An analytical methodology was developed for the first time in this work enabling the simultaneous enantiomeric separation of the fungicide fenpropidin and its acid metabolite by Capillary Electrophoresis. A dual cyclodextrin system consisting of 4 % (w/v) captisol with 10 mM methyl-beta-cyclodextrin was employed in a 100 mM sodium acetate buffer at pH 4.0. Optimal experimental conditions (temperature 25 degrees C, separation voltage -25 kV, and hydrodynamic injection of 50 mbar x 10 s) allowed the simultaneous separation of the four enantiomers in <10.7 min with resolutions of 3.1 (fenpropidin) and 3.2 (its acid metabolite). Analytical characteristics of the method were evaluated and found adequate for the quantification of both chiral compounds with a linearity range from 0.75 to 70 mg L-1, good accuracy (trueness included 100 % recovery, precision with RSD<6 %), and limits of detection and quantification of 0.25 and 0.75 mg L-1, respectively, for the four enantiomers. No significant differences were found between the concentrations determined and labelled of fenpropidin in a commercial agrochemical formulation. The stability over time (0-42 days) of fenpropidin enantiomers using the commercial agrochemical formulation was evaluated in two sugar beet soils, revealing to be stable at any time in one sample, while in the other a decrease of 45 % was observed after 42 days. Individual and combined toxicity of fenpropidin and its metabolite was determined for the first time for marine organism Vibrio fischeri, demonstrating higher damage caused by parent compound. Synergistics and antagonists' interactions were observed at low and high effects levels of contaminants.

The root-knot nematode, Meloidogyne javanica, is one of the most damaging plant-parasitic nematodes, affecting chickpea and causing substantial yield losses worldwide. The damage potential and population dynamics of this nematode in chickpea in Ethiopia have yet to be investigated. In this study, six chickpea cultivars were tested using 12 ranges of initial population densities (Pi) of M. javanica second-stage juveniles (J2): 0, 0.125, 0.25, 0.5, 1, 2, 4, 8, 16, 32, 64 and 128 J2 (g dry soil)-1 in a controlled glasshouse pot experiment. The Seinhorst yield loss and population dynamics models were fitted to describe population development and the effect on different measured growth variables. The tolerance limit (TTFW) for total fresh weight ranged from 0.05 to 1.22 J2 (g dry soil)-1, with corresponding yield losses ranging from 31 to 64%. The minimum yield for seed weight (mSW) ranged from 0.29 to 0.61, with estimated yield losses of 71 and 39%. The 'Haberu' and 'Geletu' cultivars were considered good hosts, with maximum population densities (M) of 16.27 and 5.64 J2 (g dry soil)-1 and maximum multiplication rate (a) values of 6.25 and 9.23, respectively. All other cultivars are moderate hosts for M. javanica; therefore, it is crucial to initiate chickpea-breeding strategies to manage the tropical root-knot nematode M. javanica in Ethiopia.

Ensuring the accuracy of free-field inversion is crucial in determining seismic excitation for soil-structure interaction (SSI) systems. Due to the spherical and cylindrical diffusion properties of body waves and surface waves, the near-fault zone presents distinct free-field responses compared to the far-fault zone. Consequently, existing far-fault free-field inversion techniques are insufficient for providing accurate seismic excitation for SSI systems within the near-fault zone. To address this limitation, a tailored near-fault free-field inversion method based on a multi-objective optimization algorithm is proposed in this study. The proposed method establishes an inversion framework for both spherical body waves and cylindrical surface waves and then transforms the overdetermined problem in inversion process into an optimization problem. Within the multi-objective optimization model, objective functions are formulated by minimizing the three-component waveform differences between the observation point and the delayed reference point. Additionally, constraint conditions are determined based on the attenuation property of propagating seismic waves. The accuracy of the proposed method is then verified through near-fault wave motion characteristics and validated against real downhole recordings. Finally, the application of the proposed method is investigated, with emphasis on examining the impulsive property of underground motions and analyzing the seismic responses of SSI systems. The results show that the proposed method refines the theoretical framework of near-fault inversion and accurately restores the free-field characteristics, particularly the impulsive features of near-fault motions, thereby providing reliable excitation for seismic response assessments of SSI systems.

In geotechnical engineering, the development of efficient and accurate constitutive models for granular soils is crucial. The micromechanical models have gained much attention for their capacity to account for particle-scale interactions and fabric anisotropy, while requiring far less computational resources compared to discrete element method. Various micromechanical models have been proposed in the literature, but none of them have been conclusively shown to agree with the critical state theory given theoretical proof, despite the authors described that their models approximately reach the critical state. This paper modifies the previous CHY micromechanical model that is compatible with the critical state theory based on the assumption that the microscopic force-dilatancy relationship should align with the macroscopic stress-dilatancy relationship. Moreover, under the framework of the CHY model, the fabric anisotropy can be easily considered and the anisotropic critical state can be achieved with the introduction of the fabric evolution law. The model is calibrated using drained and undrained triaxial experiments and the results show that the model reliably replicates the mechanical behaviors of granular materials under both drained and undrained conditions. The compatibility of the model with the critical state theory is verified at both macroscopic and microscopic scales.

Pile foundations are frequently used in the construction of bridges, offshore platforms, and offshore wind turbines, which are often subjected to complex lateral cyclic loading from wind, wave, or current. These lateral loads usually come from different directions or constantly change their direction, which is ignored by most existing calculation models. A two-dimensional p -y model is proposed in this study for the lateral response of the pile subjected to multi-directional cyclic loading in sand. Without introducing additional parameters, the p -y response in two dimensions is coupled by developing the model within the framework of the bounding surface p -y model. Combined with the collapse and recompression model, the effect of sand collapse around the pile during cyclic loading is considered to approach reality. The pile lateral displacement and soil resistance are obtained in incremental form using the finite difference method in the two-dimensional case. By comparing with the model test results, it is demonstrated that the proposed model is able to reasonably predict the lateral cyclic response of the pile as well as the effects of multi-directional cyclic loading. The distribution and variation characteristics of the soil resistance are further discussed by analyzing the results calculated by the proposed model.

Large-diameter monopiles of offshore wind turbines are subjected to continuous multistage cyclic loads of different types (one-way or two-way) and loading amplitudes over time. The loading history is likely to affect the lateral response during the subsequent loading stage. This paper conducts a systematic study on the lateral response of monopiles with and without reinforcement in multilayer soil. Two groups of monotonic centrifuge tests of monopiles with and without reinforcement are carried out to compare and study the influence of reinforcement on the displacement, bending moment and earth pressure of monopile foundations. Local reinforcement in the shallow layer effectively improved the bearing capacity of the monopile foundation. The ultimate bearing capacity of monopile foundations in monotonic tests provides a load basis for cyclic tests. Four groups of continuous multistage cyclic centrifuge tests of monopiles with and without reinforcement with different cyclic modes and loading amplitudesare carried out to investigate the influence of loading history on the lateral cumulative displacement, unloading secant stiffness and bending moment. Empirical design recommendations for monopiles under continuous multistage cyclic loads with different cyclic modes and loading amplitudes are provided based on the results of the tests.

This study presents a hierarchical multiscale approach that combines the finite-element method (FEM) and the discrete-element method (DEM) to investigate tunneling-induced ground responses in coarse-grained soils. The approach considers both particle-scale physical characteristics and engineering-scale boundary value problems (BVPs) simultaneously, accurately reproducing typical tunneling-induced mechanical responses in coarsegrained soils, including soil arching and ground movement characteristics observed in laboratory tests and engineering practice. The study also unveils particle-scale mechanisms responsible for the evolution of soil arching through the underlying DEM-based RVEs. The results show that the rearrangement of microstructures and the deflection of strong contact force chains drive the rotation of macroscopic principal stress and the formation of soil arch. The microscopic fabric anisotropy direction can serve as a quantitative indicator for characterizing soil arching zones. Moreover, the effects of particle size distributions (PSD) and soil densities on ground deformation patterns are interpreted based on the stress-strain responses and contact network characteristics of DEM RVEs. These multiscale insights enrich the knowledge of tunneling-induced ground responses and the same approach can be applied to other geotechnical engineering analyses in coarse-grained soils.

Land surface temperature (LST) plays an important role in Earth energy balance and water/carbon cycle processes and is recognized as an Essential Climate Variable (ECV) and an Essential Agricultural Variable (EAV). LST products that are issued from satellite observations mostly depict landscape-scale temperature due to their generally large footprint. This means that a pixel-based temperature integrates over various components, whereas temperature individual components are better suited for the purpose of evapotranspiration estimation, crop growth assessment, drought monitoring, etc. Thus, disentangling soil and vegetation temperatures is a real matter of concern. Moreover, most satellite-based LSTs are contaminated by directional effects due to the inherent anisotropy properties of most terrestrial targets. The characteristics of directional effects are closely linked to the properties of the target and controlled by the view and solar geometry. A singular angular signature is obtained in the hotspot geometry, i.e., when the sun, the satellite and the target are aligned. The hotspot phenomenon highlights the temperature differences between sunlit and shaded areas. However, due to the lack of adequate multi-angle observations and inaccurate portrayal or neglect of solar influence, the hotspot effect is often overlooked and has become a barrier for better inversion results at satellite scale. Therefore, hotspot effect needs to be better characterized, which here is achieved with a three-component model that distinguishes vegetation, sunlit and shaded soil temperature components and accounts for vegetation structure. Our work combines thermal infrared (TIR) observations from the Sea and Land Surface Temperature Radiometer (SLSTR) onboard the LEO (Low Earth Orbit) Sentinel-3, and two sensors onboard GEO (geostationary) satellites, i.e. the Advanced Himawari Imager (AHI) and Spinning Enhanced Visible and Infrared Imager (SEVIRI). Based on inversion with a Bayesian method and prior information associated with component temperature differences as constrained, the findings include: 1) Satellite observations throughout East Asia around noon indicate that for every 10 degrees change in angular distance from the sun, LST will on average vary by 0.6 K; 2) As a better constraint, the hotspot effect can benefit from multi-angle TIR observations to improve the retrieval of LST components, thereby reducing the root mean squared error (RMSE) from approximately 3.5 K, 5.8 K, and 4.1 K to 2.8 K, 3.5 K, and 3.1 K, at DM, EVO and KAL sites, respectively; 3) Based on a dataset simulated with a threedimensional radiative transfer model, a significant inversion error may result if the hotspot is ignored for an angular distance between the viewing and solar directions that is smaller than 30 degrees. Overall, considering the hotspot effect has the potential to reduce inversion noise and to separate the temperature difference between sunlit and shaded areas in a pixel, paving the way for producing stable temperature component products.

The Land Surface Temperature (LST) is well suited to monitor biosphere-atmosphere interactions in forests, as it depends on water availability and atmospheric/meteorological conditions above and below the canopy. Satellite-based LST has proven integral in observing evapotranspiration, estimating surface heat fluxes and characterising vegetation properties. Since the radiative regime of forests is complex, driven by canopy structure, components radiation properties and their arrangement, forest radiative temperatures are subject to strong angular effects. However, this depends on the scale of observation, where scattering mechanisms from canopy-to satellite-scales influence anisotropy with varying orders of magnitude. Given the heterogeneous and complex nature of forests, multi-angular data collection is particularly difficult, necessitating instrumentation distant enough from the canopy to obtain significant canopy brightness temperature and concurrent observations to exclude turbulence/atmospheric effects. Accordingly, current research and understanding on forest anisotropy at varying scales (from local validation level to satellite footprint) remain insufficient to provide practical solutions for addressing angular effects for upcoming thermal satellite sensors and associated validation schemes. This study presents a novel method founded in the optical remote sensing domain to explore the use of microcanopies that represent forests at different scales in the footprint of a multi-angular goniometer observing system. Both Geometric Optical (GO) and volumetric scattering dominated canopies are constructed to simulate impacts of anisotropy in heterogeneous and homogeneous canopies, and observed using a thermal infrared radiometer. Results show that heterogeneous canopies dominated by GO scattering are subject to much higher magnitudes of anisotropy, reaching maximum temperature differences of 3 degrees C off-nadir. Magnitudes of anisotropy are higher in sparse forests, where the gap fraction and crown arrangement (inducing sunlit/shaded portions of soil and vegetation) drive larger off-nadir differences. In dense forests, anisotropy is driven by viewing the maximum portion of sunlit vegetation (hotspot), where the soil is mostly obscured. Canopy structural metrics such as the fractional cover and gap fraction were found to have significant correlation with off-nadir differences. In more homogeneous canopies, anisotropy reaches a lower magnitude with temperature differences up to 1 degrees C, driven largely by volumetric scattering and components radiation properties. Optimal placement of instrumentation at the canopy-scale (more heterogeneous behaviour due to proximity to the canopy and small pixel size) used to validate satellite observations (more homogeneous behaviour due to larger pixel size) was found to be in cases of viewing maximum sunlit vegetation, for dense canopies. Given upcoming high spatial resolution sensors and associated validation schemes needed to benchmark LST and downstream products such as evapotranspiration, a better understanding of anisotropy over forests is critical to provide accurate, long-term and multi-sensor products.

The environmental prevalence of the tire wear-derived emerging pollutant N-(1,3-dimethylbutyl)-N'-phenyl-p-phenylenediamine-quinone (6PPD-Q) has increasingly raised public concern. However, knowledge of the adverse effects of 6PPD-Q on soil fauna is scarce. In this study, we elucidated its impact on soil fauna, specifically on the earthworm Eisenia fetida. Our investigation encompassed phenotypic, multi-omics, and microbiota analyses to assess earthworm responses to a gradient of 6PPD-Q contamination (10, 100, 1000, and 5000 mu g/kg dw soil). Post-28-day exposure, 6PPD-Q was found to bioaccumulate in earthworms, triggering reactive oxygen species production and consequent oxidative damage to coelomic and intestinal tissues. Transcriptomic and metabolomic profiling revealed several physiological perturbations, including inflammation, immune dysfunction, metabolic imbalances, and genetic toxicity. Moreover, 6PPD-Q perturbed the intestinal microbiota, with high dosages significantly suppressing microbial functions linked to metabolism and information processing (P < 0.05). These alterations were accompanied by increased mortality and weight loss in the earthworms. Specifically, at an environmental concentration of 6PPD-Q (1000 mu g/kg), we observed a substantial reduction in survival rate and physiological disruptions. This study provides important insights into the environmental hazards of 6PPD-Q to soil biota and reveals the underlying toxicological mechanisms, underscoring the need for further research to mitigate its ecological footprint.