Abstract

The increase in environmental nutrient availability as a result of human activities has necessitated the development of mitigation strategies for nutrient removal, such as nitrate. Current methods for determining the efficiency of different mitigation strategies required measurement of changes in nitrate concentrations, however, these methods can be expensive or do not account fully for the temporal variability of nitrate concentration. This study evaluated the utility of Diffusive Gradients in Thins-Films (DGT) for determining nitrate removal in two denitrifying bioreactors, and compared DGT performance to traditional approaches for determining performance, including high and low frequency water grab sampling. The binding layer was produced using the Purolite® A520E anion exchange resin. The uptake and elution efficiencies were 98.8% and 93.4% respectively. DGTs of three material diffusion layer thicknesses were placed in piezometers along longitudinal transects, to enable calculation of the diffusive boundary layer and provide replicates. These were removed after 16, 24 and 36 h, and the accumulated nitrate masses were extracted and quantified to calculate nitrate concentration. Concentrations were subsequently utilised to calculate nitrate removal rates in both bioreactors. Grab samples were taken at 30 and 60 min intervals over those periods, nitrate concentrations were also measured to determine nitrate removal. DGTs provided nitrate removal rates at bioreactor site one (controlled flow, wastewater treatment) of 14.83–30.75 g N m−3 d−1, and 1.22–3.63 g N m−3 d−1 at site two (variable flow, agricultural run-off). DGT determined nitrate concentrations and removal rates were in strong accordance with high frequency grab sampling, but data collection via DGTs was considerably easier. Utilising DGTs for the measurement of bioreactor performance overcame many of the challenges associated with high frequency grab sampling, and other methods, such as accounting for temporal variation in nitrate concentration and reduced analytical requirements.

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