Abstract
Grocery stores provide essential services to communities all over the world. The COVID-19 pandemic has necessitated better understanding of the transport and dynamics of aerosolized viruses, particularly for the assessment of infection transmission risk within grocery stores and for other providers of essential services. In this study, a 3D computational fluid dynamics model was developed for a medium-sized grocery store in the United States using Ansys Fluent software. Different cases were simulated of a single infected person releasing viral aerosols with and without wearing a face mask. Results showed characteristic airflow and temperature distribution patterns inside the store that can drive the indoor dispersal of viral aerosols. Unsteady spatial distribution of mean age of air was used as a metric to indirectly quantify areas of higher risk of infection. Several factors affected the localization of suspended viral aerosols. Major recirculation patterns in certain locations of the store caused by persistent eddies were primarily attributed to increased mean age of air. The maximum mean age of air in the grocery store was found to be less than 30 min. Simulation results indicate that, without wearing a face mask, the aerosol particles released from a coughing infected person can be spread throughout nearly one-quarter of the grocery store in less than 6 min. The source-control strategy with a face mask showed significant reduction of viral aerosols being dispersed indoors.
