Ventilation indices for evaluation of airborne infection risk control performance of air distribution.

阅读:6
作者:Lu Yalin, Niu Dun, Zhang Sheng, Chang Han, Lin Zhang
Air distribution is an effective engineering measure to fight against respiratory infectious diseases like COVID-19. Ventilation indices are widely used to indicate the airborne infection risk of respiratory infectious diseases due to the practical convenience. This study investigates the relationships between the ventilation indices and airborne infection risk to suggest the proper ventilation indices for the evaluation of airborne infection risk control performance of air distribution. Besides the commonly used ventilation indices of the age of air (AoA), air change effectiveness (ACE), and contaminant removal effectiveness (CRE), this study introduces two ventilation indices, i.e., the air utilization effectiveness (AUE) and contaminant dispersion index (CDI). CFD simulations of a hospital ward and a classroom served by different air distributions, including mixing ventilation, displacement ventilation, stratum ventilation and downward ventilation, are validated to calculate the ventilation indices and airborne infection risk. A three-step correlation analysis based on Spearman's rank correlation coefficient, Pearson correlation coefficient, and goodness of fit and a min-max normalization-based error analysis are developed to qualitatively and quantitatively test the validity of ventilation indices respectively. The results recommend the integrated index of AUE and CDI to indicate the overall airborne infection risk, and CDI to indicate the local airborne infection risk respectively regardless of the effects of air distribution, supply airflow rate, infectivity intensity, room configuration and occupant distribution. This study contributes to airborne transmission control of infectious respiratory diseases with air distribution.

特别声明

1、本页面内容包含部分的内容是基于公开信息的合理引用;引用内容仅为补充信息,不代表本站立场。

2、若认为本页面引用内容涉及侵权,请及时与本站联系,我们将第一时间处理。

3、其他媒体/个人如需使用本页面原创内容,需注明“来源:[生知库]”并获得授权;使用引用内容的,需自行联系原作者获得许可。

4、投稿及合作请联系:info@biocloudy.com。