Comparison of existing models to simulate anaerobic digestion of lipid-rich waste. (February 2017)

• Record Type: Journal Article
• Authors: Béline, F.; Rodriguez-Mendez, R.; Girault, R.; Bihan, Y. Le; Lessard, P.
• Is Part Of: Bioresource technology. Volume 226(2017)
• Page Start: 99
• Page End: 107
• Publication Date: 2017-02
• Subjects: Modelling -- Anaerobic digestion -- ADM1 -- Inhibition -- Lipid-rich waste; 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.2016.12.007
• Languages: English
• ISSNs: 0960-8524

Abstract

Highlights: ADM1 cannot simulate anaerobic digestion of lipid-rich waste. LCFA inhibition has to be considered to simulate substrates and acids accumulation. Acetogenesis and methanogenesis are most sensitive to LCFA inhibition. Models fail to simulate pH when approaching 6.5–6.0. Abstract: Models for anaerobic digestion of lipid-rich waste taking inhibition into account were reviewed and, if necessary, adjusted to the ADM1 model framework in order to compare them. Experimental data from anaerobic digestion of slaughterhouse waste at an organic loading rate (OLR) ranging from 0.3 to 1.9 kgVS m −3 d −1 were used to compare and evaluate models. Experimental data obtained at low OLRs were accurately modeled whatever the model thereby validating the stoichiometric parameters used and influent fractionation. However, at higher OLRs, although inhibition parameters were optimized to reduce differences between experimental and simulated data, no model was able to accurately simulate accumulation of substrates and intermediates, mainly due to the wrong simulation of pH. A simulation using pH based on experimental data showed that acetogenesis and methanogenesis were the most sensitive steps to LCFA inhibition and enabled identification of the inhibition parameters of both steps.