The effect of mineral dust emitted from arid and semiarid surfaces upon climate and ecosystems depends fundamentally on their particle size distribution (PSD) and size-resolved mineralogical composition. However, soil mineralogy atlases used for mineral-speciated dust modelling are highly uncertain as they are derived extrapolating mineralogical analyses of soil samples that are particularly scarce in dust-source regions. This extrapolation neglects the processes affecting the formation of different dust-emitting surface sediments, such as dunes, crusts, and paved sediments. The Lower Drâa Valley, an inland drainage basin and preferential dust-source located in southern Morocco, was chosen for a comprehensive analysis of sediment grain size and mineralogy. Different sediment types samples were collected, including paleo-sediments, paved surfaces, crusts, and dunes, and analysed through PSD analysis of minimally and fully dispersed samples, and X-ray diffraction mineralogical analysis of bulk samples. We also performed Fe sequential wet extraction to characterize Fe mineralogy, including the contents of (oxyhydr)oxides (goethite and hematite), key to dust radiative effects, and poorly crystalline pool of Fe (readily exchangeable ionic Fe and nano-Fe-oxides), relevant to dust impacts upon ocean biogeochemistry. Based on the results we propose a conceptual model where both particle size and mineralogy are segregated by transport and deposition of sediments during runoff of water across the basin, and by the precipitation of salts, which causes a sedimentary fractionation. Coarser particles substantially richer in quartz are more present in elevated areas, and finer particles rich in clay, carbonates, and Fe-oxides are present in depressed areas, where dust emission is maximized. When water ponds and evaporates, secondary carbonates and salts precipitate, and the clays are enriched in readily exchangeable ionic Fe, due to sorption of dissolved Fe by illite. Our results differ from currently available mineralogical atlases and highlight the need for observationally-constrained global high-resolution mineralogical data for mineral-speciated dust modeling.
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González-Romero et al. (2023) studied this question.