Under varying flow rate conditions, the transport and retention of polydisperse microplastics (MPls), with an average particle size of 16 ± 6 µm, were investigated in saturated porous media. First-order reversible and irreversible kinetic sorption models were used to describe the sorption kinetics. Sensitivity analyses provided insight into the effects of each sorption parameter. Both numerical modeling and experimental measurements were utilized to evaluate the retention rates of sand filters. The influence of flow rate on sorption was reflected in variations in the distribution coefficient (K_d), the mass transfer coefficient (β), and the irreversible sorption rate (K₁). Lower flow rates were associated with higher K_d and β values, indicating increased sorption and reduced mass transfer rates. An increase in K_d resulted in a more gradual sorption process, with a decrease in peak concentration, whereas changes in β had a comparatively smaller impact on sorption rate and peak concentration. Lower K₁ values were linked to higher peak concentrations and decreased retention efficiency. Numerical modeling revealed retention rates of 28 ± 1% at a flow rate of 31 mL min⁻¹ and 17 ± 1% at 65 mL min⁻¹. The introduction of MPls into saturated sand environments modifies the transport dynamics within the medium. Consequently, these alterations affect the hydrological characteristics of porous media, impacting groundwater quality and agricultural output. The mean absolute error (MAE) of 6% between the modeled and observed retention rates indicated a high level of accuracy. This study underscores the importance of examining retention efficiency and the accuracy of numerical models in understanding MPl transport in porous media.

The limited availability of competent foundation soils in rapidly urbanizing regions makes construction on weak clayey deposits increasingly unavoidable. Such soils typically exhibit low shear strength, high compressibility, and pronounced deformation under undrained conditions, posing significant risks to structural safety and long-term serviceability. In this study, the effect of basalt fiber inclusion on the undrained shear behavior of clay soil obtained from the Kızılyer region of Eskişehir, Türkiye, was experimentally investigated using a ring shear apparatus. Initially, soil classification and index property tests were performed to characterize the material. Subsequently, clay specimens were reinforced with varying basalt fiber contents and subjected to large-strain shearing conditions. The evolution of peak and residual shear strength with increasing fiber dosage was systematically evaluated. The results indicate that basalt fiber reinforcement leads to a substantial enhancement in both peak and residual shear strength and contributes to improved post-peak ductility. The observed improvements are primarily attributed to fiber–soil interaction mechanisms, including tensile bridging and crack-arrest effects, which modify the failure process and delay shear localization. Overall, the findings demonstrate that basalt fiber represents an environmentally compatible and mechanically effective alternative for sustainable soil improvement applications, particularly in clayey soils subjected to undrained loading conditions.

This study concerns the transport and retention of polydisperse micron-sized (16 ± 6 µm) of microplastics (MPls) in porous media under varying flow rate conditions. Sorption kinetics were modeled using first-order reversible and irreversible kinetic sorption models, with sensitivity analyses providing insights into each sorption parameter's effect. Both numerical modeling and experimental measurements were employed to assess sand filter retention rates. The impact of flow rate on sorption reveals variations in distribution coefficient (Kd), mass transfer coefficient (β), and irreversible sorption rate (K1). Lower flow rates are correlated with higher Kd and β values, indicating an increase in sorption and diminished mass transfer rates. The findings revealed that an increase in Kd resulted in a more gradual sorption process with a decrease in peak concentration, whereas changes in β influenced the rate of sorption and peak concentration to a lesser extent compared to Kd. Lower K1 values are associated with higher peak concentrations and decreased retention efficiency. Retention rates were evaluated by a numerical model and found as 28 ± 1% at a flow rate of 31 ml min⁻¹ and 17 ± 1% at 65 ml min⁻¹. The introduction of MPls into soil environments has been noted to modify transport dynamics into soil. As a result, these alterations effects hydrological characteristics of soil, thereby impacting quality of groundwater and agricultural output. The mean absolute error (MAE) of 6% between modeled and observed retention rates suggests minor discrepancies. This study highlights the importance of examining retention efficiency and the accuracy of numerical models in porous media during MPl transport.

Physical and chemical processes related to global and regional climate changes are important factors in shaping the Earth’s surface. These processes form various erosion and deposition landforms on the Earth’s surface. These landforms reflect the traces of past and present climate conditions. This study shows that geomorphometric parameters can effectively distinguish between geomorphometrically and climatically distinct geomorphic provinces. In this context, supervised machine learning models were developed using geomorphometric parameters and the Köppen-Geiger climate classes observed in Türkiye. These models, Random Forest, Support Vector Machines, and K-Nearest Neighbor algorithms, were developed using a training data set. Classification analysis was performed using these models and a test dataset that was independent of the training dataset. According to the classification results, the overall accuracy values for the Random Forest, Support Vector Machines, and K-Nearest Neighbor models were calculated as 99.27%, 99.70%, and 99.30%, respectively. The corresponding kappa values were 0.99, 0.99, and 0.99, respectively. This study shows that among the geomorphometric parameters used in the analyses, maximum altitude, elevation, and valley depth were determined as important parameters in distinguishing geomorphic provinces.

Climate change is increasingly altering forest ecosystems worldwide, reshaping species phenology, productivity, and resilience. In this study, we evaluate the phenoclimatic responses of European beech (Fagus sylvatica L.) forests across Europe by assessing their phenological responses to climate change across climatic zones and altitudinal gradients using remote-sensing data. We used 24 years of satellite-derived land-surface phenology and climate data to quantify phenological trends at 356 beech-dominant locations from the EUFGIS database, of which 274 remained after land-cover homogeneity and data-quality filtering. To reduce land-cover mixing at the MODIS resolution, we applied a land-cover homogeneity filter based on ESA WorldCover. The analysis was structured across the seven climatic zones in Europe. Phenological responses to climate change were assessed through climate–phenology sensitivity analyses and a composite phenoclimatic departure index integrating climatic trends, phenological shifts, and interannual variability. Phenological sensitivity varied across climatic zones and phenological phases. Temperature-related sensitivity was most evident in spring in several continental zones, whereas precipitation sensitivity was more apparent for growing-season length and autumn timing in some regions. The composite phenoclimatic departure analysis showed that regional profiles were not uniform across the European beech range. Although warming was widespread, precipitation trends, phenological shifts, and interannual variability differed strongly among zones. These findings demonstrate heterogeneous and location-specific phenoclimatic responses across Europe, but the departure index should not be interpreted as a direct measure of ecological vulnerability or risk.