American Association for Aerosol Research - Abstract Submission

AAAR 34th Annual Conference
October 12 - October 16, 2015
Hyatt Regency
Minneapolis, Minnesota, USA

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Dispersion of Aeolian Aerosols in Atmospheric Boundary Layer Following Dust Emission from Source Areas

BORIS KRASOVITOV, Itzhak Katra, Tov Elperin, Andrew Fominykh, Hezi Yizhaq, Ben-Gurion University of the Negev, Israel

     Abstract Number: 237
     Working Group: Aerosols, Clouds, and Climate

Abstract
Mineral dust is a key agent involved in a wide range of physical, chemical and biological processes of the Earth system. It has been recognized that dust as aerosol has significant impacts on the atmosphere composition as well as on human health. In the present investigation, we suggested a two-dimensional model for particulate matter (PM) dispersion due to dust emission from soils. The study is focused on the local spatial scale (10 km), which is the most important for the process of dust loading to the atmosphere. Aeolian field experiments were performed at a dust source site (loess soil in Northern Negev, Israel) with a portable boundary layer wind tunnel to determine the emitted PM fluxes for different wind speeds and varying soil conditions. The numerical model is formulated using parametrization based on the aeolian experiments. The wind velocity profiles used in the simulations were fitted from data obtained in field measurements with wind mast. Size distribution of the emitted dust particles in the numerical simulations was taken into account using a Monte Carlo method. The numerical simulations enabled to determine the particulate matter concentration distributions under specific shear velocities and dust fluxes from the soil. The calculations were performed for particulate matter PM5, PM10, and PM20 emitted from uniform and limited source areas. The calculated concentrations are supported by PM data recorded over time in a standard environmental monitoring station. The model enhances our capacity of quantification of dust processes to support climate models as well as health risk assessment.