New Research into Eddy Diffusivity (D)

One cannot teach (or blog) without learning.  It is one of the very real perks of trying to convey knowledge and information. 

At the recent conference of the American Industrial Hygiene Association in Salt Lake City, I and many of my colleagues were treated to some of the excellent work coming out of the University of Minnesota under the leadership of Dr. Gurumurthy Ramachandran or, as many of us know him, Ram.   Two of his graduate students presented their work which I will be summarizing here over the next few weeks. 

This week, it is my pleasure to summarize the presentation and work of Yuan Shao who told us of his efforts to determine of Eddy Diffusivity Coefficient (D) from more easily measured quantities such as ventilation rates and room dimensions.  

You may remember a blog I did some time ago on this subject published on December 30, 2013 (http://jayjock-associates.blogspot.com/2013/12/the-eddy-diffusion-near-field-model-is.html) entitled:  The Eddy Diffusion Near Field Model is Now Useable.   In that 2013 blog I discussed how the Eddy Diffusivity Model should be ideally suited for modeling many indoor sources; however, the major problem with the use of the model is the determination and use of a critical model parameter; specifically, the Eddy Diffusivity Coefficient (D).  Indeed, the predictions of this model are highly depended on D as defined below.

The critical variable D is dependent on how the air moves about randomly within the indoor environment.  Unfortunately, it (D) has historically proven itself to be very difficult to measure or estimate.   As a result many of us wishing to use this model have been forced to use a very wide range of estimates for D.  As such the utility of this model has been quite limited.   In that blog I discussed the research of Dr. Kai-Chung Cheng from Stanford University and his work to relate D to the ventilation rate expressed as air changes per hour and the room’s dimensions.   I noted Dr. Kai-Chungs work as a real advancement in our ability to use the Eddy Diffusivity Model which, by the way, is one of the available modules in the freeware spreadsheet: IH MOD.

It would appear that Yuan Shao has advanced that effort and provided us with more data and analysis of this important topic.   His conclusions are presented below: 

•    An exposure chamber was constructed to create conditions for the eddy diffusion studies.
•     A diffusion model accounting for chamber boundary, advection and the removal of contaminant due to the local ventilation system was developed.
•     In this study, the measured and modeled data fit well over a range of experimental conditions. There is a strong linear relationship between D and ACH, providing a surrogate parameter for estimating D in real-life settings.
•     The values of D obtained from the experiments are generally consistent with values reported in the literature.
•     These findings make the use of turbulent eddy diffusion models for exposure assessment in workplace environments more feasible.

This is exactly the type of work that has been needed for many years but is now coming out as a result of these excellent research programs.

Yuan Shao has given me permission to send his full slide deck to whoever asks me for it at:  mjayjock@gmail.com.

As always, I would be very interested in your comments about this work and your experience with the Eddy Diffusivity Model and IH MOD.