Efficient air cleaning technologies for separation and inactivation of pathogens
Motivation and Objective
Airborne transmission of pathogens became known to a wider public in the context of the COVID-19 pandemic. Recently required applications in hospitals as well as preparedness for future global threats demand the development of efficient air cleaning technologies for separating and inactivating pathogenic aerosol particles.
Modeling and Simulation of UV-based pathogen inactivation in aerosol streams
Disinfection by using UV-light has proven to be an effective way of rendering microorganisms inactive. From the engineering point of view, the use of mathematical models for the prediction of disinfection efficiency is highly important as the alternative, performing experiments to evaluate UV-light devices, is complex and expensive due to the bio-safety regulations that are involved. At HZDR we have developed a model that allows to perform computational experiments with a high degree of accuracy so that it can be used as a tool for designing and assessing UV-light devices in different flow scenarios.
The model allows the fast, accurate and affordable prediction of deactivation rate in UV light-based systems. It can be used for improvement of available systems or design of new products .The software is easy to use without expensive lab tests and can be adapted in a flexible way to different product constructions. The tool is not limited to CORONA viruses. Simulations with many viruses and bacteria listed in the literature database are possible. Simultaneous inactivation of multiple pathogens can be simulated.
Development of a wet filtering system
The separation of aerosol particles in gas-liquid systems plays a central role in a variety of industrial and natural applications, among which stand out air purification and filtration systems as well as precipitation scavenging. The particle size significantly affects the separation rate. The diffusion of particles in the nanometer range is largely dominated by molecular diffusion. In this regime, predictive models accurately estimate the separation rates. Model inaccuracy increases, however, significantly when the particle size ranges from 0.1 μm to 2.5 μm. In this impaction-dominated regime, the complex interplay between the flow dynamics and the particle inertia makes it difficult to apply predictive tools. A novel concept based on gas-liquid cyclone for particle separation is here to be conceived, tested and compared to a traditional wet filtering system.
Funding
Supported by the Initiative and Networking Fund of the Helmholtz Association of German Research Centres (HGF) under the CORAERO project (KA1-Co-06).