Deposition and transport of Pseudomonas aeruginosa in porous media: Lab-scale experiments and model analysis
- Deposition and transport of Pseudomonas aeruginosa in porous media: Lab-scale experiments and model analysis
- 권규상; 김성배; 최낙철; 김동주; 이순재; 이상협; 최재우
- Bacteria transport; Pseudomonas aeruginosa; Quartz sand; Transport model; Deposition
- Issue Date
- Environmental technology
- VOL 34, NO 19, 2761-2768
- In this study, the deposition and transport of Pseudomonas aeruginosa on sandy porous materials have been investigated
under static and dynamic flow conditions. For the static experiments, both equilibrium and kinetic batch tests were performed
at a 1:3 and 3:1 soil:solution ratio. The batch data were analysed to quantify the deposition parameters under static conditions.
Column tests were performed for dynamic flow experiments with KCl solution and bacteria suspended in (1) deionized water,
(2) mineral salt medium (MSM) and (3) surfactant + MSM. The equilibrium distribution coefficient (Kd ) was larger at a
1:3 (2.43mLg−1) than that at a 3:1 (0.28mLg−1) soil:solution ratio. Kinetic batch experiments showed that the reversible
deposition rate coefficient (katt) and the release rate coefficient (kdet) at a soil:solution ratio of 3:1 were larger than those at
a 1:3 ratio. Column experiments showed that an increase in ionic strength resulted in a decrease in peak concentration of
bacteria, mass recovery and tailing of the bacterial breakthrough curve (BTC) and that the presence of surfactant enhanced
the movement of bacteria through quartz sand, giving increased mass recovery and tailing. Deposition parameters under
dynamic condition were determined by fitting BTCs to four different transport models, (1) kinetic reversible, (2) two-site, (3)
kinetic irreversible and (4) kinetic reversible and irreversible models. Among these models, Model 4 was more suitable than
the others since it includes the irreversible sorption term directly related to the mass loss of bacteria observed in the column
experiment. Applicability of the parameters obtained from the batch experiments to simulate the column breakthrough data is evaluated.
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