Literature DB >> 27717291

Turbulent eddy diffusion models in exposure assessment - Determination of the eddy diffusion coefficient.

Yuan Shao1, Sandhya Ramachandran2, Susan Arnold1, Gurumurthy Ramachandran3.   

Abstract

The use of the turbulent eddy diffusion model and its variants in exposure assessment is limited due to the lack of knowledge regarding the isotropic eddy diffusion coefficient, DT. But some studies have suggested a possible relationship between DT and the air changes per hour (ACH) through a room. The main goal of this study was to accurately estimate DT for a range of ACH values by minimizing the difference between the concentrations measured and predicted by eddy diffusion model. We constructed an experimental chamber with a spatial concentration gradient away from the contaminant source, and conducted 27 3-hr long experiments using toluene and acetone under different air flow conditions (0.43-2.89 ACHs). An eddy diffusion model accounting for chamber boundary, general ventilation, and advection was developed. A mathematical expression for the slope based on the geometrical parameters of the ventilation system was also derived. There is a strong linear relationship between DT and ACH, providing a surrogate parameter for estimating DT in real-life settings. For the first time, a mathematical expression for the relationship between DT and ACH has been derived that also corrects for non-ideal conditions, and the calculated value of the slope between these two parameters is very close to the experimentally determined value. The values of DT obtained from the experiments are generally consistent with values reported in the literature. They are also independent of averaging time of measurements, allowing for comparison of values obtained from different measurement settings. These findings make the use of turbulent eddy diffusion models for exposure assessment in workplace/indoor environments more practical.

Entities:  

Keywords:  Diffusion model; eddy diffusivity; exposure assessment; indoor air pollution; turbulent eddy diffusion coefficient (DT)

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Year:  2017        PMID: 27717291     DOI: 10.1080/15459624.2016.1238476

Source DB:  PubMed          Journal:  J Occup Environ Hyg        ISSN: 1545-9624            Impact factor:   2.155


  2 in total

1.  Bayesian State Space Modeling of Physical Processes in Industrial Hygiene.

Authors:  Nada Abdalla; Sudipto Banerjee; Gurumurthy Ramachandran; Susan Arnold
Journal:  Technometrics       Date:  2019-07-22

2.  Predicting the spatio-temporal infection risk in indoor spaces using an efficient airborne transmission model.

Authors:  Zechariah Lau; Ian M Griffiths; Aaron English; Katerina Kaouri
Journal:  Proc Math Phys Eng Sci       Date:  2022-03-16       Impact factor: 2.704

  2 in total

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