Particulate Matter Dispersion Modeling in Agricultural Applications: Investigation of a Transient Open Source Solver

Agriculture is a major emitter of particulate matter (PM), which causes health problems and can act as a carrier of the pathogen material that spreads diseases. The aim of this study was to investigate an open-source solver that simulates the transport and dispersion of PM for typical agricultural applications. We investigated a coupled Eulerian–Lagrangian solver within the open source software package OpenFOAM. The continuous phase was solved using transient large eddy simulations, where four different subgrid-scale turbulence models and an inflow turbulence generator were tested. The discrete phase was simulated using two different Lagrangian solvers. For the validation case of a turbulent flow of a street canyon, the flowfield could be recaptured very well, with errors of around 5% for the non-equilibrium turbulence models (WALE and dynamicKeq) in the main regions. The inflow turbulence generator could create a stable and accurate boundary layer for the mean vertical velocity and vertical profile of the turbulent Reynolds stresses R11. The validation of the Lagrangian solver showed mixed results, with partly good agreements (simulation results within the measurement uncertainty), and partly high deviations of up to 80% for the concentration of particles. The higher deviations were attributed to an insufficient turbulence regime of the used validation case, which was an experimental chamber. For the simulation case of PM dispersion from manure application on a field, the solver could capture the influence of features such as size and density on the dispersion. The investigated solver is especially useful for further investigations into time-dependent processes in the near-source area of PM sources.

Implementation of a synthetic inflow turbulence generator in idealised WRF v3.6.1 large eddy simulations under neutral atmospheric conditions

A synthetic inflow turbulence generator was implemented in the idealised Weather Research and Forecasting large eddy simulation (WRF-LES v3.6.1) model under neutral atmospheric conditions. This method is based on an exponential correlation function and generates a series of two-dimensional slices of data which are correlated both in space and in time. These data satisfy a spectrum with a near “-5/3” inertial subrange, suggesting its excellent capability for high Reynolds number atmospheric flows. It is more computationally efficient than other synthetic turbulence generation approaches, such as three-dimensional digital filter methods. A WRF-LES simulation with periodic boundary conditions was conducted to provide prior mean profiles of first and second moments of turbulence for the synthetic turbulence generation method, and the results of the periodic case were also used to evaluate the inflow case. The inflow case generated similar turbulence structures to those of the periodic case after a short adjustment distance. The inflow case yielded a mean velocity profile and second-moment profiles that agreed well with those generated using periodic boundary conditions, after a short adjustment distance. For the range of the integral length scales of the inflow turbulence (±40 %), its effect on the mean velocity profiles is negligible, whereas its influence on the second-moment profiles is more visible, in particular for the smallest integral length scales, e.g. those with the friction velocity of less than 4 % error of the reference data at x/H=7. This implementation enables a WRF-LES simulation of a horizontally inhomogeneous case with non-repeated surface land-use patterns and can be extended so as to conduct a multi-scale seamless nesting simulation from a meso-scale domain with a kilometre-scale resolution down to LES domains with metre-scale resolutions.