This research explores the stabilization of clay soil through the application of geopolymer binder derived from silicomanganese slag (SiMnS) and activated by sodium hydroxide (NaOH). This research aims to evaluate the effects of key parameters, including the percentage of slag, the activator-to-stabilizer ratio, and curing conditions (time and temperature), on the mechanical properties of the stabilized soil. Unconfined compressive strength (UCS) tests were conducted to assess improvements in soil strength, while scanning electron microscopy (SEM) was employed to analyze the microstructural changes and stabilization mechanisms. The results demonstrated that clay soil stabilized with SiMnS-based geopolymers exhibited significant strength enhancement. Specifically, the sample stabilized with 20% SiMnS and an activator-to-slag ratio of 1.6, cured at room temperature for 90 days, achieved a UCS of 27.03 kg & frasl;cm2. The uniaxial strength was found to be positively correlated with the SiMnS content, activator ratio, curing time, and temperature. Additionally, the strain at failure remained below 1.5% for all samples, indicating a marked improvement in soil stiffness. SEM analysis revealed that geopolymerization led to the formation of a dense matrix, enhancing soil particle bonding and overall durability. These results emphasize the potential of SiMnS-based geopolymers as a sustainable and effective soil stabilizer for geotechnical applications.

Expansive soil, characterized by significant swelling-shrinkage behavior, is prone to cracking under wet-dry cycles, severely compromising engineering stability. This study combines experimental and molecular dynamics (MD) simulation approaches to systematically investigate the improvement effects and micromechanisms of polyvinyl alcohol (PVA) on expansive soil. First, direct shear tests were conducted to analyze the effects of PVA content (0 %-4 %) and moisture content (30 %-50 %) on the shear strength, cohesive force, and internal friction angle of modified soil. Results show that PVA significantly enhances soil cohesive force, with optimal improvement achieved at 3 % PVA content. Second, wet-dry cycle experiments revealed that PVA effectively suppresses crack propagation by improving tensile strength and water retention. Finally, molecular dynamics simulations uncovered the distribution of PVA between montmorillonite (MMT) layers and its influence on interfacial friction behavior. The simulations demonstrated that PVA forms hydrogen bonding networks, enhancing interlayer interactions and frictional resistance. The improved mechanical performance of PVAmodified soil is attributed to both nanoscale bonding effects and macroscale structural reinforcement. This study provides theoretical insights and technical support for expansive soil stabilization.

Shallow cut-and-cover underground structures, such as subway stations, are traditionally designed as rigid boxes (moment-resisting connections between the main structural members), seeking internal hyperstaticity and high lateral (transverse) stiffness to achieve important seismic capacity. However, since seismic ground motions impose racking drifts, this proved rather prejudicial, with great structural damage and little resilience. Therefore, two previous papers proposed an opposite strategy seeking low lateral (transverse) stiffness by connecting the structural elements flexibly (hinging and sliding). Under severe seismic inputs, these structures would accommodate racking without significant damage; this behaviour is highly resilient. The seismic resilience of this solution was numerically demonstrated in the well-known Daikai station (Kobe, Japan) and a station located in Chengdu (China). This paper is a continuation of these studies; it aims to extend, deepen, and ground this conclusion by performing a numerical parametric study on these two stations in a wide and representative set of situations characterised by the soil type, overburden depth, engineering bedrock position, and high- and lowlateral-stiffness of the stations. The performance indices are the racking displacement and the structural damage (quantified through concrete damage variables). The findings of this study validate the previous remarks and provide new insights.

Forests are increasingly impacted by climate change, affecting tree growth and carbon sequestration. Tree-ring width, closely related to tree growth, is a key climate proxy, yet models describing ring width or growth often lack comprehensive environmental data. This study assesses ERA5-Land data for tree-ring width prediction compared to automatic weather station observations, emphasizing the value of extended and global climate data. We analyzed 723 site-averaged and detrended tree-ring chronologies from two broadleaved and two gymnosperm species across Europe, integrating them with ERA5-Land climate data, CO2 concentration, and a drought index (SPEI12). A subset was compared with weather station data. For modelling interannual variations of tree-ring width we used linear models to assess parameter importance. ERA5-Land and weather-station-based models performed similarly, maintaining stable correlations and consistent errors. Models based on meteorological data from weather stations highlighted SPEI12, sunshine duration, and temperature extremes, while ERA5-Land models emphasized SPEI12, dew-point temperature (humidity), and total precipitation. CO2 positively influenced the growth of gymnosperm species. ERA5-Land facilitated broader spatial analysis and incorporated additional factors like evaporation, snow cover, and soil moisture. Monthly assessments revealed the importance of parameters for each species. Our findings confirm that ERA5-Land is a reliable alternative for modeling tree growth, offering new insights into climate-vegetation interactions. The ready availability of underutilized parameters, such as air humidity, soil moisture and temperature, and runoff, enables their inclusion in future growth models. Using ERA5-Land can therefore deepen our understanding of forest responses to diverse environmental drivers on a global scale.

Soil-plant-atmosphere interaction (SPAI) plays a significant role on the safety and serviceably of geotechnical infrastructure. The mechanical and hydraulic soil behaviour varies with the soil water content and pore water pressures (PWP), which are in turn affected by vegetation and weather conditions. Focusing on the hydraulic reinforcement that extraction of water through the plant roots offers, this study couples advances in ecohydrological modelling with advances in geotechnical modelling, overcoming previous crude assumptions around the application of climatic effects on the geotechnical analysis. A methodology for incorporating realistic ecohydrological effects in the geotechnical analysis is developed and validated, and applied in the case study of a cut slope in Newbury, UK, for which field monitoring data is available, to demonstrate its successful applicability in boundary value problems. The results demonstrate the positive effect of vegetation on the infrastructure by increasing the Factor of Safety. Finally, the effect of climate change and changes in slope vegetation cover are investigated. The analysis results demonstrate that slope behaviour depends on complex interactions between the climate and the soil hydraulic properties and cannot be solely anticipated based on climate data, but suctions and changes in suction need necessarily to be considered.

Predictive modeling of dielectric heating in porous foods is challenging due to their nature as multiphase materials. To explore the relationship between the topological structure of multiphase foods and the accuracy of dielectric mixture models, the degree of anisotropy of two cooked rice samples with 26 and 32 % porosity was determined, and their dielectric properties were estimated using the Lichtenecker (LK), Landau-LifshitzLooyenga (LLL), and Complex Refractive Index Mixture (CRIM) equations. These properties were used in a predictive finite-element model for reheating an apparent homogeneous rice sample on a flatbed microwave (MW) for 120 s. The results were compared with experimental data and a validated two-element model. Unlike LK and LLL equations, the CRIM equation predicted heat accumulation towards the edges of the container at the two values of porosity ratio evaluated, in accordance with the experimental results and the isotropic nature of the sample. The simulated temperature distributions suggest that the three evaluated equations could predict the MW heating behavior of rice to some extent, but that in order to obtain more accurate results, it could be useful to obtain an empirical topology-related parameter specific for this sample. These results can provide insight on the relationship between the topology of the porous structure in the sample and the adequacy of different dielectric mixture models.

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.

Excessive phosphorus emissions can result in the eutrophication of water bodies, causing severe environmental damage as well as influencing the efficiency of water treatment equipment. The impacts of carbon/phosphorus ratios on performance and mechanism of the upflow anaerobic sludge bed reactor remain unclear. Henrie, the effects of different carbon/phosphorus ratios (i.e., 80:1, 40:1, and 20:1) on the transformation of phosphorus in the biological treatment process of an upflow anaerobic sludge blanket (UASB) reactor were studied. The results showed that phosphines are of great importance in the phosphate reduction process. After a stable operation, the phosphine reached the highest 81.91 mg/m3 at a C/P ratio of 40:1. It was proved that the optimum operating condition of the reactor was carbon to phosphorus ratio of 40:1. Phosphate-reducing bacteria were present in the UASB reactor, and the relative abundance of Clostridia in the sludge was 1.90 % and 1.59 % when the C/P was 80:1 and 20:1, respectively. This implied that the low carbon to phosphorus ratio reduces the phosphorusreducing microbial activity in the reactor. Lower C/P values could inhibit the uptake and use of P in the phosphonate transport system and the transport of phosphate in the cell by the microbial Pst system, impeding the mineralization of organophosphates. The study provides new insights into improving the efficiency of treating phosphorus-rich wastewater.

Invasive weeds cause substantial ecological, economical, and social problems, and are currently being controlled by herbicide applications. However, how herbicides affect other ecological interactions of invasive weeds, including their symbiosis with arbuscular mycorrhizal fungi (AMF), remains poorly understood. In this study, we therefore conducted field investigation to understand how the herbicide glyphosate affects the AMF diversity in the rhizosphere of the invasive weed Solidago canadensis. We also performed a greenhouse experiment to study if AMF can contribute to herbicide resistance. The results showed that the AMF colonization rate was significantly higher in S. canadensis when exposed to glyphosate in the field or in greenhouse settings. AMF diversity was also found to be higher in the rhizosphere soil after glyphosate application in the field. AMF colonization in greenhouse experiments also positively correlated with plant growth and reduced amounts of damaged leaves and the plant's content of the stress markers flavonol and anthocyanin. Chlorophyll content was significantly enhanced by AMF colonization, regardless of glyphosate application. These results indicate that herbicide can promote AMF colonization and diversity, and that AMF can enhance the herbicide resistance of S. canadensis. These findings suggest that herbicide application may promote the spread of S. canadensis through enhanced microbial interactions, posing new eco-environmental risks.

Destructive earthquakes result in significant damage to a wide variety of buildings. The resulting damage data is crucial for evaluating the seismic resilience of buildings in the region and investigating urban resilience. Field damage data from 38 destructive earthquakes in Sichuan Province were collected, classified, and statistically analysed according to the criteria of the latest Chinese seismic intensity scale for evaluating building damage levels. Meanwhile, the construction features and seismic damage characteristics of these buildings were also examined. These results facilitated the development of a damage probability matrix (DPM) for various building typologies, such as raw-soil structures (RSSs), stone-wood structures (SWSs), brick-wood structures (BWSs), masonry structures (MSs), and reinforced concrete frame structures (RCFSs). The damage ratio was employed as the parameter for vulnerability assessment, and a comprehensive analysis was performed on the differences in damage levels among all buildings in various intensity zones and time frames. Furthermore, the DPMs were further refined by simulating additional data from high-intensity zones to more accurately represent the seismic resistance of existing buildings in multiple-intensity zones. Vulnerability prediction models were developed using the biphasic Hill model, which elucidates varying damage trends across different construction typologies. Finally, empirical fragility curves were established based on horizontal peak ground acceleration (PGA) as the damage indicator. This study is based on multiple seismic damage samples from various regions, accounting for the influence of earthquake age. The DPMs, representative of the regional characteristics of Sichuan Province, were developed for different building types. Furthermore, multidimensional vulnerability regression models and empirical fragility curves are established based on these DPMs. These models and curves provide a theoretical foundation for seismic disaster scenario simulations and the seismic capacity analysis of buildings within Sichuan Province.