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 a result, the acquired data might be considerably biased with respect to their size representativity and, as a consequence, also composition. In this study, individual particle analysis by automated scanning electron microscopy coupled with energy-dispersive X-ray analysis was used to characterize different, commonly used passive samplers with respect to their size-resolved deposition rate and concentration. This study focuses on the microphysical properties, i.e., the aerosol concentration and deposition rates as well as the particle size distributions. In addition, computational fluid dynamics modeling was used in parallel to achieve deposition velocities from a theoretical point of view. Scanning electron microscopy (SEM)-calculated deposition rate measurements made using different passive samplers show a disagreement among the samplers. Modified Wilson and Cooke (MWAC) and Big Spring Number Eight (BSNE) – both horizontal flux samplers – collect considerably more material than the flat plate and Sigma-2 samplers, which are vertical flux samplers. The collection efficiency of MWAC increases for large particles in comparison to Sigma-2 with increasing wind speed, while such an increase is less observed in the case of BSNE. A positive correlation is found between deposition rate and PM10 concentration measurements by an optical particle spectrometer. The results indicate that a BSNE and Sigma-2 can be good options for PM10 measurement, whereas MWAC and flat-plate samplers are not a suitable choice. A negative correlation was observed in between dust deposition rate and wind speed. Deposition velocities calculated from different classical deposition models do not agree with deposition velocities estimated using computational fluid dynamics (CFD) simulations. The deposition velocity estimated from CFD was often higher than the values derived from classical deposition velocity models. Moreover, the modeled deposition velocity ratios between different samplers do not agree with the observations.
Mineral dust composition affects a multitude of processes in the atmosphere and adjacent compartments. Dust dry deposition was collected near source in northwest Africa, in Central Asia, and on Svalbard and at three locations of the African outflow regime. Samples were subjected to automated scanning electron microscopy with energy-dispersive X-ray analysis to obtain size and composition of 216,000 individual particles. Results show low temporal variation in estimated optical properties for each location, but considerable differences between the African, Central Asian, and Arctic regimes. No significant difference was found between the K-feldspar relative abundances, indicating comparable related ice-nucleation abilities. The mixing state between calcium and iron compounds was different for near source and transport regimes, potentially in part due to size sorting effects. As a result, in certain situations (high acid availability, limited time) atmospheric processing of the dust is expected to lead to less increased iron solubility for near-source dusts (in particular for Central Asian ones) than for transported ones (in particular of Sahelian origin).Atmosphere 2020, 11, 269 2 of 16 Dust composition also affects the marine and terrestrial biosphere by supplying nutrients, but also supplying substances with adverse health effects [20]. Tropical as well as extra-tropical ecosystems apparently rely in part on atmospheric inputs [21,22]. Ocean surface waters can be depleted in essential nutrients supplied by the dust [23,24], thus composition plays an important role [25,26].Several of these effects are not only affected by the overall composition, but also by the distribution of the compounds between the particles (i.e., internal or external mixing). For example, optical properties are strongly dependent on the mixing state [27,28]. In addition, chemical processes might be considerably affected by the particle mixing state [29].Consequently, a more detailed knowledge of dust composition is expected to yield a better understanding and increased model quality. Information on bulk aerosol is available with respect to different properties (e.g., [6,7,30,31]) and finds its way into models [32]. In contrast, detailed properties like the aerosol mixing state are generally not yet regarded, probably due to scarcity of this information.In the present study, dust from different transport regimes-African near-source and outflow, Central Asian near-source, and a high-latitude source-is analyzed to provide information on its composition and variation. With respect to the importance of the mixing state, a single particle attempt was chosen. A particular focus of this study is the distribution of iron amongst individual particles, and its internal mixture with calcium compounds, as the iron compounds are of high interest for different processes. These processes include radiation absorption, photocatalytic reactions, and ocean fertilization.
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 PM10 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 PM10 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.
Interactive comment on "Field comparison of dry deposition samplers for collection of atmospheric mineral dust: results from single-particle characterization" by Andebo Waza et al. Andebo Waza et al.
Interactive comment on "Field comparison of dry deposition samplers for collection of atmospheric mineral dust: results from single-particle characterization" by Andebo Waza et al. Andebo Waza et al.
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