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Estimating Sediment Denitrification Rates Using Cores and N2O Microsensors
Published on: December 6, 2018
Modeling denitrification byproducts during bioelectrochemical denitrification mediated by hydrogen oxidizing bacteria
Francesco Savio1, Adam Kovalovszki1, Krist V Gernaey2
1Department of Environmental and Resource Engineering, Technical University of Denmark, Bygningstorvet, Bygning 115, 2800 Kgs. Lyngby, Denmark.
None:
Denitrifying bioelectrochemical systems (d-BES) represent a promising approach for nitrate (NO3-) remediation from contaminated groundwater. In these systems, hydrogen (H2), produced through water electrolysis at cathodic electrodes, serves as the electron donor for autotrophic denitrification. However, process efficiency is often limited by low temperatures and the formation of undesirable intermediates such as nitrite (NO2-), nitrous oxide (N2O), or ammonium (NH4+) by competing dissimilatory nitrate reduction to ammonium (DNRA) pathway. This study aims to develop and validate a mechanistic biofilm model that predicts nitrogen transformations and by-product formation during hydrogenotrophic denitrification at different temperatures. A one-dimensional biofilm model was formulated, explicitly coupling electrochemical H2 generation with four-step hydrogenotrophic denitrification and DNRA processes. The model was calibrated and validated using batch data from d-BES operated at 20, 10, and 4°C. Global sensitivity analysis identified key parameters controlling NO3- removal and by-product formation, which differed with temperature. Cathodic H2 efficiency and boundary-layer thickness were the most influential parameters. The model accurately reproduced experimental dynamics of NO3- and N2O across all temperatures, obtaining Theil's Inequality Coefficients (TIC) below 0.3, while for NH4+ a better fit (TIC = 0.12) was obtained at higher temperature (20°C). The model additionally revealed strong spatial segregation of microbial guilds, with denitrifiers dominating the outer biofilm layers, while DNRA bacteria prevailed near the electrode surface, where H2 is produced. The proposed framework provides a predictive basis for optimizing d-BES operation and developing digital twins for NO3- removal under cold, real-field groundwater conditions.
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