The raw-material mix ratio and preparation of similar materials are crucial for the success of physical model tests and for accurately reflecting prototype properties. In this study, an optimum similar material for plateau alluvial and lacustrine (PAL) round gravel was developed based on similarity theory. The similar materials were subjected to sensitivity factor analysis and microscopic analysis. Subsequently, the optimum similar material was applied to a three-dimensional (3D) physical model test of an ultradeep foundation pit (FP). The findings show that the similar material prepared with gypsum, LD, bentonite, water, barite powder, and DS at a ratio of 1:1:1.4:3.5:8.8:13.2 was the best for a 3D physical model test of the ultradeep FP in PAL round gravel strata. The sensitivity-factor analysis revealed that barite powder had the greatest impact on gamma, that c and phi were primarily affected by bentonite, and that the LD-gypsum ratio controlled E. A nonuniform particle-size distribution as well as the presence of edge-to-face contacts and small pores between particles constituted the microphysical factors affecting the mechanical properties of the optimum similar material. Using dolomite with a Mohs hardness of 3.5-4 instead of traditional quartz sand with a Mohs hardness of 7 as the raw material can produce a similar material for the target soil with mechanical parameters closer to those of the ideal similar material. The application of the optimum similar material in physical model tests has revealed the stress field response law of ultra deep foundation pit excavation. This study could provide reference and inspiration for the development of similar materials in gravel formations with weaker mechanical properties.

Karst regions represent fragile landscapes that are particularly vulnerable to environmental changes. The study aims to assess the soil quality in the karst basin of Ioannina, which is located in the north-western region of Greece. Factor analysis was employed to evaluate the concentrations of trace elements in the soil. Additionally, Geographical Information Systems (GIS) was utilized to visualize the spatial distribution of these trace elements and their potential sources in relation to the local geology and land use. The study findings underscored that most of the karst landscape in the research area is comprised of Quaternary deposits and it is predominantly occupied by agricultural land. The soil displays substantial levels of clay and silt, with noticeably elevated concentration of iron (Fe), manganese (Mn), nickel (Ni), chromium (Cr), lead (Pb), copper (Cu), vanadium (V), and phosphorous (P) compared to the median concentrations observed in European topsoil. The factor analysis is applied to the dataset of elements content in soil to identify the factors controlling their distribution. Factor 1 involves the geological contribution and the adsorption of Fe-Ni-Cr-Pb-V and lithium (Li) into clay minerals. Factor 1 may be termed as lithogenic factor. The cultivated land and road network showed a significant correlation with the higher positive loadings of Fe, Mn, Pb and Cu for Factor 2 which may be termed agricultural-road network factor. Agricultural activities and cultivated land presented a significant correlation with the higher positive loadings of nitrate (NO3-), nitrite (NO2-), organic matter (OM), ammonium (NH4+) and P for Factor 3 which may be termed as agricultural factor. The higher positive loadings of Factor 4 suggest a variation in the mechanical properties of the Quaternary deposits and may be termed as soil texture factor. Quaternary deposits and agricultural land exhibit a strong spatial relationship with factor scores of each factor. Combining factor analysis and GIS proved to be an effective method for identifying and confirming the sources of elements content in soil.

Liquefaction is a significant challenge in the fields of earthquake risk assessment and soil dynamics, as it has the potential to cause extensive damage to buildings and infrastructure through ground failure. During the 2011 Great East Japan Earthquake, Urayasu City in the Chiba Prefecture experienced severe soil liquefaction, leading to evacuation losses due to the effect of the liquefaction on roads. Therefore, developing quantitative predictions of ground subsidence caused by liquefaction and understanding its contributing factors are imperative in preparing for potential future mega-earthquakes. This research is novel because previous research primarily focused on developing predictive models for determining the presence or absence of liquefaction, and there are few examples available of quantitative liquefaction magnitude after liquefaction has occurred. This research study extracts features from existing datasets and builds a predictive model, supplemented by factor analysis. Using the Cabinet Office of Japan's Nankai Trough Megathrust Earthquake model, liquefaction-induced ground subsidence was designated as the dependent variable. A gradient-boosted decision-tree (GDBT) prediction model was then developed. Additionally, the Shapley additive explanations (SHAP) method was employed to analyze the contribution of each feature to the prediction results. The study found that the XGBoost model outperformed the LightGBM model in terms of predictive accuracy, with the predicted values closely aligned with the actual measurements, thereby proving its effectiveness in predicting ground subsidence due to liquefaction. Furthermore, it was demonstrated that liquefaction assessments, which were previously challenging, can now be interpreted using SHAP factors. This enables accountable wide-area prediction of liquefaction-induced ground subsidence.

Loess is widely distributed in China and it is commonly considered as the problematic soil due to its collapsibility subjected to the water invasion. The microstructure plays an important role in the mechanical properties of the loess soil. In this note, the microstructures of intact loess samples and the inundated loess sample were investigated by using both mercury intrusion porosimetry (MIP) and nuclear magnetic resonance cryoporometry (NMRC). It is observed from the results of both MIP and NMRC tests that the intact loess has a multi-model pore size distribution function while the inundated loess has a unimodal pore size distribution function. As the coefficient of collapsibility (delta s) is a key parameter commonly used for the evaluation of the engineering properties of the loess, the delta s of the specimens tested under different conditions was measured. Subsequently, a new multi-variable linear model was proposed for the estimation of delta s from the index properties based on the results of factor analyses. The estimated results of delta s from the proposed model show good agreements with the measured data.

Fluorescence spectroscopy is a commonly used technique to analyze dissolved organic matter in aquatic environments. Given the high sensitivity and non-destructive analysis, fluorescence has recently been used to study water-soluble organic carbon (WSOC) in atmospheric aerosols, which have substantial abundance, various sources and play an important role in climate change. Yet, current research on WSOC characterization is rather sparse and limited to a few isolated sites, making it challenging to draw fundamental and mechanistic conclusions. Here we presented a review of the fluorescence properties of atmospheric WSOC reported in various field and laboratory studies, to discuss the current advances and limitations of fluorescence applications. We highlighted that photochemical reactions and relevant aging processes have profound impacts on fluorescence properties of atmospheric WSOC, which were previously unnoticed for organic matter in aquatic environments. Furthermore, we discussed the differences in sources and chemical compositions of fluorescent components between the atmosphere and hydrosphere. We concluded that the commonly used fluorescence characteristics derived from aquatic environments may not be applicable as references for atmospheric WSOC. We emphasized that there is a need for more systematic studies on the fluorescence properties of atmospheric WSOC and to establish a more robust reference and dataset for fluorescence studies in atmosphere based on extensive source specific experiments. (C) 2020 Elsevier Ltd. All rights reserved.

Arctic landscapes are experiencing intense warming and modification of precipitation regimes with climate change. Permafrost disturbances and climate change impacts on hydrology of Arctic watersheds are likely to modify the quantity and composition of exported dissolved organic matter (DOM). In July 2007, intense rainfall and active layer thickening caused widespread active layer detachments at Cape Bounty, Melville Island (Canada). This study investigates the impacts of seasonal hydrology and permafrost disturbance on DOM composition exported from High Arctic headwater catchments. In 2012, streams were sampled from three disturbed catchments and one undisturbed catchment. The composition of DOM was characterized using absorbance and fluorescence spectroscopy. DOM was mostly exported during the spring freshet. Throughout this period, the undisturbed catchment exported humifiedDOMwith high humic-like fluorescence that likely originated from runoff through shallow organic rich soil. In contrast, DOM exported from disturbed catchments was fresher, less humified with a high proportion of low molecular weight humic acid. We demonstrate that disturbed catchments delivered likely more labile DOM derived from either thawed permafrost or enhanced microbial activity. If this labile DOM comes from an ancient pool, as indicated by other studies at this site, disturbances may strengthen the permafrost carbon feedback on climate change.

The area of desertified land has increased by 27.3% from 1987 to 2000 in Maduo County, northeastern Qinghai-Tibet Plateau. Driving forces of land degradation has been extensively studied in the region. Using Factor Analysis (FA), we evaluate contribution of human activity and natural environmental change to land degradation. Four common factors were extracted in this study. The result shows that climate related other than human-related factors, are the major inducing factors of land degradation in Maduo County. Climate change and consequent change of permafrost account for 70% to the land degradation. Increasing evaporation and declining precipitation in the beginning of the growing season hamper seedling establishment. Decreasing frozen days and rising active layer lower bound make surface soil loose and less soil moisture available for plant.