The recent emphasis on environmental justice by the U.S. EPA has motivated the aerosol research community to develop innovative and cost-effective particulate matters (PMs) control technologies for subpopulations who are frequently exposed to indoor PMs. PM collection by electrostatic precipitation (ESP) has been proposed for indoor usage because it provides advantageous features over conventional fabric filters, such as lower energy consumption and being filterless. However, further research is needed before ESP can be used in indoor spaces, as ESPs suffer from low collection efficiency of submicron particles due to lower particle charging rates. Electrostatic particle clustering can potentially improve the shortcoming of ESPs if electrohydrodynamic (EHD) flow can be manipulated and controlled. A large-scale electrohydrodynamic (EHD) vortex flow was experimentally observed in the streamwise direction of a cylindrical ESP due to variation in current density. The objective of this study is to numerically characterize this novel large-scale EHD vortex flow for drag reduction and its potential ability to induce electrostatic particle clustering for submicron particles. The numerical model developed in COMSOL Multiphysics® solves the large-scale EHD vortex flow by coupling electrostatic physics with RANS k- turbulent flow physics, involving three numerical domains. The results show that increasing the inlet velocity by one order of magnitude increases the maximum velocity near the discharge electrode by 1.25%. In addition, under negligible inlet velocity, the ionic flow dominates, leading to pulsated EHD/Re2 numbers 1000 in the regions near the discharge and collection electrodes. The peak EHD can be increased by 1.75% as the discharge voltage increases from 20 to 26 kV. The large-scale EHD vortex flow can modify the turbulent boundary layer and result in reduction in viscous drag near the collection electrode under low inlet velocity and high discharge voltage, which can potentially lead to prolonged entrainment of submicron particles for electrostatic particle clustering.