Modeling infection risk and energy use of upper-room Ultraviolet Germicidal Irradiation systems in multi-room environments

Abstract

The effectiveness of ultraviolet irradiation at inactivating airborne pathogens is well proven, and the technology is also commonly promoted as an energy-efficient way of reducing infection risk in comparison to increasing ventilation. However, determining how and where to apply upper-room Ultraviolet Germicidal Irradiation devices for the greatest benefit is still poorly understood. This article links multi-zone infection risk models with energy calculations to assess the potential impact of a Ultraviolet Germicidal Irradiation installation across a series of inter-connected spaces, such as a hospital ward. A first-order decay model of ultraviolet inactivation is coupled with a room air model to simulate patient room and whole-ward level disinfection under different mixing and ultraviolet field conditions. Steady-state computation of quanta-concentrations is applied to the Wells-Riley equation to predict likely infection rates. Simulation of a hypothetical ward demonstrates the relative influence of different design factors for susceptible patients co-located with an infectious source or in nearby rooms. In each case, energy requirements are calculated and compared to achieving the same level of infection risk through improved ventilation. Ultraviolet devices are seen to be most effective where they are located close to the infectious source; however, when the location of the infectious source is not known, locating devices in patient rooms is likely to be more effective than installing them in connecting corridor or communal zones. Results show an ultraviolet system may be an energy-efficient solution to controlling airborne infection, particularly in semi-open hospital environments, and considering the whole ward rather than just a single room at the design stage is likely to lead to a more robust solution.

Predicting airborne coronavirus inactivation by far-UVC in populated rooms using a high-fidelity coupled radiation-CFD model

“…Fully resolved spatially distributed far-UVC intensities enable more accurate predictions of virus removal over simplified 1/r 2 strategies 19 , diffusion radiation models 20 , and, potentially, empirical data taken from physical measurements [21][22][23] . The use of LES models 24 provide more detailed descriptions of viral transport over other modelling methods, such as Reynolds Averaged Navier-Stokes 21,23 or analytical zone-mixing methods 23,25 , and despite their increased computational requirement, and hence limited use, their importance is now being recognised in the field of atmospheric viral transport predictions 24 .…”

Upper-room ultraviolet air disinfection might help to reduce COVID-19 transmission in buildings: a feasibility study

“…Upper-room UVGI utilizes UV-C light at wavelengths close to 254 nm to create an irradiation field above the heads of room occupants ( Fig. 1 ) that disinfects aerosolised bacteria and viruses suspended in the air ( Beggs et al, 2006 ; Beggs & Sleigh, 2002 ; Noakes, Khan & Gilkeson, 2015 ). Because UV-C light is harmful to humans, such systems utilize louvers or shields that obscure the UV lamps from eyesight so that room occupants are kept safe.…”

Inactivation of airborne bacteria using different UV sources: Performance modeling, energy utilization, and endotoxin degradation

“…Utilization of the Chick-Watson model (Ryan et al, 2010;Xu et al, 2003;Kowalski and William, 2000) is the standard method for modeling the response of microorganisms to UVGI. In some cases, the two-stage curve (Noakes et al, 2015), such as Rennecker-Marinasis model (Crittenden et al, 2011) and Collins-Selleck model (Collins and Selleck, 1971), were used to describe the unusually high resistance of microorganisms to irradiation because many microbial decay curves exhibit a decay curve shoulder (time-delayed response) when exposed to UVGI. Most of the previous models were kinetic fitting of inactivation efficiency, while the present work takes mechanism of photoreaction into account, providing more insight into the process of UV inactivating bacteria.…”