Asset Details
Do you wish to reserve the book?
Characterization of Congolese Woody Biomass and Its Potential as a Bioenergy Source
Hey, we have placed the reservation for you!
By the way, why not check out events that you can attend while you pick your title.
Oops! Something went wrong.
Looks like we were not able to place the reservation. Kindly try again later.
Are you sure you want to remove the book from the shelf?
Characterization of Congolese Woody Biomass and Its Potential as a Bioenergy Source
Do you wish to request the book?
Characterization of Congolese Woody Biomass and Its Potential as a Bioenergy Source
Please be aware that the book you have requested cannot be checked out. If you would like to checkout this book, you can reserve another copy
We have requested the book for you!
Your request is successful and it will be processed during the Library working hours. Please check the status of your request in My Requests.
Oops! Something went wrong.
Looks like we were not able to place your request. Kindly try again later.
Journal Article
Characterization of Congolese Woody Biomass and Its Potential as a Bioenergy Source
2025
Overview
This study assesses and characterizes six woody biomass (WB) species commonly harvested in the Republic of Congo: Millettia laurentii (WB1), Millettia eetveldeana (WB2), Hymenocardia ulmoides (WB3), Markhamia tomentosa (WB4), Pentaclethra eetveldeana (WB5), and Hymenocardia acida (WB6). Characterization was performed using proximate analysis with a Thermo Gravimetric Analyser (TGA), ultimate analysis with a CHNS Analyser, higher heating value (HHV) determination, metal content analysis by X-ray fluorescence (XRF), and aboveground biomass (AGB) estimation. The proximate analysis results showed that volatile matter varied between 74.6% and 77.3%, while the ultimate analysis indicated that carbon content ranged from 43% to 46%, with low nitrogen content. XRF analysis revealed low levels of heavy metals in all samples. The HHV results, using three models (Dulong’s equation, Friedl, and proximate analysis), showed higher values with Friedl’s method (17.3–18.2 MJ/kg) and proximate analysis (15.26–19.23 MJ/kg) compared to Dulong’s equation (13.9–14.9 MJ/kg). Savannah biomass (WB6) exhibited high AGB (7.28 t), 14.55 t/ha, and carbon stock (7.28 t). Compared to forest biomass, savannah biomass presents a higher potential for bioenergy production. Minimal statistical analysis of wood biomass showed that parameters such as volatile matter (VM), carbon (C), hydrogen (H), and calculated HHV have low variability, suggesting the biomass is relatively homogeneous. However, moisture and nitrogen showed significant standard deviations, indicating variability in storage conditions or sample nature. Statistical analysis of forest biomass estimation revealed different mean values for diameter, AGB (t and t/ha), and carbon stock, with high standard deviations, indicating a heterogeneous forest with both young and mature trees. These analyses and estimates indicate that these WB species are suitable for biofuel and bioenergy production using gasification, pyrolysis, and combustion processes. Among these thermochemical processes, gasification is the most efficient compared to combustion and pyrolysis.
