**1. Introduction**

The largest repository of lignocellulosic biomass is generated by the cell walls of plants [1]. Its main chemical components are cellulose, hemicelluloses and lignin. 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]. Thus, CO2 sequestered by plants during photosynthesis would balance the CO2 generated by biofuels and their use would not contribute to global warming [5, 6]. On the other hand, after cellulose,

lignin is the most abundant polymer in nature and the main natural source of aromatic compounds [1, 7]. For this reason, lignin is important in the chemical industry and it has been projected as a replacement for aromatic polymers derived from fossil fuels [8].

Lignocellulosic biomass, like other non-volatile complex materials, cannot be directly analyzed in its original state by gas chromatography. Therefore, one of the most common methods for its analysis is the Pyrolysis-Gas Chromatography/ Mass Spectrometry (Py-GC/MS). This method consists of the rapid heating of the materials under analysis (close 300°C), to break the covalent bonds and produce individual fragments. The compounds derived from pyrolysis pass through a capillary column of fused silica in a Gas Chromatograph using an inert gas as carrier (e.g., He). Then the fragments are separated based on their retention times. The selective fragmentation pattern caused by Electron Impact and the m/z ratio for each pyrolysis product are registered by a detector on a Mass Spectrometer. Finally, each compound is identified by comparing its mass spectrum to those in the reference electronic libraries (NIST, MONA, etc.) or to the mass spectra produced by analytical standards [9–12]. 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].

Analytical pyrolysis is currently implemented as a standard method for determining the ratio of H/G/S subunits in plant biomass, agricultural and industrial waste, soil samples and organic matter [6]. This technique has also been useful to elucidate the series of reactions and products derived from the pyrolysis of carbohydrates [14, 15] and lignins [16, 17]. It has been applied for monitoring changes during the delignification and bleaching process as well as for the characterization of different lignocellulosic materials [12]. In addition, it has been used to determine the S/G ratio in lignin of drought-resistant succulent species with results highly comparable to other characterization techniques [18]. On the other hand, its high sensitivity has enabled the detection of hundreds of chemical compounds, including less abundant monomers in lignin, such as acetylated subunits (i.e., sinapyl and coniferyl acetates [19]) and 5-hydroxyguaiacyl units [20]. Recently, Py-GC/MS applied to the analysis of cacti spines, with the use of cheminformatics, allowed a detailed characterization of lignocellulosic matrix, as well as the classification of the samples from a chemotaxonomic approach [21].

### **1.1 Advantages of Py-GC/MS**

Different advantages confer great versatility of application to Py-GC/MS. Firstly, its efficiency, precision and relatively low operating costs [6] make it a suitable routine technique. In addition, it is a fast technique that requires a very small sample size [22, 23]. Volatilization of samples by pyrolysis minimizes the need for pre-isolation, even when analyzing macromolecules in complex mixtures [24]. Therefore, it can be used to analyze a wide variety of materials: e.g., fibers and textiles, wood, bark and paper, artistic materials, synthetic polymers and heteropolymers [12, 13]. Likewise, comparable and reproducible results can be obtained when the conditions of the analysis are kept constant: i.e., carrier gas, heating rate, maximum temperature, homogeneous particle size and removal of non-structural compounds [18, 21]. Therefore, samples with the same composition will produce the same derivatives of pyrolysis [13, 21]. On the other hand, the advantages of the coupled GC/MS system are associated with a high speed, specificity and sensitivity, in both the separation of the pyrolysis products and in their identification [9, 12]. In addition, Py-GC/ MS allows the identification of compounds without the necessity of standards.

It enables the comparison to commercial or open access libraries, including some already curated for different classes of chemical compounds [21, 25–28]. Finally, the raw data generated can be exported for quantitative or qualitative analysis [29, 30].
