Brown carbon (BrC) is the ubiquitous part of the atmospheric organic carbon. It absorbs solar lights and greatly impacts the Earth's radiative balance. This study examines the spectral characteristics of BrC and its radiative effect in the Dhaka South (DS) site and Dhaka North (DN) site from July 2023 to January 2024 with a high-volume particulate matter sampler on quartz filters. Spectral characteristics such as absorption coefficient (babe,), mass absorption efficiency (MAE), absorption angstrom exponent (AAE), and refractive index (Kabs-x) were determined by using a UV -visible spectrophotometer, and fluorescence emission spectra were analyzed in different pH by the fluorescent spectrophotometer. The concentrations of BrC and black carbon (BC) were determined by an aethalometer. The mean concentrations of BrC and BC in Dhaka city were 18.63 +/- 3.84 mu g 111-3 and 17.93 +/- 3.82 pg M-3, respectively. The AAE values lie in the range of 3.20-4.01 (DN) and 3.27-4.53 (DS), and the radiative forcing efficiency of BrC was obtained at 4.43 +/- 1.02 W g-1 in DN and 3.93 +/- 0.74 W g-1 in DS, indicating the presence of highly light-absorbing BrC in these locations. Average MAE and Kabs_k values were 1.55 +/- 0.45 m2g1 and 0.044 + 0.013, respectively, in DS, alternatively 1.84 +/- 0.59 m2g1 and 0.052 +/- 0.016 in DN. The fluorescence excitation-emission spectra confirmed the presence of a polyconjugate cyclic ring with multifunctional groups in the structure of BrC. Light absorption properties and fluorescence emission spectra were varied with the change of pH. As the pH increased (2-8), the AAE value decreased and MAEB,c_365 increased due to protonation or deprotonation. This study highlights that the BrC has a significant impact on the air quality as well as the Earth's radiative balance, emphasizing its strong light-absorbing properties and variability with environmental factors.

The paper presents the strategic project of Tomsk State University devoted to studying the carbon cycle in the arctic land-shelf system. The obtained carbon cycle characteristics should be used for global climate model correction. The main objective of the consortium is to obtain new data on the variability of climatic and biological factors of various ecosystems, monitor them, and create archives of data on their dynamics. The area of the project includes the basins of the Great Siberian Rivers, and the shelf of the adjacent Arctic seas. A consortium of approximately twenty universities and research institutions was formed to study the carbon cycle in various environments, including seas, rivers, wetlands, and permafrost. In addition to studying the carbon cycle, the project also aims to develop methods for carbon sequestration and ecosystems remediation. One of such methods was developed for the assessment and cleanup of bottom sediments from oil and petroleum products as well as other hydrophobic contaminants and has been patented and tested in a series of field trials. Several special monitoring methods are described, such as novel sampling and sample laboratory processing techniques to assess microplastics in the environment; and holographic methods for underwater monitoring of the plankton behavior for early bioindication of hazards in the water area. This is particularly relevant for areas with dangerous objects, such as nuclear power plants, oil platforms, and gas pipelines. The methods of math modeling of the impact of climate change and anthropogenic factors on indigenous and local population lives were used.

The Arctic experiences rapid climate change, but our ability to predict how this will influence plant communities is hampered by a lack of data on the extent to which different species are associated with particular environmental conditions, how these conditions are interlinked, and how they will change in coming years. Increasing temperatures may negatively affect plants associated with cold areas due to increased competition with warm-adapted species, but less so if local temperature variability is larger than the expected increase. Here we studied the potential drivers of vegetation composition and species richness along coast to inland and altitudinal gradients by the Nuuk fjord in western Greenland using hierarchical modelling of species communities (HMSC) and linear mixed models. Community composition was more strongly associated with random variability at intermediate spatial scales (among plot groups 500 m apart) than with large-scale variability in summer temperature, altitude or soil moisture, and the variation in community composition along the fjord was small. Species richness was related to plant cover, altitude and slope steepness, which explained 42% of the variation, but not to summer temperature. Jointly, this suggests that the direct effect of climate change will be weak, and that many species are associated with microhabitat variability. However, species richness peaked at intermediate cover, suggesting that an increase in plant cover under warming climatic conditions may lead to decreasing plant diversity.

Global warming due to climate change has substantial impact on high-altitude permafrost affected soils. This raises a serious concern that the microbial degradation of sequestered carbon can result in alteration of the biogeochemical cycles. Therefore, the characterization of permafrost affected soil microbiomes, especially of unexplored high-altitude, low oxygen arid region, is important for predicting their response to climate change. This study presents the first report of the bacterial diversity of permafrost-affected soils in the Changthang region of Ladakh. The relationship between soil pH, organic carbon, electrical conductivity, and available micronutrients with the microbial diversity was investigated. Amplicon sequencing of permafrost affected soil samples from Jukti and Tsokar showed that Proteobacteria and Actinobacteria were the dominant phyla in all samples. The genera Brevitalea, Chthoniobacter, Sphingomonas, Hydrogenispora, Clostridium, Gaiella, Gemmatimonas were relatively abundant in the Jukti samples whereas the genera Thiocapsa, Actinotalea, Syntrophotalea, Antracticibcterium, Luteolibacter, Nitrospirillum dominated the Tsokar sample. Correlation analyses highlighted the influence of soil geochemical parameters on the bacterial community structure. PCoA analyses showed that the bacterial beta diversity varied significantly between the sampling locations (PERMANOVA test (F-value: 2.3316; R2 = 0.466, p = 0.001) and similar results were also obtained while comparing genus abundance data using the ANOSIM test (R = 0.345, p = 0.007).

Soil thermal conductivity (STC) plays a crucial role in regulating the energy distribution of both the surface and underground soil layers. It is widely applied in various fields, including engineering design, geothermal resource development and climate change research. A rapid and accurate estimation of STC remains a key focus in the study of soil thermodynamic parameters. However, the methods for estimating STC and their distinct characteristics have yet to be systematically reviewed. In this study, we used bibliometrics to comprehensively and systematically review the literature on STC, focusing on knowledge graph characteristics to analyze the development trend of calculation schemes. The main conclusions drawn from the study are as follows: (1) In recent years, most studies have been focused on soil thermal characteristics and their main contributing factors, the soil hydrothermal process in the Qinghai-Tibet Plateau, geothermal equipment and numerical simulations, and the exploration of geothermal resources. (2) A systematic review of various schemes indicates that no single scheme is universally applicable to all soil types. Moreover, a single parameterization scheme fails to meet the practical requirements of land surface process models. We evaluated the advantages and disadvantages of the traditional heat conduction schemes, parameterization schemes, and machine learning-based schemes and the findings suggest that a comprehensive scheme that integrates these three different schemes for STC simulations should be urgently developed.

Permafrost degradation is one of the most significant consequences of climate change in the Arctic. During summers, permafrost degradation is evident with cryospheric hazards like retrogressive thaw slumps (RTSs) and active layer detachment slides (ALDs). In parallel, the Arctic has become a popular tourist destination for nature-based activities, with summer being the peak touristic season. In this context, cryospheric hazards pose potential risks for tourists' presence in Arctic national parks and wilderness in general, like in the Yukon. This essay provides the basis for investigating further periglacial, geomorphological and tourism intersections, highlighting the critical need for future interdisciplinary research on thawing permafrost impacts. More so, this requires moving beyond the predominant focus on permafrost impacts on infrastructure and to also consider the direct threats posed to human physical presence in Arctic tourist destinations affected by permafrost degradation. Such interdisciplinary approach is critical not only to mitigate risks, but also to provide policy- and decision-makers with valuable insights for implementing measures and guidelines.

Ongoing and widespread permafrost degradation potentially affects terrestrial ecosystems, whereas the changes in its effects on vegetation under climate change remain unclear. Here, we estimated the relative contribution of progressive active layer thickness (ALT) increases to vegetation gross primary productivity (GPP) in the northern permafrost region during the 21st century. Our results revealed that ALT changes accounted for 40% of the GPP increase in the permafrost region during 2000-2021, with amplified effects observed in late growing season (September-October) (43.2%-45.4%) and was especially notable in tundra ecosystems (51%-52.6%). However, projections indicated that this contribution could decrease considerably in the coming decades. Model simulations suggest that once ALT increments (relative to the 2001-2021 baseline) reach approximately 90 cm between 2035 and 2045, the promoting effect of ALT increase on vegetation growth may disappear. These findings provide crucial insights for accurately modelling and predicting ecosystem carbon dynamics in northern high latitudinal regions.

This study employs the Global Navigation Satellite System-Interferometric Reflectometry (GNSS-IR) technique, along with in situ hydrothermal data, to explore the details and mechanisms of permafrost ground surface deformation in the hinterland Tibetan Plateau. Through analyzing GNSS data collected from November 2021 to April 2024, seasonal deformation of up to approximately 5 cm, caused by active layer freeze-thaw cycles, was identified. Additionally, more than 2 years of continuous monitoring revealed a clear ground subsidence rate of 2.7 cm per year due to permafrost thawing. We compared the GNSS-IR monitored deformation with simulated deformation using in situ soil moisture and temperature profiles at 5-220 cm depth and found that the correlation reached 0.9 during the active-layer thawing and freezing period; we also observed that following an exceptionally thawing season, the subsequent thawing season experiences notably greater thaw subsidence. Furthermore, we analyzed the differences in GNSS-IR monitoring results with and without the inclusion of Beidou Navigation Satellite System (BDS) signals, and found that the inclusion of BDS signals reduced the standard deviation of GNSS-IR results by an average of 0.24 mm on snow-free periods, but increased by an average of 0.12 mm during the snow cover periods. This may be due to the longer wavelength of the BDS signal, which exhibits greater diffraction through snow and reduces signal reflectivity compared to other satellite systems. The research results demonstrate the potential and ability of continuous GNSS-IR ground surface deformation monitoring in revealing and exploring the hydrothermal processes within permafrost under climate change.

Alpine treelines ecotones are critical ecological transition zones and are highly sensitive to global warming. However, the impact of climate on the distribution of treeline trees is not yet fully understood as this distribution may also be affected by other factors. Here, we used high-resolution satellite images with climatic and topographic variables to study changes in treeline tree distribution in the alpine treeline ecotone of the Changbai Mountain for the years 2002, 2010, 2017, and 2021. This study employed the Geodetector method to analyze how interactions between climatic and topographic factors influence the expansion of Betula ermanii on different aspect slopes. Over the past 20 years, B. ermanii, the only tree species in the Changbai Mountain tundra zone, had its highest expansion rate from 2017 to 2021 across all the years studied, approaching 2.38% per year. In 2021, B. ermanii reached its uppermost elevations of 2224 m on the western aspects and 2223 m on the northern aspects, which are the predominant aspects it occupies. We also observed a notable increase in the distribution of B. ermanii on steeper slopes (> 15 degrees) between 2002 and 2021. Moreover, we found that interactions between climate and topographic factors played a more significant role in B. ermanii's expansion than any single dominant factor. Our results suggest that the interaction between topographic wetness index and the coldest month precipitation (Pre(1)), contributing 91% of the observed variability, primarily drove the expansion on the southern aspect by maintaining soil moisture, providing snowpack thermal insulation which enhanced soil temperatures, decomposition, and nutrient release in harsh conditions. On the northern aspect, the interaction between elevation and mean temperature of the warmest month explained 80% of the expansion. Meanwhile, the interaction between Pre(1) and mean temperature of the growing season explained 73% of the expansion on the western aspect. This study revealed that dominant factors driving treeline upward movement vary across different mountain aspects. Climate and topography play significant roles in determining tree distribution in the alpine treeline ecotone. This knowledge helps better understand and forecast treeline dynamics in response to global climate change.

Background and AimsMicroorganisms are essential for carbon and nitrogen cycling in the active layer of permafrost regions, but the distribution and controlling factors of microbial functional genes across different land cover types and soil depths remain poorly understood. This gap hinders accurate predictions of carbon and nitrogen cycling dynamics under climate change. This study aims to explore how land cover type and soil depth influence microbial functional gene distribution in the Qinghai-Tibet Plateau's permafrost regions.MethodsSoil samples (0-50 cm) were collected from alpine wet meadows, alpine meadows, and alpine steppes. We analyzed the samples for physicochemical properties, microbial amplicon sequencing, and metagenomic sequencing. Correlation analyses were conducted between microbial community structure, functional genes, and environmental factors to identify the drivers of microbial carbon and nitrogen cycling.ResultsBacterial richness was 6.03% lower in steppe soils compared to wet meadow soils. Steppe soils exhibited the highest aerobic respiration potential, while deeper wet meadow soils had enhanced anaerobic carbon fixation potential and a higher abundance of carbon decomposition-related genes. Nitrogen assimilation was highest in steppe surface soils, whereas denitrification and ammonification were greatest in wet meadow soils. Carbon cycling potential was influenced by total soil carbon, nitrogen, phosphorus, and belowground biomass, while nitrogen cycling was driven by belowground biomass, soil moisture, and pH.ConclusionOur findings underscore the role of environmental factors in microbial functional gene distribution, providing new insights for modeling carbon and nitrogen cycling in alpine permafrost ecosystems under climate change.