Mathematical Modeling of a Raceway Pond System for Biofuels Production

Abstract

Abstract The need for low-cost biofuels has sparked renewed interest in raceway pond systems as cheap means for microbial biomass cultivation. The development of reliable dynamic bioprocess models is necessary for the optimal design of raceway pond systems. This paper presents a detailed model based on the high-rate algal-bacterial pond model and dynamic flux balance analysis (DFBA). With DFBA, all possible growth modes of the microorganisms in the pond are considered, as opposed to unstructured models which can only consider single growth modes. Multiple growth modes can occur over time in raceway pond systems due to day/night transitions and multiple substrate limitations. Different cultivation alternatives for oleaginous yeast and algae are explored and their biomass and lipids productivities are predicted. The case studies show that algae growth can become CO 2 and light limited and yeast growth can become O 2 limited. The model predicts better carbon utilization by an algae/yeast coculture than the respective monocultures and it captures complex phenomena such as the exchange of CO 2 and O 2 , the competition for nitrogen sources, and the effect of pH on growth rates. The model predicts that the lipids productivity attained by the algae/yeast coculture is attractive for biofuels production. This paper is a summary of the results presented in Gomez et al. (2016.