Results of the International Energy Agency Round Robin on fast pyrolysis bio-oil production

Abstract

An international round robin study of the production of fast pyrolysis bio-oil was undertaken. A total of 15 institutions in six countries contributed. Three biomass samples were distributed to the laboratories for processing in fast pyrolysis reactors. Samples of the bio-oil produced were transported to a central analytical laboratory for analysis. The round robin was focused on validating the pyrolysis community understanding of production of fast pyrolysis bio-oil by providing a common feedstock for bio-oil preparation. The round robin included: distribution of three feedstock samples, hybrid poplar, wheat straw, and a blend of lignocellulosic biomasses, from a common source to each participating laboratory, preparation of fast pyrolysis bio-oil in each laboratory with the three feedstocks provided, and return of the three bio-oil products (minimum of 500 mL) with operational description to a central analytical laboratory for bio-oil property determination. The analyses of interest were CHN, S, trace element analysis, water, ash, solids, pyrolytic lignin, density, viscosity, carboxylic acid number, and accelerated aging of bio-oil. In addition, an effort was made to compare the bio-oil components to the products of analytical pyrolysis through gas chromatography/mass spectrometry (GC/MS) analysis. The results showed that clear differences can occur in fast pyrolysis bio-oil properties by applying different process configurations and reactor designs in small scale. The comparison to the analytical pyrolysis method suggested that pyrolysis (Py)-GC/MS could serve as a rapid qualitative screening method for bio-oil composition when produced in small-scale fluid-bed reactors. Gel permeation chromatography was also applied to determine molecular weight information. Furthermore, hot vapor filtration generally resulted in the most favorable bio-oil product, with respect to water, solids, viscosity, and carboxylic acid number. These results can be helpful in understanding the variation in bio-oil production methods and their effects on bio-oil product composition.