Chromatographic analysis of bio-oil formed in fast pyrolysis of lignocellulosic biomass

Abstract

Fast pyrolysis of lignocellulosic biomass is one of the most promising methods of the production of renewable fuels. However, an optimization of the conditions of bio-oil production is not possible without comprehensive analysis of the composition of formed products. There are several methods for the determination of distribution of products formed during thermal decomposition of biomass with chromatography being the most versatile among them. Although, due to the complex structure of bio-oil (presence of hundreds chemical compounds with different chemical character), an interpretation of the obtained chromatograms is not an easy task. Therefore, the aim of this work is to present an application of different chromatographic methods to the analysis of the composition of the mixture of products formed in high temperature decomposition of lignocellulosic feedstock. It includes pyrolysis-gas chromatography/mass spectrometry (Py-GC/MS), two dimensional gas (GC x GC) or liquid chromatography (LC x LC) and initial fractionation of bio-oil components. Moreover, the problems connected with the analysis of bio-oils formed with the use of various fast pyrolysis reactors and capabilities of multivariate analysis are discussed.

Cheminformatics Applied to Analytical Pyrolysis of Lignocellulosic Materials

“…However, some authors have successfully carried out quantitative analyses in the optimization of aromatic hydrocarbon production from biomass [29]. Also for the quantification of only small amounts of aromatic hydrocarbons, applying the external calibration method [3,30].…”

“…In addition, it is considered that the large number of derivatives makes the description of the chemical composition of sample difficult. Therefore, the detailed interpretation of the results is difficult and probably not necessary [3]. For example, when analyzing carbohydrate samples, low molecular weight derivatives can originate from hexoses or pentoses [12,32].…”

“…Among multivariate analyses, Principal Component Analysis (PCA) is the most common method for extracting information from large datasets generated by analytical pyrolysis [3,12]. The PCA has different objectives, it is mainly used to reduce the dimensions of the datasets by extracting the most important information.…”

“…The proportions are variable but close to 4:3:3, respectively, and the element content is 50% C, 6% H, 44% O y ≤ 0.4% N, for resources such as wood [1]. Because biomass is a renewable resource, its study for the production of energy and valueadded aromatic compounds has gained importance in recent decades [2,3]. It has been considered that lignocellulosic biomass as a renewable energy source would satisfy around 25% of energy requirements [4].…”

“…or to the mass spectra produced by analytical standards [9][10][11][12]. The sequential combination of these three processes in Py-GC/MS makes it a versatile and powerful tool for the analysis of lignocellulosic materials and other complex mixtures, such as polymers and copolymers [3,13].…”