In-situ biogas upgrading process: Modeling and simulations aspects. (December 2017)

• Record Type: Journal Article
• Authors: Lovato, Giovanna; Alvarado-Morales, Merlin; Kovalovszki, Adam; Peprah, Maria; Kougias, Panagiotis G.; Rodrigues, José Alberto Domingues; Angelidaki, Irini
• Is Part Of: Bioresource technology. Volume 245:Part A(2017)
• Page Start: 332
• Page End: 341
• Publication Date: 2017-12
• Subjects: Biogas upgrading -- Hydrogenotrophic methanogens -- Mathematical modeling -- Sensitivity analysis; Biomass -- Periodicals; Biomass energy -- Periodicals; Bioremediation -- Periodicals; Agricultural wastes -- Periodicals; Factory and trade waste -- Periodicals; Organic wastes -- Periodicals; Bioénergie -- Périodiques; Déchets agricoles -- Périodiques; Déchets industriels -- Périodiques; Déchets organiques -- Périodiques; Déchets (Combustible) -- Périodiques; 662.88
• DOI: 10.1016/j.biortech.2017.08.181
• Languages: English
• ISSNs: 0960-8524

Abstract

Graphical abstract: Highlights: The biological biogas upgrading process by in-situ hydrogen injection was modeled. Hydrogenotrophic kinetics and hydrogen balance was added to a previous model. The model was effective in predicting biogas, methane and hydrogen rates. pH and ammonia simulation were also well predicted. The model is highly sensitive to hydrogen injection and mass transfer coefficients. Abstract: Biogas upgrading processes by in-situ hydrogen (H2 ) injection are still challenging and could benefit from a mathematical model to predict system performance. Therefore, a previous model on anaerobic digestion was updated and expanded to include the effect of H2 injection into the liquid phase of a fermenter with the aim of modeling and simulating these processes. This was done by including hydrogenotrophic methanogen kinetics for H2 consumption and inhibition effect on the acetogenic steps. Special attention was paid to gas to liquid transfer of H2 . The final model was successfully validated considering a set of Case Studies. Biogas composition and H2 utilization were correctly predicted, with overall deviation below 10% compared to experimental measurements. Parameter sensitivity analysis revealed that the model is highly sensitive to the H2 injection rate and mass transfer coefficient. The model developed is an effective tool for predicting process performance in scenarios with biogas upgrading.