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A Dynamic Lagrangian, Field-Scale Model of Dust Dispersion from Agriculture Tilling Operations
Published by the American Society of Agricultural and Biological Engineers, St. Joseph, Michigan www.asabe.orgCitation: Transactions of the ASABE. 51(5): 1763-1774. @2008
Authors: J. Wang, A. L. Hiscox, D. R. Miller, T. H. Meyer, T. W. Sammis
Keywords: Disking, Dust, Field scale, Lagrangian transport, Laser radar, LIDAR, Near-field, Particulate matter, PM10, Random walk model
Dust exposure in and near farm fields is of increasing concern for human health and may soon be facing new emissions regulations. Dust plumes of this nature have rarely been documented due to the unpredictable nature of the dust plumes and the difficulties of accurately sampling the plumes. This article presents a dynamic random-walk model that simulates the field-scale PM10 (particle diameter <10 µm) dust dispersion from an agriculture disking operation. The major improvements over traditional plume models are that it can simulate moving sources and plume meander. The major inputs are the friction velocity (u*), wind direction in the simulation period, atmospheric stability, and source strength (µg s-1). In each time step of the model simulation, three instantaneous wind velocities (x, y, and z directions) are produced based on friction velocity, mean wind speed, and atmospheric stability. The computational time step is 0.025 times the Lagrangian time scale. The resulting instantaneous wind vectors transport all the individual particles. The particle deposition algorithm calculates if a particle is deposited based on the particle settling speed and vertical wind velocity when it touches the ground surface. The particle mass based concentration in 3-D can be obtained at any instant by counting the particle numbers in a unit volume and then converting to mass based on the particle size and density. Simulations from this model are verified by comparison with dust dispersion and plume concentrations obtained by an elastic backscatter LIDAR. The simulated plume spread parameters (s y, s z) at downplume distances up to 160 m were within ±73% of those measured with a remote aerosol LIDAR. Cross-correlations between a modeled plume and LIDAR measurements of the actual plume were as high as 0.78 near the ground and decreased to 0.65 at 9 m above ground, indicating close pattern similarity between the modeled and measured plumes at lower heights but decreasing with elevation above the ground.