Sustainable enhancement of anaerobic digestion: Leveraging microbiome insights to improve stability and biomethane production during anaerobic digestion of heterogenous organic wastes

This proposal seeks to establish a new partnership on harvesting renewable natural gas and hydrogen production from heterogeneous organic waste through anaerobic digestion and microbiome modeling. Anaerobic digestion (AD) is a well-established biotechnology for organic waste conversion and great potential exists to expand AD systems to more complex, highly available feedstocks like food waste, or to include different feedstocks to a single digester. However, challenges with reactor stability under heterogeneous feeding limits widespread adoption. Microbiome insights and machine learning tools have potential to prevent digester instabilities and optimize production of renewable energy. The overall objective of the proposed project is to develop a database of AD microbiome dynamics as a function of feedstock characteristics and digester operational parameters. The central hypothesis is that microbiome dynamics data can be used to construct an accurate model of digester performance that can be applied to prevent digester upsets under dynamic feeding of heterogeneous organic waste. The specific aims are to 1) identify shifts in AD microbiome structure in response to dynamic feedstock composition and operational parameters and 2) incorporate microbiome structure characteristics to the development of bioaugmentation strategies that improve digester stability. The team consists of two Assistant Professors in MG-CAFE and P-COE with expertise in anaerobic digestion and microbiome/metagenomics who seek to build fundamental preliminary data for planned full grant applications to NSF ECO-CBET (Environmental Convergence Opportunities in Chemical, Bioengineering, Environmental, and Transport Systems) and DOE IED (Industrial Efficiency and Decarbonization Office) opportunities.