Biodegradation of mixed wastes : basic kinetics and reaction engineering for cyclic reactor operation

This study dealt with the determination of the detailed kinetics of the biodegradation of mixed substrates by pure cultures, and with reaction engineering studies of bioreactors employed in treatment of substitutable substrates under cyclic operation. In the first part of the study the degradation of phenol and 4-chlorophenol (4-CP) by two strains of Pseudomonas species was investigated. Strain P. putida 0 was found to be capable of utilizing both phenol and 4-CP as sole carbon and energy sources. This suggests that this strain follows the ortho-cleavage pathway for the aromatic ring. Strain P. putida N could grow on phenol, and in its presence, could transform 4-CP to intermediates which are long-lived and do not serve as carbon and/or energy sources for the culture. These results suggest that P. putida N follows the meta-cleavage pathway for the aromatic ring. The second part of the study dealt with the kinetics of glucose and phenol utilization by a pure culture of P. putida OR. It was found that the two substrates could serve as carbon and energy sources for the culture. The two substrates were used simultaneously, but were involved in a cross-inhibitory uncompetitive kinetic interaction. Inhibition from glucose on phenol removal was stronger. The kinetics were described by detailed mathematical expressions. Based on the kinetic expressions obtained in the second part of the study, a detailed model describing biodegradation of phenol/glucose mixtures in a continuously operated cyclic reactor was derived. The dynamics of the system were studied numerically with computer codes based on the bifurcation theory for forced systems. The results, presented in the form of two-dimensional operating diagrams, show that there are regions in the parameter space where multistability occurs. The theoretical predictions were tested in experiments with a fully automated laboratory-scale unit. The experimental data validated the theoretical predictions. The quantitative agreement between theory and experiments was excellent. The experimentally validated model can be used in design and process optimization studies