ALBA: A comprehensive growth model to optimize algae-bacteria wastewater treatment in raceway ponds

WATER RESEARCH

卷:190

Article

Casagli, Francesca¹  Zuccaro, Gaetano²  Bernard, Olivier³  Steyer, Jean-Philippe²  Ficara, Elena¹ 

[1] Politecn Milan, Dip Ingn Civile & Ambientale DICA, Piazza L da Vinci 32, I-20133 Milan, Italy

[2] Univ Montpellier, LBE, INRAE, 102 Ave Etangs, Narbonne, France

[3] Univ Cote dAzur, INRIA, Biocore, Sophia Antipolis, France

关键词: Modelling;    Microalgae;    Wastewater;    Long-term validation;    Raceway;    Mass transfer rate;   

DOI  :  10.1016/j.watres.2020.116734

来源: Elsevier

【 摘 要 】

This paper proposes a new model describing the algae-bacteria ecosystem evolution in an outdoor raceway for wastewater treatment. The ALBA model is based on mass balances of COD, C, N and P, but also H and O. It describes growth and interactions among algae, heterotrophic and nitrifying bacteria, while local climate drives light and temperature. Relevant chemical/physical processes are also included. The minimum-law was used as ground principle to describe the multi-limitation kinetics. The model was setup and calibrated with an original data set recorded on a 56 m(2) raceway located in the South of France, continuously treating synthetic wastewater. The main process variables were daily measured along 443 days of operations and dissolved O-2 and pH were on-line recorded. A sub-dataset was used for calibration and the model was successfully validated, along the different seasons over a period of 414 days. The model proved to be effective in reproducing both the short term nycthemeral dynamics and the long-term seasonal ones. The analysis of different scenarios reveals the fate of nitrogen and the key role played by oxygen and CO2 in the interactions between the different players of the ecosystem. On average, the process turns out to be CO2 neutral, as compared to a standard activated sludge where approximately half of the influent carbon will end up in the atmosphere. The ALBA model revealed that a suboptimal regulation of the paddle wheel can bring to several detrimental impacts. At high velocity, the strong aeration will reduce the available oxygen provided by photo-oxygenation, while very low aeration can rapidly lead to oxygen inhibition of the photosynthetic process. On the other hand, during night, the paddle wheel is fundamental to ensure enough oxygen in the system to support algal-bacteria respiration. The model can be used to support advanced control strategies, including smart regulation of the paddle wheel velocity to more efficiently balance the mixing, aeration and degassing effects. (C) 2020 Elsevier Ltd. All rights reserved.

【 授权许可】

Free