Field-scale dynamic modeling of agriculture-operation dust dispersion

The frequency and intensities of dust exposures in and near farm fields, which potentially contribute to high intensity human exposure events, are rarely documented due to the transient nature of local dust plumes and the difficulties of making accurate concentration measurements. This paper presents a dynamic random-walk model which simulates the field-scale PM10 (particle diameter ≤10 μm) dust dispersion from agriculture disking operation. The major inputs are the friction velocity (u*) and wind direction in the simulation period, atmospheric stability, and source strength (mg/s, or particle numbers/s). In each time step (Lagrangian time scale, usually dt «1 s determined by the friction velocity and stability) of the model simulation, 3 instantaneous wind velocities (x, y and z directions) are produced randomly based on friction velocity and atmospheric stability. Then, the wind velocities drive each particle to fly. The particle deposition algorithm judges if a particle is deposited based on the particle settling speed and vertical wind velocity when it touches the ground surface. The particle concentration in 3-D can be obtained at any instant in time by counting the particle numbers in a unit volume. The time resolution of the outputs can be less than 1 s and the spatial resolution can be smaller than 1 m. Simulations from this model are compared with point sampler measurements (PM10) and spatial distributions of dust concentration data which were obtained by elastic Lidar. The model accuracy is acceptable.