*3.4. Validation of the TGA-PKM Method*

In order to check the validity of the method, an additional fit of the poplar biomass devolatilization was performed using, simultaneously, three heating rates: 3, 5 and 10 ◦C min−<sup>1</sup> datasets.

Figure 13 shows the graphical results by fitting the model to the DTG and TG curves for each heating rate.

Additionally, the quality of the fit achieved for each heating rate and for the global fit are summarized in Table 10, where QOF% and R2 Adj are shown for each heating rate dataset and for the three heating rates simultaneously.


**Table 10.** Quality of the fit for each dataset.

The results obtained (Figure 13 and Table 10) indicate that the quality of the fit obtained is very satisfactory, since the model is capable of representing the evolution of the devolatilization process when different heating rates are used.

**Figure 13.** *Cont*.

**Figure 13.** Model fitted to the experimental poplar DTG and TG curves: (**a**) DTG at 3 ◦C min−1, (**b**) 5 ◦C min−1 and (**c**) 10 ◦C min−1. (**d**) TG at the three heating rates.

Table 11 shows the kinetic parameters by fitting the model using a single heating rate and three heating rates simultaneously. The obtained results by both datasets are very similar. For example, the activation energy obtained is identical for almost all the pseudocomponents, and only pseudocomponents 3 and 7 have a relative standard deviation of 4%.


**Table 11.** Kinetic parameters of each pseudocomponents calculated using a single heating rate and three simultaneous heating rates.

Finally, the results obtained in the determination of the lignocellulosic fractions are shown in Table 12. The results obtained with a single heating rate are comparable to those obtained with three heating rates, because the deviation between the results calculated by the model and by the analytical method are of the same order when a single heating rate or three heating rates are considered. However, slightly better results are achieved if a single heating rate of 5 ◦C min−<sup>1</sup> is used, but mainly, it requires considerably less analysis time, which justifies the use of a single heating rate.

**Table 12.** Comparison between TGA-PKM results using three simultaneous heating rates and the analytical method.


#### **4. Conclusions**

Five lignocellulosic samples have been characterized by the TGA-PKM experimental protocol, covering different types of woody and herbaceous biomasses from both forest and agricultural origins (spruce bark, pine bark, poplar, willow and wheat straw).

The TGA-PKM method developed allows the determination of the main lignocellulosic fractions of biomasses without the need to use long and complex chemical methods; e.g., TAPPI methods T222 and T249 require several long successive steps (hydrolysis, extraction, filtration, neutralization, reduction, etc.) [41], which may require several days of work in the laboratory, while the new method may be performed in a few hours. Thus, it would be possible to reduce the cost of analysis and processing time by 80–90%.

The accuracy of the TGA-PKM method was tested and proved to be significantly good and consistent within the order of magnitude of the standard analytical methods to determine the contents of the main lignocellulosic fractions.

**Author Contributions:** Conceptualization, D.D. and A.U.; methodology, D.D. and A.U.; software, D.D. and A.U.; validation, D.D., A.U., R.P.; formal analysis, D.D., A.U., A.B. and T.T.; investigation, D.D. and A.U.; resources, A.B., T.T. and R.P.; data curation, D.D., A.U.; writing (original draft preparation), D.D., A.U.; writing (review and editing), R.P, A.B. and T.T.; visualization, D.D., A.U., R.P., A.B. and T.T.; supervision, D.D., A.U., R.P., A.B. and T.T.; project administration, A.B; funding acquisition, A.B., T.T. and R.P. All authors have read and agreed to the published version of the manuscript.

**Funding:** This research was funded by the European Union's Horizon 2020 research and innovation programme under grant agreement No 723670, with the title "Systemic approach to reduce energy demand and CO2 emissions of processes that transform agroforestry waste into high added value products (REHAP)".

**Acknowledgments:** The authors would like to thank María González Martínez from IMT Mines Albi (Université de Tolousse) for her technical contribution and support.

**Conflicts of Interest:** The authors declare no conflict of interest.
