Integral microalgae-bacteria model (BIO_ALGAE): application to wastewater high rate algal ponds
An integral mechanistic model describing the complex interactions in mixed algal-bacterial systems was developed. The model includes crucial physical, chemical and biokinetic processes of microalgae as well as bacteria in wastewater. Carbon-limited microalgae and autotrophic bacteria growth, light a...
| Autores: | , , , |
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| Tipo de recurso: | artículo |
| Fecha de publicación: | 2017 |
| País: | España |
| Institución: | Universitat Politècnica de Catalunya (UPC) |
| Repositorio: | UPCommons. Portal del coneixement obert de la UPC |
| Idioma: | inglés |
| OAI Identifier: | oai:upcommons.upc.edu:2117/105616 |
| Acceso en línea: | https://hdl.handle.net/2117/105616 https://dx.doi.org/10.1016/j.scitotenv.2017.05.215 |
| Access Level: | acceso abierto |
| Palabra clave: | Microalgae Microalgae-bacteria model wastewater high rate algal ponds (HRAP) biomass production microalgae/bacteria proportion light attenuation Monod kinetics Microalgues Àrees temàtiques de la UPC::Desenvolupament humà i sostenible::Enginyeria ambiental::Tractament de l'aigua |
| Sumario: | An integral mechanistic model describing the complex interactions in mixed algal-bacterial systems was developed. The model includes crucial physical, chemical and biokinetic processes of microalgae as well as bacteria in wastewater. Carbon-limited microalgae and autotrophic bacteria growth, light attenuation, photorespiration, temperature and pH dependency are some of the new features included. The model named BIO_ALGAE was built using the general formulation and structure of activated sludge models (ASM), and it was implemented in COMSOL Multiphysics™ platform. Calibration and validation were conducted with experimental data from two identical pilot HRAPs receiving real wastewater. The model was able to simulate the dynamics of different components in the ponds, and to predict the relative proportion of microalgae (58–68% in average of total suspended solids (TSS) and bacteria (30–20% in average of TSS). Microalgae growth resulted strongly influenced by the light factor fL(I), decreasing microalgae concentrations from 40 to 60%. Furthermore, reducing the influent organic matter concentration of 50% and 70%, model predictions indicated that microalgae production increased from (8.7 g TSS m- 2d- 1 to 13.5 g TSS m- 2d- 1) due to the new distribution of particulate components. The proposed model could be an efficient tool for industry to predict the production of microalgae, as well as to design and optimize HRAPs. |
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