Slope failures resulting from thaw slumps in permafrost regions, have developed widely under the influence of climate change and engineering activities. The shear strength at the interface between the active layer and permafrost (IBALP) at maximum thawing depth is a critical factor to evaluate stability of permafrost slopes. Traditional direct shear, triaxial shear, and large-scale in-situ shear experiments are unsuitable for measuring the shear strength parameter of the IBALP. Based on the characteristics of thaw slumps in permafrost regions, this study proposes a novel test method of self-weight direct shear instrument (SWDSI), and its principle, structure, measurement system and test steps are described in detail. The shear strength of the IBALP under maximum thaw depth conditions is measured using this method. The results show that under the condition that the permafrost layer is thick underground ice and the active layer consists of silty clay with 20% water content, the test results are in good agreement with the results of field large-scale direct shear tests and are in accordance with previous understandings and natural laws. The above analysis indicates that the method of the SWDSI has a reliable theoretical basis and reasonable experimental procedures, and meets the needs of stability assessment of thaw slumps in permafrost regions. The experimental data obtained provide important parameter support for the evaluation of related geological hazards.

Infrastructure in northern regions is increasingly threatened by climate change, mainly due to permafrost thaw. Prediction of permafrost stability is essential for assessing the long-term stability of such infrastructure. A key aspect of geotechnical problems subject to climate change is addressing the surface energy balance (SEB). In this study, we evaluated three methodologies for applying surface boundary conditions in longterm thermal geotechnical analyses, including SEB heat flux, n-factors, and machine learning (ML) models by using ERA5-Land climate reanalysis data until 2100. We aimed to determine the most effective approach for accurately predicting ground surface temperatures for climate-resilient design of northern infrastructure. The evaluation results indicated that the ML-based approach outperformed both the SEB heat flux and n-factors methods, demonstrating significantly lower prediction errors. The feasibility of long-term thermal analysis of geotechnical problems using ML-predicted ground surface temperatures was then demonstrated through a permafrost case study in the community of Salluit in northern Canada, for which the thickness of the active layer and talik were calculated under moderate and extreme climate scenarios by the end of the 21st century. Finally, we discussed the application and limitations of surface boundary condition methodologies, such as the limited applicability of the n-factors in long-term analysis and the sensitivity of the SEB heat flux to inputs and thermal imbalance. The findings highlight the importance of selecting suitable boundary condition methodologies in enhancing the reliability of thermal geotechnical analyses in cold regions.

Human disturbance in the Arctic is increasing. Abrupt changes in vegetation may be expected, especially when spots without vegetation are made available; additionally, climate change alters competition between species. We studied whether 34- to 35-year-old seismic operations had left imprints on local vegetation and whether changes could be related to different soil characteristics. The study took place in Jameson Land in central east Greenland where winter seismic operations in search of oil took place from 1985 to 1989. This area is dominated by continuous dwarf shrub heath with Cassiope tetragona, Betula nana, and Vaccinium uliginosum as dominant species. Using point frame analyses, we registered vascular plants and other surface types in frames along 10-m transects in vehicle tracks (hereafter damages) and in undisturbed vegetation parallel to the track (hereafter references) at eleven study sites. We also measured temperature and pH and took soil samples for analysis. Damaged and reference vegetation types were compared with S & oslash;rensen similarity indices and detrended correspondence analyses. Although most vascular plant species were equally present in damaged vegetation and in references the detrended correspondence analyses showed that at ten out of eleven study sites the damages and references still differed from each other. Graminoids and the herb Polygonum viviparum had the highest occurrence in damages. Shrubs and the graminoid Kobresia myosuroides had the highest occurrence in references. Cassiope tetragona was negatively impacted where vehicles had compacted the snow. Moss, organic crust or biocrust, soil, and sand occurred more often in damages than in references, whereas lichens and litter had the highest occurrence in references. The richness of vascular plant species varied between the eleven study sites, but between damages and references the difference was only up to four species. Temperature was the soil parameter with the most significant differences between damages and references. Total recovery of the damaged vegetation will most likely not occur within several decades. The environmental regulations were important to avoid more serious impacts.

Liquefaction hazard analysis is crucial in earthquake-prone regions as it magnifies structural damage. In this study, standard penetration test (SPT) and shear wave velocity (Vs) data of Chittagong City have been used to assess the liquefaction resistance of soils using artificial neural network (ANN). For a scenario of 7.5 magnitude (Mw) earthquake in Chittagong City, estimating the liquefaction-resistance involves utilizing peak horizontal ground acceleration (PGA) values of 0.15 and 0.28 g. Then, liquefaction potential index (LPI) is determined to assess the severity of liquefaction. In most boreholes, the LPI values are generally higher, with slightly elevated values in SPT data compared to Vs data. The current study suggests that the Valley Alluvium, Beach and Dune Sand may experience extreme liquefaction with LPI values ranges from 9.55 to 55.03 and 0 to 37.17 for SPT and Vs respectively, under a PGA of 0.15 g. Furthermore, LPI values ranges from 25.55 to 71.45 and 9.55 to 54.39 for SPT and Vs correspondingly. The liquefaction hazard map can be utilized to protect public safety, infrastructure, and to create a more resilient Chittagong City.

Correlations between the mechanical properties and surface scratch resistance of polylactic acid (PLA) are investigated via tensile and scratch tests on samples after degradation in soil for various times. The results show that the tensile yield strength of PLA is inversely proportional to the natural logarithm of the degradation time, and the scratch resistance and fracture toughness of PLA and the temperature rise near the indenter all increase and then decrease. The surface crystallinity of PLA also increases and then decreases, indicating that it and the scratch resistance are closely related. These findings provide useful information about how PLA behaves under degradation conditions. (c) 2025 Author(s). All article content, except where otherwise noted, is licensed under a Creative Commons Attribution-NonCommercial 4.0 International (CC BY-NC) license (https://creativecommons.org/licenses/by-nc/4.0/).

To investigate the effect of interface temperature on the soil-reinforcement interaction mechanism, a series of pullout tests were conducted considering different types of reinforcement (geogrid and non-woven geotextile), backfill (dry sand, wet sand, and clay), and six interface temperatures. The test results indicate that at interface temperatures of 0 degrees C and above, reinforcement failure didn't occur during the pullout tests, whereas it predominantly occurred at subzero temperatures. Besides, the pullout resistance for the same soil-reinforcement interface gradually decreased as the interface temperature rose. At a given positive interface temperature, the pullout resistance between wet sand and reinforcement was significantly higher than that of the clayreinforcement interface but lower than that of the dry sand-reinforcement interface. Compared with geotextile reinforcements, geogrids were more difficult to pull out under the same interface temperature and backfill conditions. In addition, the lag effect in the transfer of tensile forces within the reinforcements was significantly influenced by the type of soil-reinforcement interface and the interface temperature. Finally, the progressive deformation mechanism along the reinforcement length at different interface temperatures was analyzed based on the strain distribution in the reinforcement.

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.

Black carbon (BC) is a major pollutant entering the human body through PM2.5 and posing major health effects. India lying in the Asia region is a major contributor to BC emissions from the combustion of biofuels. BC present in the atmosphere is a pollutant deteriorating air quality and is a light-absorbing aerosol (LAA), thus playing a dual role. In India, several studies have been published quantifying BC concentration. The optical measurement of BC has been carried out at multiple locations in India, and its radiative effect has been studied using the Santa Barbara DISORT Atmospheric Radiative Transfer (SBDART) model. This review is an attempt to collate those studies that have measured BC and estimated its radiative effect. The BC levels, spectral Aerosol Optical Depth (AOD), single scattering albedo (SSA) and direct radiative forcing (DRF) at the top of the atmosphere (TOA), at the surface (SUR) and heat within the atmosphere (ATM) for 20 years (2002 to 2023) have been analysed. It was found that many studies for performing DRF calculations have not used BC measurements and have used AOD analysis to characterise the sources of aerosols as direct BC measurements are not required to estimate the DRF. The selection of AOD wavelength 500 nm or 550 nm is not clear in the literature for BC-RF calculations and needs to be standardised for DRF. IPCC AR6 has estimated Effective Radiative Forcing (ERF) due to BC with temperature and surface feedbacks, and future studies for ERF need to use climate models with tools like WRF-Chem. The source of BC is mostly from fossil fuel or biomass burning during the winter season, while it is dust aerosols during the summer. Biomass burning, use of traditional cook stoves and aerosol episodes contribute to the warming of the ambient environment. Beijing, China, has reduced ATM forcing in the summer when compared to Delhi, India, and has reduced the fraction of heat exerted in the atmosphere. The interactions of BC-UHI are not studied yet in India, and with the ARFINET network, an attempt can be made in this direction. The Urban Pollution Island (UPI)-Urban Heat Island (UHI) review identified PM2.5 contributing to UHI intensity during the summer and winter in metro cities, while BC-UHI interactions are not dealt with in detail.

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.

The soil strength of soft clay is influenced by strain rate effect. Models considering strain rate effect always ignore the impact of loading rate on pore pressure and have poor applicability to 3D engineering problems. Based on the classic inelastic core boundary surface model, a logarithmic rate function representing the strain rate effect of soft soil was introduced to the hardening law. A new parameter H was added to adjust the plastic modulus while another new parameter mu is introduced to account for the strain rate effect. A rate-effect boundary surface constitutive model suitable for saturated clay was subsequently proposed. Combined with the implicit integral numerical algorithm and stress-permeability coupling analysis, the innovative model was implemented in the finite element software and validated by comparing with the results of triaxial tests. By analysing the rate-effect of 11 types of soft soil, a formula to calculate the rate parameter was derived. The developed model was used to calculate the undrained vertical bearing capacity and sliding resistance of a movable subsea mudmat. The mudmat frictional coefficient from soil undrained to partial drained and finally undrained state was obtained and compared with those from the Modified Cam-Clay model. Identical results were obtained without considering the rate effect. When considering the strain rate effect on the improvement of soil strength, the friction resistance coefficient initially decreases and then increases with the decrease of the sliding speed, eventually stabilising after reaching the limit value. The rate-effect on the friction resistance coefficient is most prominent under undrained conditions with high sliding speeds. The soil strain rate effect is suggested to be considered in the design of the subsea mudmat avoid underestimating the friction resistance.