GAC adsorber design protocol for the removal of off-flavors

Pirbazari, Massoud; Ravindran, Varadarajan; Badriyha, Badri N.; Craig, Shala; McGuire, Michael J.

doi:10.1016/0043-1354(93)90007-5

Cited by 65 publications

(36 citation statements)

References 11 publications

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“…involving the homogeneous surface diffusion model HSDM ŽCrittenden and Weber, 1978a,b;Crittenden et al, 1987Crittenden et al, , 1991 . Kim and Pirbazari, 1989;Pirbazari et al, 1993 . The parameter D , which represents the diffusion of the compound along s the pore-wall surfaces, determines the uptake rate of a compound by activated carbon, and its value was validated by simulating the mini-column adsorption breakthrough profiles using the nonbioactive version of the biofiltration model Ž .…”

Section: Determination Of Model Parametersmentioning

confidence: 97%

“…The biofilm density X and biofilm thickness L were f f estimated from biomass measurements conducted after each biokinetic experiment using appropriate empirical correla-Ž . tions Law et al, 1976;Pirbazari et al, 1993 Adsorption Equilibrium Parameters. The mini-column adsorption experiments facilitated the generation of a series of TCE breakthrough profiles corresponding to different influent concentrations and GAC masses.…”

Section: Determination Of Model Parametersmentioning

confidence: 99%

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Modeling and design of vapor‐phase biofiltration for chlorinated volatile organic compounds

Den

Pirbazari

2002

AIChE Journal

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IntroductionIndustrial gas-phase emissions of hazardous contaminants Ž . including volatile organic compounds VOCs are widely regarded as risks to environmental and occupational health. A broad spectrum of innovative treatment technologies are currently available for the control of such industrial emissions, among which biofiltration is a viable alternative. The biofiltration process involves the growth of heterotrophic microorganisms immobilized on a solid surface and sustained by the organic components of the gas stream. The technology has several advantages over traditional physical or chemical processes such as thermal destruction, carbon adsorption, and liquid scrubbing; and these include low energy consumption, and, consequently, low operating and maintenance costs. Ž . Furthermore, granular activated carbon GAC employed as a biofilter packing material not only provides a favorable environment for biofilm growth, but also extends the contact time between the biofilm and contaminants due to its desirCorrespondence concerning this article should be addressed to M. Pirbazari. Current address of W. Den: Dept. of Environmental Science, Tunghai University, Tai-Chung, Taiwan. able adsorptive characteristics. These beneficial features attributed to the adsorptive characteristics of GAC and biodegradative ability of the biofilm are particularly important in the degradation of recalcitrant compounds. These aspects have been well addressed by several researchers in both Ž aqueous-phase systems Ying and Weber, 1979; Kim and Pir-. bazari, 1989; Ravindran et al., 1997 and in gas-phase systems Ž . De heyder et al., 1994; Man et al., 1996 . An important aspect regarding implementation of full-scale biofiltration systems is their economic planning and design. A modeling and design protocol may indeed be a valuable tool to minimize the scope of elaborate, time-consuming, and expensive pilot-scale testing normally considered before a fullscale design is contemplated upon. Therefore, the present study focuses on the development of a mathematical modeling technique for performance prediction and simulation of biofilters under various operating conditions. The proposed model has the versatility of using either adsorbing or nonadsorbing media. The study is also intended to establish a systematic approach in determining the model input parameters, and to verify the predictive capability of the model. In the present study, GAC was employed as the biofilter packSeptember 2002 Vol. 48, No. 9AIChE Journal 2084 Ž . ing medium, and trichloroethylene TCE was chosen as the model compound.

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Section: Determination Of Model Parametersmentioning

confidence: 97%

Section: Determination Of Model Parametersmentioning

confidence: 99%

Modeling and design of vapor‐phase biofiltration for chlorinated volatile organic compounds

Den

Pirbazari

2002

AIChE Journal

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“…The main challenge faced by the utilities in treatment of geosmin, 2-MIB, and other odor-causing substances is associated with their extremely low odor threshold concentrations (OTC) (McGuire 1995). The OTC for geosmin and MIB is 4 ng/L and 9 ng/L, respectively (Pirbazari et al 1993). Another factor that adds to the challenge faced by drinking water facilities in the removal of these contaminants is the presence of natural organic matter (NOM).…”

Section: Introductionmentioning

confidence: 99%

“…Numerous studies have looked into GAC and PAC adsorption of MIB and geosmin (Cook et al 2001;Ho and Newcombe 2005;Jung et al 2004;Ng et al 2002;Pirbazari et al 1993). However, NOM levels of 3-10 mg/L competitively reduce activated carbon adsorption capacity for MIB or geosmin (Newcombe et al 2002a, b;Pirbazari et al 1993). In natural waters, the size and concentration of NOM particles is many folds higher than that of MIB or geosmin, and as a result a large volume of the GAC is not utilized for MIB/geosmin adsorption, thereby significantly reducing the GAC adsorption capacity.…”

Section: Introductionmentioning

confidence: 99%

Adsorption of Geosmin and MIB on Activated Carbon Fibers–Single and Binary Solute System

Srinivasan

Sorial

2009

Water Air Soil Pollut: Focus

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The adsorption of two taste-and odorcausing compounds, namely MIB (2-methyl isoborneol-C 11 H 20 O) and geosmin (C 12 H 22 O) on activated carbon was investigated in this study. The impact of adsorbent pore size distribution on adsorption of MIB and geosmin was evaluated through single solute and multicomponent adsorption of these compounds on three types of activated carbon fibers (ACFs) and one granular activated carbon (GAC). The ACFs (ACC-15, ACC-20, and ACC-25) with different degrees of activation had narrow pore size distributions and specific critical pore diameters whereas the GAC (F-400) had a wider pore size distribution and lesser microporosity. The effect of the presence of natural organic matter (NOM) on MIB and geosmin adsorption was also studied for both the single solute and binary systems. The Myers equation was used to evaluate the single solute isotherms as it converges to Henry's law at low coverage and also serves as an input for predicting multicomponent adsorption. The single solute adsorption isotherms fit the Myers equation well and pore size distribution significantly influenced adsorption on the ACFs and GAC. The ideal adsorbed solute theory (IAST), which is a wellestablished thermodynamic model for multicomponent adsorption, was used to predict the binary adsorption of MIB and geosmin. The IAST predicted well the binary adsorption on the ACFs and GAC. Binary adsorption isotherms were also conducted in the presence of oxygen (oxic) and absence of oxygen (anoxic). There were no significant differences in the binary isotherm between the oxic and anoxic conditions, indicating that adsorption was purely through physical adsorption and no oligomerization was taking place. Binary adsorptions for the four adsorbents were also conducted in the presence of humic acid to determine the effect of NOM and to compare with IAST predictions. The presence of NOM interestingly resulted in deviation from IAST behavior in case of two adsorbents, ACC-15 and F-400.

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“…Individuals' sensitivity toward odorants has been found to be quite different. For example, the odor threshold concentration (OTC) levels of geosmin and 2-MIB have been reported to range from 4 to 10 ng/L and 9 to 42 ng/L, respectively (Pirbazari et al, 1993;Lloyd et al, 1998;Watson et al, 2000;Worley et al, 2003). At the same time, adaptation due to long-term exposure to a background odor in drinking water could lead to the loss of sensitivity to some odors (Dalton and Wysocki, 1996;Whelton and Dietrich, 2004).…”

Section: Introductionmentioning

confidence: 99%

Quantitative method to determine the regional drinking water odorant regulation goals based on odor sensitivity distribution: Illustrated using 2-MIB

An¹,

Cao²,

Yang³

et al. 2014

Journal of Environmental Sciences

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Taste and odor (T/O) in drinking water often cause consumer complaints and are thus regulated in many countries. However, people in different regions may exhibit different sensitivities toward T/O. This study proposed a method to determine the regional drinking water odorant regulation goals (ORGs) based on the odor sensitivity distribution of the local population. The distribution of odor sensitivity to 2-methylisoborneol (2-MIB) by the local population in Beijing, China was revealed by using a normal distribution function/model to describe the odor complaint response to a 2-MIB episode in 2005, and a 2-MIB concentration of 12.9 ng/L and FPA (flavor profile analysis) intensity of 2.5 was found to be the critical point to cause odor complaints. Thus the Beijing ORG for 2-MIB was determined to be 12.9 ng/L. Based on the assumption that the local FPA panel can represent the local population in terms of sensitivity to odor, and that the critical FPA intensity causing odor complaints was 2.5, this study tried to determine the ORGs for seven other cities of China by performing FPA tests using an FPA panel from the corresponding city. ORG values between 12.9 and 31.6 ng/L were determined, showing that a unified ORG may not be suitable for drinking water odor regulations. This study presents a novel approach for setting drinking water odor regulations.

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GAC adsorber design protocol for the removal of off-flavors

Cited by 65 publications

References 11 publications

Modeling and design of vapor‐phase biofiltration for chlorinated volatile organic compounds

Modeling and design of vapor‐phase biofiltration for chlorinated volatile organic compounds

Adsorption of Geosmin and MIB on Activated Carbon Fibers–Single and Binary Solute System

Quantitative method to determine the regional drinking water odorant regulation goals based on odor sensitivity distribution: Illustrated using 2-MIB

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