Assessing and modeling biocatalysis in field denitrification beds reveals key influencing factors for future constructions. (1st January 2021)

• Record Type: Journal Article
• Authors: Grießmeier, Victoria; Wienhöfer, Jan; Horn, Harald; Gescher, Johannes
• Is Part Of: Water research. Volume 188(2021)
• Publication Date: 2021-01-01
• Subjects: Denitrification bed -- microbial diversity -- system limitations -- hydraulic model; Water -- Pollution -- Research -- Periodicals; 363.7394
• DOI: 10.1016/j.watres.2020.116467
• Languages: English
• ISSNs: 0043-1354

Abstract

Highlights: Four years of continuous denitrification bed observation led to a process model. Temperature and hydraulic retention time influence nitrate removal the most. Hydraulic retention time impacts the flow path through a denitrification bed. Bioinformatic analysis reveals a division of labor and a low amount of methanogens. Abstract: Environmental contamination with fertilizers is threatening biodiversity in many ecosystems due to nitrate-based eutrophication. One opportunity for a cost-efficient nitrate elimination are denitrification beds in which a microbial community thrives under anoxic conditions with polymeric plant material as a carbon and an electron source. Incoming nitrate is used as electron acceptor and reduced to molecular nitrogen. Projects realizing denitrification beds in field scale are sparse and robust data on their efficiency throughout the year mostly not available. This study analyzed the nitrate elimination efficiency and microbiology of a 216 m 3 denitrification bed over the time course of more than three years. Phylogenetic as well as transcriptomic analysis revealed that the reactor contained a biofilm community growing on the surface of the wood chips and a planktonic community. Both differed in composition but their variance was affected only to a minor extend by seasonal temperature changes. Cellulose degradation was mainly conducted by the biofilm population while denitrification was mostly conducted by the planktonic community. Methanogens were detectable only to a very minor extend. Using online data from the nitrate concentration of in- and outflowing water as well as a hydrological model to predict the water inflow, it was possible to establish a process model that sufficiently describes the denitrification process. This model clearly indicates that the denitrification efficiency is mostly impacted by temperature and hydraulic retention time. It also suggests that the simple design of the denitrification bed most likely leads to different flow paths through the reactor depending on the volumetric flow rate. This study allows for the first time a robust estimation of the necessary reactor size for nitrate removal in a moderate continental climate setting. It also suggests how future denitrification beds could be improved for better performance. Graphical abstract: Image, graphical abstract