Backward-time Lagrangian stochastic dispersion models and their application to estimate gaseous emissions

Abstract

"Backward' Lagrangian stochastic models calculate an ensemble of fluid element (particle) trajectories that are distinguished by each passing through an observation point. As shown, they can be faster and more flexible in calculating short-range turbulent dispersion from surface area sources than "forward' models, which simulate trajectories emanating from a source. A "well-mixed' backward model is exploited to calculate the touchdown points of particles passing over a small plot on their way to an observation tower and it is shown how to use those data to estimate the plot emission rate from a single measurement of average concentration, wind speed, and wind direction on the tower. The method was evaluated using 36 field experiments. Predicted emission rates using the backward method agreed well with mass balance estimates. -from Authors