With a diverse portfolio of biomass sources that includes agricultural and forest residue, municipal solid waste, and purpose-grown energy crops (herbaceous and woody), the southeastern U.S. is projected to provide more than 60 percent of the Nation’s supply of alternative renewable fuel. To meet this expectation, the concept of a centralized preprocessing depot capable of handling different biomass types has been advocated. Housing operations for size reduction, drying, densification and related pretreatment methods, the depot will: 1) introduce supply chain efficiencies to lower feedstock cost, 2) eliminate dependence on a single biomass source, 3) allow construction of larger-scale biorefineries to improve economics, and 4) improve quality and consistency of delivered feedstock for specific platforms. Several technological advances are needed to realize this vision, including improved real-time access to information on the chemical composition and physical property changes that are induced by multiple preprocessing steps. Recent work has generated new data on the variation in carbon content, moisture content, and ash content and composition (alkali and alkali earth metals) of several high-impact biomass sources, including switchgrass and pine residue. Multivariate statistical analysis of near infrared spectroscopic data was used to model (Projection to Latent Structures) these important properties. This presentation will discuss quality of the different models while highlighting related progress in the development of online sensors to monitor biomass properties that directly impact downstream conversion to fuels. As a result of this effort, a valuable new tool is emerging to directly evaluate the impact of biomass properties on preprocessing operations, and provide new insight into aspects of the feedstock-conversion interface.

Formulated feedstocks for biorefining: Monitoring key biomass chemical characteristics

2019 Fall National Meeting

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