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The hydrodynamic behaviour of a full-scale wastewater treatment plant (WWTP) bioreactor treating municipal wastewater, situated in Granollers (Barcelona, Spain), has been studied by means of a residence time distribution (RTD) technique using lithium (chloride) as tracer. The bioreactor studied is designed to work as a plug-flow reactor and it is divided into two independent lanes (1 and 2), each one composed of four compartments in series resulting in a total volume of 3970 m 3 per lane. During the RTD experiments, working flow was 1000 m 3 h −1 per lane, which implied an ideal mean residence time of 3.97 h. When a lithium chloride tracer was injected in the bioreactor, both lanes showed a similar highly non-ideal hydrodynamic behaviour, which had an important effect on the reactor's performance. This global RTD was complemented by means of local RTDs in different locations of the bioreactor in order to determine qualitatively the reactor's mixing regime. Different non-ideal models (namely axial dispersion, tanks-in-series and some simple compartment models) have been tested for the modelling of the experimental RTD. The best model fitting RTD data for Lanes 1 and 2 was a configuration consisting of four mixed tanks in series. The RTD study proposed in this work will permit improvement of the reactor's mixing performance, which is of special interest in future projects including simultaneous removal of carbon, nitrogen and phosphorus.

A simple structured mathematical model coupled with a methodology of state and parameter estimation is developed for lipase production by Candida rugosa in batch fermentation. The model describes the system according to the following qualitative observations and hypothesis: Lipase production is induced by extracellular oleic acid present in the medium. The acid is transported into the cell where it is consumed, transformed, and stored. Lipase is excreted to the medium where it is distributed between the available oil-water interphase and aqueous phase. Cell growth is modulated by the intracellular substrate concentration. Model parameters have been determined and the whole model validated against experiments not used in their determination. The estimation problem consists in the estimation of three state variables (biomass, intra- and extracellular substrate) and two kinetic parameters by using only the on-line measurement provided by exhaust gas analysis. The presented estimation strategy divides the complex problem into three subproblems that can be solved by stable algorithms. The estimation of biomass (X) and the specific growth rate (mu), is achieved by a recursive prediction error algorithm using the on-line measurement of the carbon dioxide evolution rate. mu is then used to perform an estimation of intracellular substrate and the other kinetic parameter related to substrate transport (A) by an adaptive observer. Extracellular substrate is then evaluated by means of the estimated values of intracellular substrate and biomass through the material balance of the reactor. Simulation and experimental tests showed good performance of the developed estimator, which appears suitable to be used for process control and monitoring. (c) 1995 John Wiley & Sons, Inc.

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