Snow Samples Research Articles

Characterization of Small Micro-and Nanoparticles in Antarctic Snow by Electron Microscopy and Raman Micro-Spectroscopy

The impact of the anthropic activities in Antarctica is a concerning issue. According to the Scientific Committee on Antarctic Research, attention has to be paid to the next-generation contaminants deriving from both long-range atmospheric transport and local sources. In this study, the capabilities of transmission electron microscopy with energy-dispersive X-ray spectroscopy and Raman micro-spectroscopy were exploited to evaluate the size, morphology, and chemical composition of small micro- and nanoparticles, as well as their aggregates, in surface snow samples collected during the 2020–2021 austral summer in the coastal area of Victoria Land near the Mario Zucchelli research station. The presence of biological particles, mineral dust, sea salts, and small carbonaceous and plastic micro- and nanoparticles was assessed. Sulfate, carbonate, and nitrate minerals were detected in all the samples, whereas polyethylene, poly(ethylene-co-vinyl-acetate), and different kinds of carbonaceous materials were predominantly identified in the samples closest to the research base. The presence of small micro- and nanoparticles containing heavy metals and plastic polymers in samples collected in the areas surrounding the Italian research base highlights the impact of anthropogenic activities on the polar environment, suggesting the need for continuous monitoring to evaluate possible threats to the delicate Antarctic ecosystem.

Characteristics and quantification of small microplastics (

Small microplastics (SMPs < 100 µm) can easily be transported over long distances far from their sources through the atmospheric pathways and reach even remote regions, including the Arctic. However, these sizes of MPs are mostly overlooked due to different analytical challenges; besides, their pathways through atmospheric depositions, such as snow depositions, are mostly unknown. The spatial variability in bulk snow samples was investigated for the first time in distinct sites (e.g., glaciers) near Ny Ålesund, the world-known northernmost permanent research settlement in the Svalbard Islands, to better comprehend the presence of SMP pollution in snow. Seasonal snow deposited over the tundra and the summits of different glaciers were also sampled. A sampling procedure was designed to obtain representative samples while minimizing plastic contamination, thanks to rigorous quality assurance and quality control protocol. SMPs’ weight (µg SMP L-1) and deposition load (mg SMPs m-2) result from being lower in the remote glaciers, where they may be subject to long-range transport. The SMPs’ minimum length was 20 µm, with the majority less than 100 µm. Regarding their size distribution, there was an increase in the size length deriving from the local input of the human presence near the scientific settlement. The presence of some polymers might be site-specific in relation to the pathways that affect their distribution at the sites studied. Also, from the snow surface layer collected at the same sites to evaluate the variability of SMPs during specific atmospheric deposition events, the results confirmed their higher weight and load in surface snow near the scientific settlement compared to the glaciers. The results will enhance the limited knowledge of the SMPs in polar atmospheric compartments and deposition processes.

Material mapping strategy to identify the density-dependent properties of dry natural snow

The mechanical properties of natural snow play a crucial role in understanding glaciers, avalanches, polar regions, and snow-related constructions. Research has concentrated on how the mechanical properties of snow vary, primarily with its density; the integration of cutting-edge techniques like micro-tomography with traditional loading methods can enhance our comprehension of these properties in natural snow. This study employs μ\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\mu$$\\end{document}CT imaging and uniaxial compression tests, along with the Digital Volume Correlation (DVC) to investigate the density-dependent material properties of natural snow. The data from two snow samples, one initially non-compressed (test 1) and the other initially compressed (test 2), were fed into Burger’s viscoelastic model to estimate the material properties. μ\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\mu$$\\end{document}CT imaging with 801 projections captures the three-dimensional structure of the snow initially and after each loading step at -18∘\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$${^\\circ }$$\\end{document}C, using a constant deformation rate (0.2 mm/min). The relative density of the snow, ranging from 0.175 to 0.39 (equivalent to 160–360 kg/m3\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$^3$$\\end{document}), is determined at each load step through binary image segmentation. Modulus and viscosity terms, estimated from Burger’s model, exhibit a density-dependent increase. Maxwell and Kelvin–Voigt moduli range from 0.5 to 14 MPa and 0.1 to 0.8 MPa, respectively. Viscosity values for the Maxwell and Kelvin–Voigt models vary from 0.2 to 2.9 GPa-s and 0.2 to 2.3 GPa-s within the considered density range, showing an exponent between 3 and 4 when represented as power functions. Initial grain characteristics for tests 1 and 2, obtained through image segmentation, reveal an average Specific Surface Area (SSA) of around 55 1/mm and 40 1/mm, respectively. The full-field strain distribution in the specimen at each load step is calculated using the DVC, highlighting strong strain localization indicative of non-homogeneous behavior in natural snow. These findings not only contribute to our understanding of natural snow mechanics but also hold implications for applications in fields such as glacier dynamics and avalanche prediction.

Finger flow modeling in snow porous media based on lagrangian mechanics

Practical formulation for finger flow is lacking even though such a non-Darcy flow is commonly observed in homogeneous snow porous media. This study generalized physics for porous media flow based on the Lagrangian Mechanics; for instance, Darcy formula was theoretically derived minimizing the energy loss by solving the Euler-Lagrange Equation with Rayleigh dissipation function. This least energy loss (LEL) principle was then used to elucidate the finger flow formation in homogenous media. It was found that the inactive saturation (non-contributing void fraction) plays an important role in finger flow formation. This new theory also linked Darcy-Richards capillary flow and Newtonian viscous flow theories. Predicted flow area fractions by the LEL model were verified by the cold room laboratory experiment using well-controlled, homogeneous snow sample, as performed and documented by Katsushima et al. (2013).

Spatial and temporal variability analysis of snow cover parameters according to the urbanized area profile system

The purpose of the study is to analyze the spatial and temporal variability of snow cover parameters in the urbanized area of the city of Irkutsk and its adjacent areas according to the system of profiles reflecting the features of the area microrelief. Field surveys were conducted in accordance with standard recommendations for snow and geochemical surveys. Snow sampling was carried out at the entire snow depth, with the exception of the snow depth of 0.5-1 cm. Sampling points located at least 25 meters away from the roads. Snow sampling in the residential areas of the city was carried out in the places with undisturbed snow cover and free from extraneous snow banks and landfills. Global Mapper, Golden Software Surfer, Statistica software were used to carry out statistical analysis, build the models of profile sections and obtain the diagrams of snow cover parameter distribution. A 3D relief model was obtained on the basis of radar topographic survey data, which revealed a multiple formation relief of the studied area featuring mountains, high plains with undulating flat gently sloping watersheds, valleys, hollows and depressions. The height difference is up to 230 m. The diagrams of snow depth distribution built with regard to the profiles made it possible to identify the territories with the deepest snow cover. A geochemical analysis of the melt water filtrate was carried out over a three-year period. In 2021 a high correlation with electrical conductivity was found for the contents of tungsten, sodium, bromine, calcium, molybdenum, sulfur, barium, magnesium, antimony, tantalum, cesium, titanium, chromium, and silicon. The average correlation level with electrical conductivity was recorded for arsenic, copper, and lead. The analysis data obtained indicate a different contamination level of the area as a result of atmospheric precipitation in those years due to the activity of industrial facilities. The distribution patterns of the pH snow index have been revealed. It is shown that zones with pH&lt;6 are mostly confined to the Irkutsk aluminum smelter. The zones with pH &gt;6 are caused by the influence of the power plants using hydrocarbon fuels: gasoline, kerosene, fuel oil, diesel fuel, coal. The snow cover was subjected to field and laboratory studies using GIS technologies and physico-chemical methods. The distribution and migration of pollutants in various spatial and temporal aspects have been revealed taking into account the terrain relief. The conducted study opens up opportunities for modeling the landscape structure, taking into account meteorological parameters, phenological processes and snow cover state for the purposes of the national economy and the location of construction of various facilities.

Combined effect of algae and dust on snow spectral and broadband albedo

The optical properties of snow can be strongly modified by the presence of a variety of impurities including mineral dust and snow algae. We made use of measured concentration of snow algae and mineral dust to parameterize the BioSNICAR radiative transfer model. Surficial snow samples were gathered during a field campaign on 7th July 2020 at the Presena glacier (Rhaetian Alps). We collected 18 samples of surface snow containing different amount of snow algae and mineral dust. Through radiative transfer simulations we estimated an average broadband albedo reduction of 7.4 ± 6.1 % and 35.3 ± 7.4 % compared to clean snow, caused by snow algae and mineral dust presence, respectively. When we considered the combined effect of snow algae and dust, we estimated a broadband albedo reduction equal to 40.8 ± 8.4 %. We estimated an average instantaneous radiative forcing induced by snow algae, mineral dust and both impurities equals to 42.3 (± 36.1) W/m2, 203.7 (±45.5) W/m2, and 211.8 (±45.9) W/m2, respectively.Using BioSNICAR simulations, we also tested a series of narrowband spectral indices to determine the concentration of mineral dust and snow algae from multi- and hyper-spectral data. Results showed that most spectral indices used for snow algae mapping are correlated also with mineral dust concentration. We found that only an index correlates uniquely with snow algae: the scaled band integral at 680 nm. A new spectral index, namely the Green Blue Normalized Index, is therefore proposed to discriminate mineral dust from snow algae when both impurities are present. The high spectral resolution of current (e.g. PRISMA, EnMAP) and future (e.g. CHIME, SBG) hyperspectral satellite missions will be fundamental to decouple the effect of mineral dust and snow algae on the optical properties of snow. In fact, from those data it is possible to calculate all narrowband indices presented in this study.

Variation in urban snow quality indicated by three seasonal sampling surveys conducted in Luleå (Sweden) within a span of 27 years

Concentrations of total suspended solids (TSS), trace metals (Cu, Cd, Cr, Zn, Cd, Pb), Na and 16 US EPA priority PAHs in urban snow were studied in the City of Luleå in Northern Sweden. Snow was sampled at six central urban and suburban sites with various traffic intensities, in three sampling surveys (1994–95, 2002–03, 2020–21), repeated for three ages of the urban snow cover of 40, 80, and 120 days, respectively. The older data, from the 1994–95 and 2002–03 surveys, were obtained from the existing literature. The concentrations and mass loads of TSS and most trace metals studied (Zn, Cu, Pb, and Cd) varied with time. TSS, Zn, and Cu showed slightly higher concentrations and mass loads in the 2003 (TSS avg = 2300 μg/L, Zn avg = 620 μg/L and Cu avg = 250 μg/L) and 2021 (TSS avg = 1500 μg/L, Zn avg = 530 μg/L and Cu avg = 220 μg/L) sampling surveys, compared to the 1995 survey (TSS avg = 620 μg/L, Zn avg = 240 μg/L and Cu avg = 97 μg/L). However, no evident trend was observed between the 2003 and 2021 sampling surveys. The highest concentrations of Pb and Cd were observed in snow samples from the 1994–95 sampling survey (Pb max = 570 μg/L, Cd max = 4.6 μg/L). Results indicated higher concentrations of the pollutants studied in the city centre, compared to the residential suburbs, and in areas with heavier traffic, where concentrations of metals correlated well with traffic intensity. Fractionation analysis of trace metals indicated that Zn, Cu and Pb occurred mostly in the particulate-bound phase (>0.45 μm) containing the most of Zn, Cu, and Pb mass, at 80, 84 and 94% of the total, respectively. Over 50% of the dissolved phase of Zn and Cu was in the truly dissolved fraction (<3000 MWCO). Concentrations of PAHs also increased with traffic intensity, with pyrene being the most frequently detected PAH, likely because of the strength of sources and various physical processes influencing the snowbanks development and causing spatial and temporal variations in pollutant concentrations.

Uncertainty analysis of IceCube instrument to enhance accuracy of specific surface area measurements

The specific surface area (SSA) is a measure of the snow microstructure and can be determined using an instrument called IceCube. IceCube measures the reflectance from surface of a snow sample with a 1310 nm infrared laser. In this study, the uncertainties associated with IceCube measurements of SSA were analyzed in two locations: Sodankylä, Finland and Queen Maud Land, Antarctica. The study tests the repeatability of the measurements by measuring several samples from the same height of a homogenous snowpack. Additionally, snow samples were rotated to find minimum and maximum reflectance values to test the uncertainty related to the direction of the sample under the laser. The study also observed the uncertainty related to potential melting of the sample in warm conditions due to slow measurement process. The study resulted that the highest uncertainty is related to the sampling process. Overall, this study provides insights into the uncertainties associated with IceCube measurements of SSA, which will improve the precision and reliability of future measurements.

Mapping of density-dependent material properties of dry manufactured snow using μ\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\mu$$\\end{document}CT

Despite the significance of snow in various cryospheric, polar, and construction contexts, more comprehensive studies are required on its mechanical properties. In recent years, the utilization of μ\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\mu$$\\end{document}CT has yielded valuable insights into snow analysis. Our objective is to establish a methodology for mapping density-dependent material properties for dry manufactured snow within the density range of 400–600 kg/m3\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$^3$$\\end{document} utilizing μ\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\mu$$\\end{document}CT imaging and step-wise, quasi-static, mechanical loading. We also aim to investigate the variations in the structural parameters of snow during loading. The three-dimensional (3D) structure of snow is captured using μ\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\mu$$\\end{document}CT with 801 projections at the beginning of the experiments and at the end of each loading step. The sample is compressed at a temperature of − 18 o\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\mathrm {^o}$$\\end{document}C using a constant rate of deformation (0.2 mm/min) in multiple steps. The relative density of the snow is determined at each load step using binary image segmentation. It varies from 0.44 in the beginning to nearly 0.65 at the end of the loading, which corresponds to a density range of 400–600 kg/m3\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$^3$$\\end{document}. The estimated modulus and viscosity terms, obtained from the Burger’s model, show an increasing trend with density. The values of the Maxwell and Kelvin–Voigt moduli were found to range from 60 to 320 MPa and from 6 to 40 MPa, respectively. Meanwhile, the viscosity values for the Maxwell and Kelvin–Voigt models varied from 0.4 to 3.5 GPa-s, and 0.3–3.2 GPa-s, respectively, within the considered density range. In addition, Digital Volume Correlation (DVC) was used to calculate the full-field strain distribution in the specimen at each load step. The image analysis results show that, the particle size and specific surface area (SSA) do not change significantly within the studied range of loading and densities, while the sphericity of the particles is increased. The grain diameter ranges from approximately 100 μ\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\upmu$$\\end{document}m to nearly 400 μ\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\upmu$$\\end{document}m, with a mode of nearly 200 μ\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\upmu$$\\end{document}m. The methodology presented in this study opens up a path for an extensive statistical analysis of the material properties by experimenting more snow samples.

Occurrence, distribution, potential sources, and risks of organophosphate esters in fresh snow on Urumqi Glacier No. 1, eastern Tien Shan, China

Organophosphate esters (OPEs), extensively used as flame retardants, are widely detected in various regions and environments. The potential toxicity of OPEs has caused great concern in recent years. Based on the global distillation model, the Tien Shan glaciers, such as Urumqi Glacier No. 1, could be as a potential “sink” for OPEs. However, little is known about the concentration, distribution, potential sources, and ecological risks of OPEs in Tien Shan glaciers. In this study, fresh snow samples were collected at various altitudes on the Urumqi Glacier No. 1, eastern Tien Shan, China. The total concentrations of ten OPEs (Σ10OPEs) ranged from 116 to 152 ng/L. The most abundant OPE was tris-(2-chloroisopropyl) phosphate (TCIPP), contributing to 74 % of the total OPEs. Σ10OPEs, tri-n-butyl phosphate (TnBP), and TCIPP concentrations showed positive correlations with altitude, indicating the effect of cold condensation on OPEs deposition. Based on air mass back-trajectory analysis and principal component analysis, we found that emissions from both traffic and household products in indoor environment were the important sources, and OPEs on the Urumqi Glacier No. 1 might mainly originate from Europe. Our assessment also showed triphenyl phosphate (TPhP) posed a low ecological risk in snow. This is the first systematic study of OPEs on the Tien Shan glaciers.

African dust transport and deposition modelling verified through a citizen science campaign in Finland

African desert dust is emitted and long-range transported with multiple effects on climate, air quality, cryosphere, and ecosystems. On 21–23 February 2021, dust from a sand and dust storm in northern Africa was transported to Finland, north of 60°N. The episode was predicted 5 days in advance by the global operational SILAM forecast, and its key features were confirmed and detailed by a retrospective analysis. The scavenging of dust by snowfall and freezing rain in Finland resulted in a rare case of substantial mineral dust contamination of snow surfaces over a large area in the southern part of the country. A citizen science campaign was set up to collect contaminated snow samples prepared according to the scientists’ instructions. The campaign gained wide national interest in television, radio, newspapers and social media, and dust samples were received from 525 locations in Finland, up to 64.3°N. The samples were utilised in investigating the ability of an atmospheric dispersion model to simulate the dust episode. The analysis confirmed that dust came from a wide Sahara and Sahel area from 5000 km away. Our results reveal the features of this rare event and demonstrate how deposition samples can be used to evaluate the skills and limitations of current atmospheric models in simulating transport of African dust towards northern Europe.

Development of a handheld integrating sphere snow grain sizer (HISSGraS)

Abstract We developed a Handheld Integrating Sphere Snow Grain Sizer (HISSGraS) for field use to measure the specific surface area (SSA) of snow. In addition to snow samples, HISSGraS can directly measure snow surfaces and snow pit walls. The basic measurement principle is the same as that of the IceCube SSA instrument. The retrieval algorithm for SSA from reflectance employs two conversion equations formulated using spherical and nonspherical grain shape models. We observed SSAs using HISSGraS, IceCube and the gas adsorption method in a snowfield in Hokkaido, Japan. Intercomparison of the results confirmed that with HISSGraS direct measurement, SSA profile observations can be completed in just ~1/10 the time required for measurement of snow samples. Our results also suggest that HISSGraS and IceCube have similar accuracy when the same snow samples are measured using the same grain shape model. However, SSAs of near-surface snow layers measured using the three techniques exhibited some biases, possibly due to rapid snow metamorphism or melting during measurement and some technical issues with optical techniques. When excluding SSA data for the surface layer, which metamorphosed remarkably during measurement, IceCube- and HISSGraS-derived SSAs correlated strongly with those obtained by gas adsorption and HISSGraS accuracy is 21–34%.

Lichen-associated microbial members are prevalent in the snow microbiome of a sub-arctic alpine tundra.

Snow is the largest component of the cryosphere, with its cover and distribution rapidly decreasing over the last decade due to climate warming. It is imperative to characterize the snow (nival) microbial communities to better understand the role of microorganisms inhabiting these rapidly changing environments. Here, we investigated the core nival microbiome, the cultivable microbial members, and the microbial functional diversity of the remote Uapishka mountain range, a massif of alpine sub-arctic tundra and boreal forest. Snow samples were taken over a two-month interval along an altitude gradient with varying degree of anthropogenic traffic and vegetation cover. The core snow alpine tundra/boreal microbiome, which was present across all samples, constituted of Acetobacterales, Rhizobiales and Acidobacteriales bacterial orders, and of Mycosphaerellales and Lecanorales fungal orders, with the dominant fungal taxa being associated with lichens. The snow samples had low active functional diversity, with Richness values ranging from 0 to 19.5. The culture-based viable microbial enumeration ranged from 0 to 8.05×103 CFUs/mL. We isolated and whole-genome sequenced five microorganisms which included three fungi, one alga, and one potentially novel bacterium of the Lichenihabitans genus; all of which appear to be part of lichen-associated taxonomic clades.

Snow sampling strategy can bias estimation of meltwater fractions in isotope hydrograph separation

The Isotope based Hydrograph Separation (IHS) has been instrumental in understanding the partitioning of streamflow sources and processes. However, uncertainties persist in the accuracy of IHS estimations and the appropriate definition and sampling of endmembers. To address these uncertainties, we used field data of snowpack, snowfall, and snow meltwater isotopes (δ18O) from Pallas, Northern Finland to estimate the total meltwater contribution during the snowmelt period. We investigated the biases resulting from the application of different sampling strategies for event water endmember. The total meltwater contribution to streamflow was 59.6 % (±2% uncertainty) using the time-variant rolling runoff-corrected melt flux-weighted meltwater 18O isotope value. However, replacing it with either snowfall or winter snowpack 18O isotope weighted average values underestimated the meltwater contribution by 17.8 % or 22.6 %, respectively. Conversely, using time-variant instantaneous meltwater 18O isotope values overestimated the meltwater contribution by only 1.5 %. These discrepancies highlight the importance of choosing the appropriate endmember isotopes in IHS. The large differences in meltwater contribution for a 2-week peak discharge period based on different endmembers can lead to different interpretations of hydrological, ecohydrological, and biogeochemical processes. Thus, to better understand streamflow generation processes, we suggest using rolling runoff-corrected meltwater 18O or 2H isotope values in the IHS. In the absence of meltwater samples, the 18O or 2H isotope values of snowpack samples during the peak melt season may provide reasonable estimates of the meltwater contribution, with some minor underestimations. Our study highlights the importance of appropriate event meltwater endmember selection and sampling methodology for the IHS.

Sample pretreatment effects on isotopic compositions of oxygen and sulfur in BaSO4 derived from atmospheric sulfate.

Preparation of BaSO4 from samples of atmospheric rain, snow, and aerosols has been used for δ18 O and δ34 S analyses. In the present study, we investigated the effect of various sample pretreatments on δ18 O and δ34 S values determined from a Na2 SO4 reagent solution and samples of atmospheric precipitation to improve assay time and cost efficiency. BaSO4 was prepared from a Na2 SO4 solution by (a) evaporative concentration, (b) evaporation to dryness, (c) evaporation to dryness after adding HCl, and (d) evaporation to concentration after adding HCl, followed by cooling and then precipitation using a BaCl2 solution. To analyze the atmospheric precipitation samples for δ18 O, BaSO4 prepared from the samples was treated with diethylenetriaminepentaacetic acid (DTPA) and SO4 2- and separated chromatographically. The values of δ18 O and δ34 S were measured using a continuous-flow elemental analyzer coupled to an isotope-ratio mass spectrometer. The δ34 S values in BaSO4 precipitated from Na2 SO4 solution determined by methods (a)-(c) were consistent within precisions of ±0.5‰. The δ18 O values of methods (a) and (b) were consistent within ±0.2‰, whereas the δ18 O values of methods (c) and (d) increased with increasing HCl concentrations. Similar results were obtained from samples of atmospheric precipitations. The δ18 O values from DTPA-treated BaSO4 were consistent with those obtained by chromatographic separation within ±0.5‰. We found no significant differences in the effects of various pretreatments (acidification, heating, concentration, and drying) on δ18 O and δ34 S values in sulfate from samples of atmospheric precipitation and aerosols extracted as BaSO4 if HCl was not added to the sample before heating and BaSO4 was treated with DTPA for the δ18 O analysis.

Distribution of Hydrocarbons in the Snow Cover of Natural and Urbanized Landscapes in the South of the Far East, Russia.

This study analyzed total organic carbon (TOC), petroleum products (PP), suspended materials (SM), volatile aromatic hydrocarbons (toluene, o-xylene, etc.) and n-alkanes in the snow cover of Bol'shekhekhtsirsky, Zeysky state natural reserves and Khabarovsk, on 4, 5 and 9 stations in the south of the Russian Far East in March 2020. In Bol'shekhekhtsirsky reserve, the concentrations of TOC, PP, and SM in snow samples were in the range of 1.5-2.4, 0.06-0.11, and 11.4-1.9mg/L, 1.4-1.9, 0.02-0.05, and 11-23mg/L in Zeysky reserve, while in Khabarovsk were 1.7-23.7, 0.12-1.26, and 25-294mg/L, respectively. In addition, the benzene, toluene, and o-xylene concentrations of snow samples ranges from not detected (ND) to 2.4, ND-3.1, and 1.1-2.7µg/L in Khabarovsk, ND-1.3, ND-2.1, and ND-2.7µg/L, respectively in Bol'shekhekhtsirsky reserve. Carbon preference index values of n-alkanes were consistent with anthropogenic sources for stations 7, 8 and 2 in Khabarovsk (Heat Power Plants 1, 2 and city roads). The snow of the Zeysky Reserve is not contaminated with organic pollutants, and can be used as a conditional background for the south of the Russian Far East.

Examining the relationships between big data analytics capability, entrepreneurial orientation and sustainable supply chain performance: moderating role of trust

PurposeUsing a dynamic capability view, this study examined the relationships between big data analytics capability (BDAC), entrepreneurial orientation (EO) and sustainable supply chain performance (SSCP) by exploring the moderating role of trust among supply chain partners.Design/methodology/approachQuestionnaires were collected from 300 manufacturing organizations using snow sampling. The moderating connections and direct relationships were examined using Hays' process macro and structural equation modeling.FindingsBDAC was positively related to EO and SSCP. When supply chain partners experienced low levels of trust, an increase in BDAC did not enhance SSCP. As trust increased, the relationship between BDAC and SSCP became more positive, underpinning the moderating effects of trust. Moreover, trust did not moderate the relationship between BDAC and EO. The moderating effect of trust on the relationship between EO and SSCP showed a positive relationship between EO and SSCP when trust was low; however, the relationship became negative when trust was high.Practical implicationsDeveloping technology alone may not be sufficient, as supply chain managers need to establish a strong business relationship based on mutual trust. However, they also need to be aware of the dangers of high levels of trust because these may negatively affect performance. Therefore, supply chain managers need to achieve an optimal level of trust that is neither excessive nor insufficient.Originality/valueAdvances in technology and entrepreneurial drive for supply chain sustainability make it pertinent to examine trust levels among supply chain partners and the varying impact on BDAC, EO and SSCP. The current study shows the negative aspects of too much trust among supply chain partners.

Environmental distribution of per- and polyfluoroalkyl substances (PFAS) on Svalbard: Local sources and long-range transport to the Arctic

The environmental distribution of per- and polyfluoroalkyl substances (PFAS) in water, snow, sediment and soil samples taken along the west coast of Spitsbergen in the Svalbard archipelago, Norwegian Arctic, was determined. The contribution of potential local primary sources (wastewater, firefighting training site at Svalbard airport, landfill) to PFAS concentrations and long-range transport (atmosphere, ocean currents) were then compared, based on measured PFAS levels and composition profiles. In remote coastal and inland areas of Spitsbergen, meltwater had the highest mean ΣPFAS concentration (6.5 ± 1.3 ng L−1), followed by surface snow (2.5 ± 1.7 ng L−1), freshwater (2.3 ± 1.1 ng L−1), seawater (1.05 ± 0.64 ng L−1), lake sediments (0.084 ± 0.038 ng g−1 dry weight (dw)) and marine sediments (<method detection limit (MDL)–0.46 ng g−1 dw, median 0.015 ng g−1 dw). Perfluoroalkyl sulfonates (PFSA) and 6:2 fluorotelomer sulfonate (FTSA) were predominant in water and soil samples influenced by local sources, while perfluoroalkyl carboxylates (PFCA) were predominant in water and sediment from remote coastal and inland areas of Svalbard. The PFAS composition profiles observed in remote areas indicated that atmospheric transport and oxidation of volatile precursors is an important source of PFCA on Svalbard. Shorter-chain PFAS such as perfluorobutanoate (PFBA) were the predominant PFAS in freshwater, reflecting replacement of C8-chained PFAS with shorter-chained compounds. The comparatively high PFAS (especially PFBA) concentration in meltwater indicated that melting of snow and ice during the Arctic spring is an important diffuse local PFAS source. This source may become even more important with climate warming-induced melting of Arctic glaciers and ice sheets. Further studies of mobilisation and transport of PFAS in the Arctic region are needed to confirm this trend.

Recent decline in atmospheric Pb deposition and isotopic constraints on changes in source contributions in snow from northwestern Greenland

We present lead (Pb) concentrations and isotope ratios in a continuous series of 38 snow samples from a 1.9-m snow pit, covering the period from winter 2012 to summer 2017, at the East Greenland Ice-core Project (EGRIP) ice core drill site in northwestern Greenland. Pb concentrations were highly variable, ranging from 1.53 to 94.9 pg g−1 (mean value of 10.6 pg g−1), with higher concentrations during winter and spring and lower concentrations during summer and fall. Our results show a substantial reduction in the Pb concentration of ∼50% between the 2000s and 2010s, reaching a level close to that observed in the mid-18th century, that is, the time of the Industrial Revolution. Remarkably low radiogenic Pb isotope compositions were observed in our samples compared to previously reported values during the 2000s. The Pb isotope mixing model results indicated a decreasing Chinese contribution from the 2000s onwards, while Europe/Russia emerged as a relatively more important contributor to the anthropogenic Pb input to central Greenland during the corresponding period. Thus, we hypothesized that the reduction in Pb pollution in central Greenland is largely due to a decreasing contribution from Chinese sources in response to the effectiveness of stringent emission control measures in China.

Bromine, iodine and sodium along the EAIIST traverse: Bulk and surface snow latitudinal variability

During the East Antarctic International Ice Sheet Traverse (Eaiist, december 2019), in an unexplored part of the East Antarctic Plateau, snow samples were collected to expand our knowledge of the latitudinal variability of iodine, bromine and sodium as well as their relation in connection with emission processes and photochemical activation in this unexplored area. A total of 32 surface (0–5 cm) and 32 bulk (average of 1 m depth) samples were taken and analysed by Inductively Coupled Plasma Mass Spectrometry (ICP-MS). Our results show that there is no relevant latitudinal trend for bromine and sodium. For bromine they also show that it has no significant post-depositional mechanisms while its inland surface snow concentration is influenced by spring coastal bromine explosions. Iodine concentrations are several orders of magnitude lower than bromine and sodium and they show a decreasing trend in the surface samples concentration moving southward. This suggests that other processes affect its accumulation in surface snow, probably related to the radial reduction in the ozone layer moving towards central Antarctica. Even though all iodine, bromine and sodium present similar long-range transport from the dominant coastal Antarctic sources, the annual seasonal cycle of the ozone hole over Antarctica increases the amount of UV radiation (in the 280–320 nm range) reaching the surface, thereby affecting the surface snow photoactivation of iodine. A comparison between the bulk and surface samples supports the conclusion that iodine undergoes spring and summer snow recycling that increases its atmospheric lifetime, while it tends to accumulate during the winter months when photochemistry ceases.