Electrostatic precipitators clean away the particulate matter of exhaust gases in manifold industrial pro-cesses.Parameter studies of particle separation in the size range of several 100 nm to 25 pm is of particular interest for the prediction of precipitation efficiencies and emissions.Models typically cover the transport of particles towards walls of the precipitator.However,no model yet covers the possible re-entrainment of particles from layers formed at the walls back into the gas flow.This study presents the implemen-tation of a new time-resolving model for electrostatic precipitation utilizing a re-entrainment model.Experimental data support the results of modelling.The model uses a statistical approach based on prop-erties of the particulate layer forming at the precipitator walls.The model is used for the analysis of the redispersion of particles in a laboratory-scale electrostatic precipitator(Sander,Gawor,& Fritsching,2018).Results show reduced precipitation efficiencies for particles larger than 5 μm as particles have higher kinetic impact energies and lower bounding energy at the layer surface.Time dynamics reveal a steady-state behavior of the separation for CaCO3(limestone,trademark“Ulmer Weiss?”)while Al2O3(trademark“Pural NF?”)precipitation is affected by layer buildup at the walls increasing over several minutes.