Limits...
Methodology for modeling the microbial contamination of air filters.

Joe YH, Yoon KY, Hwang J - PLoS ONE (2014)

Bottom Line: The antimicrobial efficiency and flow rate were the dominant parameters affecting the number of bioaerosols downstream of the filter in the transitional and stationary phase, respectively.It was found that the nutrient fraction of dust particles entering the filter caused a significant change in the number of bioaerosols in both the transitional and stationary phases.The proposed model would be a solution for predicting the air filter life cycle in terms of microbiological activity by simulating the microbial contamination of the filter.

View Article: PubMed Central - PubMed

Affiliation: School of Mechanical Engineering, Yonsei University, Seoul, Republic of Korea.

ABSTRACT
In this paper, we propose a theoretical model to simulate microbial growth on contaminated air filters and entrainment of bioaerosols from the filters to an indoor environment. Air filter filtration and antimicrobial efficiencies, and effects of dust particles on these efficiencies, were evaluated. The number of bioaerosols downstream of the filter could be characterized according to three phases: initial, transitional, and stationary. In the initial phase, the number was determined by filtration efficiency, the concentration of dust particles entering the filter, and the flow rate. During the transitional phase, the number of bioaerosols gradually increased up to the stationary phase, at which point no further increase was observed. The antimicrobial efficiency and flow rate were the dominant parameters affecting the number of bioaerosols downstream of the filter in the transitional and stationary phase, respectively. It was found that the nutrient fraction of dust particles entering the filter caused a significant change in the number of bioaerosols in both the transitional and stationary phases. The proposed model would be a solution for predicting the air filter life cycle in terms of microbiological activity by simulating the microbial contamination of the filter.

Show MeSH

Related in: MedlinePlus

Determination of the growth rate and entrainment constant.Comparison of the calculation results (line) and the experimental finding (solid square).
© Copyright Policy
Related In: Results  -  Collection

License
getmorefigures.php?uid=PMC3921200&req=5

pone-0088514-g001: Determination of the growth rate and entrainment constant.Comparison of the calculation results (line) and the experimental finding (solid square).

Mentions: By substituting  = 1.66×106 CFU/cm2[17] into Eq. 23 and comparing our calculated results with experimental data of a previous work of Verdenelli et al. [17], the growth rate () and the entrainment constant () were determined with SigmaPlot 8.0. Finally, 0.0012 1/hour and 3.0×10−10 1/m were selected as proper values for the growth rate and entrainment constant, respectively, showing R2 of 0.97, as presented in Fig. 1.


Methodology for modeling the microbial contamination of air filters.

Joe YH, Yoon KY, Hwang J - PLoS ONE (2014)

Determination of the growth rate and entrainment constant.Comparison of the calculation results (line) and the experimental finding (solid square).
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC3921200&req=5

pone-0088514-g001: Determination of the growth rate and entrainment constant.Comparison of the calculation results (line) and the experimental finding (solid square).
Mentions: By substituting  = 1.66×106 CFU/cm2[17] into Eq. 23 and comparing our calculated results with experimental data of a previous work of Verdenelli et al. [17], the growth rate () and the entrainment constant () were determined with SigmaPlot 8.0. Finally, 0.0012 1/hour and 3.0×10−10 1/m were selected as proper values for the growth rate and entrainment constant, respectively, showing R2 of 0.97, as presented in Fig. 1.

Bottom Line: The antimicrobial efficiency and flow rate were the dominant parameters affecting the number of bioaerosols downstream of the filter in the transitional and stationary phase, respectively.It was found that the nutrient fraction of dust particles entering the filter caused a significant change in the number of bioaerosols in both the transitional and stationary phases.The proposed model would be a solution for predicting the air filter life cycle in terms of microbiological activity by simulating the microbial contamination of the filter.

View Article: PubMed Central - PubMed

Affiliation: School of Mechanical Engineering, Yonsei University, Seoul, Republic of Korea.

ABSTRACT
In this paper, we propose a theoretical model to simulate microbial growth on contaminated air filters and entrainment of bioaerosols from the filters to an indoor environment. Air filter filtration and antimicrobial efficiencies, and effects of dust particles on these efficiencies, were evaluated. The number of bioaerosols downstream of the filter could be characterized according to three phases: initial, transitional, and stationary. In the initial phase, the number was determined by filtration efficiency, the concentration of dust particles entering the filter, and the flow rate. During the transitional phase, the number of bioaerosols gradually increased up to the stationary phase, at which point no further increase was observed. The antimicrobial efficiency and flow rate were the dominant parameters affecting the number of bioaerosols downstream of the filter in the transitional and stationary phase, respectively. It was found that the nutrient fraction of dust particles entering the filter caused a significant change in the number of bioaerosols in both the transitional and stationary phases. The proposed model would be a solution for predicting the air filter life cycle in terms of microbiological activity by simulating the microbial contamination of the filter.

Show MeSH
Related in: MedlinePlus