Characterizing the Performance of Denitrifying Bioreactors during Simulated Subsurface Drainage Events.

The need to mitigate nitrate export from corn and soybean fields with subsurface (tile) drainage systems, a major environmental issue in the midwestern United States, has made the efficacy of field-edge, subsurface bioreactors an active subject of research. This study of three such bioreactors located on the University of Illinois South Farms during their first 6 mo of operation (July-Dec. 2012) focused on the interactions of seasonal temperature changes and hydraulic retention times (HRTs), which were subject to experimental manipulation. Changes in nitrate, phosphate, oxygen, and dissolved organic carbon were monitored in influent and effluent to assess the benefits and the potential harmful effects of bioreactors for nearby aquatic ecosystems. On average, bioreactors reduced nitrate loads by 63%, with minimum and maximum reductions of 20 and 98% at low and high HRTs, respectively. The removal rate per unit reactor volume averaged 11.6 g NO-N m d (range, 5-30 g NO-N m d). Multiple regression models with exponential dependencies on influent water temperature and on HRT explained 73% of the variance in NO-N load reduction and 43% of the variance in its removal rate. Although concentrations of dissolved reactive phosphorus and dissolved organic carbon in the bioreactor effluent increased relative to the influent by an order of magnitude during initial tests, within 1 mo of operation they stabilized at nearly equal values.

Spatial variation in the bacterial and denitrifying bacterial community in a biofilter treating subsurface agricultural drainage.

Denitrifying biofilters can remove agricultural nitrates from subsurface drainage, reducing nitrate pollution that contributes to coastal hypoxic zones. The performance and reliability of natural and engineered systems dependent upon microbially mediated processes, such as the denitrifying biofilters, can be affected by the spatial structure of their microbial communities. Furthermore, our understanding of the relationship between microbial community composition and function is influenced by the spatial distribution of samples.In this study we characterized the spatial structure of bacterial communities in a denitrifying biofilter in central Illinois. Bacterial communities were assessed using automated ribosomal intergenic spacer analysis for bacteria and terminal restriction fragment length polymorphism of nosZ for denitrifying bacteria.Non-metric multidimensional scaling and analysis of similarity (ANOSIM) analyses indicated that bacteria showed statistically significant spatial structure by depth and transect,while denitrifying bacteria did not exhibit significant spatial structure. For determination of spatial patterns, we developed a package of automated functions for the R statistical environment that allows directional analysis of microbial community composition data using either ANOSIM or Mantel statistics.Applying this package to the biofilter data, the flow path correlation range for the bacterial community was 6.4 m at the shallower, periodically in undated depth and 10.7 m at the deeper, continually submerged depth. These spatial structures suggest a strong influence of hydrology on the microbial community composition in these denitrifying biofilters. Understanding such spatial structure can also guide optimal sample collection strategies for microbial community analyses.

Phosphorus removal in denitrifying woodchip bioreactors varies by wood type and water chemistry.

Denitrifying woodchip bioreactors are a practical nitrogen (N) mitigation technology but evaluating the potential for bioreactor phosphorus (P) removal is highly relevant given that (1) agricultural runoff often contains N and P, (2) very low P concentrations cause eutrophication, and (3) there are few options for removing dissolved P once it is in runoff. A series of batch tests evaluated P removal by woodchips that naturally contained a range of metals known to sorb P and then three design and environmental factors (water matrix, particle size, initial dissolved reactive phosphorus (DRP) concentration). Woodchips with the highest aluminum and iron content provided the most dissolved P removal (13±2.5 mg DRP removed/kg woodchip). However, poplar woodchips, which had low metals content, provided the second highest removal (12±0.4 mg/kg) when they were tested with P-dosed river water which had a relatively complex water matrix. Chemical P sorption due to woodchip elements may be possible, but it is likely one of a variety of P removal mechanisms in real-world bioreactor settings. Scaling the results indicated bioreactors could remove 0.40 to 13 g DRP/ha. Woodchip bioreactor dissolved P removal will likely be small in magnitude, but any such contribution is an added-value benefit of this denitrifying technology.