Windblown Dust Algorithm Development and Numerical Simulation for a Historical Case

Soil-derived dust represents one of the major components of the natural atmospheric aerosols. Arid and semiarid areas with unpaved and unvegetated land cover are particularly vulnerable to windblown dust, which results in high particulate matter pollution. To understand, predict, and mitigate the impact of dust aerosol on air quality and climate, it is necessary to parameterize the emission rate of dust particles from the wind erosion processes accurately. However, windblown dust emission is still poorly represented in existing air quality models. In this paper, a windblown dust emission model has been built based on a parameterization of threshold wind friction velocity depending on the roughness of surface, vegetation type, soil type, soil moisture content and on the size distribution of aerosols. The proposed dust model incorporates into a region air quality modeling system to simulate a North American dust storm episode occurring near the border of southwestern United States (US) and northwestern region of Mexico on 23 February 2007. It is shown that the implementation of windblown dust model in air quality model can significantly improve model capability of capturing the dust episode. The simulation of the model is in good agreement of the evolution of dust distribution. The modeled dust spatial patterns matched with the dust cloud patterns appearing on satellite images. Implementation of windblown dust model successfully captured the time of peak particulate matter (PM) concentrations for both PM10 and PM2.5 as well as the peak value of PM2.5 concentration. The modeled results clearly demonstrate an improved ability to predict PM event by applying windblown dust emission scheme.