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Predicting the performance of activated carbon filters at low concentrations using accelerated test data


Predicting the performance of activated carbon filters at low concentrations using accelerated test data

Khazraei Vizhemehr, Ali (2014) Predicting the performance of activated carbon filters at low concentrations using accelerated test data. PhD thesis, Concordia University.

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Indoor air quality (IAQ) is a major concern in non-industrial buildings since it can remarkably influence buildings occupants’ health, comfort and productivity. Adsorption-based granular activated carbon (GAC) filters are one of the common types of air purifying devices. They are considered to be an effective approach in maintaining IAQ by removing volatile organic compounds (VOC) which are the most conspicuous gaseous contaminants inside the buildings. Predicting the breakthrough time of filters is necessary for scheduling their maintenance and/or regeneration. However, determining their replacement time at low concentrations of contaminants similar to those encountered indoors is still questionable.
The main objective of this study is to develop and validate a reliable procedure to predict the long-term breakthrough time of GAC filters, when exposed to low indoor concentrations, using accelerated tests at high concentrations.
A comprehensive time-dependent model was proposed for predicting the performance of an in-duct GAC filter under the conditions relevant to the actual applications. The model integrates both pore diffusion and surface diffusion phenomena. Good agreement between the model prediction and the experimental data was observed at high concentration levels (down to 5ppm). Simulation results also indicated that the surface diffusion has a dominant role during VOC adsorption on activated carbon.
Furthermore a simplified framework featured by three practical pathways was developed for the estimation of the performance of an in-duct GAC filter. The developed framework is based on the dry air VOC adsorption isotherm and empirical breakthrough models. VOCs concentrations typically encountered in indoor environment are very low thus increasing the influence of humidity on filter performance. Therefore, the framework was then extended to the humid conditions.
A series of experiments was carried out on a small-scale experimental set-up (ASHRAE Standard 145.1) for a large range of VOC concentration levels, and also on a full-scale set-up (ASHRAE Standard 145.2) at different relative humidity levels. MEK, n-hexane and toluene were used as challenge gases.
The results showed that the developed framework can predict the breakthrough curve at very low concentrations (down to 1 ppm) with confidence for both dry and humid air conditions. Non-concentration dependent parameters extracted from empirical equations play an important role in developing the framework. However, these indicators do not remain constant in the presence of relative humidity. The overall mass transfer coefficient (in Wheeler-Jonas equation) and proportionality constant (in Yoon-Nelson equation) (both as a function of adsorption capacity) are influenced by humidity.
Using the proposed framework reduces the experimental work required by the user to predict GAC filter service life so that one can extrapolate data to untested vapor concentration and relative humidity levels.

Divisions:Concordia University > Gina Cody School of Engineering and Computer Science > Building, Civil and Environmental Engineering
Item Type:Thesis (PhD)
Authors:Khazraei Vizhemehr, Ali
Institution:Concordia University
Degree Name:Ph. D.
Program:Civil Engineering
Date:14 August 2014
Thesis Supervisor(s):Haghighat, Fariborz
ID Code:979033
Deposited On:20 Nov 2014 19:21
Last Modified:18 Jan 2018 17:48
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