Biological watewater treatment: Dynamic global sensitivity analysis and parameter estimation in a system of waste stabilization ponds

FACUNDO ITURMENDI; VANINA ESTRADA; MARIA PAZ OCHOA; PATRICIA HOCH; MARIA SOLEDAD DIAZ

COMPUTER AIDED CHEMICAL ENGINEERING

ELSEVIER B. V.

Lugar: Oxford; Año: 2012 vol. 30 p. 212 - 216

1570-7946

Waste stabilization ponds are used as a natural method of wastewater treatment. They are usually a combination of three different pond types: anaerobic, facultative and maturation. Facultative ponds can be classified into primary (inflows without treatment) and secondary (inflows are pre-treated in anaerobic ponds). Due to the different nature of the processes taking place in the different types of ponds, also different chemical and biochemical processes take place within the different zones, including mutual relationships between microalgae, heterotrophic bacteria and fungi that have the largest influence in the pond efficiency for biological wastewater treatment. A few models have been proposed for waste stabilization ponds describing hydrodynamic (Manga et al., 2004, Shilton and Mara, 2005) or biochemical processes (Kayombo et al., 2000; Dochain et al., 2003). However, the different pollutant removal processes have yet not been entirely understood. In this work, we propose a dynamic mathematical model based on first principles representing the major biogeochemical processes that take place within aerobic and facultative ponds. Mass balances for bacteria, fungi, main groups of microalgae (cyanobacteria, diatomea, chlorophyta), protozoo, yeast, nitrogen (nitrate, ammonium and organic nitrogen), phosphorus (phosphate and organic phosphorus), dissolved oxygen and biochemical demand of oxygen have been formulated. Algebraic equations represent rate equations and the profiles for the process variables (temperature, solar radiation, pH, inflows and concentrations, among others). The wastewater biological treatment system is composed of three stages of oxygenated ponds in series. The first two ponds are aerobic oxygenated and the last one is facultative oxygenated. The facultative pond has been modeled as composed of two horizontal layers, to represent dissolved oxygen concentration gradient along the water column, as well as the different associated processes taking place in each zone (Estrada et al., 2009). Global sensitivity analysis has been performed applying Sobol´ method (Sobol, 2001) to determine most influential parameters. Based on these results, a parameter estimation problem has been formulated, subject to the differential algebraic system describing the biological wastewater treatment system. Experimental data from a juice plant have been collected along one year with a frequency of fifteen days in the intensive working period. The model has been implemented in gPROMS (PSEnterprise, 2009) and numerical results provide a deep insight on the complex relations among microorganisms, nutrients and organic matter concentration. References Dochain, D., Gregoire, S., Pauss, A., Schaegger, M., 2003. Dynamic modelling of a waste stabilization pond. Bioprocess and Biosystems Engineering 26, 19?26. Estrada, V., Parodi, E. R., Diaz, M. S. 2009. Addressing the Control Problem of Algae Growth in Water Reservoirs with Advanced Dynamic Optimization Approaches. Comp. & Chem. Eng, 33, 2063-2074. Kayombo, S., Mbwette, T.S.A., Mayo, A.W., Katima, J.H.Y., Jorgensen, S.E., 2000. Modelling diurnal variation of dissolved oxygen in waste stabilization ponds. Ecological Modelling 127, 21?31. Manga, J.G., Molinares Nelson, R., Orlando Soto, E., Arrieta, J., Escaf Germa, J., Hernandez Gustavo, A., 2004. Influence of inlet-outlet structures on the flow pattern of a waste stabilization pond. In: Proceedings 6th International Conference of Waste Stabilization Ponds. Avignon, France. PSEnterprise, 2009, gPROMS User guide. Shilton, A.N., Mara, D.D., 2005. CFD (computational fluid dynamics) modelling of baffles for optimizing tropical waste stabilization pond system. Water Science and Technology 51, 103?106. Sobol?, I.M.. Global sensitivity indices for nonlinear mathematical models and their Monte Carlo estimates, Mathematics and Computers in Simulation 55, 2001, 271-280.