Computational Fluid Dynamics and Discrete Dipole Approximation Applied to Predict Airborne Viruses Disinfection by Ultraviolet Irradiation
Year: 2026
Type: preprint
Abstract: Ultraviolet (UV) inactivation of airborne viruses involves coupled multiphysics and multiscale processes, yet UV scattering within virus-laden saliva droplets is commonly neglected. Here, for the first time we combine computational fluid dynamics (CFD) and the discrete dipole approximation (DDA) to investigate the influence of droplet-scale UV scattering on airborne virus inactivation. A benchmark CFD-DDA case study is developed and demonstrated that infected saliva droplets can exhibit highly non-uniform UV scattering under representative flow and irradiance conditions. This non-uniformity can substantially affect the predicted number of surviving viral copies, $N_s$ , indicating that UV scattering should be considered when modeling UV-based airborne disinfection systems. We systematically investigate the effect on $N_s$ by varying: the initially emitted saliva droplets diameter distribution, their number ($n(t = 0) = 10^3$ or $10^4$), volumetric airflow rate ($Q_v$ = 100, 150, or 200 $m^3/h$), droplet-wall interaction (stick vs escape), and coronavirus UV susceptibility constant (Z = 0.018 or 0.377 $m^2$/J). The simulations consider initially infected saliva droplets containing $7.4 \times 10^8$ RNA copies/mL, with a viral capsid diameter of $d_{cap}$ = 100 nm, at an air temperature of 21 °C and relative humidity of 65%. UV irradiation is represented by a 10 W cylindrical UV-lamp (34.3 mW/$cm^2$). The DDA results further enable development of an extended virus-inactivation model based on the classical Chick-Watson law that accounts for UV scattering in both spherical and nonspherical infected droplets. The results highlight the importance of resolving local UV-droplet interactions in airborne virus disinfection models and demonstrate the potential of the coupled CFD-DDA approach for improving the design and performance of UV-based airborne disinfection systems.
Source: arXiv (Cornell University)
Authors: Dbouk, Talib, Yurkin, Maxim
Language: English
Subfield: Pulmonary and Respiratory Medicine
Field: Medicine
Domain: Health Sciences
Open Access status: green
OpenAlex ID: W7167837888