DUST.ES · Addressing key uncertainties in mineral DUST EmiSsion modelling to better constrain the global dust cycle

Addressing key uncertainties in mineral DUST EmiSsion modelling to better constrain the global dust cycle

Mineral soil dust created by the wind erosion of arid and semi-arid surfaces is the dominant contributor to the total aerosol mass in the atmosphere, significantly affecting radiative fluxes, cloud properties, atmospheric chemistry, and ocean biogeochemistry. While numerical models that predict the emission, transport, and deposition of dust have notably improved over the last decade, they still face numerous challenges. A central challenge is to constrain dust emission globally, a complex process that depends on the wind stress and the land-surface condition. The quantification of dust emission is highly interdisciplinary as it links meteorology, pedology, geomorphology, and geology. Deficits of state-of-the-art global dust models include (1) an incomplete representation of the physics of dust emission, (2) a lack of skill to reproduce certain atmospheric processes that drive dust emission, and (3) a poor representation of small-scale dust sources and regions where anthropogenic changes in land use due to cultivation and grazing may have enhanced dust emission. Apart from effects on climate, mineral dust aerosol also directly affects society in various ways. Dust events events can severely reduce air quality and can cause, for example, respiratory and cardiovascular deceases. It also reduces visibility and thereby affects road and air traffic. The renewable energy sector is also strongly affected by dust, because dust can be deposited on solar power plants reducing their efficiency, in particular in regions such as northern Africa, which have a large potential for solar power production. A better prediction of dust events will help to mitigate some of the aforementioned dust effects, in addition to help to better understand and estimate dust effects upon climate. Our goal in this project was to redress model deficits related to the dust emission mechanism and meteorological dust injection processes, and hence to reduce uncertainty in modelled dust emission along with its attribution to natural and anthropogenic origin.

Data: CORDIS, © European Union