Development of a technique for measuring atmospheric dry deposition and its application to mineral dust

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 was used to characterize different, commonly used passive samplers with respect size-resolved chemical and physical properties of mineral dust aerosol particles. In addition, computational fluid dynamics simulations were conducted to predict the deposition of particles on to different passive samplers and thereby 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 Flat plate and the Sigma-2, 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 simulations (CFD). 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. Results also show that mineral dust is found to be the dominating mineral particle type during this campaign, comprising of different classes of classes of silicates, quartz-like, calcite-like, dolomite-like and gypsum-like particles. In addition, the analysis clearly indicates that the composition of dust aerosol particles remains largely unaffected by the sampler type. By using the relative abundance of the particle groups, size-resolved complex refractive index of dust particles is calculated. It is found that average refractive index is mainly wavelength dependent. The calculated real part of refractive index varied in between 1.71 and 1.53 for wavelengths ranging from 370 to 950 nm. Likewise, the imaginary part of refractive index is calculated for iron oxide particles and is varied in between 3.28*10-4 to 7.11*10-5 for wavelengths in the range of 250-1640 nm. Additionally, the refractive index values have shown a slight decrease with particle size. In the study, the potential for buffering of dust aerosol particles on the acid mobilization of iron particles is also analyzed. From analysis, it is found that the buffering potential depends on the environmental conditions and time. Moreover, by analyzing the ratio of sulfate mass to the total mass of dust of individual particles with the particle sizes, the mixing state of sulfate particles in the total dust particles were investigated. The analysis indicates that the ﬁner dust particles were associated with higher content of sulfur, while the coarse dust particles corresponds to lower sulfur contents revealing only fine mode sulfate is internally mixed with mineral dust aerosol particles. Overall, the results show that passive sampling techniques coupled with an automated single particle analysis could be a good option to assess physical and chemical properties of atmospheric mineral dust particles.