Quantitative study of the influence of masks on airflow dynamics during breathing using particle image velocimetry

The dynamics of airflow are critical to respiratory disease transmission, particularly in indoor environments and industrial settings with high particulate matter, where airflow governs the dispersion and inhalation of infectious aerosols and dust. This study uses particle image velocimetry to perform a quantitative analysis of airflow during breathing, with and without face masks, using live human participants. We investigate three scenarios: no mask, a 2-ply cloth mask, and a filtering face piece 2 (FFP2) mask with an exhalation valve. Results show that cloth masks reduce mean exhalation velocity by 70% and maximum jet velocity from 4.2 m/s to under 2 m/s, while FFP2 masks with valves reduce peak velocities by 45.2% and redirect airflow downward. Directional analysis reveals that cloth masks deflect exhaled air forward and upward (30°–90°), increasing the potential for long-range droplet suspension, whereas valved FFP2 masks direct flow downward (330°), limiting forward dispersion. We further adapt multiphase puff models to quantify the transport of respiratory droplets ranging from 5 to 50 μm. These adapted models, which incorporate drag and entrainment effects, show that omitting drag can overestimate droplet travel by up to 1.5 orders of magnitude (e.g., 5 μm droplets can travel 15 m vs 0.5–1.5 m when drag is included). During inhalation, we find that droplets up to 10 μm can be drawn into the respiratory tract from distances up to 40 cm. These findings demonstrate the significant influence of mask type on airflow and droplet dispersion patterns, providing critical insights for public health guidelines and mask design in airborne disease mitigation.