Abstract. The microphysical properties, composition and mixing state of mineral dust, sea salt and secondary compounds were measured by active and passive aerosol sampling, followed by electron microscopy and X-ray fluorescence in the Caribbean marine boundary layer. Measurements were carried out at Ragged Point, Barbados during June–July 2013 and August 2016. Techniques are presented and evaluated, which allow for statements on atmospheric aerosol concentrations and aerosol mixing state based on collected samples. It became obvious that in the diameter range with the highest dust deposition the deposition velocity models disagree by more than 2 orders of magnitude. Aerosol at Ragged Point was dominated by dust, sea salt and soluble sulfates in varying proportions. The contribution of sea salt was dependent on local wind speed. Sulfate concentrations were linked to long-range transport from Africa and Europe, and South America and the southern Atlantic Ocean. Dust sources were located in western Africa. The dust silicate composition was not significantly varied. Pure feldspar grains were 3 % of the silicate particles, of which about a third were K-feldspar. The average dust deposition observed was 10 mg m−2 d−1 (range of 0.5–47 mg m−2 d−1), of which 0.67 mg m−2 d−1 was iron and 0.001 mg m−2 d−1 phosphorus. Iron deposition was mainly driven by silicate particles from Africa. Dust particles were mixed internally to a minor fraction (10 %), mostly with sea salt and less frequently with sulfate. It was estimated that the average dust deposition velocity under ambient conditions is increased by the internal mixture by 30 %–140 % for particles between 1 and 10 µm dust aerodynamic diameter, with approximately 35 % at the mass median diameter of deposition (7.0 µm). For this size, an effective deposition velocity of 6.4 mm s−1 (geometric standard deviation of 3.1 over all individual particles) was observed.

In the paper "Composition and mixing state of atmospheric aerosols determined by electron microscopy: method development and application to aged Saharan dust deposition in the Caribbean boundary layer" by K. Kandler et al. (2018) an incorrect version of Fig. 9 was published.The published version was based on particle data partly uncorrected for particle shape, which is relevant in particular for the FWI data and the ratio of dust to total aerosol. A corrected version of Fig. 9 is found below. Because the overlapping region between FWI and DSDS is barely visible in the corrected version, a magnification is shown in addition.The corrected data processing also affects the discussion in the first paragraph of Sect. 3.2.1. While in the previously published version a considerable discrepancy between FWI as DSDS size distributions was visible, in the corrected version both curves agree rather well. Therefore, the discussion and potential explanations given in the first paragraph of Sect. 3.2.1 can be mostly disregarded. Instead, the FWI data confirm the general suitability of the Piskunov model as an estimator for atmospheric dust concentrations (dashed lines), whereas the hypothesis still persists that a major uncertainty of the total aerosol concentration (continuous lines) is related to the particle hygroscopicity. The maximum at 10 µm particle diameter found in the airborne data remains undetected in the ground-based data.

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.