Removing nutrients from wastewater is essential because high concentrations in aquatic systems lead to severe eutrophication problems, the most common impairment of surface waters such as lakes and oceans. Total phosphorus (TP) and total Kjeldahl nitrogen (TKN) were removed from mixed wastewater using an aerobic granular sludge process in a sequencing batch reactor (AGS-SBR). An artificial neural network (ANN) and response surface methodology (RSM) were applied to evaluate the main parameters of the process. For TKN removal, only cycle time (CT) (0.0475) was a significant variable, achieving removal efficiencies of up to 81%. In TP case removal, two parameters, VER and AR, were substantial for this process, completing elimination efficiencies of around 40%. On comparing the models with statistical indices, ANN coupled with the moth-flame optimization algorithm (ANN-MFO) demonstrated higher performance with an adjusted R2 (0.9866) for the case of TP removal and (0.9519) for TKN removal.
Biological nitrogen removal from industrial wastewater (pharmaceutical synthetic wastewater) was studied. Sequencing batch reactor (SBR) and sequencing batch biofilm reactor (SBBR) were utilized to treat ammonium-rich wastewater. No external carbon source was added to the reactors. At nitrogen loading rate (NLR) of 2.5 kg N/(m3·day), the efficiency of ammonium removal from synthetic wastewater in SBR was 86.9%. SBBR ammonium removal efficiency under fixed dissolved oxygen (DO) concentration of 0.3 mg O2/dm3 was 98.4%. Specific nitrification rate (SNR) and specific denitrification rate (SDNR) in SBR were 9.24 mg NH4 +-N/(g MLVSS·h) and 18.56 mg NO3 – -N/(g MLVSS·h), respectively. Nitrite accumulation rate (NAR) showed high correlation with DO decrement (R2 = 0.983), NAR and simultaneous nitrification and denitrification (SND) had high correlation, too (R² = 0.976). SND efficiency in SBBR reached 94.1% while ammonium oxidizing bacteria (AOB) were dominant and NAR in SBBR process at the DO level of 0.3 mg O2/dm3 was 90.3%.
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