Environmental Earth Sciences最新文献

Responses of soil organic matter (SOM) to changes in temperature and precipitation were helpful to understanding biogeochemical processes in soils. In the current study, two groups of soil samples were used to distinguish the respective effects of precipitation and temperature on SOM. The first group was named as mean annual temperature (MAP) gradient group including 13 samples with similar mean annual temperature (MAT) (13.0–14.9 °C) but different MAP (71.4–1072.8 mm). The second group was named as MAT gradient group including 13 samples with high MAP (> 1000 mm) but different MAT (15.9–24.8 °C). The SOM molecular composition was analyzed by a pyrolysis gas chromatography mass spectrometry. Variance partitioning analysis showed that in the MAP gradient group the variation in SOM composition was only independently explained 1% and 6% by MAT and MAP, respectively, but jointly explained 28%. In the MAT gradient group, although MAP explained 22% variation in SOM composition, MAT and MAP together explained more than 51%. These results indicated that the effect of MAT alone on SOM was negligible in the MAP gradient group and MAT was the dominant influencing factor in MAT gradient group. In the MAP gradient group, SOC content and the proportion of lignin and nitrogen-containing compounds were significantly positively related to MAP. In the MAT gradient group, the proportion of aliphatic, aliphatic and terpenoid compounds was significantly positively related to MAT but the proportion of aromatic compounds was opposite. Structural equation modeling showed that MAP was significantly positively related to SOM molecular diversity and stability, and MAT was significantly negatively related to SOM stability.

To study the effect of vertical stress on the collapsibility and hydraulic properties of Lanzhou loess during infiltration, a series of constant head permeability tests were conducted on unsaturated remolded loess under different vertical stresses using a one-dimensional soil column permeameter. The tests yielded collapse deformation curves, wetting front, cumulative infiltration volume, volumetric water content time-history curves, and soil–water characteristic curves. The unsaturated permeability coefficient was calculated using the wetting front advancement method, and its relationship with suction and volumetric water content was established. The study results indicated: (1) The wetting front advancement rate gradually slowed down over time, especially under higher vertical stress; the relationship between the wetting front advancement and time can be described by a power function. (2) The infiltration rate experienced three stages with increasing time: rapid infiltration, significant infiltration, and stable infiltration, significantly influenced by vertical stress. The relationship between cumulative infiltration volume and time can be described by the Philip infiltration model. (3) The collapse deformation over time can be divided into three stages, with stress significantly affecting the time intervals and collapse deformation amounts at each stage. (4) The soil–water characteristic curves during the infiltration process shifted upward with increasing stress, which also significantly impacts the air entry value and the absorption rate. The unsaturated permeability coefficient increased with decreasing matric suction and increased with increasing volumetric water content.

Dams are engineering structures with a substantial influence on environmental systems, making it necessary to regularly monitor their effects on the climate of the region they are located. In the recent years, the advent of remote sensing technologies has enabled faster analysis of their effects on climate, even for large-extent areas. This study aims to investigate the climate-related influences of five dams that started to receive water in 2005, 2006, 2012, 2015, and 2022 in the Artvin province of Türkiye. To do so, time series analysis were conducted using multi-sensor satellite data for the years between 1995 and 2023. To better reveal the dam reservoir-induced climate change effects, the experiments were carried out for both the entire Artvin region and the 10-km buffer zone generated through the Coruh River on which the dams were built. The investigated climate parameters included land surface temperature (LST), precipitation (Pre), evapotranspiration (ET), relative humidity (RH), heat index (HI), wind speed (WS) and normalized vegetation difference index (NDVI). The trends of these parameters were investigated with Mann-Kendall, Sen’s Slope and Pettitt tests. Dam reservoirs were found to cause a warming effect from the buffer zone to the entire region, with no significant impact on Pre. The increase in temperature led to higher ET, especially in summer, while RH decreased and HI increased, indicating drier but hotter conditions during the time period examined. Most climate changes were found to occur when the dams started filling, and the reservoirs also contributed to enhanced vegetation in the region.

Facility agriculture is a modern intensive cultivation method that is widely seen as the future of global agriculture. However, large-scale emissions of concentrated pollutants during production pose serious threats to groundwater quality. Identifying the sources of pollutants and assessing source-specific risks are critical for developing effective risk mitigation strategies. In this study, a combination of methodologies including Self-Organizing Maps (SOM), K-means clustering, factor analysis, and ion ratio analysis were utilized to investigate pollution risks in a typical facility agriculture area in Shouguang City, Shandong Province, China. The groundwater quality in the study area is poor and slightly alkaline, with NO₃⁻ being the main pollutant. The chemical composition of groundwater in the aquifer is influenced by both human activities (41.89%, such as agricultural activities) and natural processes (58.11%, such as water–rock interactions). Furthermore, pollution sources in the study area were spatially categorized into two clusters: Cluster 1, mainly located on the right bank of the Mi River, is primarily related to urban domestic sewage discharge, and Cluster 2, primarily on the left bank of the Mi River, is mainly related to agricultural activities. The average concentrations of Cl⁻ and Na⁺, both of which have high mobility, are significantly higher in Cluster 2 than in Cluster 1, suggesting that the groundwater system in Cluster 2 is relatively closed, resulting in higher ion concentrations and pollution levels. These findings provide valuable insights for the prevention, control, and remediation of groundwater pollution in the study area, and in facility agriculture regions generally.

Shallow water flow on semiarid hillslopes with shrubs or cultivated with crops often occurs as laminar flow without concentration. Typically, the flow has a low Reynolds number, usually below 100, and the surface hydraulic resistance generated from the interaction between the soil surface and vegetation that obstructs the flow is governed by the Froude number. This study conducted field experiments on Brazilian shrub and semiarid crop fields and applied the Crompton framework to model hydraulic resistance. The overland flow observed on semiarid hillslopes under crops or natural vegetation always presented Reynolds numbers between 32 and 54, and the flow was laminar and subcritical. By employing the kinematic wave approximation, the Crompton framework was found to model overland flow resistance over semiarid hillslopes with acceptable accuracy.

This study examines the spatial and temporal variability of precipitation seasonality across Serbia using various seasonality indices. The research focuses on understanding the intra- and inter-annual variability of precipitation regimes over two sub-periods: 1946–1984 and 1985–2023. For this purpose, monthly precipitation data from 24 synoptic stations across Serbia were analyzed using seasonality indices such as the General Seasonality Index ((overline{SI})), Individual Seasonality Index (SI_i), Mean Individual Seasonality Index ((overline{{SI_{i} }})), and Replicability Index (RI)). The results shown on the SI maps indicate a more irregular rainfall distribution during the first sub-period, with a noticeably higher seasonality in the northern part of Serbia. The mean SI_i shows an increasing gradient from southwest to northeast, with the highest variability shifting from the central and southeastern parts (1946–1984) to the northern and eastern parts of Serbia (1985–2023). Minimum values reveal a shift from a “very equitable” regime in the first sub-period to “equitable with a definite wetter season” in the second, while maximum values generally decreased. RI values remain low across Serbia, reflecting significant variability in precipitation regimes.

Geothermal resources, as a renewable and clean source of energy, are attracting widespread attention globally. In China, most medium to high enthalpy geothermal resources are developed in the Tibetan Plateau, especially in the rift zone of Southern Tibet. To further investigate the genesis mechanisms of geothermal resources, this study collected geothermal spring samples from the Cuona-Woka rift zone in Southern Tibet. Hydrochemical and isotopic characteristics were analyzed to reveal the origin, evolution, reservoir temperature, and circulation mechanisms of the geothermal waters. The exposed temperature of the geothermal spring ranges from 34 to 67 °C. Compared with HCO₃-Ca·Na and HCO₃-Na type samples, HCO₃·Cl-Na and HCO₃·SO₄-Na type samples have higher concentrations of Cl⁻ and trace elements. The geothermal springs are recharged by a mixture of meteoric water, snow-melt water, and magmatic water. The recharge areas had an elevation range from 5091 to 6087 m, with temperatures from −5 to −10 °C. The hydrochemical processes are dominated by silicate and carbonate dissolution, and positive cation exchange, with local gypsum dissolution. Solute geothermometers, silica-enthalpy mixing models, and geothermal conceptual model indicate that there exist shallow geothermal reservoirs (temperature = 137–162 °C) mixed by surficial cold groundwater and initial deep geothermal reservoirs (temperature = 196–212 °C), respectively. Finally, two genesis models of geothermal waters are proposed: the deep melt mixing and heating model (Type A) and the high-temperature steam heating model (Type B). The achievements of this study would provide valuable insight into geothermal research and exploitation in the Tibetan Plateau.

Heavy metal contamination in soil poses significant environmental and geotechnical challenges, requiring effective stabilization to limit contaminant mobility, enhance soil stability, and reduce deformation. This study investigates the dynamic response and microstructural changes in heavy metal-contaminated clayey sand, emphasizing the effects of clay type (kaolin and bentonite) and zeolite stabilization at varying contents (5%, 10%, and 15%). Laboratory tests, including cyclic triaxial, bender element, adsorption, sedimentation, pH measurements, Atterberg limits, and SEM analyses, were performed. Results reveal that contamination significantly reduces liquefaction resistance, with kaolin-based mixtures more susceptible than bentonite-based ones due to differences in plasticity, specific surface area, and swelling capacity. Zeolite stabilization, especially at 10% content, improves resistance by strengthening the soil structure and mitigating pore pressure under cyclic loading. Contamination affects shear modulus and damping ratio differently for kaolin and bentonite mixtures, with zeolite amplifying these impacts at higher contents through enhanced particle dispersion. Heavy metal adsorption increases with bentonite and zeolite addition, with bentonite exhibiting 180% greater lead adsorption than kaolin. Optimal adsorption performance is achieved with 10% zeolite. Microstructural analysis indicates contamination disrupts hydrogen bonding of kaolin, induces flocculation in bentonite, and has minimal effect on the stable structure of zeolite. These findings highlight the importance of clay type, zeolite content, and soil composition in mitigating contamination effects, providing insights into effective soil stabilization strategies.

Backbreak is an undesirable outcome in blasting operations caused by factors such as equipment failure, improper fragmentation, unstable mine walls, reduced drilling efficiency, and other issues that contribute to increased mining operation costs. To overcome these problems effectively, this study developed a least square support vector machine (LSSVM) model and optimized it using metaheuristic algorithms, including genetic algorithm (GA)-LSSVM, particle swarm optimization (PSO)-LSSVM, and grey wolf optimization (GWO)-LSSVM, to predict the efficiency and accuracy of backbreak due to blasting in surface mines using burden (m), spacing (m), stemming (m), powder factor (kg/m^s), and stiffness ratio (m/m) as input parameters. Among the models evaluated, the GWO-LSSVM model demonstrated superior performance compared to the LSSVM, GA-LSSVM, and PSO-LSSVM models, achieving a coefficient of determination of 0.998 and 0.997, mean absolute error of 0.0068 and 0.1209, root mean squared error of 0.0825 and 0.1936, and SI of 0.021 and 0.044 on the training and testing datasets, respectively. Sensitivity analysis of the GWO-LSSVM model revealed that the powder factor exerted the most significant influence, while the burden had the least impact on backbreak. This developed method has proven to significantly enhance the performance evaluation of backbreak in surface mines and offers valuable engineering applications in mining and other related fields.

The Grombalia Basin, located in Northern Tunisia, is facing significant challenges related to water scarcity. The cultivation of citrus fruits in this region, supported by the government, has become increasingly vulnerable to the impacts of climate change, including reduced rainfall and more frequent drought periods. The agricultural sector faces a crisis due not only to the lack of water resources but also to inadequate management (water losses in irrigation systems). This study aims to delineate the most suitable areas for implementing solar photovoltaic (PV) desalination farms utilizing abandoned brackish groundwater. A Fuzzy Analytical Hierarchy Process (FAHP), integrated with Geographic Information Systems (GIS), is employed as a Multi-Criteria Decision Analysis (MCDA) approach. This paper evaluates potential sites based on climatic, socioeconomic, and environmental factors. The FAHP framework determines criteria weights through pairwise comparisons, ensuring robust and systematic decision-making. The results indicate that the most suitable sites are located north of the Grombalia basin, which currently lacks access to external water resources for irrigation. The "Dependence of Farmers on Water Resources (DFWR)" is the most sensitive criterion, and the most suitable sites remain relatively the same despite variations in weighting. These findings will assist farmers in using solar energy to desalinate brackish groundwater, thus ensuring the sustainability of their crops and preserving their citrus heritage.