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Biological Phosphorus and Nitrogen Removal From Wastewater Using Moving Bed Biofilm Process



Kermani M1 ; Bina B2 ; Movahedian H2 ; Amin MM2 ; Nikaeen M2
Authors
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Authors Affiliations
  1. 1. Department of Environmental Health Engineering, School of Public Health, Iran University of Medical Sciences, Tehran, P.O. Box 15875-4199, Iran
  2. 2. Department of Environmental Health Engineering, School of Public Health, Isfahan University of Medical Sciences, Isfahan, P.O. Box 81746-73461, Iran

Source: Iranian Journal of Biotechnology Published:2009

Abstract

In this research, an experimental study to evaluate nutrient removal from synthetic wastewater by a labscale moving bed biofilm process was investigated. Also, kinetic analysis of the process with regard to phosphorus and nitrogen removal was studied with different mathematical models. For nutrient removal, the moving bed biofilm process was applied in series with anaerobic, anoxic and aerobic units in four separate reactors that were operated continuously at different loading rates of phosphorus and nitrogen and different hydraulic retention times. Under optimum conditions, almost complete nitrification with an average ammonium removal efficiency of 99.72% occurred in the aerobic reactor. In the aerobic reactor, the average specific nitrification rate was 1.92 g NOx-N (NOx-N=NO2-N +NO3-N) produced/kg volatile suspended solids. hour (VSS.h). Denitrification rate increased with increasing NOx-N loading in the second anoxic reactor. The aerobic phosphate removal rate showed good correlation with the anaerobic phosphate release rate. Under optimum conditions, the average total nitrogen and phosphorus removal efficiencies were 80.9% and 95.8%, respectively. As a result of the moving bed biofilm process (MBBR) kinetic analysis, the Stover-Kincannon model was chosen for modeling studies and experimental data analysis. The Stover-Kincannon model gave high correlation coefficients for phosphorus and nitrogen removal, which were 0.9862 and 0.986, respectively. Therefore, this model could be used in predicting the behavior or design of the moving bed biofilm process.
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