This dissertation aims to expand our knowledge of glycerol-driven engineered biological nitrogen removal processes by elucidating the link between operational controls and the structure and function of the microbial ecology grown under stoichiometrically-limited and excess glycerol conditions. Specific objectives were to:
1. Develop and experimentally evaluate an improved metric for denitratation performance that can be objectively compared across studies;
2. characterize the process kinetics, nitrogen conversion efficiencies, and microbial ecology of a glycerol-driven, stoichiometrically-limited denitratation process;
3. elucidate the impact of kinetic limitation on microbial community structure and function in a glycerol-driven, stoichiometrically-limited denitratation process;
4. explore the biological mechanisms contributing to nitrite (NO2-) accumulation in a glycerol-driven denitratating microbial community; and,
5. characterize the nitrogen conversion efficiencies and microbial ecology that favor dissimilatory nitrate reduction to ammonium (DNRA) in a glycerol-driven denitrification process at stoichiometric excess.
Accordingly, a nitrate (NO3-) conversion ratio (NaCR) was first proposed as an improved metric of denitratation performance metric. Previous metrics used throughout literature were deemed insufficient as they provided an incomplete and subjective representation of denitratation performance by not accounting for residual NO3- remaining in the system following the selective reduction of NO3- to NO2-. The NaCR represented a singular metric that better signifies true denitratation performance and can be compared across studies regardless of carbon source or system configuration.
Second, a glycerol-driven denitratation process was optimized according to different operational controls. Steady-state reactor operation and in situ and ex situ batch assays indicated that the influent chemical oxygen demand to NO3- (COD:NO3--N) ratio was determined to influence process kinetics and nitrogen conversion efficiencies leading to significant NO2- accumulation. A singular microbial community structure correlated to system performance was identified.
Third, the application of kinetic limitation (by imposing different solids retention times [SRTs]) at a given influent COD:NO3--N ratio was demonstrated as an effective mechanism in the selection for a denitratating microbial ecology capable of significant NO2- accumulation. Steady-state reactor operation was used to characterize process kinetics and nitrogen conversion ratios supporting the determination of the optimal SRT for reactor operation. Analysis of the microbial community structure elucidated the impacts of kinetic limitation on the microbial ecology which were correlated to system performance. Functional denitrification gene transcripts were found to be significantly different under kinetic limitation, indicating that NO2- accumulation was driven more by differences in microbial community structure as opposed to differential expression at different operating SRTs.
Fourth, ex situ batch assays were used to elucidate the microbial transcriptional response to the presence of varied sequences of electron acceptors. The microbial community was found to be enriched with NO3--respirers, or microorganisms incapable of NO2- reduction, and progressive onset denitrifiers, which express functional denitrification genes in sequence. The presence or re-introduction of NO3- in a NO2--reducing community was found to elicit an immediate transcriptional change and shift of electron flow to NO3- reductase. Electron competition as the primary contribution to NO2- accumulation was confirmed through the artificial inactivation of NO3- reductase.
Lastly, an influent COD:NO3--N ratio was applied in stoichiometric excess to create the conditions necessary to support DNRA over denitrification. System performance at steady-state was found to vary under different kinetic regimes. The induction of DNRA was found to be far more complex than simply providing glycerol in stoichiometric excess. Additionally, glycerol does not appear to be an optimal COD source for DNRA under these conditions.
In sum, the optimization of engineered biological nitrogen removal processes through the manipulation of process kinetics and the resulting impacts on nitrogen conversion efficiencies and microbial community structure and function was investigated in detail. From an engineering perspective, this knowledge can help guide the design and operation of biological nitrogen removal processes to systematically maximize the accumulation of targeted nitrogenous products or mitigate unintentional and undesired products.
| Identifer | oai:union.ndltd.org:columbia.edu/oai:academiccommons.columbia.edu:10.7916/d8-20tx-am64 |
| Date | January 2019 |
| Creators | Baideme, Matthew |
| Source Sets | Columbia University |
| Language | English |
| Detected Language | English |
| Type | Theses |
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