We present a new method for chemical characterization of micro- and nanoplastics based on thermal desorption–proton transfer reaction–mass spectrometry. The detection limit for polystyrene (PS) obtained is <1 ng of the compound present in a sample, which results in 100 times better sensitivity than those of previously reported by other methods. This allows us to use small volumes of samples (1 mL) and to carry out experiments without a preconcentration step. Unique features in the high-resolution mass spectrum of different plastic polymers make this approach suitable for fingerprinting, even when the samples contain mixtures of other organic compounds. Accordingly, we got a positive fingerprint of PS when just 10 ng of the polymer was present within the dissolved organic matter of snow. Multiple types of microplastics (polyethylene terephthalate (PET), polyvinyl chloride, and polypropylene carbonate), were identified in a snowpit from the Austrian Alps; however, only PET was detected in the nanometer range for both snowpit and surface snow samples. This is in accordance with other publications showing that the dominant form of airborne microplastics is PET fibers. The presence of nanoplastics in high-altitude snow indicates airborne transport of plastic pollution with environmental and health consequences yet to be understood.

We investigated the interactions of air and snow over one entire winter accumulation period as well as the importance of chemical markers in a pristine free-tropospheric environment to explain variation in a microbiological dataset. To overcome the limitations of short term bioaerosol sampling, we sampled the atmosphere continuously onto quartzfiber air filters using a DIGITEL high volume PM10 sampler. The bacterial and fungal communities, sequenced using Illumina MiSeq, as well as the chemical components of the atmosphere were compared to those of a late season snow profile. Results reveal strong dynamics in the composition of bacterial and fungal communities in air and snow. In fall the two compartments were similar, suggesting a strong interaction between them. The overlap diminished as the season progressed due to an evolution within the snowpack throughout winter and spring. Certain bacterial and fungal genera were only detected in air samples, which implies that a distinct air microbiome might exist. These organisms are likely not incorporated in clouds and thus not precipitated or scavenged in snow. Although snow appears to be seeded by the atmosphere, both air and snow showed differing bacterial and fungal communities and chemical composition. Season and alpha diversity were major drivers for microbial variability in snow and air, and only a few chemical markers were identified as important in explaining microbial diversity. Air microbial community variation was more related to chemical markers than snow microbial composition. For air microbial communities Cl − , TC/OC, SO 4 2− , Mg 2+ , and Fe/Al, all compounds related to dust or anthropogenic activities, were identified as related to bacterial variability while dust related Ca 2+ was significant in snow. The only common driver for snow and air was SO 4 2− , a tracer for anthropogenic sources. The occurrence of chemical compounds was coupled with boundary layer injections in the free troposphere (FT). Boundary layer injections also caused the observed variations in community composition and chemistry between the two compartments. Long-term monitoring is required for a more valid insight in post-depositional selection in snow.

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We investigate the influence of Saharan dust on the chemical composition and deposition loads of a 31-year long snow chemistry data set (1987-2017) of high alpine snow packs situated close to the Sonnblick Observatory, a global GAW (Global Atmospheric Watch) station, in the National Park Hohe Tauern in the Austrian Alps. Based on the snow pack of the winter accumulation period 2015/2016, when two Saharan dust events were visible by a reddish color of the snow, we define a pH > 5.6 together with a Ca 2+ concentration > 10 µeq/l as thresholds to identify Saharan dust affected snow layers. This criterion is checked with an intercomparison with trajectories and on-line aerosol data determined at the Sonnblick Observatory. This check was extended to the accumulation periods 2014/2015 and 2016/2017 before the whole time series is investigated regarding the contribution of Saharan dust to ion deposition loads. Especially Mg 2+ , Ca 2+ , and H + depositions are strongly affected by Saharan dust input causing, as average values across the 30 years period, increased Mg 2+ (25%) and Ca 2+ (35%) contributions of affected snow layers, while the contribution to the snow water equivalent was only 11%. For H + Saharan dust affected snow layers show a much lower contribution (2%) while the contribution of other ions is well comparable to the deposition amount expected according to the snow water equivalent of affected snow layers. The pH range of Saharan dust affected snow layers covers 5.58-7.17, while the median value of all samples is 5.40. The long term trends of ion deposition are not affected by the deposition of Saharan dust.

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Mineral dust is one of the main natural sources of atmospheric particulate matter, with the Sahara being one of the most important source regions for the occurrence and deposition of mineral dust in Europe. The occurrence of dust events in the European Alps is documented via measurements of airborne dust and its deposits onto the glaciers. Dust events occur mainly in spring, summer, and early autumn. Dust layers are investigated in ice cores spanning the last millennium as well as in annual snow packs. They strongly affect the overall flux of dust-related compounds (e.g., calcium and magnesium), provide an alkaline input to wet deposition chemistry, and change the microbial abundance and diversity of the snow pack. Still airborne mineral dust particles can act as ice nuclei and cloud condensation nuclei, influencing the formation of cloud droplets and hence cloud formation and precipitation. Dust deposits on the snow lead to a darkening of the surface, referred to as “surface albedo reduction,” which influences the timing of the snowmelt and reduces the annual mass balance of glaciers, showing a direct link to glacier retreat as observed presently in a warming climate.

Abstract. The determination of mineral dust and elemental carbon in snow samples is of great interest, since both compounds are known to be light-absorbing snow impurities. Different analytical methods have to be used to quantify both compounds. The occurrence of mineral dust, which contains hematite, leads to a bias in the quantification of elemental carbon and organic carbon via thermal–optical analysis. Here we present an approach which utilizes this interference to determine the concentration of iron via thermal–optical analysis using a Lab OC / EC Aerosol Analyzer (Sunset Laboratory Inc.) and the EUSAAR2 protocol. For this, the temperature dependency of the transmittance signal determined during the calibration phase, i.e., when all carbonaceous compounds are already removed, is evaluated. Converting the transmittance signal into an attenuation, a linear relationship between this attenuation and the iron loading is obtained for loadings ranging from 10 to 100 µg Fe cm−2. Furthermore, evaluation of the transmittance signal during the calibration phase allows to identify samples which need to be re-evaluated, since the analysis of elemental carbon and organic carbon is biased by constituents of mineral dust. The method, which was initially designed for snow samples, can also be used to evaluate particulate matter samples collected within the same high alpine environment. When applying the method to a new set of samples it is crucial to check whether the composition of iron compounds and the sample matrix remain comparable. If other sources than mineral dust determine the iron concentration in particulate matter, these samples cannot be evaluated with thermal–optical analysis. This is shown exemplarily with data from particulate matter samples collected in a railway tunnel.