Optimization of an Empirical Model for Microorganism-Immobilized Media to Predict Nitrogen Removal Efficiency

• Published in: Water (Basel) Vol. 15; no. 1; p. 83
• Main Authors: Shin, Dongchul, Chung, Wonsik, Lee, Jongkeun
• Format: Journal Article
• Language: English
• Published: Basel MDPI AG 01.01.2023
• Subjects: Alkalinity; Biofilms; Carbon sources; Chemical oxygen demand; Correlation coefficient; Correlation coefficients; Denitrification; Design techniques; Efficiency; Effluent standards; Effluent treatment; Effluents; experimental design method; Experiments; microorganism-immobilized media; Microorganisms; Nitrification; Nitrogen; Nitrogen removal; Optimization; optimization model; Optimization models; Organic matter; Parameters; Polyethylene glycol; Polyvinyl alcohol; Purification; Quality standards; Reactors; Sewage; Wastewater; Wastewater treatment; Water quality; Water quality standards; Water treatment
• ISSN: 2073-4441; 2073-4441
• DOI: 10.3390/w15010083

The purpose of this study was to develop a model to predict the total nitrogen (T-N) concentration in treated wastewater effluent when microorganism-immobilized media are applied. The operational data for this study were obtained using synthetic wastewater and actual wastewater within a lab-scale reactor. The organic matter removal, nitrification, and denitrification rates were 81.8, 87, and 82.9%, respectively. These rates adequately satisfied the effluent water quality standard. The observed parameters from the lab-scale reactor operation were applied to develop the optimization model, and the model showed correlation coefficients as 0.9785 and 0.9811 for nitrification and denitrification efficiencies, respectively. The model predicted that T-N concentration could be reduced to <10 mg/L with the injection of the external carbon source. The predicted value for the T-N concentration was higher than the observed value from the lab-scale reactor, which operated under the same conditions. The model showed comparable values to the observed data, and the model seems to be useful for predicting related parameters in effluent water quality, with further development of the specifications required in the treatment facilities under various operating conditions.