Optimization of operational parameters in moving bed biofilm reactor with low cost polystyrene biocarrier by the response surface method
Author(s) -
Anjali Barwal,
Rubina Chaudhary
Publication year - 2015
Publication title -
water quality research journal
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.339
H-Index - 44
eISSN - 2408-9443
pISSN - 1201-3080
DOI - 10.2166/wqrjc.2017.026
Subject(s) - kjeldahl method , aeration , response surface methodology , chemical oxygen demand , turbidity , central composite design , effluent , wastewater , biochemical oxygen demand , moving bed biofilm reactor , pulp and paper industry , environmental science , environmental engineering , total suspended solids , chemistry , nitrogen , chromatography , biofilm , engineering , oceanography , organic chemistry , biology , bacteria , genetics , geology
The combined effects of three independent variables (carrier filling ratio, aeration rate and reactor run time (RRT)) were evaluated in a continuous moving bed biofilm reactor (MBBR) through central composite design (CCD) of the response surface methodology (RSM) for experimental design, analysis and process optimization for municipal wastewater treatment processes. A low-cost polystyrene biocarrier was designed and its efficiency in terms of organic and nutrient removal was evaluated in an MBBR. A mathematical–statistical tool represented by CCD was employed to assess the interactive effects of the three key independent operational parameters, inclusive of biocarrier filling ratio (0–70%), aeration rate (0.21–0.63 m 3 h –1 ) and RRT (1–15 days), on the removal efficiency of chemical oxygen demand (COD), biochemical oxygen demand (BOD), total Kjeldahl nitrogen (TKN), total phosphorus (TP) and turbidity. The maximum efficiency obtained was at carrier filling rate 50%, aeration rate 0.42 m 3 h –1 and RRT of 9 days, respectively. The results obtained for COD, BOD, TKN, TP and turbidity were 91.6, 92.9, 72.0, 55.0 and 46.0%, respectively. This study provides valuable information about interrelations of process parameters at different values of the operating variables. The results illustrate that this statistical tool could be effectively utilized for effluent organic load, nutrient and turbidity removal.
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