ACP Atmospheric Chemistry and Physics ACP 1680-7324 Copernicus GmbH Göttingen, Germany 10.5194/acp-12-845-2012 Technical Note: High-resolution mineralogical database of dust-productive soils for atmospheric dust modeling Nickovic S. 1 Vukovic A. 2 3 Vujadinovic M. 2 3 Djurdjevic V. 3 4 Pejanovic G. 3 World Meteorological Organization, Geneva, Switzerland Faculty of Agriculture, University of Belgrade, Serbia South East European Virtual Climate Change Center, Belgrade, Serbia Institute of Meteorology, University of Belgrade, Serbia 18 01 2012 12 2 845 855 This is an open-access article ditributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. This article is available from http://www.atmos-chem-phys.net/12/845/2012/acp-12-845-2012.html The full text article is available as a PDF file from http://www.atmos-chem-phys.net/12/845/2012/acp-12-845-2012.pdf

Dust storms and associated mineral aerosol transport are driven primarily by meso- and synoptic-scale atmospheric processes. It is therefore essential that the dust aerosol process and background atmospheric conditions that drive dust emissions and atmospheric transport are represented with sufficiently well-resolved spatial and temporal features. The effects of airborne dust interactions with the environment determine the mineral composition of dust particles. The fractions of various minerals in aerosol are determined by the mineral composition of arid soils; therefore, a high-resolution specification of the mineral and physical properties of dust sources is needed. <br></br> Several current dust atmospheric models simulate and predict the evolution of dust concentrations; however, in most cases, these models do not consider the fractions of minerals in the dust. The accumulated knowledge about the impacts of the mineral composition in dust on weather and climate processes emphasizes the importance of including minerals in modeling systems. Accordingly, in this study, we developed a global dataset consisting of the mineral composition of the current potentially dust-producing soils. In our study, we (a) mapped mineral data to a high-resolution 30 s grid, (b) included several mineral-carrying soil types in dust-productive regions that were not considered in previous studies, and (c) included phosphorus.

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