Performance Evaluation and Substrate Removal Kinetics of an Anaerobic Packed-Bed Biofilm Reactor

• Published in: International Journal of Environmental Research 2019-04, Vol.13 (2), p.223-233
• Main Authors: Pandey, Siddhartha, Sarkar, Sudipta
• Format: Article
• Language: English
• Subjects: Anaerobic processes; Beads; Biofilms; Correlation coefficients; Earth and Environmental Science; Environment; Environmental Engineering/Biotechnology; Environmental Management; Geoecology/Natural Processes; Kinetics; Landscape/Regional and Urban Planning; Mathematical models; Molasses; Natural Hazards; Performance evaluation; Reaction kinetics; Reactors; Research Paper; Steady state; Substrates; Wastewater treatment
• ISSN: 1735-6865; 2008-2304
• DOI: 10.1007/s41742-019-00168-x

The present study is based on the investigation of process kinetics of a two-phase anaerobic packed-bed biofilm reactor (AnPBR) with PVA gel beads as biocarrier treating synthetic wastewater-containing molasses. During the steady-state conditions, the reactor system was attributed to 89% of COD removal efficiency. For the comparison of substrate loading removal rate with the prediction of Grau’s second-order model and Stover–Kincannon substrate removal model, AnPBR reactor was run under different hydraulic retention times (HRT) and organic loads. The experimental data obtained from the steady-state conditions showed that Stover–Kincannon model and Grau’s second-order model were the most appropriate models for the proper description of the reactor. Both the Grau’s second-order model and Stover–Kincannon model gave very high correlation coefficients of 98.36% and 98.37%, respectively, for the overall reactor system. Thus, both of these models can be used efficiently for the prediction of behavior and to design the AnPBR reactors. Article Highlights Grau second order model gave a high correlation coefficient of 98.36% Stover–Kincannon model also gave high correlation coefficients of 98.37% Both the models can be used to design the AnPBR reactors Efficient prediction of behavior of AnPBR reactors can be done by these models