Black carbon (BC) is a major short-lived climate pollutant (SLCP) with significant climate and environmentalhealth impacts. This review synthesizes critical advancements in the identification of emerging anthropogenic BC sources, updates to global warming potential (GWP) and global temperature potential (GTP) metrics, technical progress in characterization techniques, improvements in global-regional monitoring networks, emission inventory, and impact assessment methods. Notably, gas flaring, shipping, and urban waste burning have slowly emerged as dominant emission sources, especially in Asia, Eastern Europe, and Arctic regions. The updated GWP over 100 years for BC is estimated at 342 CO2-eq, compared to 658 CO2-eq in IPCC AR5. Recent CMIP6-based Earth System Models (ESMs) have improved attribution of BC's microphysics, identifying a 22 % increase in radiative forcing (RF) over hotspots like East Asia and Sub-Saharan Africa. Despite progress, challenges persist in monitoring network inter-comparability, emission inventory uncertainty, and underrepresentation of BC processes in ESMs. Future efforts could benefit from the integration of satellite data, artificial intelligence (AI)assisted methods, and harmonized protocols to improve BC assessment. Targeted mitigation strategies could avert up to four million premature deaths globally by 2030, albeit at a 17 % additional cost. These findings highlight BC's pivotal roles in near-term climate and sustainability policy.

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.

Thaw hazards in high-latitude and glaciated regions are becoming increasingly frequent because of global climate warming and human activities, posing significant threats to infrastructure stability and environmental sustainability. However, despite these risks, comprehensive investigations of thaw-hazard susceptibility in permafrost regions remain limited. Here, this gap is addressed by a systematic and long-term investigation of thaw hazards in China's Qinghai Province as a representative permafrost area. A detailed inventory of 534 thawhazard sites was developed based on remote sensing, field verification, and surveys by a UAV, providing critical data for susceptibility analysis. Eleven environmental factors influencing thaw hazards were identified and analyzed using information gain and Shapley additive explanation. By using the random forest model, a susceptibility map was generated, categorizing the study area into five susceptibility classes: very low, low, moderate, high, and very high. The key influencing factors include precipitation, permafrost type, temperature change rate, and human activity. The results reveal that 17.5 % of the permafrost region within the study area is classified as high to very high susceptibility, concentrated primarily near critical infrastructure such as the Qinghai-Tibet Railway, potentially posing significant risks to its structural stability. The random forest model shows robust predictive capability, achieving an accuracy of 0.906 and an area under the receiver operating characteristic curve of 0.965. These findings underscore the critical role of advanced modeling in understanding the spatial distribution and drivers of thaw hazards, offering actionable insights for hazard mitigation and infrastructure protection in permafrost regions under a changing climate.

The Arctic has been warming much faster than the global average, known as Arctic amplification. The active layer is seasonally frozen in winter and thaws in summer. In the 2017 Arctic Boreal Vulnerability Experiment (ABoVE) airborne campaign, airborne L- and P- band synthetic aperture radar (SAR) was used to acquire a dataset of active layer thickness (ALT) and vertical soil moisture profile, at 30 m resolution for 51 swaths across the ABoVE domain. Using a thawing degree day (TDD) model, ALT=K root TDD, we estimated ALT along the ABoVE swaths employing the 2-m air temperature from ERA5. The coefficient (K) calibrated has an R2=0.9783. We also obtained an excellent fit between ALT and K root(TDD/theta) where theta is the soil moisture from ERA5 (R2=0.9719). Output based on shared-social economic pathway (SSP) climate scenarios SSP 1-2.6, SSP 2-4.5, and SSP 5-8.5 from seven global climate models (GCMs), statistically downscaled to 25-km resolution, was used to project the impacts of climate warming on ALT. Assuming ALT=K root TDD, the projections of UKESM1-0-LL GCM resulted in the largest projected ALT, up to about 0.7 m in 2080s under SSP5-8.5. Given that the mean observed ALT of the study sites is about 0.482 m, this implies that ALT will increase by 0.074 to 0.217 m (15% and 45%) in 2080s. This will have substantial impacts on Arctic infrastructure. The projected settlement Iset (cm) of 1 to 7 cm will also impact the infrastructure, especially by differential settlement due to the high spatial variability of ALT and soil moisture, given at local scale the actual thawing will partly depend on thaw sensitivity of the material and potential thaw strain, which could vary widely from location to location.

Temperature and precipitation are the primary factors restricting litter decomposition in desert ecosystems. The desert ecosystems in Central Asia are ecologically fragile regions, and the climate shows a trend of warm and wet due to the regional climate change. However, the influencing mechanisms of warming and winter snow changes on litter decomposition are still poorly understood in desert ecosystems. Furthermore, the litter decomposition rate cannot be directly compared due to the large variations in litter quality across different ecosystems. Here, we simulated warming and altered winter snow changes in the field, continuously monitored litter decomposition rates of standard litter bags (i.e., red tea and green tea) and a dominant plant species (i.e., Erodium oxyrrhynchum) during a snow-cover and non-snow-cover period over five months. We found that warming and increased snow cover increased the litter decomposition rate of red tea, green tea, and Erodium oxyrhinchum, and had significant synergistic effects on litter decomposition. The effects of warming and winter snow changes on litter decomposition were more pronounced in April, when the hydrothermal conditions were the best. The decomposition rates of all three litter types belowground were higher than those on the soil surface, highlighting the important roles of soil microbes in accelerating litter decomposition. Furthermore, we found that warming and winter snow changes altered litter decomposition by influencing soil enzyme activities related to soil carbon cycling during the snow-cover period, while influencing soil enzyme activities related to soil phosphorus cycling during the non-snow-cover period. And, notably, decreased snow cover promoted soil enzyme activities during the snow-cover period. More interestingly, our results indicated that the decomposition rate (k) was the lowest, but the stability factor (S) was the highest in the Gurbant & uuml;ngg & uuml;t Desert based on the cross-ecosystem comparison using the Tea Bag Index method. Overall, our results highlighted the critical roles of warming and winter snow changes on litter decomposition. In future research, the consideration of relationships between litter decomposition and soil carbon sequestration will advance our understanding of soil carbon cycling under climate change in desert ecosystems.

Bats are indispensable members of the natural world, supporting its delicate balance. Bats have vital roles in controlling insect populations and enhancing soil fertility. They also help in the harvesting and dispersal of seeds, pollination in plants, and nutrient recycling and distribution. However, through evolution over millions of years, they have also adapted their immune system so that they may carry numerous types of pathogens, the majority of which are viruses, without these pathogens having any serious ill effects on bats themselves. Their anatomical adaptation to flight and the reduced immune response to DNA damage during flight have also contributed to bats becoming reservoirs of deadly pathogenic diseases. This review discusses the different adaptations of bats with a special focus on the immune system that have helped them evolve as a reservoir for various viruses. The study also enumerates how the increase in global warming, the consequent changes in climatic conditions, habitat destruction, and bushmeat consumption increase the chances of an outbreak of novel zoonotic disease when humans come in contact with bats.

Permafrost degradation on the Tibetan Plateau (TP) has triggered widespread retrogressive thaw slumps (RTSs), affecting hydrology, carbon sequestration and infrastructure stability. To date, there is still a lack of long-term monitoring of RTSs across the TP, the thaw dynamics and comprehensive driving factors remain unclear. Here, using time-series Landsat imagery and change detection algorithm, we identified RTSs on permafrost regions of the TP from 1986 to 2020. Existing RTSs inventories and high-resolution historical imagery were employed to verify the identified results, the temporal validation of RTSs disturbance pixels demonstrated a high accuracy. In the study area, a total of 3537 RTSs were identified, covering a total area of 5997 ha, representing a 26-fold increase since 1986, and 69.2 % of RTSs formed since 2010. Most RTSs are located on gentle slope (4-12 degrees) at elevations between 4500 m and 5300 m, with a tendency to form in alpine grassland and alpine meadow. Annual variations in RTSs area exhibited a significant positive correlation with minimum air temperature, mean land surface temperature, and annual thawing index, while it showing a significant negative correlation with the decrease in downward shortwave radiation. Spatially, RTSs were more common in areas with higher soil water content and shallower active layer. Landsat imagery captured the vast majority of RTSs on the TP and revealed interannual disturbance details, but the 30 m resolution remains inadequate for delineating the refined boundaries of some micro-scale (< 0.18 ha) RTSs. Detected RTSs disturbances on the TP will aid in hazard management and carbon feedback assessments, and our findings provide novel insights into the impacts of climate change and permafrost environments on RTSs formation.

Rare earth elements (REEs) are a type of frequently reported emerging pollutant that affects plant growth. The harm caused by continuous exposure to low-dose REEs has rarely been studied. Quickly, accurately, and noninvasively monitoring the continuous influence of low-dose REEs on plant growth in situ is key to indicating and warning of its harm to plants and ecosystems. In this study, after continuous exposure to low-dose lanthanum [La(III), a REE] for 14 days, invisible damage occurred in leaf cells, and La accumulated continuously in the soybean plants (leaves > stems > roots > pods > seeds), causing potential human health risks. Two proteins [vitronectin-like protein (VN) and arabinogalactan proteins (AGP)] in leaf cells that bound La(III) were selected as biomarkers, and changes in these two proteins were detected by constructing dual-sensors in living leaf cells after continuous exposure to low-dose La(III) for 14 days. The results showed that the electrochemical outputs from leaf cells-the electron transfer resistance Ret(VN) and Ret(AGP)-were related to the damage indices such as MDA, chlorophyll content, electrolyte leakage, cell vitality, fresh and dry weight of leaves, and leaf area. Using this output, two warning intervals of visible damage were obtained: Ret(VN) was 8.53 %-47.22 %, and Ret(AGP) was 12.75 %-51.31 %. This study successfully demonstrated the real-time in situ detection of plant cell biomarker changes and invisible damage under low-dose La(III) exposure, providing methods for early warning monitoring of plant damage caused by low-dose continuous exposure to REEs.

Waves can cause significant accumulation of pore water pressure and liquefaction in seabed soils, leading to instability of foundations of marine hydrokinetic devices (MHKs). Geostatic shear stresses (existing around foundations, within slopes, etc.) can substantially alter the rate of pore pressure buildup, further complicating the liquefaction susceptibility assessments. In this study, the development of wave-induced residual pore water pressure and liquefaction within sandy seabed slopes supporting MHK structures is evaluated. Unlike most earlier studies that excluded the impact of shear stress ratios (SSR) on the residual pore pressure response of sloping seabeds, asymmetrical cyclic loadings are considered herein for a range of SSRs. To obtain wave-induced loading in the seabed (and cyclic shear stress ratios, CSRs), the poroelasticity equations governing the seabed response, coupled with those for fluid and structure domains, are solved simultaneously. Utilizing an experimental model based on anisotropic cyclic triaxial test data that includes CSR and SSR impacts, an equation for the rate of pore pressure buildup is developed and added as a source term to the 2D consolidation equation. Numerical investigations were performed by developing finite element models in time domain. The models were calibrated using particle swarm optimization method and validated against wave flume experimental data. The results indicate that the consideration of static shear stresses has led to sudden rise in residual pore pressures followed by fast dissipations at early and late time steps, respectively, beneath the structure. The exclusion of SSR is shown to cause significant overestimation of pore pressure accumulations at late cycles, potentially causing significant overdesign of MHK foundations. The impact of proximity to the free drainage boundary, CSR amplitude, and loading frequency on the accumulation of residual pore pressure is illustrated. The residual liquefaction susceptibility of the seabed is shown to decline by increase of the seabed slope angle.

The present work introduces an analytical framework based on the limit-equilibrium method for the determination of the local factor of safety (FS) and global factor of safety (FSG), and local displacements along the critical slip surface using the Morgenstern-Price (MP) method of slices. This proposed work computes displacements along the critical slip surface in addition to a single FSG. The unsaturated shear strength models, in conjunction with the soil-water characteristic curve (SWCC), are considered. The MP-based equilibrium equations to determine FSG are utilized as an objective function in the metaheuristic search algorithm of particle swarm optimization to determine the critical center, critical radius, and minimum FSG for unsaturated finite slopes. It is recommended to use a particle size of 75 and conduct 50 iterations for optimal results. The effects of SWCC fitting parameters on the critical slip surface, FSG, point FS, and point displacements are also investigated. Two distinct benchmark slope scenarios with and without negative pore water considerations are utilized in the current study. This approach enables a detailed investigation into the influence of various unsaturated soil parameters, such as af (related to the air-entry value), nf (related to the slope of the SWCC), and mf (related to the residual water content), as well as constitutive model parameters including the linear shear modulus (G) and the fitting parameter (rho). The maximum displacement occurs at the slope's top crest. Under benchmark conditions, the first scenario shows a reduction in point displacement by 3.30%, 1.98%, and 10.23% for SWCC-1, SWCC-2, and SWCC-3, respectively. However, in the second scenario with SWCC-3, the critical slip surface's position changes, affecting local displacements. This results in an increase of 32.72% (i.e., from 21.45 to 28.47 mm) in point displacement at the top when comparing SWCC-3 with no SWCC consideration. The current study advocates that the effect of fitting parameters of the SWCC should be used to better understand the local FS and displacement, because the critical slip surface is contingent on the values of the SWCC. Ignoring SWCC parameters can lead to an underestimation of slope displacement, because they significantly influence the critical slip surface position and displacement magnitude. Their inclusion is essential for accurately assessing slope stability and preventing errors in displacement prediction.