Search Results (10,235)

In the cement-based stabilization of organic soil, the alkaline environment produced by cement hydration dissolves organic matter from the soil skeleton while simultaneously promoting the precipitation of neophases. This study investigates the coupled effects of structural deterioration and neophase compensation on the microstructural and mechanical properties of organic soil. Organic soil was treated with an alkaline Ca(OH)₂ solution (pH = 12.0) utilizing a model testing apparatus over an 80-day duration. Consolidation and permeability tests were combined with microstructural analyses (FTIR, XRD, and SEM-EDS) to elucidate the fundamental mechanisms. The results show that humus acid in organic soil was dissolved in an alkaline environment, significantly enlarging soil pores and forming interconnected dissolution channels. Consequently, the permeability coefficient and additional settlement increased by 49.21% and 18.07%, respectively, compared to the pristine soil samples. Concurrently, within the OH⁻-and Ca²⁺-rich environment, clay minerals underwent a pozzolanic reaction, generating C-(A)S-H gels. Dissolved humus acid formed complexes with Ca²⁺ ions. While these formed neophases provide microstructural compensation for the organic soil, their compensatory effect is limited. These findings provide a critical theoretical framework for understanding the coupled deterioration–compensation mechanisms, which is essential for optimizing engineering design and promoting the long-term durability of alkaline-reinforced organic geotechnical environments. Full article

This study systematically investigates the effects of solution temperature ranging from 1060 to 1150 °C on grain growth kinetics, microstructural evolution, and tensile properties of GH4698 superalloys. The results indicate that grain size coarsens parabolically with increasing solution temperature. Based on the Sellars model, the grain growth time exponent n is determined to be 3.4 and the activation energy Q is 478.7 kJ·mol⁻¹. This confirms that the grain growth process is significantly influenced by both MC carbide pinning and alloying element drag effects. Additionally, due to the coarsening of grains, the precipitation density of M₂₃C₆ carbides per unit grain boundary length increased from 0.26 μm⁻¹ to 0.39 μm⁻¹. The ultimate tensile strength at room temperature decreased from 1268 MPa to 1226 MPa, and the yield strength decreased from 840 MPa to 807 MPa, while the elongation remained at 28–32%. At 700 °C, the ultimate tensile strength decreases from 974 MPa to 904 MPa, and the yield strength decreases from 755 MPa to 696 MPa, with the elongation remaining at ~6%. Quantitative analysis reveals that the decrease in strength is primarily due to the weakening of grain boundary strengthening caused by grain coarsening. At 700 °C, the deformation mechanism transitions from dislocation shearing at room temperature to stacking fault shearing. This not only leads to a reduction in strength but also, accompanied by grain boundary weakening, results in a decrease in elongation. Full article

Understanding how medicinal plant distributions shift in response to climate change is essential for developing forward-looking conservation strategies. Cibotium barometz (L.) J. Sm., a tree fern from the family Dicksoniaceae, is not only ecologically significant but also holds considerable medicinal value. Despite its importance, wild populations of this species have been steadily declining due to ongoing habitat loss and unsustainable harvesting. To address this concern, we constructed a multi-model ensemble framework that integrated nine different algorithms, including Generalized Linear Models, various machine learning approaches, and a MaxEnt model optimized through ENMeval using a regularization multiplier of 2 and a feature class of LQH. Using this modeling framework, we simulated the habitat suitability dynamics of C. barometz under current climate conditions (1970–2000) and two future periods (2050s and 2090s) across four Shared Socioeconomic Pathways (SSP126, SSP245, SSP370, and SSP585). Our analysis identified water availability and low temperature stress as the primary factors limiting the species’ distribution. The suitable range for precipitation during the driest quarter extends from 3.25 to 640.20 mm, with optimal conditions occurring when precipitation reaches at least 96.84 mm. Annual precipitation suitable for the species lies between 74.58 and 4209.60 mm, and the most favorable range falls between 3834.10 and 4209.60 mm. While the minimum temperature of the coldest month can vary from −35.41 to 22.35 °C, optimal survival requires temperatures of 8.79 °C or higher. In addition, the species grows best within an annual temperature range of 16.25 to 27.92 °C, with an optimum around 20.47 °C. Projections based on the multi model ensemble suggest that future climate warming may lead to a southwestward shift in the centroid of suitable habitat for this species. By the 2090s, under the SSP245, SSP370, and SSP585 scenarios, the centroid shifts southwestward by 331.3 km, 335.1 km, and 180.2 km, respectively. Meanwhile, areas with high habitat suitability are expected to retreat toward mid-to-high elevation zones, especially in southeastern Yunnan, southern Guizhou, and western Guangxi. The effects of different emission pathways vary considerably; under the high-emission SSP585 scenario, the reduction in total suitable area is projected to be more severe and habitat fragmentation more extensive compared to the low-emission SSP126 pathway. In contrast, implementing ambitious emissions reduction measures could play a key role in supporting the long-term stability of C. barometz populations. This study clarifies how this species responds to climate change and the spatial strategies it may adopt, providing a scientific basis and spatial references for conserving its germplasm resources, restoring its habitats, and advancing its sustainable use. Full article

Rising human-caused nitrogen (N) deposition and increased rainfall variability threaten the capacity of temperate forests to sequester carbon. However, the combined effects of N enrichment and moisture changes on total soil respiration (Rs), including its autotrophic (Ra) and heterotrophic (Rh) components, remain poorly understood, especially in northern China’s warm-temperate forests. To explore this, a factorial field experiment was conducted at the Beijing Yanshan Earth Critical Zone National Research Station in Huairou District, Beijing. The experiment involved N addition (50 kg N ha⁻¹ yr⁻¹ as urea [CO(NH₂)₂]) and precipitation manipulation (±50% of ambient throughfall) during the 2024 growing season. Six treatments were implemented: control (CK), nitrogen addition (NA), 50% increased precipitation (W+50%), 50% decreased precipitation (W−50%), nitrogen addition with increased precipitation (NW+50%), and nitrogen addition with decreased precipitation (NW−50%). Under natural rainfall conditions, N addition increased Rs (+11.8%; p < 0.05). However, the effects of N largely depended on water availability: with increased rainfall, N addition significantly boosted Rs, Rh, and Ra by promoting fine root biomass and accelerating litter decomposition; under reduced rainfall, N addition still increased Rs, Rh, and Ra compared to drought alone (NW−50% vs. W−50%), though the extent of stimulation was considerably lower than under elevated precipitation, indicating that water availability influences the strength of N effects on forest soil respiration. Structural equation modelling (SEM; χ²/df = 1.8, RMSEA = 0.040, CFI = 0.97) revealed that water availability was a key mediator of the interaction between N addition and precipitation. These findings enhance understanding of how nitrogen supply and water availability interact in temperate forest soils, though further validation across other forest types and over longer periods remains necessary. Full article

Afghanistan is highly vulnerable to the effects of climate change, which poses significant challenges to food security and environmental systems. To mitigate these challenges and promote sustainable development, it is important to adopt an integrated method that promotes food production and climate resilience for environmental sustainability. This manuscript aims to estimate the decoupling impact of green energy on CO₂ emissions and food crop production in Afghanistan, with a focus on promoting Sustainable food production. In this research article, the Nonlinear Auto Regressive Distributed Lag (NARDL) model was used to estimate data from 1996 to 2021 in Afghanistan. The NARDL bounds test confirms a stable long-run equilibrium relationship between climatic factors and food crop production. The long-run results reveal an asymmetric decoupling impact of green energy on CO₂ emission and food crop production. Specifically, a 1% positive or negative shock in the interaction between green energy and CO₂ emissions produces different outcomes for food crop production. Increasing temperature tends to decrease food production, while precipitation increases food production over the long term. Furthermore, raising CO₂ emissions negatively affects long-term food production, while greater use of green energy contributes to food production in the future. These findings underscore the need to adopt climate-resilient technologies, including climate-smart agriculture, to help farmers withstand the adverse effects of climate change. In addition, to ensure long-term stability in food production, Afghanistan should prioritize the development of green technologies. This approach would reduce agriculture’s dependence on fossil fuels and foster the growth of sustainable agricultural industries. Full article

Understanding long-term hydroclimatic variability in arid and semi-arid regions is essential for sustainable water resource management in the context of accelerating climate change. This study examines historical trends (1950–2024) and data-driven extrapolations to 2040 for precipitation and temperature across 30 secondary river basins in Iran using ERA5 reanalysis dataset and the Light Gradient Boosting Machine (LightGBM) model. Results reveal pronounced spatial heterogeneity in precipitation, with more than two-thirds of basins showing median values of 0 mm, reflecting extreme rainfall intermittency. Long-term analysis indicates significant precipitation increases in northern basins, whereas decadal trends show widespread drying since the early 2000s, particularly in eastern regions (30–60 mm per decade). Mean, maximum, and minimum temperatures exhibit significant upward trends (0.015–0.045 °C yr⁻¹), with stronger warming in northern and northwestern basins; however, minimum temperatures increased faster than maximum temperatures, reducing the diurnal temperature range and indicating a shift in regional thermal dynamics. Maximum temperature is negatively correlated with precipitation (R ≈ −0.27 to −0.34), suggesting enhanced evapotranspiration under warming conditions. LightGBM extrapolations to 2040 indicate continued warming (1–3 °C) and precipitation declines across more than 80% of Iran, underscoring intensifying hydroclimatic stress and increasing challenges for water resource management in dryland environments. Full article

In a high-mountain gorge region, landslide hazards pose a serious threat to the upper Minjiang River, located at the eastern edge of the Tibetan Plateau. To map susceptibility in the upper Minjiang River basin, this study used a Random Forest model in conjunction with slope unit subdivisions. First, a landslide inventory containing 3785 landslides was established using human–machine interactive interpretation techniques. After a multicollinearity analysis, 11 key conditioning factors were selected to construct a spatial database, including elevation, slope, aspect, curvature, topographic wetness index, stream power index, distance to fault, peak ground acceleration, distance to road, vegetation index, and rainfall. The r.slopeunits algorithm was implemented to partition the study area into discrete slope units. The ideal parameter combination for slope units was determined through integrating the normalized slope aspect standard deviation and Moran’s I using an equal-weight scheme. Ultimately, 30,513 slope units were delineated in the upper Minjiang River. The random forest model trained on these ideal slope units was validated using a 70/30 split of landslide and non-landslide samples. In receiver operating characteristic (ROC) curve analysis, the model demonstrated excellent performance, with an area under the curve (AUC) of 0.852. The results indicate that small-scale landslides dominate the inventory in terms of frequency. Despite accounting for only 30% of the study area, the Very High and High susceptibility zones exhibit considerable degree of spatial overlap with current landslide clusters. Furthermore, shapley additive explanations (SHAP) explanatory metrics indicate that the random forest model’s predictive behavior is primarily influenced by terrain elevation, precipitation patterns, and proximity to transportation networks. Full article

The mountainous southwest of Saudi Arabia exhibits complex, highly seasonal precipitation driven by Indian Ocean monsoon inflows and orographic lifting. To characterize storm hyetographs, cluster analysis was applied to 8972 rainfall events recorded at 151 gauges. Two primary clusters emerged: one with early, intense peaks and another with later peak intensities, broadly reflecting windward versus leeward storm behavior. A locally derived hyetograph profile (AI) was constructed from the cluster centroids and benchmarked against standard design-storm distributions (Uniform, SCS Type II, Huff quartiles). Across fit metrics—cumulative RMSE, Kolmogorov–Smirnov distance, and cosine-intensity similarity—the AI distribution provided the best match for ~46% of storms, markedly outperforming canonical profiles (Uniform and SCS Type II each best-fit only ~11–12%). These results indicate that region-specific rainfall distributions more accurately represent precipitation patterns than conventional profiles, and that tailored hyetographs can improve hydrologic modeling and water-resources assessments in this climatically heterogeneous region. Full article

The primary aim of this study is to identify the driving mechanisms behind long-term water-level changes and drought–flood transitions in Dongting Lake. To achieve this, we employed methods including the Improved Standardized Water Level Index (ISWI), Mann–Kendall test, Sen’s slope estimator, and a random forest–SHAP model to analyze hydro-meteorological data from 1992 to 2023. The results demonstrate a significant overall decline and spatial heterogeneity in water levels, alongside a systemic shift in the regional pattern from flood-dominated conditions to frequent droughts with intense drought–flood abrupt alternations. Crucially, during the critical autumn water recession period, runoff anomalies from the Yangtze River’s three outlets emerged as the dominant factor driving water-level changes, far exceeding the influence of local precipitation. Furthermore, a recent downward shift in the water level–discharge relationship indicates that under identical inflow conditions, water levels are now 1.5 to 2.0 m lower than in previous decades. These general findings highlight that critical-period inflow reductions and altered boundary hydrodynamic conditions mutually amplify low-water-level risks, providing a scientific reference for adaptive water resource management in complex river-connected lakes. Full article

Dust concentration control in coal-fired power plants is challenged by large time delays and various disturbances, particularly in dry electrostatic precipitator-wet flue gas desulfurization (DESP-WFGD) processes, where the inner-loop dynamics are slower than those of the outer loop, limiting the effectiveness of conventional cascade tuning methods. This paper proposes a compensation-based simultaneous tuning method for cascade proportional-integral-derivative (PID)-PID control systems. The cascade structure is transformed into an equivalent single-loop system, allowing the outer-loop controller to reshape the equivalent plant dynamics. An equivalent controller is then designed using the simple internal model control method, from which the inner-loop controller is derived. Controller parameters are iteratively refined based on maximum sensitivity, overshoot, and integral absolute error. A feedforward controller is further introduced to reject measurable outer-loop disturbances. Simulation results under nominal, uncertain, and noisy conditions show that the proposed method achieves zero overshoot, improved robustness, and smoother control action compared with conventional separate tuning and Lee’s simultaneous tuning method. The proposed approach provides an effective and practical solution for dust concentration control in DESP-WFGD processes, and is extendable to industrial cascade systems with similar dynamic characteristics. Full article

An association between long-term climatic stability and endemism has been suggested, but it has been tested in plants and vertebrates rather than invertebrates. Using high-resolution paleoclimate reconstructions (CHELSA-TraCE21k; 21,000 BP–present), we tested whether non-cave localities of endemic beetles in the western Balkans are non-randomly associated with local climatic stability. For four bioclimatic variables, we quantified temporal variability using three metrics (SD, range, detrended SD) and defined stability islands as cells in the most stable quartile relative to their neighbourhood at three spatial scales (3 × 3, 5 × 5, 9 × 9). We tested whether 578 endemic-locality cells were enriched in stability islands, against elevation-matched null models. Annual mean temperature produced the highest raw frequency of endemic localities in stability islands, but this pattern was not significant after elevation control. In contrast, endemic localities showed a modest but consistent enrichment in annual precipitation stability islands (observed 9.7–10.7% vs. null 7.3–8.5%; p = 0.01–0.03) across neighbourhood sizes. At the 3 × 3 scale, 60 endemic localities fell within precipitation-stability islands; of them, 20 were outside current protected areas—indicating conservation gaps where minor boundary revisions could enable protection of endemic beetles’ habitats in precipitation-stable sites. Full article

Urban–climate interactions in a warming climate remain largely uncertain; therefore, it is crucial to realistically evaluate and project these feedbacks to establish effective adaptation strategies. This study investigates projected shifts in summertime urban–climate interactions over eastern North America by employing the GEM regional climate model coupled with the Town Energy Balance (TEB) scheme, driven by RCP4.5 and RCP8.5 scenarios for the 1981–2100 period. Evaluations for the current climate (1981–2010) demonstrate that the model simulates an urban-induced warming of 0.5–0.7 °C and a precipitation reduction of 0.2–0.4 mm/day with high fidelity. By the late 21st century (2071–2100), projections under the RCP8.5 scenario indicate a steady weakening of the summer mean Urban Heat Island (UHI) intensity by approximately 0.10 °C, with a more pronounced nighttime attenuation of 0.15 °C. Physically, this weakening is attributed to an enhanced urban-induced evaporative fraction, which limits solar radiation storage within the urban fabric during the day, thereby reducing the thermal energy available for post-sunset release. This UHI attenuation correlates strongly with localized increases in precipitation, particularly in coastal regions where urban-induced effects contribute 20–40% to the total precipitation rise. While this study intentionally utilizes static urban boundaries to isolate the specific sensitivities of current urban morphologies to global warming, these results emphasize that diverse climatological regions will undergo distinct urban–climate feedback changes, providing essential baseline data for resilient urban planning. Full article

Accurately forecasting the weighted mean temperature (Tm) is critical for converting the zenith wet delay (ZWD) into global navigation satellite system (GNSS)-based precipitable water vapor (PWV) for real-time sensing and forecasting applications. The forecast Vienna Mapping Function 1 (VMF1-FC) is a global forecast product developed by TU Wien based on numerical weather prediction models and can provide grid-wise Tm one day ahead. In this study, we evaluate the accuracy of VMF1-FC-forecasted Tm using observations from 319 global radiosonde (RS) sites during 2019–2021. The results indicate that VMF1-FC-forecasted Tm shows a relatively low RMSE but a relatively large bias (0.75 K) relative to the widely used Global Pressure and Temperature 3 (GPT3) model. To improve the accuracy of VMF1-FC-forecasted Tm, three refined models, XTm, LTm, and CTm, are developed using Extreme Gradient Boosting (XGBoost), Light Gradient Boosting Machine (LightGBM), and Categorical Boosting (CatBoost), respectively, based on observations from 319 RS sites. The models use longitude, latitude, ellipsoidal height, floating day of year (fdoy), and VMF1-FC Tm as input features, and RS Tm as the target variable. Validation using RS data from 2022 that are not involved in model development shows that the refined models significantly reduce bias, with biases of 0 K, 0 K, and −0.03 K for XTm, LTm, and CTm, respectively. Benefiting from the effective reduction in bias, the root mean square error (RMSE) is correspondingly reduced. The RMSEs of XTm, LTm, and CTm are 1.45 K, 1.45 K, and 1.46 K, respectively, achieving improvements of 18.50%/64.93%, 18.44%/64.91%, and 18.11%/64.76% compared with the VMF1-FC and GPT3 models. In addition, three refined models demonstrate higher accuracy and improve stability across different latitude bands, ellipsoidal height ranges, and temporal scales. The refined models provide more accurate global-scale Tm and offer strong potential for GNSS meteorological applications, particularly real-time GNSS-based PWV sensing and weather forecasting. Full article

Stochastic inputs are essential for incorporating hydrological variability in water resources assessment, planning, and management. However, most studies focus on the generation of precipitation and temperature, precipitation and streamflow, and precipitation and evaporation, with limited incorporation of groundwater levels. This study assessed the ability of the Variable Length Block (VLB) bootstrapping model for simultaneously generating stochastic sequences of rainfall, evaporation, and groundwater levels. The performance of the model was assessed by comparing single statistics of historical time series located within the box plots of 100 annual and monthly stochastically generated time series. The model preserved eight of the nine statistics adequately, except for skewness, across all variables, with historical values for evaporation and groundwater levels falling below and above the interquartile range for 12 months. All the historic statistics for rainfall, evaporation, and groundwater levels were within the interquartile ranges of the box plots for 83, 71, and 71% of the time, respectively. The historic statistics for rainfall, evaporation, and groundwater levels were within the box plot ranges for 100, 98, and 99% of the time, respectively. These findings indicated reasonably successful generation, and the VLB generator was therefore considered applicable for the stochastic generation of multiple hydrometric data types. Full article

Sandstone-hosted uranium deposits in the western Qaidam Basin are spatially associated with hydrocarbon-bearing structures, yet the specific roles of different sulfur sources in uranium mineralization remain poorly constrained. This study aims to distinguish the contributions of bacterial sulfate reduction and hydrocarbon-associated sulfate reduction to uranium precipitation by integrating detailed petrography, in situ trace element analyses, and sulfur isotope measurements of chalcopyrite from the Yuejin Ⅱ deposit. Chalcopyrite is restricted to high-grade uranium ores and occurs intergrown with uranium minerals, pyrite, baryte, and carbonate cements. Trace element patterns indicate that oxidizing brines acted as the main transport medium for both uranium and copper, as evidenced by positive correlations between U and brine-related elements (Ba, Sr, Na, K). Positive U-Th correlations with relatively constant Th/U ratios (0.027–0.225) reflect a combination of source composition, fluid transport capacity, and limited thorium remobilization in this near-source, hydrocarbon-rich environment. Correlations between U and high field strength elements (Sn, W) point to a highly evolved granitic origin, with Altyn granitoids likely supplying the copper. Sulfur isotopes show a clear bimodal distribution: one group exhibits heavy δ³⁴S values (+6.9‰ to +18.5‰), while the other shows extremely light values (–36.0‰ to –44.6‰). The light group reflects bacterial sulfate reduction in shallow strata, supported by framboidal pyrite textures, whereas the heavy group corresponds to surface-derived sulfate reduced at hydrocarbon-associated redox fronts, rather than direct incorporation of deep H₂S. The lack of intermediate δ³⁴S values indicates that two discrete sulfur reduction mechanisms coexisted within the same deposit, refining genetic models for uranium mineralization in petroliferous basins and challenging frameworks that invoke a single dominant sulfur source. Full article