An Experimental and Numerical Study on Deposition of Bioaerosols in a Scaled Chamber

Wong, Ling Tim; Chan, Wing-Shing; Mui, Kwok Wai; Lai, Alvin C.K.

doi:10.1080/02786820903426226

Cited by 23 publications

(26 citation statements)

References 29 publications

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“…Ideally all Reynolds' stresses are calculated individually as in the case of the RSM model. Although Wong et al [18] found good comparison using the RNG k-ε model, other studies have found that improvement achieved over standard k-ε models, still show significant differences compared to empirically measured DNS data [36].…”

Section: Cfd Methodologymentioning

confidence: 97%

“…With shedding of~10 6 skin flakes per day, they are consequently abundant in many health-care settings [17,18]. Staphylococcus aureus was chosen as the bacteriological agent given its ability to grow on general purpose media with ease.…”

Section: Bioaerosol Generationmentioning

confidence: 99%

“…Wong et al [18] undertook a small scale experimental/numerical comparison using bioaerosol deposition within a climatically controlled enclosure. They showed good comparison using the RNG k-ε turbulence model and their results are encouraging at high grid densities, despite the many reservations held regarding eddy viscosity turbulence modelling.…”

Section: Introductionmentioning

confidence: 99%

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Bioaerosol deposition in single and two-bed hospital rooms: A numerical and experimental study

King

Noakes

Sleigh

et al. 2013

Building and Environment

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Abstract:Aerial dispersion of pathogenic microorganisms and subsequent contamination of surfaces is well recognised as a potential transmission route for hospital acquired infection. Simulation approaches such as computational fluid dynamics (CFD) are increasingly used to model Results for all layouts demonstrate that small particle bioaerosols are deposited throughout a room with no clear correlation between relative surface concentration and distance from the source. However, a physical partition separating patients is shown to be effective at reducing cross-contamination of neighbouring patient zones.

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Section: Cfd Methodologymentioning

confidence: 97%

Section: Bioaerosol Generationmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Bioaerosol deposition in single and two-bed hospital rooms: A numerical and experimental study

King

Noakes

Sleigh

et al. 2013

Building and Environment

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“…Escherichia coli is regarded as highly susceptible to UVGI and are commonly used bioaerosols in UVGI system design [14,17,40]. Stock solutions of E. coli and S. marcescens were inoculated into nutrient agar plates (Oxoid), and the plates were incubated at 308C for 24 h. The incubation and harvesting methods were as described by Lai et al [17] and Wong et al [41]. The harvested cells were then transferred to 50 ml sterilized distilled water in a 24-jet collision nebulizer (BGI) for aerosolization.…”

Section: Generation and Collection Of Airborne Bacteriamentioning

confidence: 99%

Minimizing the exposure of airborne pathogens by upper-room ultraviolet germicidal irradiation: an experimental and numerical study

Yang

Chan

et al. 2012

J. R. Soc. Interface.

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There has been increasing interest in the use of upper-room ultraviolet germicidal irradiation (UVGI) because of its proven effectiveness in disinfecting airborne pathogens. An improved drift flux mathematical model is developed for optimizing the design of indoor upper-room UVGI systems by predicting the distribution and inactivation of bioaerosols in a ventilation room equipped with a UVGI system. The model takes into account several bacteria removal mechanisms such as convection, turbulent diffusion, deposition and UV inactivation. Before applying the model, the natural die-off rate and susceptibility constants of bioaerosols were measured experimentally. Two bacteria aerosols, Escherichia coli and Serratia marcescens , were tested for this purpose. It was found out that the general decay trend of the bioaerosol concentration predicted by the numerical model agrees well with the experimental measurements. The modelling results agree better with experimental observations for the case when the UVGI inactivation mechanism dominates at the upper-room region than for the case without UVGI. The numerical results also illustrate that the spatial distribution of airborne bacteria was influenced by both air-flow pattern and irradiance distribution. In addition to predicting the local variation of concentration, the model assesses the overall performance of an upper-room UVGI system. This model has great potential for optimizing the design of indoor an upper-room UVGI systems.

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“…Sub-micron sized particles are thought to remain airborne for prolonged periods of time [22], while larger droplets (>5 µm) are influenced by ventilation patterns, whereby the evaporation process followed by deposition may occur many meters from the initial source [23]. The environmental layout of a hospital room has been shown to have an impact on infection transmission, but biological experiments are only possible in specialist chambers [24,25]; in-vivo experimentation to discover where bioaerosols land in patient rooms is impossible using biological organisms [26]. Therefore, a non-biological surrogate that can faithfully mimic the trajectory of microorganisms in the indoor air is required.…”

Section: Introductionmentioning

confidence: 99%

An Effective Surrogate Tracer Technique for S. aureus Bioaerosols in a Mechanically Ventilated Hospital Room Replica Using Dilute Aqueous Lithium Chloride

et al. 2017

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Finding a non-pathogenic surrogate aerosol that represents the deposition of typical bioaerosols in healthcare settings is beneficial from the perspective of hospital facility testing, general infection control and outbreak analysis. This study considers aerosolization of dilute aqueous lithium chloride (LiCl) and sodium chloride (NaCl) solutions as surrogate tracers capable of representing Staphylococcus aureus bioaerosol deposition on surfaces in mechanically ventilated rooms. Tests were conducted in a biological test chamber set up as a replica hospital single patient room. Petri dishes on surfaces were used to collect the Li, Na and S. aureus aerosols separately after release. Biological samples were analyzed using cultivation techniques on solid media, and flame atomic absorption spectroscopy was used to measure Li and Na atom concentrations. Spatial deposition distribution of Li tracer correlated well with S. aureus aerosols (96% of pairs within a 95% confidence interval). In the patient hospital room replica, results show that the most contaminated areas were on surfaces 2 m away from the source. This indicates that the room's airflow patterns play a significant role in bioaerosol transport. NaCl proved not to be sensitive to spatial deposition patterns. LiCl as a surrogate tracer for bioaerosol deposition was most reliable as it was robust to outliers, sensitive to spatial heterogeneity and found to require less replicates than the S. aureus counterpart to be in good spatial agreement with biological results.

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An Experimental and Numerical Study on Deposition of Bioaerosols in a Scaled Chamber

Cited by 23 publications

References 29 publications

Bioaerosol deposition in single and two-bed hospital rooms: A numerical and experimental study

Bioaerosol deposition in single and two-bed hospital rooms: A numerical and experimental study

Minimizing the exposure of airborne pathogens by upper-room ultraviolet germicidal irradiation: an experimental and numerical study

An Effective Surrogate Tracer Technique for S. aureus Bioaerosols in a Mechanically Ventilated Hospital Room Replica Using Dilute Aqueous Lithium Chloride

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