The SARS-CoV-2 pandemic highlighted the need to understand aerosol transport and associated disease transmission, and motivated many numerical flow studies using different numerical approaches to predict Lagrangian particle transport for infection risk modelling, with varying degrees of accuracy and computational cost. To evaluate the trade-off between these different flow simulation approaches, we compare particle concentration predictions based on solutions of the steady and unsteady Reynolds-averaged Navier-Stokes (RANS) equations with experimental data. A ventilated generic train entry segment is chosen because it is easy to set up for experiments and numerical flow simulations. Two heated dummies are placed in this ventilated space, one of which continuously exhales aerosol. The RANS approach predicts significant particle accumulations that are not observed in either the experiments or the URANS simulations. However, the averaged absolute deviation from the experimental data is reduced by a factor of 2.4 when URANS simulations are performed, albeit at an eightfold increase in computational cost.