Search Results (1,357)

Background/Objectives: In recent years, the discharge of antibiotics into rivers and irrigation canals has increased. However, few studies have addressed the impact of these compounds on agricultural fields that use such water to meet crop demands. Methods: In this study, the transport of two types of gentamicin (pure gentamicin and gentamicin sulfate) was modeled at concentrations of 150 and 300 μL/L, respectively, in a soil with more than 60 years of agricultural use. Infiltration tests under constant head conditions and gentamicin transport experiments were conducted in acrylic columns measuring 14 cm in length and 12.7 cm in diameter. The scaling parameters for the Richards equation were obtained from experimental data, while those for the advection–dispersion equation were estimated using inverse methods through a nonlinear optimization algorithm. In addition, a fractal-based model for saturated hydraulic conductivity was employed. Results: It was found that the dispersivity of gentamicin sulfate is 3.1 times higher than that of pure gentamicin. Based on the estimated parameters, two simulation scenarios were conducted: continuous application of gentamicin and soil flushing after antibiotic discharge. The results show that the transport velocity of gentamicin sulfate in the soil may have short-term consequences for the emergence of resistant microorganisms due to the destination of wastewater containing antibiotic residues. Conclusions: Finally, further research is needed to evaluate the impact of antibiotics on soil physical properties, as well as their effects on irrigated crops, animals that consume such water, and the soil microbiota. Full article

Environmental noise is inevitable during seismic data acquisition, with major sources including heavy machinery, rivers, wind, and other environmental factors. During field data acquisition, it is important to assess the impact of environmental noise and evaluate data quality. In subsequent seismic data processing, these noise components also need to be eliminated. Accurate identification of noise traces facilitates rapid quality control (QC) during fieldwork and provides a reliable basis for targeted noise attenuation. Conventional environmental noise identification primarily relies on amplitude differences. However, in seismic data, high-amplitude signals are not necessarily caused by environmental noise. For example, surface waves or traces near the shot point may also exhibit high amplitudes. Therefore, relying solely on amplitude-based criteria has certain limitations. To improve noise identification accuracy, we use the Mel-spectrogram to extract features from seismic data and construct the dataset. Compared to raw time-series signals, the Mel-spectrogram more clearly reveals energy variations and frequency differences, helping to identify noise traces more accurately. We then employ a Vision Transformer (ViT) network to train a model for identifying noise in seismic data. Tests on synthetic and field data show that the proposed method performs well in identifying noise. Moreover, a denoising case based on synthetic data further confirms its general applicability, making it a promising tool in seismic data QC and processing workflows. Full article

The placement of hydraulic elements in existing pool-type fishways to make them more suitable for Cyprinid fish is an issue of increasing interest in fishway research. Hydrodynamic characteristics and fish behavior at the representative pool of the fishway with bottom orifices and notches were assessed at the Dagdelen hydropower plant in the Ceyhan River Basin, Türkiye. Three-dimensional velocity measurements were taken in the pool of the fishway using an Acoustic Doppler velocimeter. The measurements were taken with and without a brush block at two different vertical distances from the bottom, which were below and above the level of bristles tips. A computational fluid dynamics (CFD) analysis was conducted for the studied fishway. The numerical model utilized Large Eddy Simulation (LES) combined with the Darcy–Forchheimer law, wherein brush blocks were represented as homogenous porous media. Our results revealed that the relative submergence of bristles in the brush block plays a very important role in velocity and Reynolds shear stress (RSS) distributions. After the placement of the submerged brush block, flow velocity and the lateral RSS component were reduced, and a resting area was created behind the brush block below the bristles’ tips. Fish movements in the pool were recorded by underwater cameras under real-time operation conditions. The heatmap analysis, which is a 2-dimensional fish spatial presence visualization technique for a specific time period, showed that Capoeta damascina avoided the areas with high turbulent fluctuations during the tests, and 61.5% of the fish presence intensity was found to be in the low Reynolds shear regions in the pool. This provides a clear case for the real-world ecological benefits of retrofitting existing pool-weir fishways with such flexible hydraulic elements. Full article

Freshwater ecosystems—home to roughly 10% of known species—are losing biodiversity to river-morphology alteration, hydraulic infrastructure, and pollution, yet most ecological network (EN) studies focus on terrestrial systems and overlook hydrological connectivity under human disturbance. To address this, we devised and tested a dual EN framework in the Yangtze River Delta’s Ecological Green Integration Demonstration Zone, constructing freshwater and terrestrial networks independently before merging them. Using InVEST Habitat Quality, MSPA, the MCR model, and Linkage Mapper, we delineated sources and corridors: freshwater sources combined NDWI-InVEST indicators with a modified, sluice-weighted resistance surface, producing 78 patches (mean 348.7 ha) clustered around major lakes and 456.4 km of corridors (42.50% primary). Terrestrial sources used NDVI-InVEST with a conventional resistance surface, yielding 100 smaller patches (mean 121.6 ha) dispersed across woodlands and agricultural belts and 658.8 km of corridors (36.45% primary). Unified models typically favor large sources from dominant ecosystems while overlooking small, high-value patches in non-dominant systems, generating corridors that span both freshwater and terrestrial habitats and mismatch species migration patterns. Our dual framework better reflects species migration characteristics, accurately captures dispersal paths, and successfully integrates key agroforestry-complex patches that unified models miss, providing a practical tool for biodiversity protection in disturbed freshwater–terrestrial landscapes. Full article

Arid regions, while providing essential ecosystem services, are among the most ecologically vulnerable worldwide. Understanding and monitoring their long-term vegetation dynamics is essential for accurate environmental assessment and climate adaptation strategies. This study examined the spatiotemporal variations and driving forces of the vegetation dynamics in arid Northwestern China during 2000 to 2020, using the annual peak fractional vegetation cover (FVC) as the primary indicator. The Sen’s slope estimator with the Mann–Kendall test and the coefficient of variation were employed to assess the spatiotemporal variations in FVC, while the Pearson correlation, geographic detector model and random forest model were applied to identify the dominant driving factors for FVC. The results indicated that (1) overall vegetation cover was low (averaged peak FVC = 0.191), showing a spatial pattern of higher values in the northwest and lower values in the southeast; high FVC values were primarily observed in mountainous areas and river corridors; (2) the annual peak FVC increased significantly at a rate of 0.0508 yr⁻¹, with 33.72% of the region showing significant improvements and 5.49% degradation; (3) the spatial pattern of FVC was shaped by the distribution of land use types (59.46%), while the temporal dynamics of FVC were driven by land use changes (16.37%) and the land use intensity (37.56%); (4) both the spatial pattern and the temporal dynamics were limited by the environmental conditions. These findings highlight the critical role of anthropogenic activities in shaping the spatiotemporal variations in FVC, particularly emphasizing the distinct contributions of changes in land use types and land use intensity. This study could provide a scientific basis for sustainable land management and restoration strategies in arid regions facing global changes. Full article

Given that the Sunkoshi River watershed (located in the southern foot of the Himalayas) is sensitive to climate change and its mountain ecosystem provides important services, we aim to evaluate its spatial and temporal variation patterns of vegetation, represented by the Normalized Difference Vegetation Index (NDVI), during 2000–2021 and identify the dominant driving factors of vegetation change. Based on the NDVI dataset (MOD13A1), we used the simple linear trend model, seasonal and trend decomposition using loess (STL) method, and Mann–Kendall test to investigate the spatiotemporal variation features of NDVI during 2000–2021 on multiple scales (annual, seasonal, monthly). We used the partial correlation coefficient (PCC) to quantify the response of the NDVI to land surface temperature (LST), precipitation, humidity, and soil moisture. The results indicate that the annual NDVI in 52.6% of the study area (with elevation of 1–3 km) increased significantly, while 0.9% of the study area (due to urbanization) degraded significantly during 2000–2021. Daytime LST dominates NDVI changes on spring, summer, and winter scales, while precipitation, soil moisture, and nighttime LST are the primary impact factors on annual NDVI changes. After removing the influence of soil moisture, the contributions of climate factors to NDVI change are enhanced. Precipitation shows a 3-month lag effect and a 5-month cumulative effect on the NDVI; both daytime LST and soil moisture have a 4-month lag effect on the NDVI; and humidity exhibits a 2-month cumulative effect on the NDVI. Overall, the study area turned green during 2000–2021. The dominant driving factors of NDVI change may vary on different time scales. The findings will be beneficial for climate change impact assessment on the regional eco-environment, and for integrated watershed management. Full article

The flow characteristics at the tributary entrance are crucial for ensuring safe navigation where the main channel and tributary converge. Along the inter-basin canal, numerous tributaries feature large confluence angles and significant flow discharge ratios. An experimental study investigated how these factors influence flow patterns, leading to proposed mitigation measures. This research employed a 1:50-scale physical river model and a sediment deposition model. It analyzed navigable flow conditions including velocity, flow patterns, the confluence ratio, the bottom elevation difference, and the confluence angle at the main channel–tributary junction. Focusing on the Jiuzhou River tributary entrance (Pinglu Canal), which has a large confluence ratio, significant bottom elevation difference, and wide confluence angle, this study tested two solutions: a single energy dissipator and a combined energy dissipator system. Sediment deposition modeling compared the effectiveness of these approaches. The results showed that implementing a steep slope with a three-stage stilling pool in the Jiuzhou River entrance section effectively manages confluences with large elevation differences, wide angles, and high flow discharge ratios. This configuration significantly improves entrance flow characteristics. Full article

As a result of the catalytic decomposition of H₂O₂, hydroxyl radicals are produced. Hydroxyl radicals are strong oxidants and effectively inactivate bacteria, ensuring water disinfection without toxic chlorinated organic by-products. The kinetics of bacterial inactivation were studied in a laboratory-scale flow catalytic reactor. A granular cobalt ferrite catalyst was thoroughly characterized using XRD and XRF techniques, SEM with EDS, and Raman spectroscopy. At lower H₂O₂ concentrations, H₂O₂ decomposition follows first-order reaction kinetics. At higher H₂O₂ concentrations, the obtained kinetics lines suggest that the reaction order increases. The kinetics of bacterial inactivation in the developed flow reactor depends largely on the initial number of bacteria. The initial bacterial concentrations in laboratory tests were within the range typical of real river water. A regression model was developed that relates the degree of bacterial inactivation to the initial number of bacteria, the initial H₂O₂ concentration, and the contact time of water with the catalyst. Full article

Water quality should be tested to ensure it is acceptable for the healthy growth of plants and animals, and water hardness is one of the important testing indexes. Herein, a novel approach was proposed to achieve high accuracy and rapid quantitative analyses of water hardness by combining one-point calibration laser-induced breakdown spectroscopy (OPC–LIBS) and aerosolization. First, the water samples are aerosolized via the aerosol generation device and the LIBS spectra of aerosols are obtained. Then, a modified OPC–LIBS model is used to determine the elemental contents of the aerosols via LIBS spectra, in which the plasma temperature is calculated using the Multi-Element Saha–Boltzmann (ME–SB) plot. One suitable standard liquid sample (the concentrations of Ca, Mg, and Sr were 50 mg/L, 50 mg/L, and 500 mg/L, respectively) was selected to evaluate the quantitative performance of the modified OPC–LIBS. Then, the Ca and Mg concentrations in the three real water samples (from the Yangtze River, reservoir, and underground) were detected and quantified by the proposed method, and the quantitative results of three LIBS calibration methods were compared with that of inductively coupled plasma optical emission spectroscopy (ICP–OES). The average relative error of Ca and Mg found in the OPC–LIBS results was lower by 22.23% than the internal standard method and 14.50% lower than the external standard method. The method combining modified OPC–LIBS and aerosolization can achieve high-precision rapid quantification of water hardness detection, which provides a new path for rapid detection of water hardness and is expected to make online detection a reality in the water quality testing field. Full article

In this study, Sr_0.95Bi_0.05TiO₃ was synthesized via solid state reaction, characterized, and applied as a visible-light-active photocatalyst for the degradation of oxytetracycline, imidacloprid, and their mixture. To evaluate the influence of the aqueous matrix on pollutant degradation, photocatalytic experiments were carried out in both distilled water and a real environmental sample (surface water). The Sr_0.95Bi_0.05TiO₃ perovskite showed high photocatalytic performance under visible light, achieving nearly complete degradation of oxytetracycline after 2 h, and significant removal of imidacloprid in river water (60% after 3 h). Enhanced degradation in surface water was attributed to favorable ionic composition and pH. The perovskite oxide maintained its photocatalytic performance over five consecutive cycles, with no significant loss in photocatalytic activity or structural and morphological stability. Ecotoxicological assessment using Daphnia magna confirmed that the treated water was non-toxic, indicating that no harmful byproducts were formed. Complementary Density Functional Theory calculations were conducted to complement experimental findings, providing insights into the structural, electronic, and optical properties of the photocatalyst, enhancing the understanding of the degradation mechanisms involved. This integrated approach, combining experimental photocatalytic performance evaluation in different matrices, ecotoxicity testing, and theoretical modeling, highlights Sr_0.95Bi_0.05TiO₃ as a promising, stable, and environmentally safe photocatalyst for practical wastewater treatment applications. Full article

The energy quota trading policy is a pivotal market-oriented environmental regulation policy that propels the reform of the energy structure. Utilizing panel data from 30 provinces in China covering the period from 2012 to 2022, this study employed a difference-in-differences model to systematically examine the influence of the energy quota trading policy on the decarbonization of energy consumption, and further explores two transmission mechanisms of green technology innovation and energy consumption intensity through mechanism tests. The study reveals several key findings: (1) The energy quota trading policy significantly enhances the decarbonization of energy consumption. (2) This policy encourages the adoption of clean energy by fostering green technological innovation and decreasing overall energy consumption. As a result, it makes a considerable contribution to the decarbonization process in energy usage. (3) The heterogeneity analysis demonstrates that in areas with low levels of industrialization and plentiful resources, as well as within the Yangtze River Economic Belt and the central and western regions, the effects of the policy are significantly more pronounced. Conversely, in regions characterized by high industrialization and limited resources, particularly in the eastern region, the effectiveness of the policy is comparatively diminished. Furthermore, this study not only offers empirical evidence supporting the optimization and enhancement of the energy quota trading policy but also presents recommendations for improving the trading market, regional policies, and fostering green technological innovation. Full article

Accurate estimation of forest carbon stock is critical for understanding ecosystem carbon dynamics and informing climate mitigation strategies. This study presents a deep learning framework that integrates Sentinel-2 multispectral imagery with an enhanced residual neural network for estimating aboveground forest carbon stock in the Liuchong River Basin, Bijie City, Guizhou Province, China. The proposed model incorporates multiscale residual blocks and channel attention mechanisms to improve spatial feature extraction and spectral dependency modeling. A dataset of 150 ground inventory plots was employed for supervised training and validation. Comparative experiments with Random Forest, Gradient Boosting Decision Trees (GBDT), and Vision Transformer (ViT) demonstrate that the enhanced ResNet achieves the best performance, with a root mean square error (RMSE) of 23.02 Mg/ha and a coefficient of determination ($R^2$) of 0.773 on the test set. Spatial mapping results further reveal that the model effectively captures fine-scale carbon stock variations across mountainous forested landscapes. These findings underscore the potential of combining multispectral remote sensing and advanced neural architectures for scalable, high-resolution forest carbon estimation in complex terrain. Full article

Additive manufacturing (AM) has brought significant breakthroughs to the construction sector, such as the ability to fabricate complex geometries, enhance efficiency, and reduce both material usage and construction waste. However, several challenges must still be addressed to fully transition from conventional construction practices to innovative and sustainable green alternatives. This study investigates the use of non-cementitious traditional mixtures for green construction applications through 3D printing using Liquid Deposition Modeling (LDM) technology. To explore the development of mixtures with enhanced physical and mechanical properties, natural pine and cypress wood shavings were added in varying proportions (1%, 3%, and 5%) as sustainable additives. The aim of this study is twofold: first, to demonstrate the printability of these eco-friendly mortars that can be used for conservation purposes and overcome the challenges of incorporating bio-products in 3D printing; and second, to develop sustainable composites that align with the objectives of the European Green Deal, offering low-emission construction solutions. The proposed mortars use hydrated lime and natural pozzolan as binders, river sand as an aggregate, and a polycarboxylate superplasticizer. While most studies with bio-products focus on traditional methods, this research provides proof of concept for their use in 3D printing. The study results indicate that, at low percentages, both additives had minimal effect on the physical and mechanical properties of the tested mortars, whereas higher percentages led to progressively more significant deterioration. Additionally, compared to molded specimens, the 3D-printed mortars exhibited slightly reduced mechanical strength and increased porosity, attributable to insufficient compaction during the printing process. Full article

Background: Inflammation and oxidative stress are key mechanisms in underlying skin conditions like psoriasis and eczema. While many plants, including Australian native plants, are proposed to target these pathways due to their phytochemical content, studies on whole extracts and their synergistic effects remain limited. Objectives: This study aimed to investigate individual and combined effects of whole plant extracts on skin protection and healing, focusing on their anti-inflammatory and antioxidant properties. Methods: The antioxidant potential of the individual and combined plant extracts were investigated on 2,2-diphenyl-1-picrylhydrazyl (DPPH) and reactive oxygen species (ROS) assay followed by luciferase assay in MCF-7 AREc32 cells for nuclear factor erythroid 2-related factor 2 (Nrf2) activation. The anti-inflammatory activities were investigated on lipopolysaccharide (LPS)-induced RAW 264.7 murine macrophages for the inhibition of nitric oxide (NO), tumour necrosis factor (TNF)-α, and interleukin (IL)-6. Synergistic interaction was determined by the combination index model (CI < 1). Combination(s) showing synergistic and optimal activity were further investigated on LPS-induced human dermal fibroblasts (HDF) cells for IL-6 inhibition and wound healing activity. Results: Three of the tested Australian native plant extracts demonstrated prominent antioxidant and anti-inflammatory activities including bitter orange, mountain pepper berry and native river mint. In particular, their three-way combination (1:1:1, w/w) showed prominent synergistic (CI < 1) in reducing NO and IL-6, along with enhanced Nrf2 activation. In LPS-inflamed HDF cells, the combination maintained synergistic inhibition of IL-6 levels and promoted wound healing response. Conclusions: These findings highlight the therapeutic potential of Australian native plant as a whole extract for skin protection and repair attributed to antioxidant and anti-inflammatory activities. The observed synergistic anti-inflammatory and antioxidant effects support their use in the development of new cosmetic formulations for skin. Full article

Flow regulation and water quality maintenance are considered ecosystem services, as they provide environmental benefits with a measurable economic value to society. Distributed or semi-distributed hydrological models can help identify where land use decisions yield the greatest economic and environmental returns related to water resources. For these reasons, this study integrated simulations performed with the SWAT (Soil and Water Assessment Tool) model under varying land use conditions, aiming to balance potential benefits with the loss of ecosystem services. Among the tested parameters, those associated with surface runoff showed the highest sensitivity in simulating streamflow for the Jundiaí River Basin. Based on the statistical indicators R², Nash–Sutcliffe efficiency (NS), and Percent Bias (PBIAS), the SWAT model demonstrated a reliable performance in replicating observed streamflows on a monthly scale, even with limited spatially distributed input data. Scenario 2, which involved converting 15% of pasture/agricultural land into forest, yielded the most favorable hydrological outcomes by increasing soil water infiltration and aquifer recharge while reducing surface runoff and sediment yield. These findings highlight the value of reforestation and land use planning as effective strategies for improving watershed hydrological performance and ensuring long-term water sustainability. Full article