Transport of expiratory droplets in an aircraft cabin

Gupta, Jitendra; Lin, Chao–Hsin; Chen, Qingyan

doi:10.1111/j.1600-0668.2010.00676.x

Cited by 186 publications

(165 citation statements)

References 28 publications

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“…Therefore, it is important to assess the influence of exhaled droplets on the emission rates of particles from clothed human body measured in this study. Gupta et al (2011) indicated that the typical amount of exhaled droplets for a breath can be set as 525 per breath. The duration of a breath is about 4 s (Gupta et al, 2010).…”

Section: Influence Of Exhaled Dropletsmentioning

confidence: 99%

Measuring the Short-Term Emission Rates of Particles in the “Personal Cloud” with Different Clothes and Activity Intensities in a Sealed Chamber

You

Cui

Chen

et al. 2013

Aerosol Air Qual. Res.

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A series of measurements were conducted to determine the short-term emission rates of particles in the "personal cloud" (i.e., particle emission from a clothed human body) in a sealed chamber. By recording the concentration of particles of different sizes during a period of time in the chamber, curves monitoring the evolution of particle concentration caused by emissions from a clothed human body were obtained. Based on the measured evolution of particle concentrations and deposition rates, the emission rates of particles from a clothed human body were estimated with a physical model. Generally speaking, the size-dependent emission rates of particles from a human body wearing a clean room smock were the lowest, while those from one wearing a cotton suit were the highest among the forms of clothing examined this work. Furthermore, the emission rates of particles from a clothed human body were positively correlated with the intensity of human activity. In addition, activities tended to have a more significant impact on the emission rates with regard to coarse rather than fine particles. The experimental data for the emission rates of particles from a clothed human body provided in this study may be used in further particle exposure assessments in certain indoor environments, such as clean rooms and aircraft cabins, as a valid input parameter.

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Section: Influence Of Exhaled Dropletsmentioning

confidence: 99%

Measuring the Short-Term Emission Rates of Particles in the “Personal Cloud” with Different Clothes and Activity Intensities in a Sealed Chamber

You

Cui

Chen

et al. 2013

Aerosol Air Qual. Res.

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“…One-jet airflow shows the great potential to prevent the direct exposure to a cough. In fact, most of the latex particles were transported within a short distance from the coughing person in the first 30 s and then could be transported to the entire space with a uniform droplet distribution in 4 min (Gupta et al, 2011). As the source location significantly affects the pollutant transport within an aircraft cabin (Yan et al, 2009), the use of downward plane jet to separate the space into a few sub zones may minimize the transport of respirable particles of a cough from the source.…”

Section: Personal Protection Efficiency (Ppe)mentioning

confidence: 99%

“…Chao et al (2008) found that the lateral dispersion behaviour was dominated by the ventilation airflow and the effect of the thermal plume was relatively minor for the 1.5-45 µm droplets with lower supply airflow rate. It is well known that a cough may be one of the prime infectious sources of airborne diseases as it has a high velocity and large quantity of droplets (Gupta et al, 2009(Gupta et al, , 2011. A number of studies have investigated the basic characteristics of a human's cough regarding velocity distribution and size distribution of droplets.…”

Section: Introductionmentioning

confidence: 99%

Characterizing the Dynamic Interactions and Exposure Implications of a Particle-Laden Cough Jet with Different Room Airflow Regimes Produced by Low and High Momentum Jets

Cao

Liu

Boor

et al. 2015

Aerosol Air Qual. Res.

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The objective of this study is to examine the dynamic interaction of a cough jet with different indoor airflow distributions created by linear slot diffusers considering the inter-personal transport of coughed particles. The experimental measurements were performed in a chamber, where the interaction of a cough jet and downward jets with various momentums was visualized by smoke. In this study, parameters related to the dynamic interaction of a transient cough jet and a steady downward jet have been studied: (1) distance between the cough jet source and an exposed dummy (ED); (2) the initial momentum of the downward plane jet. The experimental results indicate that the ceiling-attached horizontal jets that are widely applied in the over-head mixing ventilation systems have difficulties in deflecting the cough jet, and thereby have difficulties in reducing inter-personal transport of the coughed particles. This study found that a downward plane jet could prevent the transport of cough particles from the cough dummy to the ED. When the ED is standing 0.5 meter away from the cough dummy, the personal exposure (PE) level to coughed particles by using a downward plane jet could be two orders of magnitude lower than by using ceiling-attached horizontal jets. In addition, this study quantifies the interaction of a cough jet and a downward plane jet in their ability to reduce exposure to coughed particles. The results may be used in the process of diffuser selection and suggests that ventilation systems employing downward plane jets with high discharge velocities might be useful in public spaces to reduce inter-personal exposure to coughed particles.

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“…For example, Chao and Wan (2006) and Gao and Niu (2007) used a Lagrangian model to investigate the dispersion of particles in a room with different ventilation modes. Gupta et al (2011a) investigated the dispersion of exhaled droplets in a section of an aircraft cabin with the Lagrangian method. Gao et al (2012) applied a Lagrangian model to study the lock-up phenomenon of exhaled droplets in a room with displacement ventilation.…”

Section: Introductionmentioning

confidence: 99%

Comparing the Markov Chain Model with the Eulerian and Lagrangian Models for Indoor Transient Particle Transport Simulations

Chen

Liu

Lin

et al. 2015

Aerosol Science and Technology

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Correctly predicting transient particle transport in indoor environments is crucial to improving the design of ventilation systems and reducing the risk of acquiring airborne infectious diseases. Recently, a new model was developed on the basis of Markov chain frame for quickly predicting transient particle transport indoors. To evaluate this Markov chain model, this study compared it with the traditional Eulerian and Lagrangian models in terms of performance, computing cost, and robustness. Four cases of particle transport, three of which included experimental data, were used for this comparison. The Markov chain model was able to predict transient particle transport indoors with similar accuracy to the Eulerian and Lagrangian models. Furthermore, when the same time step size (Courant number 1) and grid number were used for all three models, the Markov chain model had the highest calculation speed. The Eulerian model was faster than the Lagrangian model unless a super-fine grid was used. This investigation developed empirical equations for evaluating the three models in terms of computing cost. In addition, the Markov chain model was found to be sensitive to the time step size when the Courant number is larger than 1, whereas the Eulerian and Lagrangian models were not.

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Transport of expiratory droplets in an aircraft cabin

Cited by 186 publications

References 28 publications

Measuring the Short-Term Emission Rates of Particles in the “Personal Cloud” with Different Clothes and Activity Intensities in a Sealed Chamber

Measuring the Short-Term Emission Rates of Particles in the “Personal Cloud” with Different Clothes and Activity Intensities in a Sealed Chamber

Characterizing the Dynamic Interactions and Exposure Implications of a Particle-Laden Cough Jet with Different Room Airflow Regimes Produced by Low and High Momentum Jets

Comparing the Markov Chain Model with the Eulerian and Lagrangian Models for Indoor Transient Particle Transport Simulations

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