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Meta-analysis approaches were used in this first quantitative synthesis of denitrifying woodchip bioreactors. Nitrate removal across environmental and design conditions was assessed from 26 published studies, representing 57 separate bioreactor units (i.e., walls, beds, and laboratory columns). Effect size calculations weighted the data based on variance and number of measurements for each bioreactor unit. Nitrate removal rates in bed and column studies were not significantly different, but both were significantly higher than wall studies. In denitrifying beds, wood source did not significantly affect nitrate removal rates. Nitrate removal (mass per volume) was significantly lower in beds with <6-h hydraulic retention times, which argues for ensuring that bed designs incorporate sufficient time for nitrate removal. Rates significantly declined after the first year of bed operation but then stabilized. Nitrogen limitation significantly affected bed nitrate removal. Categorical and linear assessments found significant nitrate removal effects with bed temperature; a Q 10 of 2.15 was quite similar to other studies. Lessons from this meta-analysis can be incorporated into bed designs, especially extending hydraulic retention times to increase nitrate removal under low temperature and high flow conditions. Additional column studies are warranted for comparative assessments, as are field-based studies for assessing in situ conditions, especially in aging beds, with careful collection and reporting of design and environmental data. Future assessment of these systems might take a holistic view, reviewing nitrate removal in conjunction with other processes, including greenhouse gas and other unfavorable by-product production.Denitrifying Bioreactors for Nitrate Removal: A Meta-Analysis Kelly Addy, Arthur J. Gold,* Laura E. Christianson, Mark B. David, Louis A. Schipper, and Nicole A. Ratigan E xcess nitrate-nitrogen losses from agricultural watersheds generate a host of water quality problems around the globe, including eutrophication, algae blooms, and fish kills (Howarth et al., 2000;Diaz, 2001;Nixon et al., 2001;Howarth, 2008;Billen et al., 2013;Erisman et al., 2013). Among the many approaches considered to address this problem, the development and use of passive denitrifying bioreactors has drawn increasing interest in the past two decades. These bioreactors intercept nitrate-enriched water at the field edge, use a carbon (C) source (typically woodchips) to serve as an electron donor, and create the anaerobic conditions needed to stimulate rapid denitrification, the conversion of nitrate to nitrogen gases (Schipper et al., 2010b). Denitrifying bioreactors were first used to treat nitrate-enriched groundwater (Robertson and Cherry, 1995;Schipper and Vojvodić-Vuković, 1998) and were adapted for use with agricultural tile drainage water (Robertson et al., 2000) and as a polishing step for onsite wastewater treatment (Oakley et al., 2010;Schipper et al., 2010a). These bioreactors are now being used in a variety of...

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Recently, interest in denitrification bioreactors to reduce the amount of nitrate in agricultural drainage has led to increased installations across the U.S. Midwest. Despite this recent attention, there are few peer-reviewed, field-scale comparative performance studies investigating the effectiveness of these denitrification bioreactors. The object of this work was to analyze nitrate removal performance from four existing bioreactors in Iowa, paying particular attention to potential performance-affecting factors including retention time, influent nitrate concentration, temperature, flow rate, age, length-to-width ratio, and cross-sectional shape. Based on a minimum of two years of water quality data from each of the four bioreactors, annual removal rates ranged from 0.38 to 7.76 g N m-3 bioreactor volume d-1. Bioreactor and total (including bypass flow) nitratenitrogen load reductions ranged from 12% to 76% (mean 45%) and from 12% to 57% (mean 32%), respectively, removing from 0.5 to 15.5 kg N ha-1 drainage area. Multiple regression analyses showed that temperature and influent nitrate concentration were the most important factors affecting percent bioreactor nitrate load reduction and nitrate removal rate, respectively. This analysis also indicated that load reductions within the bioreactor were significantly impacted by retention time at three of the four reactors. More fieldscale performance data from bioreactors of different designs and from multiple locations around the Midwest are necessary to further enhance understanding of nitrate removal in these systems and their potential to positively impact water quality.