Journal
APPLIED SCIENCES-BASEL
Volume 11, Issue 3, Pages -Publisher
MDPI
DOI: 10.3390/app11030998
Keywords
microalgae; bacteria; modelling; wastewater treatment; nutrients; photobioreactor
Categories
Funding
- Spanish Ministry of Science and Innovation [DPI2017 84259-C2- 1-R]
- EU-ERDF funds [DPI2017 84259-C2- 1-R]
- European Union's Horizon 2020 Research and Innovation Program [727874]
- PURASOL project (Spanish Ministry of Economy and Competitiveness) [CTQ2017-84006-C3-3-R]
- Spanish Ministry of Education through the National FPU Program [FPU16/05996]
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The study introduces a microalgae-bacteria consortia model for wastewater treatment, calibrated and validated using pig slurry. The model, implemented in MATLAB and calibrated using genetic algorithms, allows simulation of different components in the system for optimal wastewater treatment.
Microalgae-bacteria consortia have been proposed as alternatives to conventional biological processes to treat different types of wastewaters, including animal slurry. In this work, a microalgae-bacteria consortia (ABACO) model for wastewater treatment is proposed, it being calibrated and validated using pig slurry. The model includes the most relevant features of microalgae, such as light dependence, endogenous respiration, and growth and nutrient consumption as a function of nutrient availability (especially inorganic carbon), in addition to the already reported features of heterotrophic and nitrifying bacteria. The interrelation between the different populations is also included in the model, in addition to the simultaneous release and consumption of the most relevant compounds, such as oxygen and carbon dioxide. The implementation of the model has been performed in MATLAB software; the calibration of model parameters was carried out using genetic algorithms. The ABACO model allows one to simulate the dynamics of different components in the system, and the relative proportions of microalgae, heterotrophic bacteria, and nitrifying bacteria. The percentage of each microbial population obtained with the model was confirmed by respirometric techniques. The proposed model is a powerful tool for the development of microalgae-related wastewater treatment processes, both to maximize the production of microalgal biomass and to optimize the wastewater treatment capacity.
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