Graduate Thesis Or Dissertation

Exploring the Anaerobic Co-digestion of Food Waste, Brewery Waste, and Fats, Oils, and Greases through Biomethane Potential Testing and Response Surface Methodology

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  • Food waste (FW), brewery waste (BW), and fats, oils, and greases (FOG), are prevalent waste streams in municipalities across the country, particularly in the Pacific Northwest (PNW). Anaerobic digestion (AD), the microbial-mediated transformation of organic waste into methane-rich biogas, offers a sustainable, energy-generating, waste management solution for these wastes. Anaerobic co-digestion (ACoD), a strategy increasingly used at wastewater reclamation facilities (WWRF), involves adding two or more wastes to a digester, which can increase biogas production and stabilize the digestion process. Despite growing interest from municipalities to add FW, BW, and FOG to their WWRF anaerobic digesters, there remains a gap in understanding the mixed ACoD of these substrates. To address this gap, response surface methodology (RSM) was utilized to develop a descriptive model of the mixed ACoD of FW, BW, and FOG. To aid in the development of the response surface model, batch biomethane potential (BMP) testing was first conducted to determine the methane production capacity and inhibitory limits of the individual substrates. The BMP of BW, FW, and FOG were determined to be 103, 345, and 992 NmL CH4/g VS added, respectively. While FW showed no inhibition within the tested substrate-to-inoculum ratios (SIRs) of 0.025-1.0, an inhibitory limit of FOG and BW was estimated to be between 0.1-0.25 SIR. Following the BMP analysis, a 31-day batch experiment was conducted in a central composite design (CCD) configuration. RSM was utilized to analyze the data and develop a descriptive model of the digestion process that can estimate methane yield at various combinations of the three substrates. The developed polynomial model explained 91% of the variability in the methane yield response and was highly significant (p<0.001). The individual effects of the substrates revealed that FW and FOG contributed positively to methane yield, while BW severely inhibited methane production. Antagonistic interactive effects between all substrate combinations suggested potential overloading and inhibition occurring with mixed co-digestion. While there was a significant lack of fit observed in the model (p<0.05), two out of three model predictions were validated via independent experimentation, indicating the model’s usefulness, despite its limitations.
  • KEYWORDS: Anaerobic digestion, Anaerobic co-digestion
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