Anaerobic co-digestion as an option to improve methane productionMorelli, Simone (Avtor) Kolbl Repinc, Sabina (Mentor) Siciliano, Alessio (Komentor) master thesisanaerobic co-digestionagricultural wastelignocellulosic substratesmethane yieldmixture designbiochemical methane potential (BMP)mathematical modellingThe progressive depletion of traditional fossil fuel sources, along with the uncontrolled rise in greenhouse gas emissions, has prompted governments to focus on innovative and sustainable energy solutions. Among renewable energy technologies, biogas production via anaerobic digestion (AD) has attracted significant global interest. AD processes degrade biodegradable biomass, providing a dual solution to waste accumulation from human activities. Agricultural residues, mainly lignocellulosic materials, are an attractive feedstock due to their wide availability. However, their recalcitrant structure limits microbial degradation, reducing methane yields. To address these limitations, anaerobic co-digestion has been proposed as a promising strategy to enhance process stability and methane production. This study employed Biochemical Methane Potential (BMP) tests to investigate the codigestion of wood mixture (WM), corn cob 12 (CC12), manure mixture (MM), and bran mixture (BM), using inoculum from the Vučja vas biogas plant (Slovenia). A simplex-lattice mixture design with augmented points produced 25 mixtures, tested in duplicate within 2 L batch reactors under real operating conditions. Mathematical modelling and optimisation were then used to describe substrate interactions and identify optimal mixture compositions. The results revealed the methanogenic potential of the individual substrates in the following order: CC12 > BM > MM > WM, as well as complex synergistic and antagonistic interactions among them. The optimal mixture consisted of 88.36%CC12 and 11.64%MM, achieving a maximum predicted methane production of 395.43 NmLCH4/gVS. Notably, balanced mixtures containing all substrates significantly outperformed mono-digestion. Future experimental validation of model predictions is essential for practical implementation.[S. Morelli]20262026-04-14 08:45:09Magistrsko delo/naloga181703UDK: 542.71:628.336.6(043.2)VisID: 179206COBISS_ID: 275326723sl