Denitrifying Bioreactors Resist Disturbance from Fluctuating Water Levels

Sarah K Hathaway,Angela D Kent,Nicholas A Bartolerio,Luis F Rodríguez,Julie L Zilles

doi:10.3389/fenvs.2017.00035

Abstract

Nitrate can be removed from wastewater streams, including subsurface agricultural drainage systems, using woodchip bioreactors to promote microbial denitrification. However, the variations in water flow in these systems could make reliable performance from this microbially-mediated process a challenge. In the current work, the effects of fluctuating water levels on nitrate removal, denitrifying activity, and microbial community composition in laboratory-scale bioreactors were investigated. The performance was sensitive to changing water level. An average of 31% nitrate was removed at high water level and 59% at low water level, despite flow adjustments to maintain a constant theoretical hydraulic retention time. The potential activity, as assessed through denitrifying enzyme assays, averaged 0.0008 mg N2O-N/h/dry g woodchip and did not show statistically significant differences between reactors, sampling depths, or operational conditions. In the denitrifying enzyme assays, nitrate removal consistently exceeded nitrous oxide production. The denitrifying bacterial communities were not significantly different from each other, regardless of water level, meaning that the denitrifying bacterial community did not change in response to disturbance. The overall bacterial communities, however, became more distinct between the two reactors when one reactor was operated with periodic disturbances of changing water height, and showed a stronger effect at the most severely disturbed location. The communities were not distinguishable, though, when comparing the same location under high and low water levels, indicating that the communities in the disturbed reactor were adapted to fluctuating conditions rather than to high or low water level. Overall, these results describe a biological treatment process and microbial community that is resistant to disturbance via water level fluctuations.

Highlights

For many coastal ecosystems worldwide, increasing problems with hypoxia are linked to anthropogenic nitrogen inputs, from agricultural use of fertilizers (Howarth and Marino, 2006; Rabalais et al, 2010)
During the period of regular disturbance (Phase III), the performance of the disturbed reactor continued to respond to differences in water level, showing similar nitrate removal to the constant reactor at high water level and increased nitrate removal at low water level (Figure 2, Phase III)
This study was designed to investigate the relationships amongst water level, bioreactor performance, microbial activity, and the microbial community composition in laboratory-scale bioreactors

Summary

Introduction

For many coastal ecosystems worldwide, increasing problems with hypoxia are linked to anthropogenic nitrogen inputs, from agricultural use of fertilizers (Howarth and Marino, 2006; Rabalais et al, 2010). The widespread use of tile or subsurface drainage systems exacerbates the problem by increasing the fraction of fertilizer nitrogen reaching surface water. In the Mississippi River Basin, subsurface drainage from fertilized agricultural fields with tile drainage is a major source of nitrate (David et al, 2010), affecting the Gulf of Mexico. One promising treatment technology for tile drainage systems is edge-of-field denitrifying bioreactors. These bioreactors typically consist of a trench of woodchips through which tile drainage effluent is directed, providing an appropriate environment for microbially-mediated denitrification and decreasing the nitrate load carried by the tile drainage to surface water (reviewed in Schipper et al, 2010; Addy et al, 2016). Much of the research on denitrifying bioreactors to date has focused on engineering design parameters (e.g., Gibert et al, 2008; Greenan et al, 2009; Cameron and Schipper, 2010; Christianson et al, 2011) or in situ evaluation of bioreactors implemented in the field (e.g., Moorman et al, 2010)

Methods

Results

Conclusion