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.

Widespread dieback of natural Mongolian pine (Pinus sylvestris var. mongolica) forests in Hulunbuir sandy land since 2018 has raised concerns about their sustainability in afforestation programs. We hypothesized that this dieback is driven by two interrelated mechanisms: (1) anthropogenic fire suppression disrupting natural fire regime, and (2) climate change-induced winter warming reducing snow cover duration and depth. To test these, we quantified dieback using Green Normalized Difference Vegetation Index (GNDVI) across stands with varying fire histories via UAV-based multispectral imagery, alongside long-term climatic observations (1960-2024) of temperature, precipitation, and snow dynamics from meteorological stations combined with remote sensing datasets. Results showed that an abrupt change point in 2018 for both annual precipitation and mean temperature was identified, coinciding with dieback. Significant negative linear relationship between GNDVI (forest health) and last fire interval indicated prolonged fire exclusion exacerbating dieback, possibly via pathogen/pest accumulation. Winter temperature rose significantly during 1960-2023, with notable acceleration following abrupt change point in 1987. Concurrently, winters during 2018-2023 exhibited pronounced warming, with snow cover duration reduced by 23 days and snow depth diminished by 7.6 cm. These conditions reduced snowmelt -derived soil moisture (critical water source) recharge in early spring, exacerbating drought stress during critical growth periods and predisposing trees to pest and disease infestations. Our results support both hypotheses, demonstrating that dieback is synergistically driven by fire regime alteration and climate-mediated snowpack reductions. Converting pure pine forests into mixed pine-broadleaf forests via differentiated water sources was proposed to restore ecological resilience in sandy ecosystems.

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.

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.

Understanding changes in water balance and land-atmosphere interaction under climate change is crucial for managing water resources in alpine regions, especially in the Qinghai-Tibet Plateau (QTP). Evapotranspiration (ET), a key process in the land-atmosphere interaction, is influenced by permafrost degradation. As the active layer in permafrost regions deepens due to climate warming, the resulting shifts in surface hydrologic connectivity and water storage capacity affect vegetation's ability to access water, thereby influencing its growth and regulating ET dynamics, though the full complexity of this process remains unclear. This study employs the Budyko-Fu model to assess the spatiotemporal dynamics of ET and the ET ratio (the ratio of ET to precipitation) on the QTP from 1980 to 2100. While ET shows a continuous upward trend, the ET ratio exhibits a non-monotonic pattern, increasing initially and then decreasing. More than two-thirds of permafrost areas on the QTP surpassed the critical ET ratio threshold by 2023, under three emission scenarios. By 2100, nearly all areas are projected to reach the tipping point, with 97 % affected under the SSP5-8.5 scenario. Meadow and steppe regions are expected to encounter this threshold earlier, whereas forested areas will be less affected, with over 80 % unlikely to reach the tipping point by 2100. Basin-level differences are notable: nearly 90 % of the Qaidam basin exceeded the threshold before 2023, compared to less than 50 % in the Yangtze basin. By 2100, more than 80 % of regions in all basins are expected to cross the tipping point due to ongoing permafrost degradation. This study advances understanding of land-atmosphere interactions in alpine regions, providing critical insights for water resource management and improving extreme weather predictions.

Aims Human disturbances and environmental changes significantly influence riparian vegetation composition and dynamics by altering hydrological regimes. In high-altitude river systems, snowmelt-driven water-level fluctuations add further complexity to these processes. However, little is known about how riparian plant functional strategies-competitor (C), stress-tolerator (S), and ruderal (R)-respond to dam-induced water-level fluctuations. This study aimed to assess the effects of water-level fluctuations and climatic factors on riparian vegetation functional strategies along the Nyang River, Qinghai-Tibet Plateau.Location This study was conducted along the Nyang River, Qinghai-Tibet Plateau, China. A total of 33 sites were surveyed, spanning upstream, reservoir, and downstream zones, which were categorized based on water-level fluctuation gradients.Methods We classified riparian vegetation functional strategies using Grime's CSR framework based on species trait data. Hydrological and climatic variables, including water-level fluctuations, temperature, precipitation, and snow cover, were derived from the Global Surface Water Mapping Layers and the FLDAS dataset. Soil properties were measured in the field. Redundancy analysis and partial least squares path modeling were applied to identify key drivers of CSR variation across different river zones.Results Riparian vegetation exhibited significant differences in stress tolerance and ruderal strategies across the Nyang River. Plants in the reservoir and upstream zones had higher S-strategy values, whereas downstream vegetation was predominantly characterized by high competitiveness. The primary drivers of CSR variation across the catchment were temperature, precipitation, and snow cover. In reservoir zones, water-level fluctuations (e.g., retention time, river width) were the dominant influences, whereas downstream vegetation was mainly governed by climate variables. In upstream zones, precipitation, water-level fluctuations, and snow cover jointly influenced CSR strategies. Water-level fluctuations directly regulated functional strategies, whereas snow cover had both direct effects and indirect effects via soil moisture changes.Conclusions This study highlights the interactive effects of climate change and flow regulation on riparian vegetation functional strategies in high-altitude river systems. The findings provide critical insights into how water-level fluctuations and climatic factors shape riparian plant strategies, offering valuable information for ecosystem-based river management and conservation in alpine regions.

Permafrost degradation, driven by rising temperatures in high-latitude regions, destabilizes previously sequestered soil organic carbon (OC), increasing greenhouse gas emissions and amplifying global warming. In these ecosystems, interactions with mineral surfaces and metal oxides, particularly iron (Fe), stabilize up to 80% of soil OC. This study investigates the mechanisms of Fe solubilization and OC release across a permafrost thaw gradient in Stordalen, Abisko, Sweden, including palsa, intermediate, and highly degraded permafrost stages. By integrating geophysical measurements-including relative elevation, thaw depth, soil water content, and soil temperature with redox potential and soil pore water chemistry, we identify the environmental conditions driving iron and organic carbon release into soil pore waters with permafrost degradation. Our results show that combining relative elevation, thaw depth, soil water content, soil pore water pH, and soil pore water conductivity with shifts in vegetation species enables very-high-resolution detection of permafrost degradation at submeter scales, distinguishing intact from degraded permafrost soils. We show that small-scale changes in thaw depth and water content alter soil pH and redox conditions, driving the release of Fe and dissolved organic carbon (DOC) and promoting the formation of Fe-DOC complexes in soil pore water. The amount of exported Fe-DOC complexes from thawed soils varies with the stage of permafrost degradation, and the fate of Fe-DOC complexes is likely to evolve along the soil-stream continuum. This study highlights how environmental conditions upon thaw control the type of Fe-DOC association in soil pore waters, a parameter to consider when quantifying what DOC is available for microbial and photo-degradation in aquatic systems which are significant sources of greenhouse gas emissions across Arctic landscapes.

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.

Soft soil subgrades often present significant geotechnical challenges under cyclic loading conditions associated with major infrastructure developments. Moreover, there has been a growing interest in employing various recycled tire derivatives in civil engineering projects in recent years. To address these challenges sustainably, this study investigates the performance of granular piles incorporating recycled tire chips as a partial replacement for conventional aggregates. The objective is to evaluate the cyclic behavior of these tire chip-aggregate mixtures and determining the optimum mix for enhancing soft soil performance. A series of laboratory-scale, stress-controlled cyclic loading tests were conducted on granular piles encased with combi-grid under end-bearing conditions. The granular piles were constructed using five volumetric proportions of (tire chips: aggregates) (%) of 0:100, 25:75, 50:50, 75:25, and 100:0. The tests were performed with a cyclic loading amplitude (qcy) of 85 kPa and a frequency (fcy) of 1 Hz. Key performance indicators such as normalized cyclic induced settlement (Sc/Dp), normalized excess pore water pressure in soil bed (Pexc/Su), and pile-soil stress distribution in terms of stress concentration ratio (n) were analyzed to assess the effectiveness of the different mixtures. Results indicate that the ordinary granular pile (OGP) with (25 % tire chips + 75 % aggregates) offers an optimal balance between performance and sustainability. This mixture reduced cyclic-induced settlement by 86.7 % compared to the OGP with (0 % TC + 100 % AG), with only marginal losses in performance (12.3 % increase in settlement and 2.8 % reduction in stress transfer efficiency). Additionally, the use of combi-grid encasement significantly improved the overall performance of all granular pile configurations, enhancing stress concentration and reducing both settlement and excess pore water pressure. These findings demonstrate the viability of using recycled tire chips as a sustainable alternative in granular piles, offering both environmental and engineering benefits for soft soil improvement under cyclic loading.