Particle dispersion models describe how atmospheric pollutants disperse through turbulence while being advected downwind. Thus, they can predict the concentration field downwind of an emission source and are therefore consulted in applications like industrial air quality impact assessments, or form the basis of decision-making in accidental pollutant releases. Existing particle dispersion models either compromise on the accuracy of their results, or on their computational costs. So, the objective was to derive quickly accessible estimates of an accurate, however costly, Lagrangian particle dispersion model.
For this purpose, a scaling framework of the ground-level concentration distribution downwind of an emission source has been derived, partly in analogy to an existing scaling framework of flux footprints. It is demonstrated, that the dispersion of concentrations and fluxes are essentially driven by the same processes. Therefore, the lateral concentration distributions could be scaled without diffculty. However, the shapes of the crosswind-integrated concentration distributions appear not to be similar due to their well-mixed concentration downwind. Thus, an indirect approach via two scaling frameworks for the crosswind-integrated maximum concentration and its location is suggested. Nonetheless, when scaling the crosswind-integrated concentration distributions resulting from the Lagrangian model according to the procedure presented, they collapse onto an ensemble of quasi-similar curves.
Consequently, a parametrization is presented, which allows for real-scale predictions of the ground-level concentration distributions in boundary layer states ranging from stable to convective, and for emission heights ranging from near-surface to mid-boundary-layer-height.
An evaluation of the predictions against independent simulations of the Lagrangian model reveals an overall good coherence. However, pronounced deviations arise in stable stratification and for very low emission heights.
Finally, an alternative scaling approach is outlined, which aims at an improved prediction of the crosswind-integrated concentration decay.