Measurement of bacterial collision efficiencies in porous media

Groß, M.; Albinger, O.; Jewett, David G.; Logan, Bruce E.; Bales, R. C.; Arnold, Robert G.

doi:10.1016/0043-1354(94)00235-y

Cited by 53 publications

(47 citation statements)

References 17 publications

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“…Bacteria transport, however, was unaffected by changes in pH in the range of 5.5 < pH < 7.0 in both systems (see Table V). The influence of ionic strength on transport parameters of other microorganisms have also been reported by Hilbert (1992), Logan et al (1993), and Kinoshita et al (1993) with results similar to the findings of Jewett et al(1995).…”

Section: Microbial Transport Influence Of Ionic Strength and Phsupporting

confidence: 79%

“…Value of a has also been estimated on 40-mm glass beads using radiolabeled P. fluorescens P17 by Gross et al (1995). The bacterial collision efficiency values, a's, reported by these investigators are in direct agreement with the results of Jewett et al (1995).…”

Section: Microbial Transport Influence Of Ionic Strength and Phsupporting

confidence: 78%

“…A large number of studies have therefore focused attention on bacteria transport in porous media. Jewett et al (1995) have reported on the influence of ionic strength and pH on the transport of the bacterium, Pseudomonas Fluorescens P17. Their experiments were performed in porous media using continuous-flow laboratory columns and a rapid screening technique in which radio labeled cells were applied to large-pore, glass-fiber filters.…”

Section: Microbial Transport Influence Of Ionic Strength and Phmentioning

confidence: 99%

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An evaluation of in-situ bioremediation processes

Cole¹,

Rashidi²

1996

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Section: Microbial Transport Influence Of Ionic Strength and Phsupporting

confidence: 79%

Section: Microbial Transport Influence Of Ionic Strength and Phsupporting

confidence: 78%

Section: Microbial Transport Influence Of Ionic Strength and Phmentioning

confidence: 99%

See 1 more Smart Citation

An evaluation of in-situ bioremediation processes

Cole¹,

Rashidi²

1996

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“…Differences in surface particle chemistry or collector surface roughness not directly included in the theoretical model are incorporated into the collision efficiency (␣), which is defined as the probability that a particle attaches to a surface based on the frequency of collisions. Mini-column tests have proven to be an effective and rapid alternative to breakthrough column tests for measuring bacterial collision efficiencies (3,5,10,19). Retention or total breakthrough can be measured by incorporating a radiolabel into the bacterium, which allows rapid calculation of the collision efficiency.…”

mentioning

confidence: 99%

“…Retention or total breakthrough can be measured by incorporating a radiolabel into the bacterium, which allows rapid calculation of the collision efficiency. To examine bacterial retention, a small slice of medium is removed from the top of the bed and analyzed by scintillation counting (10). However, a radiolabel-based method is not practical for GAC as the label sorption to the carbon does not permit subsequent measurement of bacterial retention (26).…”

mentioning

confidence: 99%

Measurement of Biocolloid Collision Efficiencies for Granular Activated Carbon by Use of a Two-Layer Filtration Model

Paramonova

Zerfoss

Logan

2006

Appl Environ Microbiol

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Point-of-use filters containing granular activated carbon (GAC) are an effective method for removing certain chemicals from water, but their ability to remove bacteria and viruses has been relatively untested. Collision efficiencies (␣) were determined using clean-bed filtration theory for two bacteria (Raoutella terrigena 33257 and Escherichia coli 25922), a bacteriophage (MS2), and latex microspheres for four GAC samples. These GAC samples had particle size distributions that were bimodal, but only a single particle diameter can be used in the filtration equation. Therefore, consistent with previous reports, we used a particle diameter based on the smallest diameter of the particles (derived from the projected areas of 10% of the smallest particles). The bacterial collision efficiencies calculated using the filtration model were high (0.8 < ␣ < 4.9), indicating that GAC was an effective capture material. Collision efficiencies greater than unity reflect an underestimation of the collision frequency, likely as a result of particle roughness and wide GAC size distributions. The collision efficiencies for microspheres (0.7 < ␣ < 3.5) were similar to those obtained for bacteria, suggesting that the microspheres were a reasonable surrogate for the bacteria. The bacteriophage collision efficiencies ranged from >0.2 to <0.4. The predicted levels of removal for 1-cm-thick carbon beds ranged from 0.8 to 3 log for the bacteria and from 0.3 to 1.0 log for the phage. These tests demonstrated that GAC can be an effective material for removal of bacteria and phage and that GAC particle size is a more important factor than relative stickiness for effective particle removal.Microbial contamination of drinking water is a major health problem in many areas around the world (8, 9). Because conventional water treatment technologies are often not available in places with the greatest water contamination problems, the World Health Organization has proposed that point-of-use (POU) water treatment devices are the most efficient solution to the problem (33). Many POU devices rely on adsorption onto granular activated carbon (GAC) as a mechanism for removal of contaminants. In order for POU water treatment to be successful, the GAC must be effective in removing both chemical and microbial contaminants from the water. While GAC is widely known to be effective for decolorization, dechlorination, and chemical removal (14, 15, 17, 31), the efficiency of this material for removal of bacteria and viruses is relatively unknown.The methods used to characterize the relative adhesion of bacteria and viruses to GAC range from batch adsorption tests to column tests. Batch adsorption tests have confirmed that microorganisms adsorb exclusively to the exterior surface of GAC due to pore size exclusion (24, 25, 27), but they do not provide information that is sufficient to predict removal rates in columns. Mass transfer models can be used to characterize chemical removal with GAC in packed beds, but they do not provide detailed information concerning ...

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