## 3 Results and Discussion
### Pyrolysis Compound Specific Isotopic Analysis (Py-CSIA)  
Major compounds released and identified by conventional analytical pyrolysis (Py-GC/MS) providing chemical structural information were also identified in the chromatograms obtained by Py-GC-C/IRMS (Py-CSIA) containing the \(\delta^{13}\)C information. This was possible by overlaying both pyrograms obtained using the same chromatographic conditions, as illustrated in Figure 3.  
It was possible to assign both structural and \(\delta^{13}\)C values for 40 major pyrolysis peaks (labeled as \"*\" in Table S1). These identified pyrolysis products corresponded to the main biogenic compound classes of carbohydrates (polysaccharides, PS), proteins (N), lignins (LH, LG, and LS), lipids (fatty acids, FA; long-chain alkanes, ALK), isoprenoids (ISO), tocopherols (TOC), and sterols (EST). Average compound-specific values for each compound family are detailed in Table S2, and the \(\delta^{13}\)C evolution during the composting process is depicted in Figure 4.  
Compound-specific \(\delta^{13}\)C values obtained by direct maize biomass pyrolysis were found in the range -8 and -25 % (Figure 4 and Table S2). It is noteworthy that our Py-CSIA analyses significantly isotopically discriminated compounds from distinct biogenic origin (Figure 4 and Table S2). Polysaccharide derived (PS) are \({}^{13}\)C enriched as it occurs in plant polysaccharides [66], whereas sterols (EST) and, mainly, alkanes (ALK) are significantly \({}^{13}\)C depleted [67]. They are well in the range of a C4 photosystem plant, such is maize. Although most compounds groups showed a good homogeneity with standard deviation values below 2%, a few groups (ALK, TOC, and UNK) showed high mean deviations up to 11%; this may be caused by: (i) a poor reproducibility as in TOC and UNK that included only a few compounds with small peaks, some with coelutions inherent to the relatively complex pyrograms, or (ii) by known \(\delta^{13}\)C shifts related to the molecular structure of a particular chemical group, like ALK, known to decrease \(\delta^{13}\)C values with increasing chain length [68]. Therefore, TOC and UNK groups were excluded from Figure 4 and from further statistical analyses. Finally, some peaks, such as that of the anhydrous  
Figure 4: Distribution of \(\delta^{13}\)C Py-CSIA values (average expressed as %; \(n=3\)) of the different compost samples comprising the time of the experiment. Treatments with the same letters indicate no significant differences (Kruskal–Wallis test, \(p<0.05\), Dunn post-hoc) between different composting times for the same biogenic group. Figure 3: Example of Py-GC/MS (above in red) compound correspondence with a compound specific \(\delta^{13}\)C chromatogram obtained by Py-CSIA (below in blue, mass 44 represented) of a representative sample of compost (T3). The three first large peaks are the reference gas signals. levoglucasne (RT: 10.64 min, Figure 3), cannot be mathematically deconvoluted from other peaks to calculate \(\delta^{13}\)C.  
Generally, \(\delta^{13}\)C values for all organic compounds became increasingly enriched during the composing process, with statistical significance from T1 to T2 for all compound groups, except for TOC and EST (stigmasta-3,5-diene). This low significance level may indicate a preferential preservation of these moieties in the humification process, which would depend on long-term microbial activity and have relatively high resident time [40]. Compounds with greater isotopic shifts can be attributed to the plant and microbial compartments, such as PS, N, FA, and EST, where the rate of isotopic enrichment between identical pyrolysis products along the composing process varied from 4 to 9%. Most biochemical processes discriminate against the heavier carbon isotope creating products depleted in \({}^{13}\)C and leaving reactants enriched in \({}^{13}\)C during the composing process.