ADVANCED BIOPROCESS DEVELOPMENT FOR THE PRODUCTION OF SUCCINIC ACID FROM BIODIESEL GLYCEROL

Abstract

Sustainability studies for the bioconversion of biodiesel glycerol to succinic acid have emphasised the requirement of fermentation processes of improved productivity up to the industrial scale. The objective of the work presented in this Thesis is to optimise the performance of the bioconversion of glycerol to succinic acid by Actinobacillus Succinogenes, a wild type strain derived from the bovine rumen and to further assess the scalability of the particular system by developing a model based approach. An initial adaptation procedure for the strain allowed to create a culture fit for conducting all parameter estimation driven experiments.CO2 availability has been identified as one of the key parameters due to its role in the metabolic pathway towards succinate and it is highly related to mass transport phenomena that are scale dependent. An unstructured double substrate model is developed where CO2 is an equally rate limiting substrate along with glycerol. This model is the first to serve the purpose of identifying any limitation due to inefficient mass transfer from the gaseous to the liquid phase and it incorporates controllable parameters (agitation, flow rate) along with parameters that account for the scale (e.g. geometry, impeller size). Variations in the concentration of the magnesium carbonate and glycerol are efficiently predicted. A second layer of resistance in the mass transfer of CO2 derives from its diffusion from the liquid phase towards the cells surface. The previously developed model was modified to account for the diffusion rate of both substrates and Monod Kinetics were related to the concentration of the substrates on the cell surface. Variations in agitation speed (200 - 800 rpm) were effectively captured by the model. The efficient ranges of agitation and gaseous flow rates for conducting scale up at a 1:10 ratio is presented and compared to conventional methods of scaling up. Finally, a robust model for process mode selection studies is presented. The model can predict the behaviour of all tested process modes (fed-batch, continuous and continuous with cell recycling system) and predicts the limits of the process in terms of attainable productivity. Continuous fermentation with cell recycle can reach the highest recorded succinic acid productivity of 2.7 g L-1 h-1.

Date of Award	1 Aug 2016
Original language	English
Awarding Institution	The University of Manchester
Supervisor	Colin Webb (Supervisor) & Konstantinos Theodoropoulos (Supervisor)