An algorithm for characterizing the aerodynamic particle size profile of bacterium-laden expiratory aerosols and its validation using benign bacteria

Yang Yang, Gin Nam Sze To, Christopher Y.H. Chao

Research output: Chapter in book / Conference proceedingConference article published in proceeding or bookAcademic researchpeer-review

Abstract

An algorithm based on stochastic modeling was proposed to predict the aerodynamic particle size profile of bacterium-laden expiratory aerosols in this study. The validation experiment was conducted to verify the proposed method by performing biological air sampling using a multi-stage impactor. A strain of benign rod-shape bacteria, E. coli, was cultured to generate the simulated bacterium-laden expiratory aerosols. The size profile of simulated bacterium-laden expiratory aerosols was predicted by the proposed algorithm and measured by a multi-stage viable impactor. The predicted results using proposed algorithm showed that the droplet number peaked at the size channel of 2.5 μm. The experimental results showed that the maximum amounts of collected viable E. coli-laden droplet nuclei fell within the size range from 2.1 μm to 3.3 μm. It was found that the prediction by the proposed algorithm matched the measured results much better than that of the method only considering evaporative shrinkage.

Original languageEnglish
Title of host publication12th International Conference on Indoor Air Quality and Climate 2011
Pages897-902
Number of pages6
Publication statusPublished - 2011
Event12th International Conference on Indoor Air Quality and Climate 2011 - Austin, TX, United States
Duration: 5 Jun 201110 Jun 2011

Publication series

Name12th International Conference on Indoor Air Quality and Climate 2011
Volume2

Conference

Conference12th International Conference on Indoor Air Quality and Climate 2011
Country/TerritoryUnited States
CityAustin, TX
Period5/06/1110/06/11

Keywords

  • Aerodynamic diameter
  • Bacterium-laden expiratory aerosols
  • Infectious respiratory disease
  • Monte Carlo method
  • Stochastic modeling

ASJC Scopus subject areas

  • Pollution

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