Aquifers are an important storage location and source of fresh groundwater. They may become polluted by a number of contaminants including mobile divalent radionuclides such as strontium-90 which is a byproduct of uranium fission. A method for remediating such divalent radionuclides is sequestration through co-precipitation into calcium carbonate. Calcium carbonate precipitation occurs naturally but can be enhanced by the use of ureolytic microorganisms living within the aquifer. The microbial enzyme urease cleaves ammonia from urea (added as a stimulant to the aquifer) increasing the pH and subsequently pushing the bicarbonate equilibrium towards precipitation.
Laboratory experimentation is necessary to better predict field scale outcomes of remediation that is driven by ureolytic calcium carbonate co-precipitation. To aid in such laboratory experiments, I constructed two ureolytic organisms which contain green fluorescent protein (GFP) so that the location of the microbes in relation to media flow
paths and precipitation can be viewed by microscopy in a 2- dimensional porous medium flow cell reactor. The reactor was operated with a parallel flow regime where the two influent media would not promote microbially induced calcium carbonate precipitation until they were mixed in the flow cell.
A demonstration study compared the results of parallel flow and mixing in the reactor operated with and without one of the GFP-containing ureolytic organisms. The growth and precipitation of calcium carbonate within the reactor pore space altered flow paths to promote a wider mixing zone and a more widely distributed overall calcium carbonate precipitation pattern. This study will allow optimization of remediation efforts of contaminants such as strontium-90 in aquifers. / Graduation date: 2012
Identifer | oai:union.ndltd.org:ORGSU/oai:ir.library.oregonstate.edu:1957/26408 |
Date | 15 November 2011 |
Creators | Kaufman, Megan J. |
Contributors | Colwell, Frederick S. |
Source Sets | Oregon State University |
Language | en_US |
Detected Language | English |
Type | Thesis/Dissertation |
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