Numerical modeling of air ionization for bioaerosol removal and deactivation of aerosolized virus by air ionization
| dc.contributor.author | Essien, Desmond | |
| dc.contributor.examiningcommittee | Levin, David (Biosystems Engineering) Coombs, Kevin (Medical Microbiology and Infectious Diseases) Zhao, Lingying (Food, Agricultural and Biological Engineering, Ohio State University) | en_US |
| dc.contributor.supervisor | Zhang, Qiang (Biosystems Engineering) | en_US |
| dc.date.accessioned | 2021-01-13T18:22:26Z | |
| dc.date.available | 2021-01-13T18:22:26Z | |
| dc.date.copyright | 2021-01-12 | |
| dc.date.issued | 2020 | en_US |
| dc.date.submitted | 2021-01-13T02:33:31Z | en_US |
| dc.degree.discipline | Biosystems Engineering | en_US |
| dc.degree.level | Doctor of Philosophy (Ph.D.) | en_US |
| dc.description.abstract | The main objectives of this study were to numerically model negative air ionization for removal of bioaerosols and, to experimentally determine the effects of air ionization on the concentrations and the infectivity of aerosolized virus in enclosed spaces without ventilation. The Finite Volume Method (FVM) was used to simulate the physical processes of bioaerosol removal from air. A commercial software package (ANSYS FLUENT) was used to implement the FVM model. The transport of bioaerosols were modeled as a discrete phase using the Lagrangian approach under discrete random walk. The ions were modelled as unipolar (negatively charged) with a constant generation rate into the confined space. Experiments were conducted using a commercial ionizer in a chamber to validate the model and to quantify the effects of ionization on viral infectivity and virion (viral particles) concentrations. The model predictions of bioaerosol removal were within 22% of the measured values. The results showed that at a steady-state ion concentration of 2.4 E13 ions/m³ , ionization significantly reduced the concentrations of bioaerosols over time. The reduction of bioaerosol concentrations led to a one log10 reduction in virion concentrations over 90 s of ionization. Furthermore, at a steady-state ion concentration of 2.4 E13 ions/m³, ionization began to cause a significant reduction in viral infectivity at 30 s of ionization until a two log10 reduction in viral infectivity was achieved at 90 s. However, at a steady state ion concentration of 3.0 E10 ions/m³, ionization did not produce any significant effect on the viral infectivity. In conclusion, ionization is an effective technology for the purification of air in enclosed spaces when a critical ion threshold is present. The model presented in this study can be used as a tool to predict the spread and removal of bioaerosols in enclosed spaces. | en_US |
| dc.description.note | February 2021 | en_US |
| dc.identifier.uri | http://hdl.handle.net/1993/35226 | |
| dc.language.iso | eng | en_US |
| dc.rights | open access | en_US |
| dc.subject | Bioaerosol | en_US |
| dc.subject | Infectivity | en_US |
| dc.subject | Ions | en_US |
| dc.subject | Ionization | en_US |
| dc.subject | Reovirus | en_US |
| dc.title | Numerical modeling of air ionization for bioaerosol removal and deactivation of aerosolized virus by air ionization | en_US |
| dc.type | doctoral thesis | en_US |