieved limits of detection as low as 0.08% (v/v) in MeCN, with high reproducibility and minimal sample preparation. Application to a real MeCN–water azeotrope confirms the method’s accuracy, matching classical refractometric measurements. Our findings highlight the potential of 1,5-DAN as a low-cost, efficient, and non-destructive fluorescent sensor for monitoring moisture in organic solvents, offering a practical alternative to conventional methods such as Karl Fischer titration for both bulk and trace water analysis. Full article

Global climate change has intensified the frequency and severity of drought events, posing significant threats to agricultural sustainability, particularly for water-sensitive crops such as tea. In northern China, where precipitation is unevenly distributed and evapotranspiration rates are high, tea plantations frequently experience water stress, leading to reduced yields and declining quality. Therefore, accurately simulating soil water content (SWC) is essential for drought forecasting, soil moisture management, and the development of precision irrigation strategies. However, due to the high complexity of soil–vegetation–atmosphere interactions in field conditions, the practical application of the HYDRUS-1D model in northern China remains relatively limited. To address this issue, a three-year continuous monitoring campaign (2021–2023) was conducted in a coastal area of northern China, covering both young tea plantations and adjacent grasslands. Based on the measured meteorological and soil data, the HYDRUS-1D model was used to simulate SWC dynamics across 10 soil layers (0–100 cm). The model was calibrated and validated against observed SWC data to evaluate its accuracy and applicability. The simulation results showed that the model performed reasonably well, achieving an R² of 0.739 for the tea plantation and 0.878 for the grassland, indicating good agreement with the measured values. These findings demonstrate the potential of physics-based modeling for understanding vertical soil water processes under different land cover types and provide a scientific basis for improving irrigation strategies and water use efficiency in tea-growing regions. Full article

This study presents a scenario-based assessment of the future sensitivity of minimal low-water runoff to climate change in Western Kazakhstan. An ensemble of global climate models from the Coupled Model Intercomparison Project Phase 6 (CMIP6), combined with dynamically downscaled projections for Central Asia, was applied to estimate minimal monthly runoff during the summer–autumn and winter low-water periods for the rivers of the Zhaiyk–Caspian water management basin. The analysis covers three future time horizons: 2040 (2031–2050), 2060 (2051–2070), and 2080 (2071–2090), under two greenhouse gas concentration scenarios: SSP3-7.0 (moderately high emissions) and SSP5-8.5 (high emissions). The results reveal a pronounced seasonal contrast in the projected hydrological response. During the winter low-water period, a steady increase in minimal runoff is projected for all rivers, with the most significant changes observed for the Or, Zhem, Temir, and Shagan rivers. This increase is primarily driven by higher winter precipitation, increased thaw frequency, and enhanced infiltration recharge. Conversely, despite modest increases in summer–autumn precipitation, minimal runoff during the summer–autumn low-water period is projected to decline significantly, particularly in the southern basins, due to elevated evapotranspiration rates and soil moisture deficits associated with rising air temperatures. These findings emphasize the importance of developing seasonally differentiated, climate-resilient water management strategies to mitigate low-flow risks and ensure water security under future climate conditions in arid and semi-arid regions. Full article

In the coal pillar dam of underground water reservoirs, groundwater exerts a certain degree of dissolution and erosion on the coal body, inducing the development of internal cracks and the deterioration of its mechanical properties. To this end, coal samples with varying moisture contents were prepared through a water-absorption experiment; the changes in the mechanical strength of coal samples with five moisture contents (0%, 3.62%, 4.93%, 5.52%, and 6.11%) were tested via uniaxial compression tests, uniaxial tension tests, and variable-angle shear tests; and the degradation in mechanical performance in water-immersed coal samples and their sensitivity to moisture content were evaluated. The experiment yielded the following results: (1) The moisture content of coal samples increases with the increase in immersion time, and the water-absorption rate first rises, then decelerates and gradually becomes stable. When the immersion time is about 72 h, the coal sample reaches a saturated state. (2) As the samples transition from a dried state to full saturation, the uniaxial compressive strength of coal samples decreases from 29.17 MPa to 7.38 MPa, and the uniaxial tensile strength decreases from 0.78 MPa to 0.33 MPa. The peak shear strength also decreases with an increase in immersion time and the increase in shear angle, while the deterioration degree gradually increases with the increase in immersion time and tends to be stable. (3) Based on a sensitivity analysis, the mechanical performance evolution of water-immersed coal samples can be divided into four stages based on the moisture content: tensile-dominated stage, shear-dominated stage, compression catching-up stage, and compression-dominated stage. Full article