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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.

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Characteristics of N˝•entrain, N˝•penet, and N˝•out of Filter 2 as a function of filter operating time. = 0.5,  = 1.0 m3/sec, and  = 0 µg/m3.
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pone-0088514-g003: Characteristics of N˝•entrain, N˝•penet, and N˝•out of Filter 2 as a function of filter operating time. = 0.5,  = 1.0 m3/sec, and  = 0 µg/m3.

Mentions: Figure 3 illustrates the temporal variations of , , and (defined as the sum of and ) of Filter 2 with 50% of antimicrobial efficiency. The air flow rate was 1 m3/sec, and dust particles were not considered. Because Filter 2 had the constant filtration efficiency (MERV 11, see Table 2), was also constant. The results show that the state of was divided into three phases: initial (A), transitional (B), and stationary (C). In the initial phase, was almost the same as , which was affected only by filtration efficiency. During this phase, , which is proportional to (see Eq. 7), was almost zero because on the filter was not substantial enough to cause any entrainment of bioaerosols into the air stream. After approximately 370 days of use, an entrained bioaerosol was observed (>1 CFU/cm2/day), and began to increase thereafter. At this transitional phase, on the filter was sufficiently increased so as to cause entrainment. Such an increase continued until approached . In the stationary phase, and stopped increasing because almost reached .


Methodology for modeling the microbial contamination of air filters.

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

Characteristics of N˝•entrain, N˝•penet, and N˝•out of Filter 2 as a function of filter operating time. = 0.5,  = 1.0 m3/sec, and  = 0 µg/m3.
© Copyright Policy
Related In: Results  -  Collection

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

pone-0088514-g003: Characteristics of N˝•entrain, N˝•penet, and N˝•out of Filter 2 as a function of filter operating time. = 0.5,  = 1.0 m3/sec, and  = 0 µg/m3.
Mentions: Figure 3 illustrates the temporal variations of , , and (defined as the sum of and ) of Filter 2 with 50% of antimicrobial efficiency. The air flow rate was 1 m3/sec, and dust particles were not considered. Because Filter 2 had the constant filtration efficiency (MERV 11, see Table 2), was also constant. The results show that the state of was divided into three phases: initial (A), transitional (B), and stationary (C). In the initial phase, was almost the same as , which was affected only by filtration efficiency. During this phase, , which is proportional to (see Eq. 7), was almost zero because on the filter was not substantial enough to cause any entrainment of bioaerosols into the air stream. After approximately 370 days of use, an entrained bioaerosol was observed (>1 CFU/cm2/day), and began to increase thereafter. At this transitional phase, on the filter was sufficiently increased so as to cause entrainment. Such an increase continued until approached . In the stationary phase, and stopped increasing because almost reached .

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