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Statistical modeling and optimization of biomass granulation and COD removal in UASB reactors treating low strength wastewaters.
Bioresour Technol. 2008 Jul; 99(10):4229-38.BT

Abstract

The aim of this work was to study the influence of influent chemical oxygen demand (COD), upflow velocity of wastewater, and cationic polymer additives in inoculum, on biomass granulation and COD removal efficiency in upflow anaerobic sludge blanket (UASB) reactor for treating low strength wastewater. Statistical models were formulated based on these three variables to optimize the biomass granulation and COD removal efficiency in UASB reactors using a two-level, full factorial design. For the thick inoculum used in this study, having suspended solids (SS) >80 g/l and volatile suspended solids (VSS) to SS ratio <0.3, cationic polymer additives in the inoculum showed adverse effect on biomass granulation and COD removal efficiency. It is concluded that for such thick inoculum, granulation can be obtained while treating low strength wastewaters in UASB reactor by selecting proper combination of influent COD and liquid upflow velocity so as to represent the organic loading rate (OLR) greater than 1.0 kg COD/m(3) d. Validation of model predictions for treatment of synthetic wastewater and actual sewage reveals the efficacy of these models for enhancing granulation and COD removal efficiency.

Authors+Show Affiliations

Environmental Engineering and Management Section, Department of Civil Engineering, Indian Institute of Technology, Kharagpur 721 302, India. puspendu@civil.iitkgp.ernet.inNo affiliation info available

Pub Type(s)

Journal Article

Language

eng

PubMed ID

17936620

Citation

Bhunia, Puspendu, and M M. Ghangrekar. "Statistical Modeling and Optimization of Biomass Granulation and COD Removal in UASB Reactors Treating Low Strength Wastewaters." Bioresource Technology, vol. 99, no. 10, 2008, pp. 4229-38.
Bhunia P, Ghangrekar MM. Statistical modeling and optimization of biomass granulation and COD removal in UASB reactors treating low strength wastewaters. Bioresour Technol. 2008;99(10):4229-38.
Bhunia, P., & Ghangrekar, M. M. (2008). Statistical modeling and optimization of biomass granulation and COD removal in UASB reactors treating low strength wastewaters. Bioresource Technology, 99(10), 4229-38.
Bhunia P, Ghangrekar MM. Statistical Modeling and Optimization of Biomass Granulation and COD Removal in UASB Reactors Treating Low Strength Wastewaters. Bioresour Technol. 2008;99(10):4229-38. PubMed PMID: 17936620.
* Article titles in AMA citation format should be in sentence-case
TY - JOUR T1 - Statistical modeling and optimization of biomass granulation and COD removal in UASB reactors treating low strength wastewaters. AU - Bhunia,Puspendu, AU - Ghangrekar,M M, Y1 - 2007/10/23/ PY - 2007/06/05/received PY - 2007/08/24/revised PY - 2007/08/25/accepted PY - 2007/10/16/pubmed PY - 2008/6/17/medline PY - 2007/10/16/entrez SP - 4229 EP - 38 JF - Bioresource technology JO - Bioresour Technol VL - 99 IS - 10 N2 - The aim of this work was to study the influence of influent chemical oxygen demand (COD), upflow velocity of wastewater, and cationic polymer additives in inoculum, on biomass granulation and COD removal efficiency in upflow anaerobic sludge blanket (UASB) reactor for treating low strength wastewater. Statistical models were formulated based on these three variables to optimize the biomass granulation and COD removal efficiency in UASB reactors using a two-level, full factorial design. For the thick inoculum used in this study, having suspended solids (SS) >80 g/l and volatile suspended solids (VSS) to SS ratio <0.3, cationic polymer additives in the inoculum showed adverse effect on biomass granulation and COD removal efficiency. It is concluded that for such thick inoculum, granulation can be obtained while treating low strength wastewaters in UASB reactor by selecting proper combination of influent COD and liquid upflow velocity so as to represent the organic loading rate (OLR) greater than 1.0 kg COD/m(3) d. Validation of model predictions for treatment of synthetic wastewater and actual sewage reveals the efficacy of these models for enhancing granulation and COD removal efficiency. SN - 0960-8524 UR - https://www.unboundmedicine.com/medline/citation/17936620/Statistical_modeling_and_optimization_of_biomass_granulation_and_COD_removal_in_UASB_reactors_treating_low_strength_wastewaters_ L2 - https://linkinghub.elsevier.com/retrieve/pii/S0960-8524(07)00719-5 DB - PRIME DP - Unbound Medicine ER -