(90b) Determining and Addressing Feedstock Variability for Thermochemical Biomass Conversion

A common and significant problem in quantitative analysis is working with a small sample, taken from tons of material, for characterization and generating a variety of values for a single property.  The question that arises from the situation is whether the variability comes from the analysis or the sample itself.  In many instances, it is assumed that the analysis holds inherent errors and no thought is given to the inconsistency or variability of the given sample.   

The quality of feedstock for any production process is extremely important for consistent performance, and the same can be said about biomass feedstock for green energy processes.  Having a uniform biomass feedstock can ensure good quality of the resulting fuel and other chemical products.  Biomass feedstocks are naturally different, starting with the fact that feedstocks cover a range of lignin based materials including corn stover, switch grass, wheat straw, as well as hard and soft woods; in addition, the material properties for each of these feedstock categories differ depending on the location of the feedstock, time of year for growth, water availability and soil properties, as well as how it was harvested, processed, and stored.   The  Idaho National Laboratory (INL) has been tasked with developing uniform feedstocks for use in biomass thermochemical processes.  The National Renewable Energy Laboratory (NREL) is developing thermochemical biomass conversion processes to fuels and chemicals.  Consequently, INL and NREL have formed a collaboration to address and minimize these issues in the future.  INL and NREL will jointly characterize an assortment of biomass feedstocks in an effort to define sample heterogeneity and determine the most effective sampling proceeses that address these variabilites.  Analytical techniques to be used include ultimate and proximate analysis, surface area, and particle size analyses.  These results, to be discussed, will be tabulated in an online database for thermochemical research.