An Innovative Computational Fluid Dynamics Discrete Dipole Approximation (CFD-DDA) Platform for Predicting Airborne Virus-in-Saliva Disinfection by Ultraviolet Irradiation

All published models of ultraviolet (UV) inactivation of airborne viruses in saliva droplets have neglected UV light scattering.

To the best of our knowledge, this work presents the first Computational Fluid Dynamics-Discrete Dipole Approximation (CFD-DDA) platform for investigating the physical mechanisms governing UV disinfection of virus-laden airborne saliva droplets.

The DDA solver predicts UV light scattering by both spherical and irregularly shaped saliva droplets, while the CFD solver predicts droplet evaporation and transport in airflow.

By coupling the DDA and CFD solvers, we demonstrate that infected saliva droplets, whether spherical or irregularly shaped due to evaporation, experience highly non-uniform UV light scattering that significantly affects virus inactivation and cannot be neglected.

This phenomenon has not previously been investigated within a fully three-dimensional framework.

The coupled Euler-Lagrange CFD-DDA model further quantifies the effects of (i) the initial droplet size distribution and concentration, (ii) airflow rate, and (iii) droplet interactions with the surrounding airflow and bounding walls on the total number of surviving coronavirus copies $N_s$, assuming a virion diameter of 100 nm, an air temperature of 21 $^{\circ}$C, and a relative humidity of 65%.

Based on the DDA results, a new virus inactivation model, referred to as the Dbouk-Yurkin law, is proposed.

This model extends the classical Chick-Watson law by explicitly accounting for UV light scattering in both spherical and non-spherical airborne saliva droplets.

The proposed three-dimensional CFD-DDA platform provides a powerful framework for improving the understanding of UV-based airborne virus disinfection and for optimizing the design and performance of UV air purification systems.