Biological nutrient removal (BNR) systems employ engineered biological processes—including nitrification, denitrification, and biological phosphorus removal—to remove nutrients from wastewater. Since their original implementation, BNR systems have adapted to challenges, such as the presence of inhibitory compounds and demands for more energy- and resource-efficient wastewater treatment. Advancements in alternative BNR technologies made in response to these demands have highlighted the metabolic versatility of microbial communities present in BNR systems. This versatility is also observed in the expanded capacity of BNR systems to remove not only human-derived carbon, but also complex trace organic emerging contaminants (ECs). Based on conventional monitoring alone, the roles of specific bacteria and metabolic mechanisms in the removal of nutrients and ECs remain unclear. A detailed understanding of the actors and mechanisms in BNR systems can be attained through application of molecular biology tools, including those targeting community (a) structure and potential function through DNA analysis and (b) extant function through RNA analysis.
This dissertation encompasses three objectives, which seek to link detailed molecular-level information to the performance and metabolic versatility of several nutrient-removing communities. The first objective was to assess the utility of gene expression assays to indicate and predict nitrification inhibition by toxic heavy metals based on functional responses of nitrifying bacteria. Through this assessment, it was found that genes related to both catabolic and anabolic pathways could be used as indicators of nitrification inhibition. The second objective was to investigate the effects of reactor operating conditions on simultaneous nitrogen and phosphorus removal by examining the microbial community structure and metabolism of a survey of full-scale BNR systems. A variety of BNR configurations and operating conditions, all capable of sustained nutrient removal, selected for different nitrogen- and phosphorus-removing communities. The activity of these communities was also dependent on configuration and operating conditions, as indicated by analysis of gene expression. Finally, the third objective was to examine the expanded capacity of BNR systems to attenuate ECs by investigating the removal of the EC bisphenol A (BPA) by microbial communities involved in nutrient removal. Communities derived from both full-scale and lab-scale systems were capable of biodegrading BPA, though each community was uniquely influenced by reactor processes and BPA exposure conditions.
Results from this work also offered insights into the utility of assessed genes as biomarkers for metabolic activity and the importance of accurately characterizing in-situ responses of BNR systems. In both lab-scale and full-scale studies, certain genes demonstrated increased sensitivity to nutrient-removing activity. At lab-scale, observed differences between inhibition of ammonia oxidation through discrete and continuous Cu(II) exposure indicated that conventional short-term, ex-situ batch assays may underestimate inhibition in a parent reactor of interest. The benefit of gene expression assays to accurately reflect in-situ responses was also examined in full-scale BNR systems removing both nitrogen and phosphorus.
Findings from full-scale BNR systems revealed the long-term effects of changes to process configurations on microbial community structure and activity. Despite differences in operating conditions and the resulting nitrogen- and phosphorus-removing communities, a variety of configurations sustained nutrient removal. Long-term effects were also characterized in the context of EC removal. Differences in BPA degradation rates and microbial community profiles in lab-scale mixed culture communities after extended BPA exposure showed the lasting influence of both reactor processes and BPA exposure conditions. Assessment of microbial community structure was also used to identify BPA-degrading bacteria.
Results from each of the three objectives could be used in the development of biomarkers to assess and predict (1) process upsets or inhibition, (2) nutrient removal process performance, or (3) capacity for EC removal. Integrating analysis of microbial community structure and function with reactor performance monitoring and mechanistic modeling that includes such advanced knowledge holds the potential to not only guide effective operation of BNR systems, but also identify opportunities for more efficient and even concomitant nitrogen, phosphorus, and EC removal.
| Identifer | oai:union.ndltd.org:columbia.edu/oai:academiccommons.columbia.edu:10.7916/d8-nkwv-pj92 |
| Date | January 2020 |
| Creators | Hoar, Catherine |
| Source Sets | Columbia University |
| Language | English |
| Detected Language | English |
| Type | Theses |
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