Indoor fine particulate matter (PM2.5) is important since people spend most of their time indoors. However, knowledge of the spatiotemporal variations of indoor PM2.5 concentrations within a city is limited. In this study, the spatiotemporal distributions of indoor PM2.5 levels in Nanjing, China were modeled by the multizone airflow and contaminant transport program (CONTAM), based on the geographically distributed residences, human activities, and outdoor PM2.5 concentrations. The accuracy of the CONTAM model was verified, with a good agreement between the model simulations and measurements (r = 0.940, N = 110). Two different scenarios were considered to examine the building performance and influence of occupant behaviors. Higher PM2.5 concentrations were observed under the scenario when indoor activities were considered. Seasonal variability was observed in indoor PM2.5 levels, with the highest concentrations occurring in the winter and the lowest occurring in the summer. Building characteristics have a significant effect on the spatial distribution of indoor PM2.5 concentrations, with multistory residences being more vulnerable to outdoor PM2.5 infiltration than high-rise residences. The overall population exposure to PM2.5 in Nanjing was estimated. It would be overestimated by 16.67% if indoor exposure was not taken into account, which would lead to a bias in the health impacts assessment.