College of Science for Women, Baghdad Science Journal, 2(18), p. 0253, 2021
DOI: 10.21123/bsj.2021.18.2.0253
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Free water surface constructed wetlands (FSCWs) can be used to complement conventional waste water treatment but removal efficiencies are often limited by a high ratio of water volume to biofilm surface area (i.e. high water depth). Floating treatment wetlands (FTWs) consist of floating matrices which can enhance the surface area available for the development of fixed microbial biofilms and provide a platform for plant growth (which can remove pollutants by uptake). In this study the potential of FTWs for ammoniacal nitrogen (AN) removal was evaluated using experimental mesocosms operated under steady-state flow conditions with ten different treatments (two water depths, two levels of FTW mat coverage, two different plant densities and a control, all replicated three times). A simple model was constructed as a framework for understanding N dynamics in each treatment. The model was calibrated using data obtained from one treatment and validated independently for the other treatments. Specifically, we hypothesized that the nitrification and volatilization rate constants are inversely proportional to water depth and proportional to mat surface area. This allowed the relative magnitude of different removal mechanisms to be estimated. The model was able to predict steady-state concentrations of AN and total oxidized nitrogen (TON) across the different treatments well (values for correlation in the regression between measured and predicted steady-state concentrations and RMSE were 0.88 and 0.40 mg N L-1 for AN, and 0.63 and 1.75 mg N L-1 for TON). The results confirm that nitrification is the principal AN removal process, with maximum removal occurring in shallow systems with high matrix cover (i.e. a high ratio of biofilm surface area to water volume). Plant uptake was a relatively minor loss process compared to nitrification. Integrated experimental and model-based approach was found to be a useful tool to improve mechanistic understanding AN dynamics in FSCWs and system performance.