Anaerobic digestion (AD) facilities provide a renewable energy source while also diverting organic material from landfills. In 2011, UW Oshkosh built the first ;;dry;; anaerobic digester in North America. Biogas in this facility is generated from the anaerobic digestion of organic feedstock material, and used to fuel a combined heat and power unit (CHP) that generates electricity and heat for the university.The organic materials that serve as a source of feedstock for biogas generation is influenced greatly by the seasonality of the region where a biogas system operates. The overall objective of this research was to evaluate the various feedstocks used at the UW Oshkosh dry digester and determine if feedstock changes had an impact on plant performance. Both actual operational data collected during the first two years of operation and a bench-scale biogas system were utilized to see the impact of feedstock changes on biogas output. In addition to biogas output, physical and chemical analyses on the feedstocks was conducted to help elucidate the impact of the many feedstock variables. Two critical parameters that were monitored for each feedstock were dry matter (DM) and organic dry matter (oDM). These parameters were chosen due to the fact that facility operators use DM metrics to monitor total recipe for stackability and drainage purposes, and oDM content is what drives biogas production. DM and oDM tests were conducted on all incoming feedstocks at the UW Oshkosh dry digester over a two year period. At the same time biogas production was also evaluated on almost a real-time basis.Within the bench-scale biogas system, food waste generated the largest biogas yield, 3092 Average Standardized Gas Volume (mL) generated. Statistical analyses conducted on the data collected as part of this project indicate that there is a significant relationship between biogas output and the seasonal influence on feedstock oDM content. Statistical analysis of seasonal impact on feedstock and total recipe mix oDM on facility operational data using Kruskal-Wallis ANOVAs generated the most consistent occurrences of significant p-values 0.05.
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EFFECT OF FEEDSTOCK COMPOSITION ON PERFORMANCE OF A DRY ANAEROBIC DIGESTER