Exhaled breath consists primarily of two phases: the vapor phase and the discrete phase. The latter is formed by a cloud of many small, exhaled breath aerosols (EBA) ejected from the lungs [1] and can influence how we perform breath sampling for breath metrology. Laboratory quantitation of EBA that are collected using breath devices encounters challenges that rise from the complexity of breath characteristics, such as the innate turbulence and the mobility of aerosols carried by the exhaled vapor phase. Computational modeling and simulation techniques such as computational fluid and particle dynamics (CFPD) can help to understand some of these complexities. In past work [2], polydisperse EBA were tracked using the Euler-Lagrange algorithm and the exhaled breath flowrate found to govern aerosol mass deposition in an impaction filter of a commercial breath device. Here, we present a robust open-source CFPD model using OpenFOAM to determine aerosol deposition during breath capture in an impaction filter (Fig. 1) and compare to the output of a commercial CFPD-based program (ANSYS FLUENT). To decouple the effect of eddy forces on aerosol mass collection, the vapor phase was simulated both as laminar and turbulent flow using the k-ε enhanced viscous model [3-5] between a range of flowrates from 0.05 L/s to 0.80 L/s. Aerosol mass deposition on the impaction filter was found to vary depending on flowrate. And while eddy forces generally improve aerosol collection, their contribution diminishes with increasing flowrate due to high inertial forces The greatest increase in deposition due to eddies occurred at lower flowrates. This indicates that turbulence has a strong influence on aerosol capture in this impaction filter and that experimentation with a greater understanding of aerosol-vapor fluid dynamics can lead to better filter understanding and breath collection procedures.