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An advanced numerical model for the assessment of airborne transmission of influenza in bus microenvironments

A CFD-based numerical model was integrated with the Wells–Riley equation to numerically assess the risk of airborne influenza infection in a popular means of public transportation, e.g. the bus microenvironment. Three mixing ventilation methods, which are widely used in current bus configurations, a...

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Detalles Bibliográficos
Autores principales: Zhu, Shengwei, Srebric, Jelena, Spengler, John D., Demokritou, Philip
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier Ltd. 2012
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7117043/
https://www.ncbi.nlm.nih.gov/pubmed/32288019
http://dx.doi.org/10.1016/j.buildenv.2011.05.003
Descripción
Sumario:A CFD-based numerical model was integrated with the Wells–Riley equation to numerically assess the risk of airborne influenza infection in a popular means of public transportation, e.g. the bus microenvironment. Three mixing ventilation methods, which are widely used in current bus configurations, and an alternative displacement ventilation method were numerically assessed in terms of their ability to limit the risk of airborne influenza infection. Furthermore, both the non air-recirculation and air-recirculation with filtration ventilation modes were investigated in terms of the influenza infection probability. According to the simulation results, air-recirculation mode with high efficiency filtration was found to cause almost the same infection risk as non air-recirculation mode (100% outdoor air supply), which indicated a potential benefit of filtration in reducing the infection risk. Additionally, for the commonly used mixing ventilation methods, air distribution method, location of return/exhaust opening and seat arrangement affected the airborne transmission of influenza between passengers. The displacement ventilation method was found to be more effective in limiting the risk of airborne infection. Overall, the developed numerical model can provide insights into how the micro-environmental conditions affect airborne infection transmission in buses. This numerical model can assist in developing effective control strategies related to airborne transmitted diseases for other frequently used public transportation systems, such as trains and airplanes.