The human lung comprises about 300 million alveoli which are located on bronchioles between the 17th to 24th generations of the acinar tree, with a progressively higher population density in the deeper branches (lower acini). The alveolar size and aspect ratio change with generation number. Due to successive bifurcation, the flow velocity magnitude also decreases as the bronchiole diameter decreases from the upper to lower acini. As a result, fluid dynamic parameters such as Reynolds (Re) and Womersley (α) numbers progressively decrease with increasing generation number. In order to characterize alveolar flow patterns and inhaled particle transport during synchronous ventilation, we have conducted measurements for a range of dimensionless parameters physiologically relevant to the upper acini. Acinar airflow patterns were measured using a simplified in vitro alveolar model consisting of a single transparent elastic truncated sphere (representing the alveolus) mounted over a circular hole on the side of a rigid circular tube (representing the bronchiole). The model alveolus was capable of expanding and contracting in-phase with the oscillatory flow through the bronchiole thereby simulating synchronous ventilation. Realistic breathing conditions were achieved by exercising the model over a range of progressively varying geometric and dynamic parameters to simulate the environment within several generations of the acinar tree. Particle image velocimetry was used to measure the resulting flow patterns. Next, we used the measured flow fields to calculate particle trajectories to obtain particle transport and deposition statistics for massless and finite-size particles under the influence of flow advection and gravity. Our study shows that the geometric parameters (β and ΔV/V) primarily affect the velocity magnitudes, whereas the dynamic parameters (Re and α) distort the flow symmetry while also altering the velocity magnitudes. Consequently, the dynamic parameters have a greater influence on the particle trajectories and deposition statistics compared to the geometric parameters. The results from this study can benefit pulmonary research into the risk assessment of toxicological inhaled aerosols, and the pharmaceutical industry by providing better insight into the flow patterns and particle transport of inhalable therapeutics in the acini.