Field comparison of dry deposition samplers for collection of atmospheric mineral dust: results from single-particle characterization

Abstract. Frequently, passive dry deposition collectors are used to sample atmospheric dust deposition. However, there exists a multitude of different instruments with different, usually not well-characterized sampling efficiencies. As result, the acquired data might be considerably biased with respect to their size representativity, and as consequence, also composition. In this study, individual particle analysis by automated scanning electron microscopy coupled with energy-dispersive X-ray was used to characterize different, commonly used passive samplers with respect to their size-resolved deposition flux and concentration. This study focuses on the microphysical properties. In addition, computational fluid dynamics modeling was used in parallel to achieve deposition velocities from a theoretical point of view. Flux measurements made using different passive samplers show a disagreement between the samplers. Both MWAC and BSNE collect considerably more material than Flat plate and the Sigma-2. The collection efficiency of MWAC for large particles increases in comparison to Sigma-2 slightly with increasing wind speed, while there is barely such increase visible for the BSNE. A correlation analysis between dust flux, derived dust concentrations and wind speed reveals a positive correlation between dust flux and dust concentration and negative correlation between dust flux and wind speed. A very good correlation is found between derived concentrations and PM 10 concentration measurements by an optical particle spectrometer. The results also suggest that a Big Spring Number Eight as horizontal flux sampler and a Sigma-2 as vertical flux sampler can be good options for PM 10 measurement, whereas a Modified Wilson and Cooke sample is not a suitable choice. Furthermore, it is found that deposition velocities calculated from classical deposition models do not agree with deposition velocities estimated using computational fluid dynamics simulations. The deposition velocity from CFD was often higher than the values derived from classical deposition velocity models. Comparatively, deposition velocity calculated using analytical approach better fits to the measurement data than deposition velocity from CFD.