# Characterization of Congolese Woody Biomass and Its Potential as a Bioenergy Source
## 3 Results
### Proximate Analysis, Ultimate Analysis, and HHV  
The proximate analysis, ultimate analysis, and HHV of the biomass samples are presented in Table 4.  
The results indicate that WB3 has a higher carbon content than the other four woody species. The nitrogen content varied between 0.5% and 1.3%. The \begin{table}
\begin{tabular}{l l l l l l l} \hline
**Analysis** & **WB1** & **WB2** & **WB3** & **WB4** & **WB5** & **WB6** \\ \hline Volatile Matter (\%db) & 77 & 77.2 & 75.6 & 77.3 & 76.1 & 74.58 \\ \hline Fixed Carbon (\%db) & 12.4 & 11.4 & 12.7 & 12 & 12.8 & 14.63 \\ \hline Moisture (\%db) & 13.4 & 7.2 & 4.7 & 5.5 & 7.9 & 8.53 \\ \hline Ash (\%db) & - & - & - & - & 3.1 & ND \\ \hline C (\%db) & 43.5 & 44.4 & 45.4 & 44.0 & 43.4 & 45.85 \\ \hline H (\%db) & 6.1 & 5.9 & 5.5 & 5.9 & 5.7 & 5.61 \\ \hline N (\%db) & 1.3 & 0.8 & 0.5 & 1.1 & 0.7 & 0.66 \\ \hline O (\%db) & 49.1 & 48.9 & 48.6 & 48.2 & 50.2 & 48.03 \\ \hline HHV (MJ/kg) db (Dulong) & 14.7 & 14.7 & 14.6 & 14.7 & 13.9 & 14.9 \\ \hline HHV (MJ/kg) db (f \({}^{\circ}\) (Proximate analysis)) & 19.23 & 16.16 & 15.26 & 15.86 & 16.84 & 17.58 \\ \hline HHV (MJ/kg) db (Friedl) & 17.4 & 17.7 & 18.0 & 17.5 & 17.3 & 18.2 \\ \hline \end{tabular}
\end{table} 
Table 4: Proximate analysis, ultimate analysis, and HHV of the woody biomasses. \begin{table}
\begin{tabular}{c c c c} \hline
**Parameters** & **Mean** & **Maximum** & **Minimum** \\ \hline Diameter (cm) & 767.882 \(\pm\) 784.489 & 1854.6 & 48.4 \\ AGB (t) & 2.708 \(\pm\) 2.24226 & 4.97 & 0.09 \\ AGB (t/ha) & 5.168 \(\pm\) 4.75773 & 9.94 & 0.18 \\ Carbon stock (tC/ha) & 2.816 \(\pm\) 1.77725 & 4.67 & 0.76 \\ \hline \end{tabular}
\end{table} 
Table 3: A statistical analysis of the estimation for the forestry biomass. biomass is also correlated with its ash content. The results of ultimate analysis of these biomasses are similar to [21]. The amounts of fixed carbon and volatile matter (VM) are important for fuel production through thermochemical conversion, as they provide insight into ignition and gasification properties [2]. Biomass with higher VM is more reactive and produces less char during pyrolysis [2]. WB4 samples contain higher VM, whereas WB3 has lower VM content. The fixed carbon content also varied, with values of 11.4% and 12.8%. In summary, ultimate, proximate, and higher heating value (HHV) analyses show good agreement for the composition of all samples collected. The values of carbon, nitrogen, hydrogen, oxygen, and sulfur for different WB species align with results available in the literature [20; 22]. The HHV results using [PERSON]'s equation range from 13.9 to 14.9 MJ/kg, which are relatively low. In contrast, HHV results from proximate analysis range from 15.26 to 19.23 MJ/kg, which are higher. Proximate analysis is a better method than [PERSON]'s equation for estimating HHV. We found that the Friedl model is the best method for estimating HHV because it provides higher values, indicating greater energy production. The HHVs in this study are lower than those found by [15], but these results are not consistent with the literature [16]. The final analysis of all wood biomass results was similar to those reported in the literature by [20]. These values are in agreement with those reported by [18; 23]. The final analysis of all wood biomass results was similar in the same range as reported in the literature by [24]. These values are in agreement with those reported by [25]. Table 5 provides a clear statistical analysis of the proximate and ultimate analyses, as well as the higher heating value (HHV) of the WB. A high proportion of volatile matter indicates the biomass is rich in compounds that release combustible gases at high temperatures, with a low standard deviation (1.08) suggesting homogeneity. Low moisture content is beneficial for energy applications, though the high standard deviation (3.07) indicates significant variability, possibly due to different sources or storage conditions.