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Modeling and Quantifying Bacterial Metal Adsorption in Aqueous Systems

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posted on 2018-10-31, 00:00 authored by Clayton R. Johnson

Metal-bacteria adsorption reactions play a role in controlling the distribution of metals in the environment. The ability to predict the fate of metals in complex geological systems is dependent on: understanding bacterial adsorption mechanisms, being able to quantify bacterial metal adsorption, and creating accurate models for bacterial metal adsorption. The research presented in this dissertation explores each of these aspects of bacterial metal adsorption. Chapter 2 describes how the ratio of Hg to bacteria, known as Hg loading, affects the mechanism of bacterial Hg adsorption. The results suggest that the mechanism of Hg-bacteria adsorption is loading dependent and that the change in mechanism must be accounted for in predictive models in order to accurately estimate the extent of bacterial Hg adsorption under low Hg loading conditions. These findings lead to the creation of a predictive model that can accurately estimate the extent of Hg adsorption over a wide range of loading and pH conditions. Chapter 3 details the development of a novel technique that uses a Cd-specific fluorescent probe in conjunction with confocal scanning laser microscopy to quantify Cd adsorption to bacteria in aqueous systems. The results demonstrate that the fluorescent probe technique is a feasible option for quantifying the total amount of Cd adsorbed to a bacterial population and that the extent of Cd adsorption is highly heterogeneous between individual bacterial cells. Lastly, Chapter 4 uses the novel Cd-specific fluorescent probe technique described in Chapter 3 to quantify Cd distribution in multi-component, bacteria-bearing systems. The experimentally determined Cd distributions are compared to component additivity surface complexation model predictions. The results show that the fluorescent probe technique is a viable option for quantifying bacterial Cd adsorption in multi-adsorbent systems and component additivity models predict Cd distribution with reasonable accuracy in systems containing bacteria, a mineral powder, and a chelating ligand.

History

Date Created

2018-10-31

Date Modified

2018-12-18

Defense Date

2018-10-25

CIP Code

  • 14.0801

Research Director(s)

Jeremy B. Fein

Committee Members

Kyle Doudrick Joshua Shrout Amy Hixon

Degree

  • Doctor of Philosophy

Degree Level

  • Doctoral Dissertation

Alternate Identifier

1062396852

Library Record

4992624

OCLC Number

1062396852

Program Name

  • Civil and Environmental Engineering and Earth Sciences

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