Dynamic modeling and simulation of the effect of multiple inhibition in anaerobic digestion of fish wast

Abstract

The anaerobic digestion (AD) of fish waste (FW), a byproduct of the growing global fisheries sector, offers significant potential for biogas recovery due to its high protein and lipid content. However, mono-digestion of FW is limited by multiple inhibitory factors, including ammonia, long-chain fatty acids (LCFAs), and volatile fatty acids (VFAs), which adversely affect methanogenesis. This study proposes a dynamic modeling and simulation approach to extend the BioWin 6.2 integrated Anaerobic Sludge Digestion Model (ASDM) by incorporating user-defined state variables and kinetic formulations with inhibition functions to simulate the degradation pathways of FW. The modified model introduces six new state variables: LCFA, amino acids, butyrate, valerate, proteins, and lipids, along with stoichiometric and kinetic parameters obtained from literature. Sensitivity analysis identified μmax_acetate, Ks_acetate, μmax_lipid, Ki_LCFA, Ki_VFA, μmax_aminoacid, and K0 as key parameters. Calibration through multiple trials yielded limited improvements due to FW composition simplifications, differences in mixing conditions, reactor scale variations, and inoculum characteristics variations. Nevertheless, the modified model aligned well with the experimental methane composition and the trend of cumulative methane production, demonstrating its applicability for FW anaerobic digestion. This work contributes a novel modeling approach for protein- and lipid-rich substrates, supporting the advancement of sustainable waste-to-energy technologies.