Selected Mineral Dust Events at the Sonnblick Observatory in 2024: Identification and Characterization Using In-Situ Data, PMF analysis and Atmospheric Transport Modelling

Mineral dust, emitted from soils in arid regions by wind erosion, represents one of the largest fractions of atmospheric aerosol by mass. Once airborne, dust can travel thousands of kilometers, influencing the atmosphere through scattering and absorption of sunlight, acting as ice-nucleating particles, and depositing on the ground where it reduces snow albedo and delivers nutrients to remote regions. High-altitude mountain stations provide a unique opportunity to study dust in the free troposphere and its long-range transport.

The Sonnblick Observatory (3106 m a.s.l.), located on the main ridge of the Austrian Alps, receives dust, particularly from Northern Africa, throughout the year. In this study, we focus on selected dust events during 2024, a year of particular interest due to one of the most intense events (aerosol mass above 700 µg/m³, 30 min averages) detected at the observatory. The observatory is a Global Atmosphere Watch (GAW) station, an Aerosol, Clouds, and Trace Gases Research Infrastructure (ACTRIS) aerosol in situ national facility and hosts a variety of aerosol, cloud and meteorological measurements.

Saharan dust events (SDEs) are initially identified using the “Saharan Dust Event Index,” routinely derived from in-situ optical measurements (nephelometer and aethalometer) at the station (Schauer et al. 2016). In addition, positive matrix factorization (PMF) of in-situ aerosol data is applied, with one significant factor interpreted as mineral dust and used for a second, independent event identification. PMF highlights events that may not be captured by the Saharan Dust Index, illustrating its potential as a complementary approach for dust detection. Individual events are further characterized using the full suite of in-situ measurements and weekly offline chemical composition analyses (inorganic ions, selected elements and carbohydrates as well as elemental and organic carbon) of PM₁₀ filter samples, again combined with PMF analysis to identify major aerosol sources. Particle size distributions up to 100 µm during SDEs are retrieved from multiple instruments, including a mobility spectrometer, optical particle counter, and holographic measurements (SwisensPoleno Jupiter). Average size distributions are calculated for each event. Meteorological and atmospheric conditions are analyzed in relation to particle size distributions and optical properties. Particular attention is given to events identified solely by PMF.

Typical transport pathways are investigated using FLEXPART, and dust concentrations are simulated with WRF-Chem (Weather Research and Forecasting (WRF) model coupled with Chemistry) and compared with in-situ observations. The WRF-Chem simulation considers only dust emissions, generated by the AFWA (Air Force Weather Agency) dust emission scheme. Hourly-resolved surface dust concentration, vertically resolved dust concentration profiles, and dust load are available on a 0.2° x 0.2° latitude-longitude grid. The data also contribute to the Sand and Dust Storms Warning Advisory and Assessment System (SDS-WAS) model ensemble.

We summarize a full season of observed dust events, identify their characteristic features and develop a data analysis strategy applicable to longer time periods. In particular, we examine PMF analysis as a potential tool for SDE detection.

Schauer, G., Kasper-Giebl, A. and Mocnik, G. (2016); https://doi.org/10.4209/aaqr.2015.05.0337

Acknowledgements
The participation of A. Skiba was supported by the program “Excellence Initiative – Research University” for the AGH University of Krakow (ID:13958).