Optimization of wastewater treatment using microalgae through the metabolic modeling of the microbial community

• Grant number: 24/18573-1
• Support Opportunities: Scholarships in Brazil - Post-Doctoral
• Start date: March 01, 2025
• End date: February 28, 2027
• Field of knowledge: Engineering - Chemical Engineering
• Principal Investigator: Ana Teresa Lombardi
• Grantee: Bruno Assis Pessi
• Host Institution: Centro de Ciências Biológicas e da Saúde (CCBS). Universidade Federal de São Carlos (UFSCAR). São Carlos , SP, Brazil

Abstract

This project aims to develop a new modeling framework to optimize the treatment of wastes using microalgae, integrating dynamic models with the analysis of metabolic networks of the microbial community in the system. The project is innovative in combining metabolic modeling with the dynamic prediction of physicochemical parameters, based on the comprehensive ALBA model and the DRUM framework for reducing metabolic networks. The ALBA model consists of a system of differential equations that represents the dynamics of physicochemical characteristics, the concentration of microalgae, and three types of bacteria. The development of the methodology can be divided into three stages: first, the preliminary expansion of the ALBA model to provide a more detailed representation of the microbial community. Secondly, the development of a framework to analyze the metabolic networks of the microbial community, determining the metabolic functions performed by the organisms, making it possible to simplify the representation of this community in the model. Finally, the extension of the ALBA model to consider the groups of organisms determined by metabolic analysis and the use of the DRUM method to model the internal composition of microalgae. The model will be validated across different types of communities using data from experiments treating three types of wastewater with microalgae: primary sanitary sewage, secondary sanitary sewage and vinasse. The validated model will be used to propose optimal operation strategies through optimization and control techniques.