Search Results (3,272)

Coastal zones face mounting pressures from rapid urban expansion and ecological degradation, posing significant challenges to achieving synergistic carbon storage and emissions reduction under China’s “dual carbon” goals. Yet, the identification of spatially explicit zones of carbon synergy (high storage–low emissions) and conflict (high emissions–low storage) in these regions remains limited. This study integrates the PLUS (Patch-generating Land Use Simulation), InVEST (Integrated Valuation of Ecosystem Services and Trade-offs), and OPGD (optimal parameter-based GeoDetector) models to evaluate the impacts of land-use/cover change (LUCC) on coastal carbon dynamics in China from 2000 to 2030. Four contrasting land-use scenarios (natural development, economic development, ecological protection, and farmland protection) were simulated to project carbon trajectories by 2030. From 2000 to 2020, rapid urbanization resulted in a 29,929 km² loss of farmland and a 43,711 km² increase in construction land, leading to a net carbon storage loss of 278.39 Tg. Scenario analysis showed that by 2030, ecological and farmland protection strategies could increase carbon storage by 110.77 Tg and 110.02 Tg, respectively, while economic development may further exacerbate carbon loss. Spatial analysis reveals that carbon conflict zones were concentrated in major urban agglomerations, whereas spatial synergy zones were primarily located in forest-rich regions such as the Zhejiang–Fujian and Guangdong–Guangxi corridors. The OPGD results demonstrate that carbon synergy was driven largely by interactions between socioeconomic factors (e.g., population density and nighttime light index) and natural variables (e.g., mean annual temperature, precipitation, and elevation). These findings emphasize the need to harmonize urban development with ecological conservation through farmland protection, reforestation, and low-emission planning. This study, for the first time, based on the PLUS-Invest-OPGD framework, proposes the concepts of “carbon synergy” and “carbon conflict” regions and their operational procedures. Compared with the single analysis of the spatial distribution and driving mechanisms of carbon stocks or carbon emissions, this method integrates both aspects, providing a transferable approach for assessing the carbon dynamic processes in coastal areas and guiding global sustainable planning. 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

Groundwater level (GWL) in unconfined aquifers is highly susceptible to climate variables and human activities, exhibiting nonlinear fluctuations; these can further contribute to or exacerbate environmental hazards, such as land subsidence. Understanding the relationship between GWL changes and external conditions is essential for effective groundwater resource management and ecological protection. However, this relationship remains unclear and variable. This study systematically analyzes the correlations between climate and human factors and GWLs, using data from monitoring stations in the unconsolidated sedimentary aquifers of Beijing, China. It evaluates the importance of influencing factors on GWL simulation accuracy and tests how different inputs affect simulation performance. The results indicate that human factors are more strongly correlated with GWLs, yet climate factors hold higher importance scores. In GWL simulations, different input variables yield varying accuracy, with the inclusion of precipitation notably decreasing simulation precision because of its lagged or indirect effects on groundwater levels. The variation in accuracy across monitoring stations further suggests that the primary differences may stem from the GWL data itself. These findings underscore the need for high-resolution, localized data and tailored input selection to improve GWL projections and inform adaptive water-resource strategies under changing climatic and anthropogenic pressures. Full article

The persistent occurrence of antibiotics like chloramphenicol (CAP) in aquatic systems poses serious environmental and public health risks. This study investigates the photocatalytic degradation of CAP using cerium oxide (CeO₂), lanthanum oxide (La₂O₃), and lanthanum-doped cerium oxide (Ce_xLa_yO_2−δ), synthesized via co-precipitation. The catalysts were tested under a solar simulator, UV-A, and UV-C radiation, both with and without hydrogen peroxide (H₂O₂). Structural characterization confirmed successful synthesis of nanometric catalysts, with La doping causing lattice expansion in CeO₂ and a reduction in crystallite size (from 27 nm in CeO₂ to ~20 nm in doped samples). Photolysis alone achieved limited CAP removal (~34–35%), while photocatalysis with La₂O₃ under UV-A and UV-C improved removal up to 58% and 55%, respectively. Complete degradation was obtained with La₂O₃ under UV-C in the presence of H₂O₂ within 15 min. Pareto analysis highlighted the dominant effect of the interaction between radiation and H₂O₂ (43%), while the catalyst type contributed minimally (0.23%). These findings confirm the potential of REE oxides, especially La₂O₃, in advanced oxidation processes and underscore the importance of light source and radical generation over catalyst selection alone. Full article

Enhanced oil recovery (EOR) techniques are essential for maximizing hydrocarbon extraction from mature reservoirs. CO₂ injection (CO₂-EOR) is a promising technology that improves oil recovery while contributing to greenhouse gas reduction. This study investigates the potential of miscible CO₂-enhanced oil recovery (CO₂-EOR) in the MakXX oilfield of southeastern Kazakhstan. The aim is to assess oil displacement efficiency and its impact on key rock properties, including porosity, permeability, and mineral composition, under reservoir conditions. Core flooding experiments were conducted at 13 MPa and 42 °C using high-precision equipment to replicate reservoir conditions. The core was analyzed before and after CO₂ injection using SEM, EDS, and XRD. The results revealed a 54% oil recovery efficiency, accompanied by a 19% decrease in permeability and 8% reduction in porosity due to mineral precipitation and clay transformation. These findings provide insight into the performance and limitations of CO₂-EOR and support its application in similar lithology. To confirm and upscale laboratory observations, numerical simulation was conducted using a compositional model. The results demonstrated improved oil recovery, pressure stabilization, and enhanced sweep efficiency under CO₂ injection, supporting the scalability and field applicability of the proposed EOR approach. Full article

Uncontrolled and excessive inflammation could negatively impact embryo implantation, potentially leading to implantation failure or miscarriage. Small extracellular vesicles (sEVs) secreted by extravillous trophoblasts (EVTs) play a significant role in mediating the homeostasis at the maternal–fetal interface. In the present work we assessed the role of EVT-derived sEVs in the protection of the human blastocyst’s integrity and function in a microenvironment with excessive Th1-induced inflammation using the Sw71 blastocyst-like surrogate (Sw71 BLS) as a model of implanting a human embryo. Conditioned media from primary trophoblast-derived EVT cells were used as the source for sEVs’ isolation by precipitation. sEVs were characterized by TEM, IEM, and protein content. To simulate Th1-induced inflammation, we performed TCR stimulation and polyclonal activation of isolated T cells, which preferentially led to Th1 cytokine production. The use of the Sw71 spheroid model allowed us to monitor directly the damaging effect of high levels of Th1 cytokines on the ability of trophoblast cells to self-organize and migrate. The addition of EVT-sEVs unlocked the absolute migration capacity of the trophoblast cells in a healthy microenvironment. However, EVT-sEV treatment could not counteract the adverse effects of excessive Th1-mediated inflammation. This study provides a platform for further elucidation of the EVT-sEV dosage and potency for trophoblast functional recovery. Full article

This study investigates the effect of copper (Cu) and silver (Ag) additions on the electrochemical behavior of the Fe40Al intermetallic alloy in artificial saliva, aiming to evaluate its potential for biomedical applications such as dental implants. Alloys with varying concentrations of Ag (0.5, 1.0, and 3.0 wt%) and Cu (1.0, 3.0, and 5.0 wt%) were synthesized and exposed to a biomimetic electrolyte simulating oral conditions. Electrochemical techniques, including open circuit potential (OCP), linear polarization resistance (LPR), potentiodynamic polarization, and electrochemical impedance spectroscopy (EIS), were employed to assess corrosion performance. Results show that unmodified Fe40Al exhibits good corrosion resistance, attributed to the formation of a stable passive oxide layer. The addition of Cu, particularly at 3.0 wt%, significantly improved corrosion resistance, yielding lower corrosion current densities and higher polarization resistance and charge transfer resistance values, surpassing even 316L stainless steel in some metrics. Conversely, Ag additions led to a degradation of corrosion resistance, especially at 3.0 wt%, due to microstructural changes and the formation of metallic Ag precipitates, AgSCN, and galvanic cells, which promoted localized corrosion. EIS results revealed that Cu- and Ag-modified alloys developed less homogeneous and less protective passive layers over time, as indicated by increased double-layer capacitance (C_dl) and reduced constant phase element exponent (n_dl) values. Overall, the Fe40Al alloy shows intrinsic corrosion resistance in simulated physiological environments, and Cu additions can enhance this performance under controlled conditions. However, Ag additions negatively affect the protective behavior of the passive layer. These findings offer critical insight into the design of Fe-Al-based biomaterials for dental or biomedical applications where corrosion resistance and electrochemical stability are paramount. Full article

Climate change poses significant challenges for viticulture, particularly in regions known for producing high-quality wines. Wine quality results from a complex interaction between climatic factors, regional characteristics, and viticultural practices. Methods: This study integrates statistical analysis, machine learning (ML) algorithms, and systems thinking to assess the extent to which wine quality can be predicted using monthly weather data and regional classification. The dataset includes average wine scores, monthly temperatures and precipitation, and categorical region data for Slovenia between 2011 and 2021. Predictive models tested include Random Forest, Support Vector Machine, Decision Tree, and linear regression. In addition, Causal Loop Diagrams (CLDs) were constructed to explore feedback mechanisms and systemic dynamics. Results: The Random Forest model showed the highest prediction accuracy (R² = 0.779). Regional classification emerged as the most influential variable, followed by temperatures in September and April. Precipitation did not have a statistically significant effect on wine ratings. CLD models revealed time delays in the effects of adaptation measures and highlighted the role of perceptual lags in growers’ responses to climate signals. Conclusions: The combined use of ML, statistical methods, and CLDs enhances understanding of how climate variability influences wine quality. This integrated approach offers practical insights for winegrowers, policymakers, and regional planners aiming to develop climate-resilient viticultural strategies. Future research should include phenological phase modeling and dynamic simulation to further improve predictive accuracy and system-level understanding. Full article

Understanding the drivers of water yield (WY) changes in ecologically sensitive, data-scarce watersheds is crucial for sustainable management, particularly in the context of accelerating forest expansion and urbanization. This study focuses on the upper Yellow River Basin (UYRB), a critical headwater region that supplies 60% of the Yellow River’s flow and is undergoing rapid land use transitions from 1990 to 2100. Using the Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST) model and the Future Land-Use Simulation (FLUS) model, we quantify historical (1990–2020) and projected (2025–2100) WY dynamics under three SSP scenarios (SSP126, SSP370, and SSP585). InVEST, a spatially explicit ecohydrological model based on the Budyko framework, estimates WY by balancing precipitation and evapotranspiration. The FLUS model combines cellular automata (CA) with an artificial neural network (ANN)-based suitability evaluation and Markov chain-derived transition probabilities to simulate land-use change under multiple scenarios. Results show that WY increased significantly during the historical period (1990–2020), primarily driven by increased precipitation, with climate change accounting for 94% and land-use change for 6% of the total variation in WY. Under future scenarios (SSP126, SSP370, and SSP585), WY is projected to increase to 217 mm, 206 mm, and 201 mm, respectively. Meanwhile, the influence of land-use change is expected to diminish, with its contribution decreasing to 9.1%, 5.7%, and 3.1% under SSP126, SSP370, and SSP585, respectively. This decrease reflects the increasing strength of climate signals (especially extreme precipitation and evaporative demand), which masks the hydrological impacts of land-use transitions. These findings highlight the dominant role of climate change, the scenario-dependent effects of land-use change, and the urgent need for integrated climate–land management strategies in forest-urbanizing watersheds. Full article

Non-uniform corrosion cracking in reinforced concrete buildings constitutes a fundamental difficulty resulting in durability failure. This work develops a microscopic-scale multi-species electrochemical phase field model to tackle this issue. The model comprehensively examines the spatiotemporal coupling mechanisms of the full “corrosion-rust swelling-cracking” process by integrating electrochemical reaction kinetics, multi-ion transport processes, and a unified phase field fracture theory. The model uses local corrosion current density as the primary variable to accurately measure the dynamic interactions among electrochemical processes, ion transport, and rust product precipitation. It incorporates phase field method simulations of fracture initiation and propagation in concrete, establishing a bidirectional link between rust swelling stress and crack development. Experimental validation confirms that the model’s predictions about cracking duration, crack shape, and ion concentration distribution align well with empirical data, substantiating the efficacy of local corrosion current density as an indicator of electrochemical reaction rate. Parametric studies were performed to examine the effects of interface transition zone strength, oxygen diffusion coefficient, protective layer thickness, reinforcing bar diameter, and reinforcing bar configuration on cracking patterns. This model’s multi-physics field coupling framework, influenced by dynamic corrosion current density, facilitates cross-field interactions, offering sophisticated theoretical tools and technical support for the quantitative analysis, durability evaluation, and protective design of corrosion-induced cracking in reinforced concrete structures. Full article

Avalanches occur frequently in mountainous areas and pose significant threats to roads and infrastructure. Clarifying how terrain conditions influence avalanche initiation and movement is critical to improving hazard assessment and response strategies. This study focused on a wet-snow slab avalanche that occurred on 26 March 2024, in the Simutas region of the northern Tianshan Mountains, Xinjiang, China. The authors combined remote sensing imagery, high-resolution meteorological station observations, field investigations, and numerical simulations (RAMMS::Avalanche) to analyze the avalanche initiation mechanism, dynamic behavior, and path recurrence characteristics. Results indicated that persistent heavy snowfall, rapid warming, and substantial daily temperature fluctuations triggered this avalanche. The predominant southeasterly (SE) winds and the northwest-facing (NW) shaded slopes created favorable leeward snow deposition conditions, increasing snowpack instability. High-resolution meteorological observations provided detailed wind, temperature, and precipitation data near the avalanche release zone, clearly capturing snowpack evolution and meteorological conditions before avalanche initiation. Numerical simulations showed a maximum avalanche flow velocity of 19.22 m/s, maximum flow depth of 12.42 m, and peak dynamic pressure of 129.3 kPa. The simulated avalanche deposition area and depth closely matched field observations. Multi-temporal remote sensing images indicated that avalanche paths in this area remained spatially consistent over time, with recurrence intervals of approximately 2–3 years. The findings highlight the combined role of local meteorological processes and terrain factors in controlling avalanche initiation and dynamics. This research confirmed the effectiveness of integrating remote sensing data, high-resolution meteorological observations, and dynamic modeling, providing scientific evidence for avalanche risk assessment and disaster mitigation in mountain regions. Full article

The development of an economical and efficient method for recovering phosphate (PO₄³⁻-P) and ammonium nitrogen (NH₄⁺-N) is of paramount importance for environmental remediation. The preparation of Mg/Fe-loaded biochar (Mg/Fe-BC) was achieved through chemical precipitation followed by pyrolysis in this study. Single solution adsorption studies indicated that temperature significantly affected how effectively Mg/Fe-BC could adsorb and remove NH₄⁺-N, whereas PO₄³⁻-P adsorption showed minimal temperature sensitivity. In mixed simulated solutions, In the mixed simulated solution, the maximum adsorption capacities of Mg/Fe-BC for PO₄³⁻-P and NH₄⁺-N were 145.97–153.05 mg/g and 112.63–121.51 mg/g, respectively. The optimal dosage for synergistic adsorption was determined to be 3 g/L, while pH values ranging from 3 to 9 exhibited negligible effects on the adsorption of both contaminants. The presence of Ca²⁺ and HCO₃⁻ in the solution may interfere with the simultaneous adsorption of PO₄³⁻-P and NH₄⁺-N. SEM-EDS and XPS analyses revealed that the primary adsorption mechanisms of PO₄³⁻-P and NH₄⁺-N by Mg/Fe-BC involved electrostatic attraction, ion exchange, and hydrogen bonding. In practical applications using chicken manure biogas slurry, Mg/Fe-BC demonstrated synergistic adsorption effects, achieving removal efficiencies of 86.86% for PO₄³⁻-P and 36.86% for NH₄⁺-N, thereby confirming its potential application value in wastewater treatment. Full article

To address the central cracking problem in continuous casting slabs of 38CrMoAl steel, high-temperature tensile tests were performed using a Gleeble-3800 thermal simulator to characterize the hot ductility of the steel within the temperature range of 600–1200 °C. The phase transformation behavior was computationally analyzed via the Thermo-Calc software, while the microstructure, fracture morphology, and precipitate characteristics were systematically investigated using a metallographic microscope (MM), a field-emission scanning electron microscope (FE-SEM), and transmission electron microscopy (TEM). Additionally, the effects of different holding times and cooling rates on the microstructure and precipitates of 38CrMoAl steel were also studied. The results show that the third brittle temperature region of 38CrMoAl steel is 645–1009 °C, and the fracture mechanisms can be classified into three types: (I) in the α single-phase region, the thickness of intergranular proeutectoid ferrite increases with rising temperature, leading to reduced hot ductility; (II) in the γ single-phase region, the average size of precipitates increases while the number density decreases with increasing temperature, thereby improving hot ductility; and (III) in the α + γ two-phase region, the precipitation of proeutectoid ferrite promotes crack propagation and the dense distribution of precipitates at grain boundaries causes stress concentration, further deteriorating hot ductility. Heat treatment experiments indicate that the microstructures of the specimen transformed under water cooling, air cooling, and furnace cooling conditions as follows: martensite + proeutectoid ferrite → bainite + ferrite → ferrite. The average size of precipitates first decreased, then increased, and finally decreased again with increasing holding time, while the number density exhibited the opposite trend. Therefore, when the holding time was the same, reducing the cooling rate could increase the average size of the precipitates and decrease their number density, thereby improving the hot ductility of 38CrMoAl steel. Full article

This study assesses future agricultural drought risk in the Ganjiang River Basin under climate change and land use change. A coupled analysis framework was established using the SWAT hydrological model, the CMIP6 climate models (SSP1-2.6, SSP2-4.5, SSP5-8.5), and the PLUS land use simulation model. Key methods included the Standardized Soil Moisture Index (SSMI), travel time theory for drought event identification and duration analysis, Mann–Kendall trend test, and the Pettitt change-point test to examine soil moisture dynamics from 2027 to 2100. The results indicate that the CMIP6 ensemble performs excellently in temperature simulations, with a correlation coefficient of R² = 0.89 and a root mean square error of RMSE = 1.2 °C, compared to the observational data. The MMM-Best model also performs well in precipitation simulations, with R² = 0.82 and RMSE = 15.3 mm, compared to observational data. Land use changes between 2000 and 2020 showed a decrease in forestland (−3.2%), grassland (−2.8%), and construction land (−1.5%), with an increase in water (4.8%) and unused land (2.7%). Under all emission scenarios, the SSMI values fluctuate with standard deviations of 0.85 (SSP1-2.6), 1.12 (SSP2-4.5), and 1.34 (SSP5-8.5), with the strongest drought intensity observed under SSP5-8.5 (minimum SSMI = −2.8). Drought events exhibited spatial and temporal heterogeneity across scenarios, with drought-affected areas ranging from 25% (SSP1-2.6) to 45% (SSP5-8.5) of the basin. Notably, abrupt changes in soil moisture under SSP5-8.5 occurred earlier (2045–2050) due to intensified land use change, indicating strong human influence on hydrological cycles. This study integrated the CMIP6 climate projections with high-resolution human activity data to advance drought risk assessment methods. It established a framework for assessing agricultural drought risk at the regional scale that comprehensively considers climate and human influences, providing targeted guidance for the formulation of adaptive water resource and land management strategies. Full article

Due to increased precipitation intensity and sea-level rise, low-lying coastal roads are increasingly vulnerable to subbase saturation. Widely applied lumped hydrological approaches cannot accurately represent time and space-varying groundwater levels in some highly conductive coastal soils, calling for more sophisticated tools. This study assesses the suitability of the Gridded Surface Subsurface Hydrologic Analysis model (GSSHA) for representing hydrological processes and groundwater dynamics in a unique coastal roadway setting in Alabama. A high-resolution model was developed to assess a 2 km road segment and was calibrated for hydraulic conductivity and aquifer bottom levels using observed groundwater level (GWL) data. The model configuration included a fixed groundwater tidal boundary representing Mobile Bay, a refined land cover classification, and an extreme precipitation event simulation representing Hurricane Sally. Results indicated good agreement between modeled and observed groundwater levels, particularly during short-duration high-intensity events, with NSE values reaching up to 0.83. However, the absence of dynamic tidal forcing limited its ability to replicate certain fine-scale groundwater fluctuations. During the Hurricane Sally simulation, over two-thirds of the segment remained saturated for over 6 h, and some locations exceeded 48 h of pavement saturation. The findings underscore the importance of incorporating shallow groundwater processes in hydrologic modeling for coastal roads. This replicable modeling framework may assist DOTs in identifying critical roadway segments to improve drainage infrastructure in order to increase resiliency. Full article