Long-range transport and deposition on the Arctic snowpack of nuclear contaminated particulate matter.

The primary environmental concern related to nuclear power is the production of radioactive waste hazardous to humans and the environment. The main scientific and technological problems to address this are related to the storage and disposal of the nuclear waste and monitoring the dispersion of radioactive species into the environment. In this work, we determined an anomalously high 14C activity, well above the modern natural background, on surface and seasonal snow sampled in early May 2019 on glaciers in the Hornsund fjord area (Svalbard). Due to the lack of local sources, the high snow concentrations of 14C suggest long-range atmospheric transport of nuclear waste particles from lower latitudes, where nuclear power plants and treatment stations are located. The analysis of the synoptic and local meteorological data allowed us to associate the long-range transport of this anomalous 14C concentration to an intrusion event of a warm and humid air mass that likely brought pollutants from Central Europe to the Arctic in late April 2019. Elemental and organic carbon, trace element concentration data, and scanning electron microscopy morphological analysis were performed on the same snow samples to better constrain the transport process that might have led to the high 14C radionuclide concentrations in Svalbard. In particular, the highest 14C values found in the snowpack (> 200 percent of Modern Carbon, pMC) were associated with the lowest OC/EC ratios (< 4), an indication of an anthropogenic industrial source, and with the presence of spherical particles rich in iron, zirconium, and titanium which, altogether, suggest an origin related to nuclear waste reprocessing plants. This study highlights the role of long-range transport in exposing Arctic environments to human pollution. Given that the frequency and intensity of these atmospheric warming events are predicted to increase due to ongoing climate change, improving our knowledge of their possible impact to Arctic pollution is becoming urgent.

Hansbreen Snowpit Dataset - over 30-year of detailed snow research on an Arctic glacier.

Snow cover is a key element in the water cycle, global heat balance and in the condition of glaciers. Characterised by high temporal and spatial variability, it is subject to short- and long-term changes in climatic conditions. This paper presents a unique dataset of snow measurements on Hansbreen, an Arctic glacier in Svalbard. The dataset includes 79 archived snow profiles performed from 1989 to 2021. It presents all available observations of physical properties for snow cover, such as grain shape and size, hardness, wetness, temperature and density, supplemented with organised metadata. All data has been revised and unified with current protocols and the present International Classification for Seasonal Snow on the Ground, allowing comparison of data from different periods and locations. The information included is essential for estimations of glacier mass balance or snow depth using indirect methods, such as ground-penetrating radar. A wide range of input data makes this dataset valuable to the greater community involved in the study of snow cover evolution and modelling related to glaciology, ecology and hydrology of glacierised areas.

Environmental and Anthropogenic Factors Shape the Snow Microbiome and Antibiotic Resistome.

Winter tourism can generate environmental pollution and affect microbial ecology in mountain ecosystems. This could stimulate the development of antibiotic resistance in snow and its dissemination through the atmosphere and through snow melting. Despite these potential impacts, the effect of winter tourism on the snow antibiotic resistome remains to be elucidated. In this study, snow samples subjected to different levels of anthropogenic activities and surrounding forest were obtained from the Sudety Mountains in Poland to evaluate the impact of winter tourism on snow bacteria using a metagenomic approach. Bacterial community composition was determined by the sequencing of the V3-V4 hypervariable region of the 16S rRNA gene and the composition of the antibiotic resistome was explored by metagenomic sequencing. Whereas environmental factors were the main drivers of bacterial community and antibiotic resistome composition in snow, winter tourism affected resistome composition in sites with similar environmental conditions. Several antibiotic resistance genes (ARGs) showed a higher abundance in sites subjected to human activities. This is the first study to show that anthropogenic activities may influence the antibiotic resistome in alpine snow. Our results highlight the need to survey antibiotic resistance development in anthropogenically polluted sites.