Environmental Earth Sciences最新文献

Lead (Pb), one of the most lethal heavy metals (priority contaminant) in environmental and human health, spreads to the air as a metal or compound and has noxious properties. Therefore, tracking and diminishing Pb pollution are urgent and priority research topics. This study aims to contribute to the determination of suitable biomonitor species that can be used to observe Pb pollution shifts over a long period and hyperaccumulator species that can be used to lessen pollution. For this reason, it was selected to use species from Düzce, one of the five most unclean municipalities in Europe, including Pinus pinaster, Pseudotsuga menziesii, Cupressus arizonica, Cedrus atlantica, and Picea orientalis. The Pb concentration variations based on the species, organ, direction, and age range in the last 4 decades were assessed by examining the samples taken from tree species. The highest Pb concentrations were found in the outer bark and the east and north directions (high vehicle density) in almost all the species. These results showed that Pb pollution increases significantly due to vehicles. In conclusion, the displacement of Pb in wood was limited in these species; therefore, they could be used to track the Pb pollution change. C. arizonica and P. menziesii were determined to be suitable for reducing Pb pollution.

Global warming has been extensively documented in the twenty-first century, resulting in increased frequency of extreme weather events that pose threats to both agriculture and human welfare worldwide. The black soil region in Northeast China (NEBS) is home to a large region and vulnerable to climate change. NEBS benefits from its fertile soil enriched with soil organic matter and has been serving as one of China’s key commodity grain bases. Great efforts have been made in previous studies evaluating the climate change in NEBS. However, spatiotemporal patterns of climate change remain unknown. Therefore, the main objective of this study was to assess climate differences under different land cover and altitude gradient in NEBS between 1981 and 2020 based on Google Earth Engine (GEE) and ECMWF Reanalysis 5th Generation Land (ERA5-Land) reanalysis dataset. Mann–Kendall (MK) trend analysis was used to conclude the climate change in the NEBS over the past 40 years. The climate differences under different altitude gradients and land cover were then analyzed. In addition, the predicted climate change in NEBS was presented with Climate Model Intercomparison Project (CMIP6) data. The results indicate a temperature rise across the entire NEBS, while a decrease in precipitation for 98% of this region. A significant effect of altitudinal difference was observed on temperature variation, while its influence on precipitation change was insignificant. The forest exhibited less significant altitude differences compared to croplands and grasslands. The CMIP6 data show that the NEBS would continue to warm but slightly humid. These results highlight the necessity to consider the climate differences under different altitudes and land cover for climate change study in NEBS.

This study aims to generate a multiple combination strategy and explore a combination of influencing factors on earthquake-induced landslides susceptibility assessments. Landslides caused by two earthquakes with similar magnitudes that both have surface rupture zones are taken as the study subjects. Data on twenty landslide influence factors including earthquakes, topography, geological structure, hydrology, stratum lithology, and human engineering activities were acquired. Based on frequency ratio analysis, normalization and correlation analysis, a multiple combination strategy is applied to develop different combinations of these factors. The logistic regression (LR) method is used to establish an evaluation model for all possible combinations. After constructing 2047 combinations of influence factors, the model with the greatest prediction accuracy was extracted. Results show that the combination of aspect, slope, distance from fault, elevation, lithology, plan curvature, profile curvature, NDVI, land cover type, PGA, and distance from river has better applicability in evaluation of earthquake-induced landslides susceptibility in the study area. The prediction accuracy of the model did not continue to improve as the number of influence factors increased, and varied depending on the type of influencing factors. We expect the multiple combination strategy to advance the prediction accuracy of modeling in the landslide susceptibility assessment process.

Geomorphic zoning can change soil physicochemistry, and the sediment formed by soil erosion contains various types of microorganisms. In this study, samples were collected from the aeolian sand and loess regions in the Wuding river basin on the Loess Plateau to determine sediment enzyme activities and microbial communities. The environmental pollution in the aeolian sand region was worse than that in the loess region. The activities of carbon and nitrogen cycling enzyme were higher in the loess region. Electric conductivity and ammonia nitrogen in runoff were significantly correlated with carbon cycling enzyme activity. Nitrogen cycling enzyme activity was significantly correlated with temperature and total phosphorus in runoff. The bacterial communities in the aeolian sand region had higher alpha diversity index, and the values of Simpson, Shannon, and Chao1 indices were 0.98, 8.17, and 2087.95, respectively. Conversely, alpha diversity index of the fungal communities in the loess region was higher, and the values of Simpson, Shannon, and Chao1 indices were 0.92, 5.99, and 424.19, respectively. Proteobacteria and Ascomycota were the dominant phyla in the microbial community. In the aeolian sand region, silt in sediment was the most significant influencing factor for bacterial community changes, while ammonia nitrogen in runoff was the most notable for fungal community changes. In contrast, electric conductivity in runoff emerged as the most significant factor affecting the changes of both bacterial and fungal communities in the loess region. This study offered new insights into the distribution of enzyme activities and microbial communities within river sediment across various geomorphic regions, contributing to understanding of the formation of sediment microbial communities on the Loess Plateau.

Low saline water flooding (LSWF) is a promising enhanced oil recovery (EOR) technique in petroleum engineering, offering a sustainable alternative to chemical EOR by targeting residual oil with minimal chemical use. However, the role of ion concentrations in influencing oil recovery remains insufficiently understood, creating a critical gap in LSWF optimization. This study addresses this gap by employing Sobol’ analysis, a global sensitivity analysis technique, to evaluate the impact of ion concentrations on oil recovery. Sobol’ analysis is applied over 81,920 samples for 2.3 pore volume injected (PVI) to assess the effects of multiphase fluid flow coupled with a reactive transport model. The results reveal that ([text {Na}^+]), ([text {Mg}^{2+}]), and ([text {Ca}^{2+}]) significantly influence oil recovery, with strong interactions between ([text {Na}^+]) and ([text {Ca}^{2+}]), as well as ([text {Ca}^{2+}]) and ([text {Mg}^{2+}]). Among all, ([text {Na}^+]) exhibits the highest Sobol’ first-order value, indicating its dominant role in recovery variation. Temporal analysis further suggests that interactive effects outweigh individual contributions. To manage uncertainties, cumulative probability values ((hbox {P}_{{10}}), (hbox {P}_{{50}}), and (hbox {P}_{{90}})) are employed for optimization, minimizing variability in recovery predictions. Finally, this research provides a toolkit for evaluating ion interactions and optimizing LSWF, underscoring the role of ionic concentrations in sensitivity analysis, supporting decision making and risk assessment in upstream applications.

The riparian zone is a transition zone between terrestrial and aquatic ecosystems and is vulnerable to human activities. Pollution sources are scattered, pollutants are diverse, and pollution loads vary greatly over time and space, leading to ecological fragility in riparian areas and difficulties in pollution management. In order to understand the distribution characteristics of N and P in soils and their ecological and environmental risks in the riparian zone of the Yanhe River Basin in northern Shaanxi Province, this study investigated the characteristics of N and P in the surface sediments of the riparian zone and their spatial and temporal distributions by means of on-site testing, spatial analysis, and mathematical statistics, and made a preliminary assessment of their environmental risks by using the risk assessment index method in order to explore the ecological and environmental risks in the riparian zone of the Yanhe River Basin. The results showed that total nitrogen (TN) had a certain pooling effect at the basin scale. TN content was higher in dry water period, smaller in rich water period and flat water period, and the trend of Total phosphorus (TP) content was not obvious in both space and time scale. The surface sediments in the riparian zone of the Yanhe River Basin are mildly to moderately polluted, and the nitrogen and phosphorus contents of the sediments are easily affected by soil water content (SWC), soil bulk density (BD) and land use (LULC) on the bank. These results provide a certain basis for watershed management and ecological environmental protection in northern Shaanxi, and are of great significance in promoting ecological restoration and sustainable development in the Yanhe River basin.

The Gadadhar River is characterized by dynamic processes that shape its channel and behaviour over time. The highly sinuous meandering channel of the Gadadhar River induces geomorphic hazards in both Cooch Behar and Alipurduar districts of West Bengal. The present study assessed changes in channel geometry, including channel width, sinuosity, meander length, radius of curvature and amplitude of meander loops, in the Gadadhar River from 1992 to 2022. For this effective study, Landsat 5 (TM), Landsat 7 (ETM +) and Landsat 8 (OLI) satellite images were used. The results reveal significant spatiotemporal changes in the channel geometry of the Gadadhar River. Over the studied period, the channel width has experienced fluctuations, with Reach A showing a net increase of 23.79 m, Reach B widening by 44.81 m and Reach C experiencing a narrowing of 35.45 m. The meander geometry analysis reveals dynamic shifts in meander amplitude (MA), meander belt width (MBW) and radius of curvature (RC) across key bends such as Karjipara, Santoshpur and Dhadial, with complex trends influenced by neck cut-off formations. The bend tightness index (BTI) fluctuated, with minimum values recorded in 1998 (0.85) and a maximum in 2010 (1.31), indicating variability in the structural integrity of meander bends. Additionally, the channel length exhibited significant variations, with a notable decline of 4.18 km between 2016 and 2022, underscoring the dynamic response of the river. We also observed the formation of meander cut-offs, in which the river carves new channels, creating shortcuts that escape previous meander bends. The research also points out the sites where meander cutoffs have been formed and probable sites where meander cutoffs may occur. Overall, this study provides valuable insights into spatiotemporal changes in channel geometry and meander cutoff formation in the Gadadhar River, which is crucial for effective river management.

Investigating the effect of gravity on the flow characteristics of granular materials is crucial for a deeper understanding of geological hazards on Earth and other celestial bodies. This research employs discrete element numerical simulation methods to systematically analyze the dynamic process of granular system collapse and flow under varying gravity conditions. By analyzing the collapse initiation angle, flow velocity, and energy evolution of the granular system at different time intervals, the study reveals that as gravity increases, both the average flow velocity and the front velocity of the granular system significantly increase. After normalizing the particle flow velocity, the velocity curves converge, indicating that both the flow velocity and duration are proportional to gravity. Higher gravity levels accelerate the accumulation of kinetic energy in the granular system, but once the kinetic energy reaches its peak, its dissipation rate also increases significantly. The energy dissipation, horizontal displacement, and evolution time of the granular system exhibit a power-law relationship with gravity. This research provides significant scientific value for further understanding the collapse and flow characteristics of granular systems in geological hazards on Earth and other extraterrestrial bodies.

Monitoring and evaluating groundwater resources is crucial as the rapid pollution challenges confronting surface water resources intensify. Failing to do so could have an adverse impact on various sectors of a nation’s economy. In this study, the groundwater quality of communities within the vicinities of the Volta Lake and Akosombo Dam in Ghana was comprehensively assessed for drinking and irrigation using multi-methodological approach. Standard experimental procedures were followed in the analysis of 107 groundwater samples. The samples showed hydrochemical concentrations in the order: TDS > HCO₃^– > Na⁺ > SO₄^2– > Mg²⁺ > Cl^– > K⁺ > NO₃^– > CO₃^2– > F^–. The pH values were alkaline (> 7.0), indicating ionized groundwaters. A high F^– concentration (3.8 mg/l) was observed in one sample. Most had acceptable NO₃^– levels (< 50 mg/l), except in four locations with levels > 80 mg/l, which could lead to chronic diseases. Overall index of pollution (OIP) ranged from 0.10 to 0.92, indicating excellent drinking water. Contrarily, the groundwater samples were categorized as excellent (48.50%), good (49.53%), and poor (1.87%) by the water quality index (WQI). The OIP and WQI consistently ranked the groundwater suitability and their spatial maps showed fewer desirable sources in the western part, while the southeastern part had the best quality water. Groundwater mineralization was influenced by natural processes and human activities, per multivariate statistical analysis. Most irrigation water quality indices indicated unsuitability of majority of groundwater stations for irrigation. For both drinking and irrigation water quality predictions, multilinear regression and artificial neural network models performed well with low model errors and R² > 0.90. It was indicated that Na⁺ had a major influence on the irrigation water quality prediction. These findings have significant implications for groundwater monitoring and protection, in the region and beyond.