Contribution of modeling in the understanding of the anaerobic digestion: application to the digestion of protein-rich substrates

Autor: Zeyneb Khedim, Jérôme Harmand, Boumediene Benyahia
Přispěvatelé: ProdInra, Migration, Laboratoire automatique de Tlemcen, Université Aboubekr Belkaid - University of Belkaïd Abou Bekr [Tlemcen], Laboratoire de Biotechnologie de l'Environnement [Narbonne] (LBE), Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro), Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut National de la Recherche Agronomique (INRA), International Water Association (IWA). INT.
Jazyk: angličtina
Rok vydání: 2017
Předmět:
Zdroj: Lectures Notes in Civil Engineering
Frontiers International Conference on Wastewater Treatment and Modelling
Frontiers International Conference on Wastewater Treatment and Modelling, International Water Association (IWA). INT., May 2017, Palerme, Italy
Lecture Notes in Civil Engineering ISBN: 9783319584201
Popis: This paper deals with the analysis of a Microalgae Anaerobic Digestion model (MAD model), to study the influence of the ammonia on the fermentation of such protein- rich substrate. Using the operating diagram of the model, we show the key role of the operating parameters: Dilution rate (\( {\mathbf{D}} \)) and the nitrogen input concentration (\( {\mathbf{N}}_{{{\mathbf{in}}}} \)), on the process performances. To investigate the ammonia toxicity phenomenon and its subsequent impact, we focus on the variation Free ammoniacal Nitrogen (FAN) concentration and the biogas yield with respect to the changes of \( {\mathbf{D}} \) and \( {\mathbf{N}}_{{{\mathbf{in}}}} \). Numerical simulations provide the FAN critical concentration leading to bacteria inhibition as well as the ideal values of the control parameters allowing to maximize biogas production, on the one hand, and to avoid any process failure, on the other hand. Our study highlights the effectiveness of the modeling to detect ammonia inhibition risk, that can then be used for control and optimization purposes of such anaerobic digestion process.
Databáze: OpenAIRE