The morphology of sheep wool applied as organic fertilizer biodegraded in the soil was examined. The investigations were conducted in natural conditions for unwashed waste wool, which was rejected during sorting and then chopped into short segments and wool pellets. Different types of wool were mixed with soil and buried in experimental plots. The wool samples were periodically taken and analyzed for one year using Scanning Electron Microscopy (SEM) and Energy-dispersive X-ray Spectroscopy (EDS). During examinations, the changes in the fibers' morphology were observed. It was stated that cut wool and pellet are mechanically damaged, which significantly accelerates wool biodegradation and quickly destroys the whole fiber structure. On the contrary, for undamaged fibers biodegradation occurs slowly, layer by layer, in a predictable sequence. This finding has practical implications for the use of wool as an organic fertilizer, suggesting that the method of preparation can influence its biodegradation rate. (sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic). (sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic), (sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic), (sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic). (sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic). (sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(SEM)(sic)(sic)(sic)(sic)(sic)X(sic)(sic)(sic)(sic)(EDS)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic). (sic)(sic)(sic)(sic)(sic)(sic), (sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic). (sic)(sic)(sic), (sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic), (sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic), (sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic). (sic)(sic), (sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic), (sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic). (sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic), (sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic).

Canopy reflectance (CR) models describe the transfer and interaction of radiation from the soil background to the canopy layer and play a vital role in the retrieval of biophysical variables. However, few efforts have focused on estimating soil background scattering operators, resulting in uncertainties in CR modelling, especially over sloping terrain. This study developed a canopy reflectance model for simulating CR over sloping terrain, which combines the general spectral vector (GSV) model, the PROSPECT model, and 4SAIL model coupled with topography (GSV-PROSAILT). The canopy reflectance simulated by GSV-PROSAILT was validated against two datasets: discrete anisotropic radiative transfer (DART) simulations and remote sensing observations. A comparison with DART simulations under various conditions revealed that the GSV-PROSAILT model captures terrain-induced CR distortion with high accuracy (red band: coefficient of determination $\lpar {\rm R 2} \rpar = 0.731$(R2)=0.731, root-mean-square error (RMSE) = 0.007; near infrared (NIR) band: $\rm R2 = 0.8319$R2=0.8319, RMSE = 0.0098). The results of remote sensing observation verification revealed that the GSV-PROSAILT model can be successfully used in CR modelling. These validations confirmed the performance of GSV-PROSAILT in soil and canopy reflectance modelling over sloping terrain, indicating that it can provide a potential tool for biophysical variable retrieval over mountainous areas.

Understanding soil organic carbon (SOC) distribution and its environmental controls in permafrost regions is essential for achieving carbon neutrality and mitigating climate change. This study examines the spatial pattern of SOC and its drivers in the Headwater Area of the Yellow River (HAYR), northeastern Qinghai-Xizang Plateau (QXP), a region highly susceptible to permafrost degradation. Field investigations at topsoils of 86 sites over three summers (2021-2023) provided data on SOC, vegetation structure, and soil properties. Moreover, the spatial distribution of key permafrost parameters was simulated: temperature at the top of permafrost (TTOP), active layer thickness (ALT), and maximum seasonal freezing depth (MSFD) using the TTOP model and Stefan Equation. Results reveal a distinct latitudinal SOC gradient (high south, low north), primarily mediated by vegetation structure, soil properties, and permafrost parameters. Vegetation coverage and above-ground biomass showed positive correlation with SOC, while soil bulk density (SBD) exhibited a negative correlation. Climate warming trends resulted in increased ALT and TTOP. Random Forest analysis identified SBD as the most important predictor of SOC variability, which explains 38.20% of the variance, followed by ALT and vegetation coverage. These findings likely enhance the understanding of carbon storage controls in vulnerable alpine permafrost ecosystems and provide insights to mitigate carbon release under climate change.

Gunung Bromo Education Forest is a forest that functions as a buffer area to maintain the balance of the surrounding area. However, the undulating to hilly topography, the presence of rivers, and land management for annual crops can make the area vulnerable to erosion-induced degradation. This research aims to analyze and classify the erosion hazard level in Gunung Bromo Education Forest and analyze the relationship between research parameters and erosion in Gunung Bromo Education Forest. Erosion was predicted using the MUSLE method. This research used an explorative-descriptive method incorporating a survey and laboratory analysis. Furthermore, data analysis used was Analysis of Variance (ANOVA), Duncan's Multiple Range Test (DMRT) at a 5% significance level, and Pearson correlation test. The results showed that Gunung Bromo Education Forest erosion ranged from 0.025 to 78.36 t ha(-1)y(-1). The erosion hazard level in Gunung Bromo Education Forest is in the very light to heavy class and is dominated by the light class. The factors of erosivity (R), erodibility (K), slope (LS), and crop management (C) are positively correlated with erosion values. The conservation factor (P) is negatively correlated with erosion values. Making remedial efforts according to the erosion hazard level is important to avoid greater damage.

The aerosol scattering phase function (ASPF), a crucial element of aerosol optical properties, is pivotal for radiative forcing calculations and aerosol remote sensing detection. Current detection methods for the ASPF include multi-sensor detection, single-sensor rotational detection and imaging detection. However, these methods face challenges in achieving high-resolution full-angle measurement, particularly for small forward (i.e., less than 10 degrees) or backward (i.e., more than 170 degrees) scattering angles in open path. In this work, a full-angle ASPF detection system based on the multi-field-of-view Scheimpflug lidar technique has been proposed and demonstrated. A 450 nm continuous-wave semiconductor laser was utilized as the light source and four CMOS image sensors were employed as detectors. To detect the full-angle ASPF, four receiving units capture angular scattering signals across different angle ranges, namely 0 degrees-20 degrees, 10 degrees-96 degrees, 84 degrees-170 degrees, 160 degrees-180 degrees, respectively. The influence of the relative illumination and angular response of the used image sensors have been corrected, and a signal stitching algorithm was developed to obtain a complete 0-180 degrees angular scattering signal. Atmospheric measurements have been conducted by employing the full-angle ASPF detection system in open path. The experimental results of the ASPF have been compared with the AERONET data from the Socheongcho station and simulated ASPF based on the typical aerosol models in mainland China, showing excellent agreement. The promising results demonstrated in this work have shown a great potential for detecting the full-angle ASPF in open path.

The presence of frozen volatiles (especially H2O ice) has been proposed in the permanently shadowed regions (PSRs) near the poles of the Moon, based on various remote measurements including the visible and near-infrared (VNIR) spectroscopy. Compared with the middle- and low-latitude areas, the VNIR spectral signals in the PSRs are noisy due to poor solar illumination. Coupled with the lunar regolith coverage and mixing effects, the available VNIR spectral characteristics for the identification of H2O ice in the PSRs are limited. Deep learning models, as emerging techniques in lunar exploration, are able to learn spectral features and patterns, and discover complex spectral patterns and nonlinear relationships from large datasets, enabling them applicable on lunar hyperspectral remote sensing data and H2O-ice identification task. Here we present H2O ice identification results by a deep learning-based model named one-dimensional convolutional autoencoder. During the model application, there are intrinsic differences between the remote sensing spectra obtained by the orbital spectrometers and the laboratory spectra acquired by state-of-the-art instruments. To address the challenges of limited training data and the difficulty of matching laboratory and remote sensing spectra, we introduce self-supervised learning method to achieve pixel-level identification and mapping of H2O ice in the lunar south polar region. Our model is applied to the level 2 reflectance data of Moon Mineralogy Mapper. The spectra of the identified H2O ice-bearing pixels were extracted to perform dual validation using spectral angle mapping and peak clustering methods, further confirming the identification of most pixels containing H2O ice. The spectral characteristics of H2O ice in the lunar south polar region related to the crystal structure, grain size, and mixing effect of H2O ice are also discussed. H2O ice in the lunar south polar region tends to exist in the form of smaller particles (similar to 70 mu m in size), while the weak/absent 2-mu m absorption indicate the existence of unusually large particles. Crystalline ice is the main phase responsible for the identified spectra of ice-bearing surface however the possibility of amorphous H2O ice beneath optically sensed depth cannot be ruled out.

Uneven displacement of permafrost has become a major concern in cold regions, particularly under repeated freezing-thawing cycles. This issue poses a significant geohazard, jeopardizing the safety of transportation infrastructure. Statistical analyses of thermal penetration suggest that the problem is likely to intensify as water erosion expands, with increasing occurrences of uneven displacement. To tackle the challenges related to mechanical behavior under cyclic loading, the New Geocell Soil System has been implemented to mitigate hydrothermal effects. Assessment results indicate that the New Geocell Soil System is stable and effective, offering advantages in controlling weak zones on connecting slopes and reducing uneven solar radiation. Consequently, the New Geocell Soil System provides valuable insights into the quality of embankments and ensures operational safety by maintaining displacement at an even level below 1.0 mm. The thermal gradient is positive, with displacement below 6 degrees C/m, serving as a framework for understanding the stability of the subgrade. This system also enhances stress and release the sealing phenomenon.

This study systematically investigated the pore structure response of kaolin and illite/smectite mixed-layer rich clay in a reconstituted state to one-dimensional (1D) compression by first performing oedometer tests on saturated clay slurries, followed by characterising their pore structure using multi-scale characterisation techniques, with the primary objective of advancing the current understanding of the microstructural mechanisms underlying the macroscopic deformation of such clays. Under 1D loading, the volume reduction observed at the macro level essentially represented the macroscopic manifestation of changes in inter-aggregate porosity at the pore scale. It was the inter-particle pores that were compressed, despite the interlayer pores remaining stable. Two distinct pore collapse mechanisms were identified: kaolin exhibited a progressive collapse of particular larger pore population in an ordered manner, whereas illite/smectite mixed-layer rich clay demonstrated overall compression of inter-aggregate pores. Accordingly, mathematical relationships between the porosity and compressibility parameters for these two soils were proposed, with the two exhibiting opposite trends arising from their distinct microstructural features. Approaching from the unique perspective of pore structure, quantitative analysis of pore orientation and morphology on the vertical and horizontal planes demonstrated some progressively increasing anisotropy during compression. These findings provide important insights into porescale mechanisms governing clay compression behaviour and enrich the limited microporosity database in soil mechanics.

This study analyzes the aerosol and precipitable water vapor (PWV) properties at six sites in the Indo-Gangetic Plains (IGP), a densely populated and highly polluted region. The main objective is to explore how the columnar PWV is related to the attenuation of shortwave solar radiation (SWR), as well as the combined role of aerosol properties and PWV on radiative forcing based on AERONET data and model (SBDART) simulations. The analysis revealed high aerosol optical depth (AOD) values (0.4-0.6) throughout the year in all the sites, associated with increased PWV (4-5 cm) during the summer monsoon. Comprehensive investigation shows that changes in PWV levels also affect aerosols' size distribution, optical properties and radiation balance in a similar way - but in different magnitudes - between the examined sites. The water vapor radiative effect (WVRE) is highly dependent on aerosol presence, with its magnitude for both surface (-130 to -140 Wm(-2)) and atmospheric forcing becoming higher under clean atmospheres (without aerosols). Aerosol presence is also considered in the computations of the WVRE. In that case, the WVRE becomes more pronounced at the top of the atmosphere (TOA) (30 to 35 Wm(-2)) but exhibits a lower forcing impact on the surface (about -45 Wm(-2)) and within the atmosphere (70-80 Wm(-2)), suggesting important aerosol-PWV interrelations. The atmospheric heating rate due to PWV is more than double (3.5-4.5 K Day(-1)) that of aerosols (1-1.9 K Day(-1)), highlighting its essential role in radiative effects and climate implications over the IGP region. The radiative impacts of PWV and aerosols are further examined as a function of the single scattering albedo, solar zenith angle, and absorbing AOD at the different sites, revealing dependence on both astronomical and atmospheric variables related to aerosol absorption, thus unravelling the combined role of aerosols and PWV in climate implications.

Thawing-triggered slope failures and landslides are becoming an increasing concern in cold regions due to the ongoing climate change. Predicting and understanding the behaviour of frozen soils under these changing conditions is therefore critical and has led to a growing interest in the research community. To address this challenge, we present the first mesh-free smoothed particle hydrodynamics (SPH) computational framework designed to handle the multi-phase and multi-physic coupled thermo-hydro-mechanical (THM) process in frozen soils, namely the THM-SPH computational framework. The frozen soil is considered a tri-phase mixture (i.e., soil, water and ice), whose governing equations are then established based on u-p-T formulations. A critical-state elasto-plastic Clay and Sand Model for Frozen soils (CASM-F), formulated in terms of solid-phase stress, is then introduced to describe the transition response and large deformation behaviour of frozen soils due to thawing action for the first time. Several numerical verifications and demonstrations highlight the usefulness of this advanced THM-SPH computational framework in addressing challenging problems involving thawing-induced large deformation and failures of slopes. The results indicate that our proposed single-layer, fully coupled THM-SPH model can predict the entire failure process of thawing-induced landslides, from the initiation to post-failure responses, capturing the complex interaction among multiple coupled phases. This represents a significant advancement in the numerical modelling of frozen soils and their thawing-induced failure mechanisms in cold regions.